CFA III, Session 14 2022

PORTFOLIO MANAGEMENT 

Reading 33: Portfolio Management for Institutional Investors 

Reading 34: Trading, Performance Evaluation and Manager Selection

33a) Discuss common characteristics of institutional investors as a group. 

1 

2 

3 

4 

5 

Scale 

AUM size improves access, capabilities, and trading costs. 

Long-term Horizon 

Generally has benefit commitment; e.g., endowment, pension plan. 

Regulatory Frameworks 

Various jurisdictional frameworks that vary in complexity. 

Governance 

Clearly defined investment model and governance. 

Principal-Agent Issues 

Less incentive because they work for a principal rather than themselves.

33b) Discuss investment policy of institutional investors. 

Institutional 

investors 

• Mission, objectives 

• Approaches to SAA 

DB Pension Plan 

100% funded ratio; return target for 

assets greater than liabilities (i.e., 

overfunded portion). 

Risk: surplus volatility. 

Banks/Insurance 

Maximize NPV of net assets while 

managing funding risk. 

Risk: VaR, CVaR, outcome of stress tests. 

Mission 

Endowment Fund 

Maintain real purchasing power 

while funding its institution. 

Risk: Volatility of total returns. 

Sovereign Wealth 

Much like an endowment. 

Risk: Investment or purchasing power losses.

33b) Discuss investment policy of institutional investors. 

Investment Approach Description/characterization Pros Cons 

Norway Model 

Traditional style, 60%/40% equity/fixed-income Low cost, transparent, Limited value-added potential. 

allocation, few alternatives, largely passive investments, suitable for large scale, easy 

tight tracking error limits, and benchmark as a starting for board to understand. 

position. 

Endowment Model 

High alternatives exposure, active management and 

outsourcing. 

High value-added potential. 

Expensive and difficult to implement 

for most sovereign wealth funds 

because of their large asset sizes, so 

they struggle to come down to niches. 

Canada Model 

High alternatives exposure, active management, and 

insourcing. 

High value-added potential 

and development of internal 

capabilities. 

Potentially expensive and difficult to 

manage. 

LDI Model 

Focus on hedging liabilities and interest rate risk 

including via duration-matched, fixed-income exposure. 

A growth component in the return-generating portfolio is 

also typical (exceptions being bank and insurance 

company portfolios). 

Explicit recognition of 

liabilities as part of the 

investment process. 

Certain risks (e.g., longevity risk, 

inflation risk) may not be hedged.

33c) Discuss the stakeholders in the portfolio, the liabilities, the investment time horizons, and the liquidity needs of 

different types of institutional investors (pension funds, endowment funds, banks/insurance, SWFs) 

Characteristics Defined Benefit Pension Plan Defined Contribution Pension Plan 

Benefit payments 

Defined by a contract between the employee and the pension 

plan (payouts are often calculated as a percentage of salary). 

Benefit payouts are determined by the performance of investments 

selected by the participant. 

Contributions 

The employer is the primary contributor, though the employee 

may contribute as well. The size of contributions is driven by 

several key factors, including performance of investments 

selected by the pension fund. 

The employee is typically the primary contributor—although the 

employer may contribute as well or may have a legal obligation to 

contribute a percentage of the employee’s salary. 

Investment decision 

making 

The pension fund determines how much to save and what to 

invest in to meet the plan objectives. 

The employee determines how much to save and what to invest in to 

meet his/her objectives (from the available menu of investment 

vehicles selected by the plan sponsor). 

Investment risk 

Mortality/Longevity risk 

The employer bears the risk that the liabilities are not met and 

may be required to make additional contributions to meet any 

shortfall. 

The employee bears the risk of not meeting his/her objectives for this 

account in terms of funding retirement. 

Mortality risk is pooled. If a beneficiary passes away early, The employee bears the risk of not meeting his/her longevity risk 

he/she typically leaves a portion of unpaid benefits in the pool objectives for this account in terms of funding retirement. 

offsetting additional benefit payments required by beneficiaries 

that live longer than expected (mortality credits) 

As a result, the individual does not bear any of the risk of 

outliving his/her retirement benefits.



Stakeholders DBP Funds DCP Funds SWFs University 

Endowments 

Private 

Foundations 

Plan sponsors Employer Employer Alumni Donors 

Plan 

beneficiaries 

Employees and 

retirees 

Board INVESCOM INVESCOM 

Financiers 

Investment 

Managers 

Customers 

Rating agencies 

Regulators/gov’t 

Others 

Employees Citizens Current and future 

students 

Grant recipients 

Banks 

Shareholders 

and lenders 

CIO et al CIO et al Asset-Liability 

Committee 

Government, 

unions 

Plan sponsor 

Government Government University 

community 

Depositors, 

borrowers. 

S&P, Fitch, 

etc. 

Insurers 

Shareholders 

and lenders 

Policy holders, 

derivative 

counter parties. 

S&P, Fitch, etc.

Factor 

Service/tenure 

Salary/earnings 

Additional or matching 

contributions 



Liquidity Needs of DBP Funds A function of liabilities: Factors Affecting DCP Liabilities 

Employer contribution = Liability 

Factors Affecting Defined Benefit Liabilities 

Impact on Liabilities 

Depending on plan design, often the longer the period of 

service or tenure, the larger the benefit payments. 

The faster salaries or earnings grow, the larger the 

benefit payments. 

Additional or matching contributions are often rewarded 

by a step change increase in benefit payments. 

Investment in Alternative 

Investments 

% of active employees 

relative to retirees 

Age of workforce 

Liquidity risk if any event causes a significant 

proportion of its participants to exit the plan. 

Liquidity Needs 

More retirees →Higher liquidity needs. 

Frozen DB face negative CF →Higher liquidity 

Open mature plans →Lower liquidity needs. 

Older age → Higher liquidity needs 

Mortality/Longevity 

assumptions 

If life expectancy increases, the obligations or liabilities 

will increase. 

DB plan funded status 

Well funded →plan sponsor may reduce 

contributions→ Higher liquidity needs 

Expected Vesting 

If employee turnover decreases, expected vesting will 

increase. 

Ability to switch/withdraw 

from plan 

Easy → Higher liquidity needs 

Expected Investment 

Returns 

In some cases, increases in expected returns will result in 

a higher discount rate being used—hence, lower 

obligations or liabilities. 

Both DBP and DCF 

Long investment horizon 

Discount Rate 

A higher (lower) discount rate results in lower (higher) 

liabilities.



Comparing DB and DC Pension Plans 

Geoff Albright is 35 years old and has been working at Henley 

Consulting in Melbourne, Australia, for 10 years. Henley 

Consulting offers a defined benefit (DB) pension plan for its 

employees. The defined benefit plan is fully funded. Geoff 

Albright’s benefit formula for monthly payments upon retirement 

is: final monthly salary × benefit percentage (=1.5%) × number 

of years of service, where final monthly salary equals his 

average monthly earnings for the last three financial years 

immediately prior to retirement date. Having been at Henley 

Consulting for 10 years, his benefits have vested and can be 

transferred to another pension plan. 

Current Employer (DBP) 

Benefit payments • Transferable to Horizon 

• Linked to years of service and 

final salary. 

• Increase by time employed as 

well as by growth in his wages. 

Consider capacity to grow wages 

Job offer: Horizon (DCP) 

Uncertain, linked to the company’s 

and his contribution rates and 

performance of plan assets. 

Compares capacity to grow wages 

to the return objectives of his 

chosen option: Horizon Growth. 

Contributions Contribution rate is not known Contribution rate is also known 

(15% of annual salary) 

Geoff has been offered a job at rival Australian firm, Horizon 

Ventures Consulting, which is offering a similar salary; however, 

Horizon Ventures Consulting offers a defined contribution (DC) 

pension plan for its employees. Horizon Ventures Consulting will 

pay 15% of annual salary into the plan each year. Employees 

can choose to invest in one of three diversified portfolios offered 

by the plan sponsor—Horizon Growth, Horizon Balanced, and 

Horizon Conservative—based upon their risk appetite, and 

employees can elect to make additional contributions to the 

plan. The monthly pension payments will depend on what has 

accumulated in Geoff’s account when he retires. 

Discuss the features that Geoff should consider in 

evaluating the two plans. 

Shortfall risk 

Mortality/longevity 

risks 

Plan is fully-funded, and Henley 

obligation to maintain funded 

status. 

Pools mortality risk, those in the 

pool who die prematurely leave 

assets that help fund benefit 

payments for those who live longer 

than expected (mortality credit) 

Can also make additional 

contributions himself 

depends on the contribution rate 

(15% from the company plus any 

additional contributions he 

chooses to make) and the 

performance of his chosen 

investments. 

Pays out the amount accumulated 

in Geoff’s account, and he bears 

the risk of outliving his savings.

33d) Describe the focus of legal, regulatory, and tax constraints affecting different types of institutional investors. 

Legal and 

regulatory 

constraints 

Breach 

Regulation 

varies per 

country 

Regulatory bodies typically cover: 

• Financial services licensing and regulation, 

• Prudential supervision, 

• Capital adequacy, 

• Market integrity, and 

• Consumer protection. 

Loss of operating licenses and/or loss of tax benefits, 

Minimum and maximum percentage allocations to certain 

asset classes 

Minimum contribution rate by employers, particularly if 

the plan’s funded ratio falls below 100%. 

Extensive reporting, not only on direct investment fees 

and costs incurred by pension plans but also on indirect 

fees and costs of external commingled vehicles. 

Governments 

encourage 

retirement 

savings 

Tax 

constraints 

Examples 

• Reduced taxes on retirement plan contributions, 

• Favorable tax rates on investment income and/or 

capital gains, and 

• Lower tax rates on benefit payments throughout 

retirement (v higher taxes on lump sum payments). 

Governments typically place restrictions on plan design, 

governance, and investment activities in order for plans 

to qualify for the favorable tax treatment. 

Plans are tax deferred, make pre-tax contributions and 

pay no tax on investment earnings. 

Benefit payments are taxed as ordinary income and early 

withdrawal taxed higher. 

Favorable capital gains tax treatment for investments 

held over 1 year incentivizes investing in lower turnover 

strategies. 

Provide investor education to employees, DC plan 

trustees, as fiduciaries, are still required to operate with 

prudence and as if they were the asset owners. 

Pension fund returns from derivatives are taxed at higher 

rates than returns from underlying securities. 

US regulates vesting, funding requirements, and 

payouts, including a fiduciary code of conduct and 

required disclosures, even discount rates. 

To reduce risk of double taxation in international 

investments, pension plans should invest via legal 

structures that provide access to double taxation treaties.

US—PRIVATE 

US—PUBLIC 


Pension Plans—Accounting Considerations—US Example 

• Overfunded (underfunded) plan must appear 

as an asset (liability) on the sponsor’s 

balance sheet. 

• Plan sponsor must report gains, losses, and 

service costs of the plan as part of net 

income. 

• Assets—Fair market values 

• Liabilities—Blended approach 

• Funded portion discounted using expected 

return on plan assets. 

• Unfunded portion discounted using (lower) 

yield on tax-exempt municipal bonds. 

Accounting treatment drives a sponsor’s investment decision making.

33e) Evaluate risk considerations of private DB pension plans in relation to 1) plan funded status, 2) sponsor financial strength, 3) 

interactions between the sponsor’s business and the fund’s investments, 4) plan design, and 5) workforce characteristics. 

Factors Affecting Risk Tolerance and Risk Objectives of Defined Benefit Plans 

Category Variable Explanation 

Plan status • Plan funded status (surplus or deficit) • Higher pension surplus or higher funded status implies potentially 

greater risk tolerance. 

Sponsor financial status and 

profitability 

• Debt to total assets 

• Current and expected profitability 

• Size of plan compared to market capitalization of 

sponsor company 

• Lower debt ratios and higher current and expected profitability imply 


• Large sponsor company size relative to pension plan size implies 


Sponsor and pension fund 

common risk exposures 

• Correlation of sponsor operating results with pension 

asset returns. 

• The lower the correlation, the greater the risk tolerance, all else 

equal. 

Plan features • Provision for early retirement 

• Provision for lump-sum distributions 

• Such options tend to reduce the duration of plan liabilities, implying 

lower risk tolerance, all else equal. 

Workforce characteristics • Age of workforce 

• Active lives relative to retired lives 

• The younger the workforce and the greater the proportion of active 

lives, the greater the duration of plan liabilities and the greater the 

risk tolerance.

33e) Evaluate risk considerations of private DB pension plans in relation to 1) plan funded status, 2) sponsor financial strength, 3) 

interactions between the sponsor’s business and the fund’s investments, 4) plan design, and 5) workforce characteristics. 

Andes Sports Equipment Corporation—Defined Benefit Plan 

Frank Smit, CFA, is chief financial officer of Andes Sports Equipment 

Company (ADSE), a leading Dutch producer of winter and water sports gear. 

ADSE is a small company based in Amsterdam, and all of its revenues come 

from Europe. Product demand has been strong in the past few years, although 

it is highly cyclical. The company has rising earnings and a strong (low debt) 

balance sheet. ADSE is a relatively young company, and as such, its defined 

benefit pension plan has no retired employees. This essentially active-lives 

plan has €100 million in assets and an €8 million surplus in relation to the 

projected benefit obligation (PBO). Several facts concerning the plan follow: 

Smit must set risk objectives for the ADSE pension plan. Because of 

excellent recent investment results, ADSE has not needed to make a 

contribution to the pension fund in the two most recent years. 

Smit considers it very important to maintain a plan surplus in relation to 

PBO. Because an €8 million surplus will be an increasingly small buffer 

as plan liabilities increase, Smit decides that maintaining plan funded 

status, stated as a ratio of plan assets to PBO at 100 percent or 

greater, is his top priority. 

2. State an appropriate risk objective for ADSE. 

a) The duration of the plan’s liabilities (all Europe-based) is 20 years. 

b) The discount rate applied to these liabilities is 6 percent. 

c) The average age of ADSE’s workforce is 39 years. 

1. Based on the information provided, discuss ADSE’s risk tolerance. 

Funded status 

Balance sheet 

Profitability 

Average age of 

workforce 

Above average or high risk tolerance: 

8% of plan assets: overfunded by €8 million. 

Strong, low use of debt 

Rising earnings despite operating in a cyclical industry. 

39 years, low [no retired employees] 

Shortfall risk 

Important to maintain a plan surplus in relation to PBO 

Example 1 • The probability that funded status falls below 100 

percent to be ≤10 percent. 

Example 2 • Minimize the present value of expected cash 

contributions. 

If a plan surplus is maintained, more years without need 

for contribution.

33f) Prepare the investment objectives section of an institutional investor’s investment policy statement. 

33g) Evaluate the investment policy statement of an institutional investor. 

33h) Evaluate the investment portfolio of a private DB plan, sovereign wealth fund, university endowment, and private foundation. 

Sample Investment Objectives of Different Pension Plans 

Corporate DC Pension Plan: 

Public DB Pension Plan: 

1. The assets of Public Plan will be invested with the objective of 

achieving a long-term rate of return that meets or exceeds the Public 

Plan actuarial expected rate of return. 

2. Public Plan will seek to maximize returns for the level of risk taken. 

3. Public Plan will also seek to achieve a return that exceeds the Policy 

Index. 

4. Public Plan will seek to achieve its objectives on an after fees basis. 

Corporate DB Pension Plan: 

The Trustee wishes to ensure that the Corporate Plan can meet its 

obligations to the beneficiaries while recognizing the cost implications to the 

Company of pursuing excessively conservative investment strategies. 

The objectives of the Plan are defined as: wishing to maximize the longterm 

return on investments subject to, in its opinion, an acceptably low 

likelihood of failing to achieve an ongoing 105% funding level. 

The Fund currently offers a range of investment options to its 

participants and has adopted an age-based default strategy for 

participants who do not choose an investment option. 

The investment strategy of the Fund is to put in place portfolios to 

achieve the objectives of its stakeholders over a reasonable period of 

time with a reasonable probability of success. 

In establishing each option’s investment objectives, the Trustee takes 

into account the average participant’s age, account balance, and risk 

appetite. The participant’s choice of investment option indicates his/her 

risk appetite. 

For example, a participants selecting the growth option indicates a 

higher risk tolerance over a longer investment time horizon. 

The investment objective for the growth option is to build an 

investment portfolio to outperform inflation + 4% per annum over 7- 

year periods while accepting a high level of risk that is expected to 

generate 4–6 negative annual returns over any 20-year period.




Asset Allocation by a Public Defined Benefit Plan 

Susan Liew, CFA, is the chief investment officer of the Lorenza State Pension 

Plan (LSPP), a public DB plan. The plan maintains an asset allocation of 30% 

US equities, 30% international equities, 30% US fixed income, and 10% 

international fixed income. Liew’s investment team developed the following longterm 

expected real returns for the asset classes in which the LSPP has 

traditionally invested. The outlook for US and international equities is slightly 

below long-term averages, while the outlook for US and international fixed 

income is well below long-term averages. 

Given the poor prospects for fixed income and the mediocre expectations for 

equities, Liew is exploring making allocations to various alternatives. 

How will the change in SAA (next slide) affect LSPP’s funded status? 

E®↑ 

Liabilities↓ 

Funded status↑ 

Volatility of 

assets↓ 

Liquidity↓ 

Manager 

selection (MS) 

risk 

Higher expected asset values over time. 

AIs have higher projected long-term returns than 

traditional debt/equities, the discount rate applied to 

liabilities can be increased →reducing their PV 

On balance, funded status would improve. 

Risk to funded status should be reduced because of 

the lower correlation among asset returns. 

AIs reduce liquidity, no impact on FS, but must be 

considered to sufficient cover prospective liabilities. 

AIs entail greater MS risk and larger dispersion of 

returns around the policy benchmark relative to a 

passive allocation to public markets. Careful manager 

selection require resources that would increase 

internal costs, and also require paying higher fees


different types of institutional investors (pension funds, SWFs, endowment funds, banks/insurance) 

SOVEREIGN WEALTH FUNDS 

TYPES AND STAKEHOLDERS 

Type Objective Examples 

Budget stabilization 

funds (BSFs) 

Development funds 

(DFs) 

Savings funds (SFs) 

Reserve funds (RFs) 

Pension reserve funds 

(PRFs) 

Set up to insulate the budget and economy from commodity price 

volatility and external shocks. 

Established to allocate resources to priority socio-economic 

projects, usually infrastructure. 

Intended to share wealth across generations by transforming nonrenewable 

assets into diversified financial assets. 

Intended to reduce the negative carry costs of holding foreign 

currency reserves or to earn higher return on ample reserves. 

Set up to meet identified future outflows with respect to pensionrelated 

contingent-type liabilities on governments’ balance sheets. 

• Economic and Social Stabilization Fund of 

Chile. 

• Timor-Leste Petroleum Fund. 

• Russia’s Oil Stabilization Fund. 

• Mubadala (UAE). 

• Iran’s National Development Fund. 

• Ireland Strategic Investment Fund. 

• Abu Dhabi Investment Authority. 

• Kuwait Investment Authority. 

• Qatar Investment Authority. 

• Russia’s National Wealth Fund. 

• China Investment Corporation. 

• Korea Investment Corporation. 

• GIC Private Ltd. (Singapore). 

• National Social Security Fund (China). 

• New Zealand Superannuation Fund. 

• Future Fund of Australia.




TYPES AND STAKEHOLDERS 

Wealth Managers




LIABILITIES AND INVESTMENT HORIZONS 

Budget 

Stabilization 

(BSFs) 

Development 

Funds (DFs) 

Savings Funds 

(SFs) 

Reserve 

(RFs) 

Pension Reserve 

(PRFs) 

• Shorterm Risk 

management 

• Increase 

productivity and 

real GDP over time 

• Transform S-T 

resource wealth to 

trans-generational 

financial wealth 

• Redeploy foreign 

currency reserves 

• Prefund future 

benefits 

• Uncertain liabilities 

• Relatively short 

horizon 

• Uncertain liabilities 

• Project-based 

horizons (e.g. 

infrastructure) 

• Uncertain n/a 

• Absolute or 

benchmark return 

driven 

• Liabilities are 

monetary 

stabilization bonds 

• Need greater 

liquidity for 

unpredictable 

health costs than 

for retirement 

• Long-term horizon 

• Very long horizon


different types of institutional investors. 



LEGAL AND REGULATORY 

Mission 

Contributions 

Withdrawal permissions 

Governance structure 

Asset allocation (some jurisdictions) 

Transparency/accountability 

IFSWF members adhere to best 

practices that promote: 

• A well-defined mission, 

• Ethics and professionalism, 

• Transparency, 

• Accountability, 

• Independence, 

• Disclosure, and compliance. 


TAX CONSTRAINTS 

SWFs receive tax-exempt status inside the country they benefit. 

Some regulators recognize tax-exempt status for SWFs; others tax SWFs similar to other taxable investors.



33h) Evaluate the investment portfolio of a private DB plan, SWF, university endowment, and private foundation. 


OBJECTIVES 

Budget Stabilization Funds (BSFs) 

Reserve Funds (RFs) 

“Capital preservation; real return with low probability of 

losses.” 

“Rate of return exceeding interest rate on monetary 

stabilization bonds.” 

Development Funds (DFs) 

Pension Reserve Funds (PRFs) 

“Real return in excess of real GDP and productivity growth.” 

Savings Funds (SFs) 

“Rate of return sufficient to defease future healthcare and 

pension liabilities.” 

“Perpetual real return sufficient to support ongoing 

governmental activities.”



33h) Evaluate the investment portfolio of a private DB plan, SWF, university endowment, and private foundation. 

The People’s Fund of Wigitania—A Pension Reserve Fund 

The People’s Fund is a pension reserve fund established by the government 

of Wigitania by setting aside current government surpluses. Its objective is to 

meet future unfunded social security payments caused by an aging population. 

The following is an extract from the People’s Fund IPS. 

Effective from 2030, the government will have the ability to withdraw assets to 

meet pension and social security liabilities falling due each year. Actuarial 

projections estimate annual payouts to be about 5% of the total fund value at 

that time. Given this level of cash flow, the Fund is expected to maintain most 

of its asset base for the foreseeable future. As such, 2030 does not represent 

an ‘end date’ for measurement purposes. A long-term investment horizon 

remains appropriate at present. However, the appropriate timeframe, risk 

tolerance, portfolio construction and liquidity profile may change. 

1. What are the liquidity needs of the People’s Fund? 

2. What factors does the Board need to consider when reviewing 

the Fund’s investment horizon? 

Board should consider two separate phases when reviewing the 

Fund’s investment horizon and investment policy: 

1 Accumulation phase - Lasts until 2030: 

• Investing with little to no liquidity needs; and 

• Investing with little concern for interim volatility. 

2 Decumulation phase - starts after 2030: 

• When the government expects to withdraw about 5% of the 

assets on an annual basis. 

Unfunded pension and 

social security liabilities 

Prior to 2030 –Low 

liquidity needs 

Post 2030 – High 

liquidity needs 

Expected to be about 5% of total fund value per 

year, starting in 2030. 

People’s Fund can invest a significant part of its 

portfolio in less-liquid alternative asset classes. 

Management must find sufficient liquidity at that 

time to meet those ongoing liabilities 

• The investment horizon, liquidity needs, and risk tolerance 

will need to be modified during this phase, which will affect 

the investment policy.




SOVEREIGN WEALTH FUNDS ASSET ALLOCATION BSFs Bonds dominate –defensive, relatively stable returns, and 

diversify against cyclically-sensitive factors (commodity prices) 

that drive government budget revenues in some countries. 

SFs 

RFs 

Cash follows, overall conservative SAA, partly explained by 

several major BSFs managed central bank or Ministry of 

Finance (typically risk averse entities) 

Tilted growth assets, equities, and AIs: 

Inter-generational, very long investment horizons. 

Similar SAA to SFS but less to AIs: 

Relatively higher liquidity needs given central bank activities. 

Public equities are the most liquid growth asset and help 

counter the negative carry generated by forex reserves, 

PRS 

Tilt to Bonds to reduce reserve funds’ portfolio volatility. 

Heavy tilt to equities, AIs (real assets, infrastructure): 

• Long-term investment horizons (but not necessarily intergenerational 

as with SFs); and 

• Low liquidity needs during their accumulation phases.


Endowments and Foundations 

Overview 

ENDOWMENTS 

Accept gifts and invest in 

capital markets to help 

fund ongoing activities for 

universities, churches, 

museums, and other 

nonprofit organizations. 

FOUNDATIONS 

Make grants to groups 

and individuals for 

social, educational, and 

other charitable 

activities. 

Social welfare

33c) Discuss the stakeholders in the portfolio, the liabilities, the investment time horizons, and 

the liquidity needs of different types of institutional investors. 


Stakeholders 

Current 

spending 

Future 

spending 

Administrators 

Endowments 

Foundations 

Trustees




Liabilities and Investment Horizon 

ENDOWMENTS 

University’s capacity for fundraising 

Percentage of annual funding 

provided by endowment 

Financial ability of 

university/endowment to issue debt 

Endowments and foundations both have perpetual time horizons.*




Endowment 

Spending policy 

Liabilities and Investment Horizon 

Defines how much of the net assets of the endowment 

fund is pout out to fund the university’s spending. 

Hybrid 

rule 

Spending rate is weighted average of the constant 

growth and market value rules (Yale Spending rule, 

weights can rage from 30 – 70%). 

Strikes balance between the shortcomings of both rules 

Constant rule 

Market value Rule 

Spending rate is a fixed amount annually adjusted for 

inflation (the growth rate). 

Disadvantage: 

Not linked to AUM –weak (strong) performance means 

spending rate as % of AUM becomes high (low). 

Will need to be completed with caps and floors, about 4- 

6% of AUM. 

Spending rate is a pre-specified % of the moving average 

of assets (4-6%), smoothed over 3-5 years MA. 

Disadvantage: 

Tends to be procyclical: when markets perform well 

(poorly), overall payout increases (decreases) 

( t)( ) ( )( )( ) 

Spending = t 1 

w Spending 1 + I + 1 − 

+ 

w Spending rate AUM 

where 

w = weight of prior period spending 

w = 0 Market value rule 

0 w 1 Hybrid rule 

w = 1 Constant growth rule




Liquidity Needs –Relative low 

ENDOWMENTS 

FOUNDATIONS 

Annual Spend of 

2‒4% of net Assets 

VS. 

Annual Spend of 

5% of Net Assets 

Donor- and budget funding‒dependent spend rate. 

Mandated minimum spend rate (US) 

Fund may have liquidity risk maximum (total NAV in illiquid 

investments/total AUM) that triggers commitment reduction/ 

stoppage or sale of illiquid investments.



Comparison Between Private US Foundations and US University Endowments 

Purpose 

US FOUNDATION 

Grant-making for social, educational, and charitable purposes; principal 

preservation focus. 

US UNIVERSITY ENDOWMENT 

General support of institution or restricted support; 

principal preservation focus. 

Stakeholders 

Founding family, donors, grant recipients, and broader community that 

may benefit from foundation’s activities. 

Current/future students, alumni, university faculty and 

administration, and the larger university community. 

Liabilities/Spending Legally mandated to spend 5% of assets + investment expenses + 100% 

of donations (flow-through). 

Flexible spending rules (headline spending rate 

between 4% and 6% of assets) with smoothing. 

Other liability considerations Future gifts and donations, or just one-time gift? 

Gifts and donations, percentage of operating budget 

supported by endowment, and ability to issue debt. 

Investment time horizon Very long-term/perpetual (except limited-life foundations). Perpetual 

Risk High risk tolerance with some short-term liquidity needs. High risk tolerance with low liquidity needs. 

Liquidity needs Annual net spending is at least 5% of assets. Annual net spending is typically 2% to 4% of assets, 

after alumni gifts and donations.



Legal and regulatory constraints 

UPMIFA (US—2006) 

Trustee Act (UK—2000) 

Total return basis (MPT) 

Appropriate diversification (MPT) 

5% spending (foundations) 

Duty of care 


Tax constraints 

Tax-exempt status: 

• Donors receive tax deduction (up to some limit). 

• Tax-exempt investment income and capital gains (at least for universities, religious organizations, and museums). 

• Donations from Endowments and Foundations to for-profit institutions are taxable. 

Foundations, which are subject to 5% minimum spend, pay 30% tax against undistributed funds below that minimum.





Objectives 

Endowments 

Primary Objective 

Achieve investment returns sufficient to support university 

budget in perpetuity, after outside contributions: 

“Achieve X% total real rate of return over K years with Y% 

expected volatility.” 

Inflation: HEPI 

Secondary Objective (optional) 

Outperform long-term policy benchmark. 

Foundations 

Primary Objective 

“Generate 5% real return, net of investment expenses, with 

reasonable expected volatility over a 3- to 5-year period.” 

Secondary Objective (optional) 

Outperform the long-term policy benchmark within tracking 

error limits. 

Tertiary Objective (optional) 

Outperform predefined set of peers.




Investment Objectives of the Ivy University Endowment 

1. Draft the investment objectives section of the IPS of the Ivy Univ Endowment. 

The Ivy University Endowment was established in 1901 by Ivy 

University and supports up to 40% of the university’s operating 

budget. Historically, the endowment has invested in a traditional 20% 

public US equities and 80% US Treasury portfolio, entirely 

implemented through passive investment vehicles. 

The investment staff at the endowment is relatively small. Endowment 

assets are US$250 million, and the endowment has an annual 

spending policy of paying out 5% of the 3-year rolling asset value to 

the university. 

An investment consultant hired assist with the investment policy 

review has provided the following 10-year (nominal) expected return 

assumptions for various asset classes: 

• US equities: 7% 

• Non-US equities: 8% 

• US Treasuries: 2% 

• hedge funds: 5%, and 

• private equity: 10%. 

Additionally, the consultant believes the endowment could generate 

an extra 50 bps per year in alpha from active management in equities. 

Expected inflation for the next ten years is 2% annually. 

Mission Maintain purchasing power of its assets while financing up to 40% 

of Ivy University’s operating budgeting in perpetuity. 

Investment 

objective 

Achieve a total real rate of return over the Higher Education Price 

Index (HEPI) of at least 5% with volatility of returns ≤15% annually. 

2. Discuss whether the current investment policy is appropriate given the 

investment objectives of Ivy University Endowment. 

20/80 portfolio E® = 0.2 × 7% + 0.8 × 2% = 3% per year (nominal) 

Expected INFL 2% 

Summary 

1% real rate of return, falls well short of the 5% spending 

rate and the stated objective of a 5% real rate of return. 

Endowment’s purchasing power deteriorate over time if it 

continues with its current asset mix and spending rate. 

3. What decisions could the CIO and board of the Ivy University Endowment 

take to align the investment policy and the spending policy? 

SAA mix 

Spending rate 

Combination 

Adopt asset mix with better probability of achieving a 5% real 

rate of return (SAA including non-US equities and PE); 

Change spending rate to more accurately reflect the expected 

real rate of return of the current investment policy 

CIO may want to recommend a combination of both.

33c) Discuss the stakeholders in the portfolio, the liabilities, the investment time horizons, and the 

liquidity needs of different types of institutional investors. 

33i) Describe considerations affecting the balance sheet management of banks and insurers. 

Banks and Insurers—Stakeholders 

Customers 

Banks 

Insurers 

Employees 

Management 

Directors 

Policy holders




Banks and Insurers— 

Liabilities and 

Investment Horizon 

BANKS 

INSURERS 

Demand deposits (ATM, checking) 

Expected claims 

Time deposits (CDs) 

Varies with product line: 

• Life claims—longer duration 

• Annuities—shorter duration 

Wholesale funding (Fed Funds and 

central bank loans) 

P&C has shorter duration, less 

probability 

As corporations, both banks and insurance companies have a perpetual time horizon; their 

liabilities have product-specific duration.

Banks and Insurers—Liquidity 




Banks 

vs. 

Insurers 

Short-duration deposits, uncertain 

timing 

Increased liquidity during adverse 

markets 

Higher-quality, lower-earning assets 

since regulation after 9/11 

Life Insurance: Interest rates 

P&C Insurers: Claims, timing 

Rising interest can cannibalize 

policies 

More cash/equivalents





Banks and 

Insurers—Legal 

and Regulatory 

Constraints 

Supranational and national bank regs 

Adequate capitalization 

Asset liability quality 

Diversification of assets/liabilities 

NAIC (insurers)/state oversight 

Banks with largest portfolios have lower volatility and lower funding costs. Banks become larger 

and larger, so the financial system has designated some banks as too big to fail.





Banks and Insurers— 

Tax and Accounting 

Considerations 

GAAP/IFRS—Shareholders (or members in the case of mutual companies), deposit or 

policyholders, and suppliers of debt capital. Smoothest reporting of value changes. 

Economic/Mark-To-Market (MTM)—Contemporaneously recognizes market value 

changes in assets/liabilities net of imputed taxes. Most volatile value changes. 

Statutory accounting (regulators)—Differs by national and local jurisdictions. Used 

by regulators to establish capital adequacy but usually also available to the public. 

Subtracts intangible assets and accelerates policy underwriting and sales costs. 

Banks and insurers are taxable entities and consider decisions in terms of 

after-tax return.




Banks and Insurers—Objectives 

Banks 

Insurers 

“Maximize long-term portfolio yield consistent with 

liquidity needs, pledging requirements, asset/liability 

management strategies, and safety of principal.” 

Asset/liability management committee (ALMCo) sets the 

IPS, monitors the portfolio, and mandates asset/liability 

adjustments. 

“Earn a return sufficient to fund all policyholder liabilities and 

match or exceed expected returns factored into product prices 

as well as contribute to the growth of surplus through capital 

appreciation.” 

A detailed IPS objective should encompass an insurer’s risk 

appetites, including market, credit, and interest rate risk. 

ALMCo also ensures interest rate/FX, credit, liquidity, and 

solvency (capital adequacy) risk is within tolerance.


Balance sheet A = L + E (assume all assets are financial) 1 

Balance sheet changes ΔA = ΔL + ΔE | → ΔE = ΔA - ΔL 2 

Isolate leverage (A/E) 

Divide through by E 

Equation 4 

ΔE = ΔA - ΔL 

E E E 

Multiply by 1: A/A, L/L ΔE = ΔA x A - ΔL x L 

E E A E L 

Re-align ΔE = ΔA x A - ΔL x L 

E A E L x E 

Substitute L = A - E ΔE = ΔA x A - ΔL x A-E 

E A E L x E 

Resolve ΔE = ΔA x A - ΔL x (A) - 1 

E A E L E 

How percentage changes in market value of both assets and 

liabilities are magnified by the leverage factors. 

3 

4 

Exhibit 22: 

MV E capital as a 

function of: 

• Declines in asset value (credit quality; liquidity of loans 

or securities held; rising interest rates (if fixed-rate loans). 

• Beginning leverage 

Finding 

Small losses in the MV assets (or increases in liabilities) has 

significant impact effect MV E capital (inverse is true). 

Exhibit 23 

MV E capital as a 

function of: 

• Increases in its liabilities (forward-funding commitment to 

a struggling company, the exercise of a guarantee, or 

high policy loss claims in case of insurers) 

• Beginning leverage 

Note 

Equity holds only loose value of investment but gain all when 

MV E capital rises 

Creditors gain nothing, must be protected from such volatility 

relative to the base capital level! Refine framework further!


Leverage equation ΔE = ΔA x A - ΔL x (A) - 1 

E A E L E 

Divide by reference yield, Δy ΔE = ΔA x A - ΔL x (A) - 1 

EΔy AΔy E LΔy E 

Multiply by 1: Δi / Δi in the 

appropriate location 

Recall, MDUR of asset W with 

respect to its YTM, r: 

ΔE = ΔA x A - ΔL (Δi) x (A) - 1 

EΔy AΔy E LΔi Δy E 

D W * = ─ ΔW 1 

W Δr 

Re-arrange Q 6 D E * = D A * x A - D L * x (A - 1) x (Δi) 

E E Δy 

4 

5 

6 

7 

8 

For modest yield Δs, the volatility of a 

Bank/insurer’s equity capital is a function of: 

• Comparative MDUR A and MDUR L ; 

• Degree of leverage, and 

• Correlation (sensitivity) of Δs in yields of As and Ls. 

Exhibit 24 /25 • Differing initial A/E (5, 10) (based on E/A of 20%, 10%), with correlation in returns 

between A & L, di/dy = Δi/Δy = 0.90 

Finding • High capital ratios (20%), volatility swings -10 to +15 

• Low capital ratio (10%) volatility swings -30 to + 25 

Implication • Regulators not keen to see very high durations for equity capitalization, so we must 

keep assets and liabilities from having large differences in duration. 

Lower A DUR 

Extend L 

DUR 

Hold cash, deposits at central banks, foreign currency reserves; loans (business, 

credit cards, etc) at floating rates. Fixed-rate mortgage loans are securitized. 

Issuance of medium to LT debt instruments, and perpetual preferred stock; use 

financial futures and interest rate swaps to alleviate asset/liability mismatches.


MegaWorld Bancorp has an equity capital ratio for financial assets of 

9%. The modified duration of its assets is 2.0 and of its liabilities is 1.5. 

Over small changes, the yield on liabilities is expected to move by 85 

bps for every 100 bps of yield change in its asset portfolio. 

1. Compute the modified duration of the bank’s equity capital. 

3. Management is considering issuing common stock, selling 

investment portfolio assets, and paying off some liabilities in order 

to achieve an equity capitalization ratio of 10%. Assuming no 

change in the durations of assets and liabilities and assuming no 

change in the sensitivity of liability yields to asset yields, what is 

the resulting MDUR of the bank’s equity capital? 

Re-arrange Q 6 D E * = D A * x A - D L * x (A - 1) x (Δi) 

E E Δy 

A/E 1/0.09 = 11.11 

A/E - 1 11.11 – 1 = 10.11 

D A * 2 

D L * 1.5 

Δy 0.85 

D E * (11.11 × 2) − (10.11 × 1.50) × 0.85 = 9.33 

8 

With this less 

leveraged 

balance sheet 

A ÷ E = 1/0.1 = 10; 

(A ÷ E) − 1 = 9 

D E * = (10× 2) − (9 × 1.50) × 0.85 = 8.53 

4. Using the facts in question 3 but assuming the bank 

rebalances its investment portfolio to achieve a MDUR A = 1.75, 

what happens to the duration of the bank’s equity capital? 

2. What would be the impact on the value of shareholder capital of a 

50 basis point rise in the level of yields on its asset portfolio? 

Equation 7 D W * = ─ΔW 1 

W Δr 

0.5% × −9.33 = −4.67%. 

Duration of 

shareholders’ 

capital now 

declines to: 

D E * = (10 × 1.75) − (9 × 1.50) × 0.85 = 6.03


Equation 6 ΔE = ΔA x A - ΔL (Δi) x (A) - 1 

EΔy AΔy E LΔi Δy E 

Equation 7 D W * = ─ ΔW 1 

W Δr 

Equation 8 D E * = D A * x A - D L * x (A - 1) x (Δi) 

E E Δy 

Model 

critique 

The above duration analysis captures the effects of only 

small Δs in interest rates and only over short time intervals: 

The duration model does not reflect well on non-linear 

factors, such as convexity and embedded options in many 

fixed-income securities and derivatives. 

Furthermore, changes in the overall levels of interest 

rates are only one source of volatility 

RECALL: σ p 

2 

w A2 σ A2 + w B2 σ 2 B + 2w A w B σ A σ B ρ A,B [−1 ≤ ρ ≤ 1] 

Equation 9 

Re-states Equation 6, in terms of volatility of the key 

components, incorporating correlation, key to LDI 

Exhibit 26 

Over the range of leverage (E/A 5% to 20%), volatility of the MV E 

decreases as the ρ between A and L value changes (ρ) increases 

toward +1.0. Most beneficial effect when highly leveraged. 

With ρ of 0.5 and 0.9, vol gap is is only 6.9% vs 3.5% for a leverage 

ratio of 20 vs 5. But it becomes dramatic 30.1 when ρ is reduced to 0.5 

If the ρ A,L is 1.0, the volatility MV E shrinks to minimal amounts, even for 

high leverage (E/A = 5.0%). 

Flip side, any divergence in ρ (e.g., turbulent markets) causes equity 

volatility to increase, and dramatically so when leverage is high.


Foresight is an international multiline insurance conglomerate. Under its 

overall strategic financial plan, it computes the annualized SD of returns on 

investment assets as 5.0% and on liabilities as 2.5%. The bulk of its 

liabilities are constituted by the Net Present Value of expected claims 

payouts. The correlation between asset and liability returns is therefore a 

very low 0.25. Foresight’s common equity to financial assets ratio is 20.0%. 

1 What is the SD of changes in the value its shareholder capitalization? 

Management believes it also needs to lower the volatility of its assets. It 

shifts out of low-quality bonds into higher quality, more liquid gov’t securities, 

expecting to lower the SD of asset returns to 4.0% per year without having 

any impact on the correlation ratio between assets and liabilities. 

4 Along with the stronger capital ratios premised in question 2, what does 

this do to the volatility of shareholder equity value? 

σ 2 ΔE/E = 4 2 × 0.04 2 + 3 2 × 0.025 2 − 2 × 4 × 3 × 0.025 × 0.25 × 0.05 = 0.025225 

Standard Deviation = √0.025225 = 0.159 = 15.9% per year ↓ 

A / E = 1/0.20 = 5; (A / E) −1 = 5 – 1 = 4 

σ 2 ΔE/E = 5 2 × 0.05 2 + 4 2 × 0.025 2 − 2 × 5 × 4 × 0.025 × 0.25 × 0.05 = 0.06. 

Standard Deviation = √0.06 = 0.245 = 24.5% per year. 

Management believes the overall risk profile of the company is too high and 

desires to increase the common equity ratio by issuing additional shares of 

common equity and listing such shares on several international stock 

market exchanges. The new target equity ratio will be 25.0%. 

2 All else same, how does this impact the volatility of value changes in 

shareholder capitalization? 

A / E = 1/0.25 = 4; (A / E) −1 = 4 – 1 = 3 

σ 2 ΔE/E = 4 2 × 0.05 2 + 3 2 × 0.025 2 − 2 × 4 × 3 × 0.025 × 0.25 × 0.05 = 0.0381256. 

Standard Deviation = √0.0381256 = 0.195 = 19.5% per year↓ 

5 What is the impact of the various portfolio and capitalisation changes 

on the value of Foresight’s common shares outstanding? 

Fall in EPS 

Fall in E(Rs) on assets 

Impact analysis 

Fall in E(Rs) on assets: 20.0% to 25.0% shift. 

Raising A/E (equity target) from 20.0% to 25.0% 

Increase number of shares outstanding. 

Lowering its equity risk exposure: 5.0% to 4.0% 

Reputation as better operated and capitalized 

Lower risk profile might improve credit rating 

Lower discount rate applied to lower EPS trajectory 

Greater percentage of safer, lower yielding assets. 

Improved long-term survivability and underwriting strength 

could result in a higher long-term growth outlook. 

Share price 

The impact on MV E cannot be predicted merely by a Δ in capital structure 

and near-term reduction in earnings and portfolio expected returns. 

↓ 

↑ 

↑ 

↑ 

↑ 

↑


SWFs, Endowments, 

Foundations, DB/DCs 

Financial institutions 

[Banks and Insurance 

Companies] 

Implementation of Portfolio Decisions 

Investment adviser must primarily focus on the 

investment of assets (Asset Only) 

ΔA = ΔL + ΔE | → ΔE = ΔA - ΔL 

ΔE = ΔA x A - ΔL x (A) - 1 

E A E L E 

Optimal management focuses on liabilities, 

• Particularly the volatility; and 

• Convexity of asset and liability payouts. 

Investment strategy must also consider the, 

• Appropriate degree of leverage; and 

• Total amount of common equity capital. 

Max long-term economic earnings: Raise leverage Lower leverage 

• Portfolio of assets Acquire Dispose 

• Portfolio of liabilities Underwrite Retire 

• Capital stock Repurchase Issue 

Financial management 

Focus 1 –Markets 

Focus 2: Capital 

Focus 3 –Competitor/s 

Focus 4 -Regulators 

Summary 

Banks and Insurance Companies (B/Is) 

Monitor the level and direction of key markets and 

factors as they impact the investment portfolio: 

• Interest rates, 

• Credit spreads, 

• Derivatives markets, 

• Economic cycles, and 

• Stock markets 

Master valuation of own common equity and debt 

capital securities. 

Requires a view on the actions of competitors: 

• Will they create a housing bubble through 

excessive lending to low-quality borrowers? 

• Will they drive down insurance policy premiums 

through overly aggressive underwriting? 

Meet existing regulations, and new ones that will 

evolve with changes in global economic 

circumstances and other political pressures. 

B/Is attempt to create positive NPV for capital holders by 

solving simultaneously several different conditions with several 

different variables (1 to 4). Key decisions at strategic level. 

Specific analysts and investment managers are assigned only 

to specialized subsets of their varied assets and liabilities.

Mini-Case A: 


A bank considers reducing its ownership of 

commercial loans in smaller businesses. These loans 

pay interest quarterly at various contractually prespecified 

spreads above the floating market reference 

rate (MRR). The runoff of the loan portfolio through 

repayments, together with proceeds of outright sales 

and securitizations of other loans, are to be reinvested 

in a portfolio of fixed-rate government securities of 

comparable maturities. 

The securities will be hedged fully against general 

interest rate risk through the use of publicly traded 

options and futures on government securities. 

Additionally, hedging interest rate risk completely would 

create a synthetic variable rate asset: 

• If interest rates rise, gains on hedges can be 

reinvested to raise overall portfolio income; 

• If interest rates fall, losses on hedges will require 

some assets to pay counterparties, thereby lowering 

overall portfolio income. 

1 How would this portfolio restructuring affect the asset/liability profile of the 

bank? 

Strategy 

Switch from variable to fixed-rate 

assets of similar maturities. 

Hedging positions on fixed-rate 

assets. 

Net effect of the portfolio alteration. 

Duration impact on overall portfolio. 

Increases duration. 

Shorten overall duration. 

Little effect on existing asset/liability 

duration profile, as floating-rate 

corporate loans also have little price 

exposure in the event of rising or 

falling interest rates. 

2. What is the expected impact on the volatility of bank shareholder equity 

valuation? 

Small business 

loans 

Liquidity Less liquid More liquid 

Sensitivity to volatility arising 

from changes in credit default 

Net effect of the portfolio alteration. 

More sensitive 

Hedged portfolio of 

government securities 

Less sensitive 

Overall volatility of assets and 

capitalisation should decrease

3. What is the likely impact on bank earnings? 


Switch from Higher Yields on B-loans, adjusting for expected default 

rates→ Lower Yields on G-sec, adjusting for the costs of hedging. 

If overall interest rates subsequently rise 

Bank earnings 

↓ 

Bank earnings 

B-loan portfolio Should generate higher income to the bank. ↓ 

4. What are reasons that argue in favor of this portfolio 

redeployment, despite the lower expected earnings? 

Liquidity 

Bank believes it needs to have a more liquid 

investment portfolio because of the risk of 

unexpected claims against assets. 

G-sec portfolio Should generate lower income to the bank. ↑ 

The portfolio 

value is 

approximately 

unchanged 

Rates up 

Rates down 

Underlying G-sec portfolio Market value drops Market value up 

Hedges on G-sec portfolio Offsetting gains Offsetting loses 

Impact 

Both portfolios have 

similar modified 

durations 

Permits more investment in now 

high yield G-sec portfolio 

Sale of appreciated 

underlying G-sec to 

cover hedge losses. 

But, the (reduced) ability to generate income has tracked interest 

rates downward. 

Changes in overall interest rates impact income-generating ability 

similarly for both the B-loan hedged G-sec portfolio. 

In any environment, the net yields on the hedged G-sec are 

lower than on the B-loans. Thus, bank net income is 

unambiguously lower due to the portfolio rebalancing. 

Regulation 

Business 

cycles 

In all three 

rationales 

The bank needs to raise its regulatory “equity to 

risky assets” ratio (by substituting low credit-risk 

for high credit-risk assets). 

The bank believes it will be able to reverse the 

trade in the future after a recession has driven 

up the effective default-adjusted spreads (i.e., 

driven down the prices) on small business loans. 

1. Overall volatility is expected to decline 

2. Reduction in volatility is expected to provide 

a benefit that more than offsets the 

anticipated reduction in earnings. 

3. Therefore, the risk-adjusted return is 

projected to rise.


Mini-Case B: 

A medium size insurer plans to sell a large portion of its diversified, 

fixed-rate, I-grade-rated securities in order to redeploy proceeds into a 

special purpose trust holding a diversified portfolio of automobile loans 

with original loan lives of 5 years. The loans are collateralized by 

direct liens on the vehicles, and the underlying borrowers meet 

minimum consumer credit scores set by a national credit rating 

agency. The underlying loans were randomly selected for the trust, 

and the collateral constitutes a nationwide sample of automobiles of 

different foreign and domestic manufacturers. 

1. What does this transaction reveal about is it regulatory capital 

• Portfolio redeployment to auto loans reduces the insurer’s liquidity. 

• These underlying illiquid auto loans require more regulatory capital 

than high-quality/I-grade, marketable, fixed-income securities. 

• Therefore, the insurance company has excess regulatory capital. 

2. What key info must the insurer know about the auto loans held by 

the trust in order to manage its asset/liability duration profile? 

Overall 

change in 

asset/liability 

profile for the 

insurer 

Depends on projected MDUR of the auto loans vs the I- 

grade to be sold. A material difference requires: 

a) Δs in the MDUR of insurer’s liabilities, such as by 

altering the maturities of future debt issuances; or 

b) implementation of interest rate-hedging transactions. 

3. What external factors might the insurer need to consider with 

respect to the duration of trust assets? 

Factors with adverse impact on the value of the 

auto loan (compared with the highly liquid I-G 

sold) and which could undermine the cash flow 

assumptions made with respect to setting the 

company’s overall asset/liability profile. 

• An adverse 

change in the 

economic cycle, 

• Changes in 

technology, and/or 

• Energy prices 

4. What is the expected impact from the proposed investment 

transaction on (a) the insurer’s earnings, and (b), the overall 

volatility of the insurer’s common equity capitalization? 

Actuarial projections 

of contractual cash 

flows from the auto 

loans, taking into 

account: 

• Full and partial pre-payments because of 

accidents, auto trade-ins, and loan defaults. 

• The acceptable credit quality of the 

borrowers and the geographical and brand 

diversity 

Earnings↑ 

Volatility↑ 

Because the expected yield on the auto loans, net of credit 

losses, is higher than for I-grade, liquid securities. 

Insurer is taking on more credit risk: 

→Higher volatility of the value of assets 

→Higher volatility of equity capitalization.


Mini-Case D: 

Floating-rate securities, paying a fixed spread over the floating MRR, are 

trading at historically narrow yield spreads over MRR. In addition, issuers 

of these securities tend to be concentrated in a small no. of industries— 

notably in banks, insurers, and other financial services companies. 

A bank considers selling the bank’s portfolio holdings of these floating-rate 

securities, which have a 5-year maturity and trade at 0.1% over MRR; and 

buy more-diversified (by issuer type), I-grade, fixed-rate securities that are 

selling at more normal spreads versus G-bond yields of comparable 

duration (which trade at 1.0% over 5-year US Treasury bond yields). 

The fixed-rate securities portfolio is to be combined with pay-fixed/receivefloating 

interest rate swaps under standard mark-to-market (MTM) 

collateralization terms. The 5-year interest rate swap terms permit one to 

receive MRR while paying 0.4% over Treasury yields. 

1. Impact of portfolio alteration on required regulatory risk-based capital? 

2. What suggests the bank’s senior managers are more concerned 

about risks to equity capitalization than are regulators? 

Securities 

Senior 

managers 

more 

concerned 

about 

systemic 

risk in the 

financial 

sector 

Short 

Floating rate concentrated 

in banks, insurers… 

Long 

Fixed rate more-diversified 

(by issuer type) 

Especially as the securities they plan to short are 

concentrated in the financial sector and are trading at 

unusually high prices (narrow spreads to MRR). 

They believe prospective volatility of floating-rate bank 

assets (and own equity capital) —is higher than 

reflected in the regulatory risk-weight framework, 

which does not take into account relative price risk. 

Thus, from the bank’s perspective, the proposed trade 

lowers asset and equity volatility. 

3. Expected effect on the bank’s asset/liability profile? 

Floating-for-Floating, 

5-to 5; 0.1% to 0.4% 

New portfolio has 

more industry 

diversification 

Little change in average credit quality, hence little 

effect on regulatory risk-based capital 

requirements. 

Thus, under robust scenario simulation testing, it 

should be more resistant to loss than the moreconcentrated 

portfolio assets being sold. 

1. Long fixed-rate and selling floating increase MDUR of bank assets. 

2. The pay-fixed/receive-floating swap is a synthetic liability, becomes 

(i) smaller as interest rates rise and (ii) greater as interest rates fall. 

3. The pay-fixed/receive-floating swap therefore increases the DUR of 

the bank’s liabilities to counterbalance the rise in asset duration.


4. What is the expected effect on expected earnings? 

Securities 

Short 

Concentrated 

in banks, 

insurers… 

Long (new portfolio) 

More-diversified (by issuer type) 

Comprises fixed-rate securities + payfixed/receive-floating 

interest rate swap 

Receipts MRR + 0.1% Fixed rate securities: 

• Receive 5-year T-yield (T) + 1.0% 

Net 

outcome 

MRR + 0.1% 

Net outcome of the hedged, 

fixed-rate holdings 

Impact on earnings 

Fixed rate leg of the interest rate swap: 

• Pay 5-year T-yield (T) + 0.4% 

Floating rate leg on the interest rate swap: 

• Receive MRR 

= T + 1.0% − (T + 0.4%) + MRR 

= MRR + 0.6%. 

This synthetic floating-rate portfolio 

compares with the original floating-rate 

portfolio that paid just MRR + 0.1%. 

Earnings are expected to rise. 

5. Summarize the rationale for the portfolio alteration. 

Securities 

Lower risk 

Better yield 

Liquidity 

Regulatory 

system 

Summary of 

trade results 

Short 

Floating-rate 

securities 

Lower 

systemic 

financial risks 

Long (new portfolio) 

Fixed-rate securities 

+ pay-fixed/receive-floating rate swap 

Better diversification 

Cheap (higher yielding) synthetic MRR 

floaters in place of true MRR floaters. 

A pay-fixed/receive-floating interest rate 

swap is “plain vanilla”; it is easy to value 

and unwind, so no major adverse impact 

on the institution’s liquidity. 

Has a statistical system that penalizes 

excessive use of derivatives by deeming 

worst-case liabilities in a stress test. 

Bank might believe this is no issue if the 

proposed trade is small enough, relative 

to the institution’s size, to have no 

significant impact on stress test results. 

Trade is duration-neutral trade, secures higher net 

earnings and lower asset and equity risk without 

significantly impacting the bank’s regulatory capital ratios.


Mini-Case D: 

In the aftermath of prolonged financial turmoil and a recession, a large 

pan-European life insurance company believes that corporate debt 

securities and asset-based securities are now very attractive relative to 

more-liquid government securities. The yield spreads more than 

compensate for default and credit downgrade risk. Interest rates for 

government securities are near cyclical lows. The insurance company is 

concerned that rates may rise and that, as a result, many outstanding 

annuities might be surrendered. 

The insurer believes the probability of a large, adverse move in interest 

rates is much higher than is currently reflected by the implied volatility of 

traded options on government securities in the eurozone. The insurer’s 

regulatory capital and reserves are deemed to be healthy. 

1. What are the consequences of lowering allocations to G-sec and 

raising allocations to corporate and asset-backed securities? 

C-Debt Sec G-sec A-backed sec. 

Maturity Similar Similar Similar 

Yields Higher Lower 

Duration Shorter Longer Lowest EFFDUR 

Duration 

Liquidity 

Regulatory 

capital 

The 

proposed 

portfolio 

moves make 

sense only if: 

Expected 

earnings 

Impact on overall portfolio: 

Lower, which is consistent with the insurer’s concerns 

about rising interest. 

Lower as corporate and asset-backed securities are 

less liquid. 

Lower regulatory risk-based capital measures, 

because the new securities are treated less favorably 

for regulatory purposes: 

• Less liquid, higher credit risk corporate debt and 

asset-backed securities require a higher equity 

charge than liquid, low credit risk government 

securities, so regulatory “equity to risky assets” is 

reduced). 

• The regulatory capital position of the insurer is 

already ample. 

• The existing liquidity elsewhere in the portfolio is 

enough to fund an uptick of annuity surrenders in 

the case of rising interest rates. 

The reallocation would increase expected earnings 

(from higher interest income) and set the stage for 

price gains if credit spreads versus government 

securities contract to more normal levels.


Mini-Case D: 

In the aftermath of prolonged financial turmoil and a recession, a large 

pan-European life insurance company believes that corporate debt 

securities and asset-based securities are now very attractive relative to 

more-liquid government securities. The yield spreads more than 

compensate for default and credit downgrade risk. Interest rates for 

government securities are near cyclical lows. The insurance company is 

concerned that rates may rise and that, as a result, many outstanding 

annuities might be surrendered. 

The insurer believes the probability of a large, adverse move in interest 

rates is much higher than is currently reflected by the implied volatility of 

traded options on government securities in the eurozone. The insurer’s 

regulatory capital and reserves are deemed to be healthy. 

2. Are there steps that the insurer should take on the liability side? 

Asymmetric risk 

Purchase OTM 

puts on G-Sec 

Purchas 

swaptions with 

the right to be a 

fixedpayer/floatingreceiver. 

A spike up in interest rates could result in a rise in 

surrenders of annuities during a time when asset 

values are coming under pressure. 

Company seems more concerned about higher 

interest rate volatility than is reflected in current option 

prices, so consider: 

Becomes valuable to the holder if prices of the 

underlying asset fall (following a rise in rates) 

Economically analogous to a put option on a bond: 

• Gain if rates rise by receive a rising stream of 

floating payments in exchange for what will have 

then become a stream of reasonably low fixed 

payments. 

• This would offset some of the burden of premature 

annuity surrenders. 

Two issues with 

low interest 

rates on liability 

side 

Reallocation investment portfolio (question 1) 

Leverage is higher, deal with an asymmetric risk, alter 

the bank liability profile to minimize potential adverse 

changes in its common equity capitalization 

If time passes without any substantial rise in interest 

rates, the cost of purchasing option protection would 

detract from the incremental benefits from the 

proposed switch into higher yielding securities.


Portfolio Strategy 


Main Factors 

Affected 

Explanation/Rationale 

Additional Regulatory Concerns 

Diversified fixed-income 

investments 

Decreases 

σΔA / A 

Debt securities are less volatile than common equities, real 

estate, and other securities. 

Effective diversification, multiplicity of issuers 

and industries, domestic/ foreign. 

High-Quality bond/debt 

investments 

Match asset and liability 

durations, KRD, and sensitivity 

to embedded borrower and 

claimant options 

Common Stock Investments 

Derivatives transparency, 

collateralization 

Liquidity of portfolio 

investments 

Decreases 

σΔA / A 

Increases ρ 

Increases 

σ ΔA /A, 

typically 

decreases ρ 

Decreases both 

σΔA/ A 

and σΔL / L, and 

increases ρ 

Decreases 

σΔA / A 

Less likely to be downgraded or default, thereby lessening 

the probability of significant loss of value through either 

losses or widening of credit spreads. 

Requires more in-depth analysis than simple durationmatching 

strategy, because must account for convexity and 

asymmetric payoffs due to (i) defaults, (ii) principal payoffs 

prior to maturity, and (iii) annuity, life-insurance policy, and 

bank CD surrenders in high interest rate scenarios. 

Only slight diversification benefits while adding to volatility. 

Also, common stock returns do not correlate well with 

financial institution returns, which pushes correlation, ρ, 

away from 1.0 toward 0.0. 

Whether derivatives are used to hedge or synthesize (i) 

assets or (ii) liabilities, the more “plain vanilla” (and 

protected against counterparty default) they are, the less 

likely they will revalue in unexpected directions. 

Includes short-maturity debt securities of highly rated 

issuers, currency reserves, access to credit lines, and 

access for banks to emergency central bank borrowing. 

Regulatory structures and central banks favor 

sovereign issuers for this reason. 

Regulatory structures penalize institutions 

with unjustifiable asset/liability mismatches. 

Regulatory structures require 100% or more 

risk weighting for common stock investments, 

thus such investments are ineligible for 

backing financial liability issuance. 

Transparency fosters regulatory “financial 

stress test” confidence. It also allows 

regulators and claimants to ascertain whether 

derivatives are being used in a justifiable 

manner. 

Problems occur for regulators when financial 

contagion extends beyond just a few 

institutions.


Portfolio Strategy 


Main Factors 

Affected 

Explanation/Rationale 

Surrender penalties Decreases σΔL / L Cushion losses to financial institutions for having to pay back 

liabilities “at par” when rising interest rates would otherwise 

have reduced the discounted present value of the obligations. 

Prepayment 

penalties on debt 

investments 

Catastrophic 

insurance risks 

Predictability of 

underwriting losses 

Diversifying 

insurance business 

Variable annuities 

Increases ρ 

Increases σΔL/L 

Decreases σΔLL 

Decreases σΔL / L 

Increases ρ, and σΔA 

/ A, 

σΔL / L diminish in 

relevance 

When interest rates are declining, borrowers must incur a 

penalty to repay loans at par to refinance. 

Also, prepayment penalties help institutions offset rising 

values of their fixed-rate liabilities in falling rate environments. 

By definition, these losses faced by insurance companies are 

less predictable and possibly very large. 

High frequency, low cost loss events caused by law of large 

numbers make total insurance liabilities less uncertain. 

Diversifying across several business lines increases 

aggregate risk-reduction potential (due to law of large 

numbers). 

Where equity/bond market risks are fully borne by 

policyholders, the correlation between asset and liability 

returns approaches 1.0, independent of investment 

performance of the underlying, segregated account assets. 

Additional Regulatory Concerns 

Regulators/customers do not tolerate 

economically justified surrender penalties (priced 

too low to offset the institution’s risk). 

None. 

Regulators and insurance customers usually 

expect (i) higher capital ratios, (ii) higher quality 

and liquid investment portfolios, and (iii) strong 

reinsurance agreements compared with typical 

home, health, auto, and fire insurance. 

Adverse changes in legal or regulatory systems 

cannot be offset by actions on the asset side of 

the financial institution. These are risks borne by 

owners of the institution’s equity capital. 

None. 

Assuming adequate risk disclosure to 

policyholders, and sufficient asset custody 

protections, regulators permit greater investment 

flexibility than in insurer’s standard business 

lines.


Decrease Asset Volatility 

• Increase FI portfolio diversification 

• Increase FI asset quality 

• Increase FI asset liquidity 

• Reduce equity allocation 

Decrease Liability Volatility 

• Surrender penalties 

• High loss predictability 

• Diversified policy base 

Increase Correlation 

• Duration mismatch 

• Key rate duration 

• Embedded option management 

• Prepayment penalties 

• Variable annuities; decrease relevance of 

asset-liability volatility 

• Reduce equity allocation 

Increasing derivatives transparency/collateralization both decreases asset and liability transparency 

AND increases correlation.


Reading 33: Portfolio Management for Institutional Investors 

Reading 34: Trading, Performance Evaluation and Manager Selection

34a) Discuss motivations to trade and how they relate to trading strategy. 

Profit seeking 

Risk mgt/ 

hedging needs 

To generate positive risk-adjusted alpha in excess 

benchmark by trading on superior signals: 

• Trade urgency is fast, to minimise risk of alpha decay. 

• Value (long-term) strategies trades on undervalued 

companies, it is less short term and less urgency. 

• Trade in index future to adjust target beta. 

• Trade in VIX futures to target volatility. 

• Trade in CDS to target credit spread risk. 

Cash flow needs • Trade to raise cash for collateral/margin. 

• Trade in ETS equitize uninvested cash. 

Corporate actions • M/As takes long, trading required expired derivatives. 

Index 

reconstitution 

• Trade to rebalance portfolio following a an index 

reconstitution. 

Variation margins • Trade to cover a margin calls or variation margin. 

The trading desk of a large firm receives three orders from the senior portfolio 

manager. Based on his research, the portfolio manager has identified two 

investment opportunities: 

• A short-term stock buy; 

• A longer-term stock sell. 

• Raise proceeds to accommodate an end-of-day client withdrawal. 

Discuss the motivation to trade and the associated trade urgency for each. 

Short-term 

buy 

Longerterm 

sell 

Client 

withdrawal 

A short-term profit-seeking trade investment opportunity: 

Trade urgency: 

High, to realize alpha before it dissipates (decays). Speed 

essential, trading is less price sensitive and more 

aggressive, resulting in higher price impact. 

Longer term profit-seeking trade investment opportunity: 


Low, managers more patient in trading and willing to wait 

for favorable prices by spreading executions over a longer 

time horizon (days or weeks). 

Cash flow–driven, raises proceeds for client withdrawal. 


High, targeting of end-of-day closing prices to match trade 

prices to funds NAV to meet daily liquidity provisions that 

allow mutual fund clients to invest and redeem at the end 

of each trading day. 

Low, Hedge funds allow redemptions only at quarter-end 

and with a relatively long notice period (1 month), allowing 

them more time to sell illiquid positions. Client-driven 

redemptions typically involve much lower trade urgency.

Order 

characteristics 

(buy, sell, 

cover or short) 

Security 

characteristics 

Market 

conditions 

Order side, buy: 

• Rising prices → higher execution risk → negative price 

impact for buyers as they wait for sellers. 

• Falling prices → higher execution risk → negative price 

impact for sellers as they wait for buyers. 

Order size 

Larger orders → greater market impact → less urgent 

trading. 

Security type: Trading cost my be lower in in trading an ADR 

or GDR than trading the underlying security in a local market. 

Security liquidity 

Greater liquidity →lower execution risk and market impact. 

Real-time market conditions are likely to be different from 

those anticipated when investment decision was made. 

More predictable : Seasonal or local market holidays and 

quarter-end or year-end dates 

34b) Discuss inputs to the selection of a trading strategy. 

Dilemma of 

market 

impact and 

execution 

risk 

This dilemma closely relates to alpha decay. 

Increasing trading urgency → decreases execution risk 

Slicing order/patient execution → decreases market impact 

‘’Trading too fast increases market risk, but trading roo 

slow increases execution risk.’’ 

Trading strategy should optimize the trade-off between 

decreasing market impact versus decreasing execution 

risk. 

IN-TEXT QUESTION 

Discuss how order size and security liquidity considerations affect market 

impact and execution risk for an order. 

Larger order 

size 

→ greater market impact and execution risk 

To minimize market impact, trade over a longer time 

horizons; →raises the execution risk of the order. 

User based 

considerations 

Less predictable: Market crisis and impact price volatility and 

bid-ask spreads. 

Also, being being removed or added to an index or, for fixed 

income securities, becoming off-the-run. 

Less risk averse managers →trade more patiently 

More risk averse managers →trade patiently 

More liquid 

security 

Higher rates of 

alpha decay 

Lower market impact and execution risk given that they 

can be transacted over shorter time horizons with 

greater certainty of execution. 

→ Lower execution risk (higher trade urgency) 

→ Higher market impact costs.

34c) Compare benchmarks for trade execution. 

Pretrade 

Decision price: The security price at the time of decision to buy or sell the 

security, used by quantitative managers. 

Previous close: Security’s closing price on the previous trading day. Used by 

quantitative managers for decision if none exists. 

Post 

trade 

Closing price: Used by index managers and mutual 

funds that wish to execute transactions at the closing 

price/NAV. 

Advantage 

Opening price: The security’s opening price for the day. Used as a proxy for the 

decision price by fundamental portfolio managers who are investing in a security 

for long-term alpha or growth potential. Unlike decision or closing price, it is free 

from overnight risk. 

Provides portfolio managers with the price used for fund 

valuation and thus minimizes potential tracking error. 

Disadvantage 

Intraday 

Not great if the trade is to be executed in the opening auction, because the trade 

itself can influence the reference benchmark. 

Arrival price: The price of the security at the time the order is entered into the 

market for execution. Best at minimize trading cost. 

Volume-Weighted Average Price (VWAP): If rebalancing portfolio, portfolio 

managers can use VWAP to structure their executions over time to ensure cash 

received from sell orders is sufficient to fund remaining buy orders. 

Price 

target 

Portfolio manager would not know whether they are 

performing more or less favorably until after trading is 

completed. 

Used to transact in a security—believed to be 

undervalued or overvalued—at a more favorable price. 

Say stock is trading at $20.00 and believed to be 

undervalued by $0.5 

Time-Weighted Average Price (TWAP): An equal-weighted average price of 

trades executed over the specified time horizon. Useful to exclude potential 

trade outliers for which market participants are not able to fully participate. 

Used to evaluate fair and reasonable trading prices in markets with high volume 

uncertainty and for securities that are subject to spikes in trading volume 

throughout the day. 

Purchase by specifying a price target of ≤ $20.50 as the 

benchmark price. 

In this setting, the portfolio manager wishes to purchase 

as many order shares as possible at a price equal to or 

better (lower) than the specified price target.

Primary 

goal of 

trading 

strategy 

Common 

trade types 

34d) Select and justify a trading strategy (given relevant facts) 

Balance the expected costs and risks with portfolio manager’s 

trading objectives, and risk aversion, as well as other factors at 

the time of trading, such as: 

• Trade urgency, 

• Order size and 

• Security liquidity 

• Market conditions.. 

Short-term alpha-driven equity trade (high trade urgency) 

Long-term alpha-driven fixed-income trade (low trade urgency) 

1 Closing price – most appropriate reference price 

• It is an index fund these are valued using official closing prices. 

• Trade motivation is to rebalance fund by maintaining the same 

security holdings and weights as the benchmark index. 

• Executing the buys and sells at the close, minimizes the fund’s 

potential tracking error to the benchmark index. 

Previous close –not appropriate benchmark price 

Risk rebalance: buy/sell basket trade to rebalance a fund’s risk 

exposure 

Cash flow driven: client redemption trade to raise proceeds 

Cash flow driven: cash equitization (derivatives) trade to invest a 

new client mandate 

A portfolio manager for a global fixed-income index fund is required to trade for 

quarterly index changes taking place at the end of the trading day. To keep the 

fund in line with the anticipated index constituent changes, the portfolio 

manager generates a fund rebalance list consisting of buys and sells. He 

approaches the senior trader to discuss the best trade strategy for the list. 

1. Identify the most appropriate reference price benchmark for his trade. 

2. Select/justify the most appropriate trading strategy to execute his trade. 

• It would be security’s closing price on the previous trading day. 

• Quantitative models or optimizers incorporate the previous 

close as an input or as a proxy for the decision price. 

Opening price –not appropriate benchmark price 

• It is often selected by portfolio managers and traders who wish 

to begin trading at the market open, and may be used as a 

proxy for the decision price. 

2 A market-on-close (MOC) trade – most appropriate. 

Trading the rebalance list at the market’s closing prices best aligns 

the trade execution prices with the same closing prices used for the 

fund’s NAV and benchmark calculation, thus minimizing tracking 

error of the fund to the benchmark index.

34e) Describe factors that typically determine the selection of a trading algorithm class. 

Implementation 

Human touch – 

• Illiquid 

securities 

• Extremely 

large trade 

sizes 

Automated 

execution 

• Liquid 

securities 

• Small sizes 

Exhibit 1 

Choices/methods to execute the chosen trade strategy: 

In principal trades, executing broker assumes all or 

part of the risk, pricing it into her quoted spread. Wider 

bid–ask spread quoted by dealer for taking on this 

additional risk. 

In agency trades, broker is agent only, finds the other 

side of the trade; risk remains with the buy-side portfolio 

manager or trader. 

Algorithmic trading, is well established in most equity, 

forex, and exchange-traded derivative markets. 

Involved Direct Market Access (DMA) all participants 

can interact directly with the order book of an exchange, 

usually through a broker’s exchange connectivity. 

In fixed income, algorithmic execution is mostly limited 

to trading highly liquid government securities, such as 

US Treasury securities. 

In most asset classes, electronic trading increased over 

the period to more than 50% of total trading volume. 

High touch: 

High-yield bonds, illiquid hard to find counter party. 

Electronic trading: 

Cash equities and futures

Execution 

algorithms. 

Profitseeking 

algorithms. 

Algorithmic Trading – 2 types 


• Input – what to buy/sell per investment style/objective. 

• Output – algorithm executes buy/sell input 

• Input –Investment style/objective. 

• Output – algorithm determines what to buy/sell, based on 

real-time price, market data (e.g., volume and volatility). 

Scheduled 

(POV, 

VWAP, 

TWAP) 

Execution algorithms. 

Appropriateness/factors determining their use in orders: 

• Expectations of adverse price movement in horizon. 

• Risk tolerance for longer execution time periods 


• More concerned with minimizing market impact. 

Scheduled 

(POV, 

VWAP, 

TWAP) 

Percentage of volume (POV) algorithms: Send orders 

following a volume participation schedule. 

A POV of 10% means for every 10,000 shares that trade in 

the market, the algorithm will execute 1,000 shares. 

Advantage: Automatically trade more shares when there is 

ample market liquidity and will not trade in times of illiquidity. 

Disadvantage: Higher trading costs by continuing to buy as 

prices move higher and to sell as prices move lower; and 

may not complete order within the time period specified. 

VWAP algorithms: Slices the order into smaller amounts 

and sends to market following a time slicing schedule based 

on historical intraday volume profiles. Typically U-shaped, 

trading a higher % of the order at the open and close and a 

smaller % during midday. 

TWAP algorithms: Slices and sends equal number (or %) 

of shares/order to be traded in each time period. 

Liquidity 

seeking or 

opportunistic 

algorithms 

• Small order sizes (




Arrival price 

Dark 

strategies/ 

liquidity 

aggregators 

These trade close to current market prices at the time the order 

is received for execution (front-loaded strategy). Tend to be 

time schedule than volume participation based. 


• Prices would move unfavorably during the trade horizon. 

• Trade more quickly to reduce the execution risk. 

• Security is relatively liquid or the order is not outsized. 

Execute shares away from “lit” markets, that provide pre- and 

post-trade transparency regarding prices, volumes, market 

spreads, and depth. 

Instead, these algorithms execute in opaque, or less 

transparent, trade venues, such as dark pools. 


• Information leakage during posting limit orders. 

• Order size is large relative to the market 

• Trading in the open market would lead to market impact. 

• Illiquid securities, or with wide bid–ask spreads. 

Smart 

order 

routers 

(SORs) 

Routes orders to the destination with the highest probability of 

executing the limit order and the venue with the best market 

price for market orders. 

The SOR continuously monitors real-time data from exchanges 

and venues and also assesses ongoing activity in dark pools. 


Market orders 

• Orders small enough that will not have a large market impact 

if sent (less than the quantity posted at the best bid or offer). 

• Orders that require immediate execution because of 

imminent price movement. 

Limit orders 

• Orders small enough that will not leak information to the 

market and move prices (orders that are similar to those 

currently posted in the market). 

• When there are multiple venues currently posting orders at 

the trader’s limit price. 

• No need to execute the order in its entirety.


A portfolio manager has identified a stock with attractive long-term growth 

potential and would like to place an order of moderate size, relative to the 

stock’s average traded volume. The stock is very liquid and has attractive 

short-term alpha potential. The portfolio manager expects short-term buying 

pressure by other market participants into the market close, ahead of the 

company’s earnings call scheduled later in the day. 

1. Explain when the following algorithms are used: (a) arrival price, (b) dark 

aggregator, and (c) SOR. 

c) Smart 

order 

routing 

systems 

(SORs) 

Appropriateness/when to use: 

Market orders 

• Orders small enough to not impact price 

• Orders require immediate execution 

Limit orders 

• Orders small enough that will not leak information 

• Multiple venues currently posting orders at the 

trader’s limit price. 

a) Arrival price 

algorithms 

b) Dark 

aggregator 

algorithms 

Appropriateness/when to use: 

• Liquid securities, order not expected to market impact. 

• Higher levels of risk aversion require more 

aggressive/faster trading to reduce the execution risk. 

• Illiquid securities, with wide bid–ask spreads 

• Large sizes with large price impact if traded in open 

market. 

• Concerns about information leakage during posting of 

limit orders in lit venues. 

2. Discuss which of the 3 algorithms is most suited to trading this order. 

Adverse 

price 

expectations 

Trade 

urgency 

Arrival price 

Manager expects short-term buying pressure into the 

market close, ahead of the company’s earnings call 

scheduled later in the day 

Has to trade more aggressively to capture alpha ahead of 

less favorable prices expected later in the day. 

Executing the order more quickly, at more favorable 

prices ahead of the adverse price movement and the less 

favorable prices expected from other participants’ buying 

pressure into the close, in line with his trade urgency. 

• When order does not need to be filled in its entirety, as 

dark pools have higher risk of unfilled executions. 

Summary 

Stocks with similar characteristics might need similar 

execution, some machine learning technique called 

“clustering” to the problem of algorithmic strategy selection.

34f) Contrast key characteristics of the following markets in relation to trade implementation: equity, fixed 

income, options and futures, OTC derivatives, and spot currency. 

Equities 

Fixed 

income 

In relation to trade implementation 

Generally traded on exchanges and dark pools: 

• Exchanges are lit markets, provide pre-trade transparency— 

namely, limit orders that reflect trader intentions for trade side 

(buy or sell), price, and size. However, detailed book data 

may be costly and available only to some market participants. 

• Dark pools provide anonymity, but regardless of the trading 

venue, transactions/quantities are always reported. Also, 

called Alternative Trading Systems (ALTs in USA) or in 

Europe, Multilateral Trading Facilities (MTF) 

and Systematic Internalisers (SI), typically regulated as 

brokers/dealer, rather than exchanges. 

• Low market transparency, 

• Sourcing market liquidity relies on dealers/counterparties (i.e., 

principal trades), via electronic RFQ platforms. 

• Limited algorithmic trading, except for on-the-run US 

Treasuries, bond and interest rate futures contracts. 

• Market illiquidity, large size and low frequency of potential 

trades creates challenges for algorithmic trading. 

• High-touch trading persists for larger trades and less liquid 

securities, urgent trades done via broker risk trades (RFQs), 

• Large, non-urgent trades are generally implemented using a 

high-touch approach, with brokers acting as agents to source 

liquidity (agency trades instead of principal trades). 

Exchangetraded 

derivatives 

(options and 

futures) 

Offexchange 

(OTC) 

derivatives 

Spot 

currencies 

trades/ 

markets 

• High market transparency as trade price, size, quote, and 

depth of book data are publicly available. 

• Electronic trading is widespread; however, algorithmic is not 

as evolved, more used for futures trading than options. 

• Large, urgent trades “sweep the book” where market depth 

is relatively good. Large, non-urgent trades done 

electronically through trading algorithms. 

• Buy-side traders generally use direct market access, 

particularly for small trades. 

• Opaque with little public data about prices, trade sizes, and 

structure details, with regulators seeking transparency and 

reducing counterparty risk. 

• Dodd–Frank Wall Act increased post-trade transparency 

with the establishment of swap data repositories (SDRs) to 

which trade details must be submitted. 

• Large, urgent trades done as broker risk trades; non urgent 

ones done via high-touch agency trade, a strong price 

concession often required to find a buyer or seller. 

• Entirely OTC, opaque, almost no cross-border regulation. 

• Multiple levels: top level is interbank (large bank/dealers); 

next level smaller banks/FSOs buy from interbank; then 

firms/retail traders commercial companies and retail traders 

that buy from middle level, paying higher bid–ask spread. 

• For large, urgent trades, RFQs are submitted to multiple 

dealers competing; non-urgent executed using algorithms 

(TWAP) or a high-touch agency approach. 

• Small trades are usually implemented using DMA.

34f) Contrast key characteristics of the following markets in relation to trade implementation: equity, fixed 

income, options and futures, OTC derivatives, and spot currency. 

IN-TEXT QUESTION 

A hedge fund manager has three trades that 

she would like to execute for her fund. The 

orders are for: 

1. a large, non-urgent sell of OTC options, 

2. a large, urgent sell of corporate bonds, 

and 

3. a small, non-urgent buy of six liquid 

emerging market currencies. 

Describe factors affecting trade 

implementation for each trade. 

1 A large, non-urgent sell of OTC options: 

• A broker agency trade, broker finds a matching buyer for the options. 

• Depending on the level of contract customization, however, a significant price 

concession may be required by the manager to complete order execution. 

2 A large, urgent sell of corporate bonds 

• Broker risk trade via the RFQ process, due corporate bond illiquidity, the 

likelihood of finding a matching buyer is low. 

• For more immediate (urgent) order execution, a broker act as counterparty 

(dealer) to the trade, taking the bonds and their associated risk into his inventory. 

3 Small, non-urgent trades in foreign exchange 

• Generally executed using direct market access (DMA). 

• DMA allows the buy-side trader to electronically route orders using the broker’s 

technology infrastructure and market access and typically involves algorithmic 

trading.

Implementation Shortfall 

A portfolio manager decides to buy 100,000 shares of RLK 

at 9:00 a.m., when the price is $30.00. He sets a limit price 

of $30.50 for the order. The buy-side trader does not 

release the order to the market for execution until 10:30 

a.m., when the price is $30.10. The fund is charged a 

commission of $0.02/share and no other fees. 

At the EOD, 80,000 shares are executed and RLK closes at 

$30.65. Order and execution details are as follows: 

34g) Explain how trade costs are measured and determine the cost of a trade. 

1. Calculate execution cost 

• Real portfolio (at transacted prices) 

less paper portfolio (at decision price) 

2. Calculate opportunity cost 

• Failure to execute all at decision price. 

30,000 shares × $30.20 

+ 20,000 shares × $30.30 

+ 20,000 shares × $30.40 

+ 10,000 shares × $30.50 

= $2,425,000 

$2,425,000 − (80,000 × $30.00) = $25,000 

(100,000 − 80,000)($30.65 − $30.00) = $13,000 

3. Calculate fixed fees 80,000 × $0.02 = $1,600 

4. Calculate implementation shortfall in 

basis points. 

Execution + opportunity + fees 

total shares 

$25,000 + $13,000 + $1,600 = $39,600 

$39,600 x 10,000 bps = 132 bps 

100,000 x $30.00 

5. Discuss how opportunity cost could be minimized for the trade. 

• Opportunity cost was $13,000 on 100,000 − 80,000 = 20,000 shares. 

• It accounts for $13,000/$39,600 = 32% of the Implementation Shortfall cost. 

• If known in advance, could have reduced the size of the order to 80,000 shares 

• Invested the extra 20,000 shares × $30.00/share = $600,000 in second most attractive 

investment opportunity.

34g) Explain how trade costs are measured and determine the cost of a trade. 

Implementation Shortfall 

A portfolio manager decides to buy 100,000 shares of 

RLK at 9:00 a.m., when the price is $30.00. He sets a 

limit price of $30.50 for the order. The buy-side trader 

does not release the order to the market for execution 

until 10:30 a.m., when the price is $30.10. The fund is 

charged a commission of $0.02/share and no other fees. 

At the EOD, 80,000 shares are executed and RLK 

closes at $30.65. Order and execution details are: 

6. Calculate delay cost 

• Price gain between decision and release to market. 

7. Calculate trading cost 

• Real portfolio (at transacted prices) 

less paper portfolio (at release price) 

8. Show expanded implementation shortfall in 

basis points 

80,000 shares x $30.10 

80,000 shares x $30.00 

$8,000 

30,000 shares × $30.20 

+ 20,000 shares × $30.30 

+ 20,000 shares × $30.40 

+ 10,000 shares × $30.50 

= $2,425,000 

= $2,425,000 − (80,000 × $30.10 = $17,000 

$8,000 + $17,000 + $13,000 $1,600 = $39,600 

Delay + Trading [= Execution] + opportunity + fees 

total shares 

$39,600 x 10,000 bps = 132 bps 

100,000 x $30.00 

9. Discuss how delay cost could be minimized for the trade. 

• Delay cost is caused by time lag between investment decision and release of order to the 

market; and accounts for a sizable $8,000/$39,600 = 20.2% of the total IS. 

• Proactively provide buy-side trader with broker performance metrics, to quickly identify the 

best broker and/or algorithm to execute the order given its characteristics and current market 

conditions. 

• This will minimizing the time lag between order receipt and market execution.

34h) Evaluate the execution of a trade. 

Trade cost analysis (TCA) 

Benchmark/REF price 

Cost (in $) 

Evaluates the execution quality of 

the trade and the overall 

performance of the trader, broker, 

and/or algorithm 

Arrival price, VWAP, TWAP, 

MOC, MAC 

Side x (P AVG – P REF ) x shares 

Cost (in $ per share) Side x (P AVG – P REF ) 

Cost (in bps) 

P AVG 

P REF 

Shares 

Side 

Buy order (+1) → P AVG > P REF 

Side x (P AVG – P REF ) x 10,000 bps 

P REF 

bps represent a standardized 

measure across order sizes, 

market prices, and currencies 

Average execution price of order 

Reference price 

Number of shares executed 

+ 1 Buy order 

─ 1 Sell order 

+ value is u/performance 

Arrival 

price 

VWAP 

TWAP 

Market price at the time the order was released to the market and the actual 

transaction price for the fund. 

Example: Buy order at P AVG = $30.05; Arrival price, P REF = $30.00. 

Arrival Cost (bps) = +1 x (30.05 - $30.00)/ $30.00 x 10 4 bps = 16.7 bps 

The fund underperform the Arrival price benchmark. 

Captures all market activity over the day, including all buying and selling 

pressure, and market noise; provides reasonable indication of the fair cost 

for market participants over the day. 

Example: Buy order at P AVG = $30.05; VWAP over trading horizon = $30.04 

VWAP Cost ($) = +1 x (30.05 - $30.04)/$30.04 x 10 4 bps = 3.3 bps 

The fund underperform the VWAP because of the bid–ask spread and the 

buying or selling pressure associated with the order. 

Alternative to VWAP, used when managers wish to exclude potential trade 

price outliers. 

Sell order (─1) → P AVG 

Buy order (+1) → P AVG 

Sell order (─1) → P AVG > P REF 

+ value is u/performance 

─ value is savings o/performance 

─ value is savings o/performance 

Example: Buy order at P AVG = $30.05; TWAP over trading horizon = $30.06 

TWAP Cost ($) = +1 x (30.05 - $30.06)/ $30.06 x 10 4 bps = ─3.3 bps (o/p) 

The fund outperformed the TWAP benchmark by 3.3 bps.


Market 

on 

Close 

(MOC) 

Used by index managers and mutual funds that wish to 

achieve the closing price on the day and compare their actual 

transaction prices with the closing price. 

Ensures benchmark cost measure will be consistent with the 

valuation of the fund and with the tracking error calculation. 

Example: A portfolio manager executing a buy order using an 

MOC strategy transacts the order at an average price of 

$30.40. The stock’s official closing price is $30.50. 

MAC 

We can isolate the price movement due to the general market from the 

cost due to the impact of the order: 

MAC (bps) = Arrival cost (bps) − β × Index cost (bps) 

Index cost (bps) = Side x (Index VWAP – Index Arrival Price) x 10 4 

Index Arrival Price 

β is the stock’s beta to the underlying index, removes the price change 

that would have occurred even if the order was not entered. 

Market- 

Adjusted 

Cost 

(MAC) 

Close (bps) = Side x (P AVG – P CLOSE ) x 10,000 bps 

P CLOSE 

= +1 x (30.40 - 30.50)/ 30.50 x 10 4 bps = ─32.80 bps 

Order was executed 32.8 bps more favorably than the closing 

price of the order. In an index fund, the outperformance would 

contribute to positive tracking error for the fund. 

Besides market impact costs, 

• Buying in a rising market incurs higher cost 

• Selling in a falling market incurs high cost 

Similarly, 

• Buying in a falling market incurs lower cost 

• Selling in a rising market incurs lower cost 

Ex. Buy order was placed at P AVG = $30.50 and arrival price = $30.00. 

Index price was $500, and market index VWAP over the trade horizon 

was $505 and β = 1.25 [buying in rising market, $500 to $505) 

Compute the Market-adjusted cost: 

Steps 1. Arrival cost (bps) = +1 x (30.50 - 30.00)/ 30.00 x 10 4 = 166.7 bps 

Interpret 

2. Index cost (bps) = +1 x (505 - 500)/500 x 10 4 = 100 bps 

3. MAC = 166.7 bps – 1.25 x 100 bps = 41.7 bps 

We spent 166.7 bps more, but 125 bps of that came from buying 

in a rising market. 

The true impact of the order was just 41.7 bps!


Selling in a Falling Market 

A PM executes a sell order at an average price of $29.50. The arrival price at the 

time the order was entered into the market was $30.00. The selected index price at 

the time of order entry was $500, and market index VWAP over the trade horizon 

was $495. The stock has a beta to the index of 1.25. 

Added 

Value 

Another methodology is to compare the arrival cost with the 

estimated pre-trade cost (EPTC). 

EPTC relies on a pre-trade model with order size, volatility, 

market liquidity, investor risk aversion, level of urgency, and 

the underlying market conditions at the time of the trade. 

1. Arrival 

cost. 

2. Index 

cost 

Arrival Cost (bps) = Side x (P AVG – P REF ) x 10 4 bps 

P REF 

─1 x (29.50 - $30.00)/ $30.00 x 10 4 bps = + 166.7 bps 

U/performed the arrival price benchmark, likely attributable to market 

movement than inferior performance from the broker or algorithm. 

Index cost (bps) = Side x (Index VWAP – Index Arrival Price) x 10 4 

Index Arrival Price 

─1 x ($495 - $500)/ $500 x 10 4 bps = + 100 bps 

Added value (bps) = Arrival cost (bps) – EPTC (bps) 

Example: PM executes a buy order at P AVG = $50.35, 

P ARR = $50.00. Prior to trading, buy-side trader performs 

pre-trade analysis and finds that the EPTC is 60 bps. 

The pre-trade adjustment is calculated as follows: 

Arrival Cost (bps) = +1 x ($50.35 - $50.00)/ $50.00 x 10 4 

= + 70 bps 

Added value = 70 bps − 60 bps = + 10 bps 

3. MAC 

(bps) 

Interpretation 

Arrival cost (bps) − β × Index cost (bps) 

166.7 bps – 1.25 x 100 bps = 41.7 bps 

Sell order was executed in a falling market, resulted in an arrival 

cost of 166.7 bps for the investor. However, 125 bps of this cost 

was due to market movement, irrespective of the order. Thus, 

MAC for order is 41.7 bps. 

Proper trade 

cost 

evaluation 

informs where 

trading 

activities may 

be improved: 

Fund underperformed pre-trade expectations by 10 bps. 

Through better trade governance, policies and 

processes used to manage trading-related activities. 

Such internal trade management practices, may 

include the use of: 

• Appropriate trading partners and 

• Venues.

Trade policy 

document 

Best Order Execution 

Optimal Order 

Execution Approach 

34i) Evaluate a firm’s trading procedures, including processes, disclosures, and record keeping with respect to good governance. 

Typically mandated by major market regulators, it 

articulates the firm’s trading policies and 

escalation procedures doe issues that cannot be 

resolved by standard procedures. 

Relevant Regulatory Frameworks require that 

Firms execute orders on terms most favorable to 

the client, by considering trade-offs between: 

• Execution price, 

• Trading costs, 

• Speed of execution, 

• Likelihood of execution and settlement, 

• Order size, and 

• Nature of the trade. 

For example, although market impact costs can 

lowered by trading more patiently, patient trading 

may be suboptimal for an asset manager that 

uses extremely short-horizon expected return 

forecasts, which decay quickly. 

Prioritise factors like: 

• Urgency of an order, 

• Characteristics of the securities traded, 

• Characteristics of the execution, 

• Venues/platforms used, 

• Investment strategy objectives (ST/LT), 

• Rationale/motivation for a trade. 

List of Eligible 

Brokers and 

Execution 

Venues 

Process Used to 

Monitor 

Execution 

Arrangements 

• Quality of service 

• Financial stability 

• Reputation 

• Settlement capabilities 

• Speed of execution 

• Cost competitiveness 

• Willingness to commit capital (act as dealer). 

All brokers and execution venues used should be subject 

to ongoing monitoring for reputational risk, irregularities 

(such as trading errors), criminal actions, and financial 

stability. 

• What was the execution quality of a trade relative to its 

benchmark (e.g., arrival price, VWAP, TWAP, MOC)? 

• Is there an appropriate balance between trading costs 

and opportunity costs (for non-executed trades)? 

Trading records should archived, used to: 

• Address client concerns 

• Address regulator concerns 

• Assist in improving execution quality. 

• Monitor the parties involved in trading/order execution 

Policies enacted, involving portfolio management, risk, 

and legal/compliance departments. If no formal committee 

is tasked with owning this document, then the 

legal/compliance should, with collaboration from portfolio 

management and risk management functions.

34i) Evaluate a firm’s trading procedures, including processes, disclosures, and record keeping with respect to good governance. 

Choice of Broker 

ABC Asset Management (ABCAM) is one of the world’s largest asset 

managers. ABCAM has been using AAA Brokerage (AAAB) as its 

exclusive broker for a number of its funds for many years. Other 

brokers are used only for market segments in which AAAB does not 

have business operations. The leadership of ABCAM explains its 

choice of broker by stating, “Because of its long-standing business 

relationship with AAAB, ABCAM has a uniquely informed insight into 

the operations of AAAB, which provides greater comfort and assurance 

that AAAB will fulfill its duties when compared with other brokers.” 

Discuss whether this practice is permissible and can be justified. 

Solution: 

ABCAM needs to show that it takes all sufficient steps to ensure best 

execution for its clients’ trades. This includes choosing brokers that 

provide the best service for potential best execution. 

In order to justify that AAAB is the right broker to use, ABCAM must 

demonstrate that it has done comparisons of different brokers, that this 

analysis is regularly conducted with updates, and that each time AAAB is 

found to be the best choice for order implementation. 

A thorough and unbiased analysis is required for this. Stating a subjective 

opinion, such as the explanation provided by ABCAM leadership, is not 

sufficient justification. 

Trade Policy Document 

For several decades, XYZ Capital has been running enhanced index funds. 

These funds have low levels of target tracking error compared with their marketweighted 

benchmarks. The firm’s trade policy document has a focus on 

minimizing trading costs and defines best execution as follows: 

“The firm takes all sufficient steps to obtain the best possible result in executing 

orders; that is, the firm makes its best attempt to achieve the best execution price 

and lowest trading cost possible for every transaction. In this way, the firm 

achieves best execution for its client portfolios.” 

Discuss whether the trade policy statement is in line with regulatory 

requirements and client best interests. 

Achieving the best execution price at the lowest trading cost possible is only 

part of the best execution effort. To ensure that clients and their portfolios are 

served in the best manner possible, other factors require consideration. 

These considerations include the speed of execution, the alignment of execution 

approach and execution horizon with the investment process, the likelihood of 

execution to be optimal, and so on. An exclusive focus on best execution price 

and lowest trading cost is too narrow a definition to achieve best client 

execution. 

For example, doing so could leave many trades unexecuted, which would 

result in increased opportunity costs from lost opportunities that could not be 

implemented.


Reading 35: Portfolio Performance Evaluation 

Reading 36: Investment Manager Selection

35a) Explain the following components of portfolio evaluation and their interrelationships: performance measurement, performance attribution, and performance appraisal. 

35b) Describe attributes of an effective attribution process. 

35c) Distinguish between return attribution and risk attribution and between macro and micro return attribution 

35d) Describe returns-based, holdings-based, and transactions-based performance attribution, including advantages and disadvantages of each. 

Performance 

measurement 

Components of portfolio evaluation 

What was the portfolio’s performance? 

• Portfolio return over benchmark return. 

Effective 

performance 

attribution 

process: 

Performance attribution 

• Account for all of the portfolio’s return or risk exposure; 

• Reflect the investment decision-making process; 

• Quantify the active decisions of the manager; and 

• Full clarity on the excess return/risk of the portfolio. 

Performance 

attribution 

• The risk incurred to achieve that return 

How was the performance achieved? 

• Return attribution analyzes the impact of active 

investment decisions on returns; 

• Returnsbased 

attribution 

Sources of returns by breakdown of total portfolio returns 

Useful when underlying portfolio holding information is not 

available (e.g. hedge funds). 

Easiest method to implement, but least accurate 

Performance 

appraisal 

• Risk attribution analyzes the risk consequences 

of those decisions. 

Extendable to: 

• Asset owner’s TAA (micro-attribution); and 

• Manager selection decisions (macro attribution) 

Was the performance achieved through manager 

skill or luck? 

Makes use of risk, return, and attribution analyses 

to draw conclusions regarding the quality of a 

portfolio’s performance. 

• Holdingsbased 

attribution 

• Transactions 

-based 

attribution 

Sources of returns by BOP holdings of the portfolio; more 

accurate over short period as holdings change overtime 

Doesn’t capture intra-period transactions, needs recon to actual 

portfolio return (residual/timing or trading effect). 

Great for passive strategies with little turnover. 

Both the weights and returns reflect all transactions during the 

period, including transaction costs. 

Best method, but most time-consuming, the underlying data must 

be complete, and reconciled from period to period. 

Return used will reconcile with the return presented to the client.

35e) Interpret the sources of portfolio returns using a specified attribution approach. 

Equity Return Attribution 

The Brinson–Hood–Beebower Model 

Energy 

Health care 

Financials 

Portfolio return, R Benchmark return, B Excess return 

+ 50% × 18% 

+ 30% × −3% 

+ 20% × 10% 

+ 50% × 10% 

+ 20% × −2% 

+ 30% × 12% 

Arithmetic 

difference, R - B 

Total 10.1% 8.2% 1.9% or 190 bps. 

Allocation effect 

Value added by having portfolio sector weights that are 

different from the benchmark sector weights: 

A i = (w i − W i )B i • Energy: (50% − 50%) × 10% = 0.0% 

• Health care: (30% − 20%) × −2.0% = −0.2% 

• Financials: (20% − 30%) × 12% = −1.2% 

• Total allocation effect = –1.4% 

Exhibit 2 

Provides data for a three-sector domestic equity 

portfolio, used to illustrate the BHB model. 

Security 

selection 

Value added by holding individual securities or within the 

sector in different-from-benchmark weights. 

S i = W i (R i − B i ) • Energy: 50% × (18% − 10%) = 4.0% 

• Health care: 20% × (–3% − –2.0%) = −0.2% 

• Financials: 30% × (10% − 12%) = −0.6% 

• Total selection effect = 3.2% 

Interaction (I) 

effect 

I i = 

(w i − W i )(R i − B i ) 

Allocation (–1.4%) and selection (3.2%) = just 1.8% of the 

1.9%. To explain the remaining 0.1%, the BHB model uses 

the ‘I effect’, between allocation and selection decision. 

• Energy: (50% − 50%) × (18% − 10%) = 0.0% 

• Health care: (30% − 20%) × (–3% − –2.0%) = −0.1% 

• Financials: (20% − 30%) × (10% − 12%) = 0.2% 

• Total interaction effect = 0.1%


In the 

BHB 

model 

BF 

Model 

R B Excess return 

Total 10.1% 8.2% 1.9% or 190 bps. 

A i = (w i − W i )B i • Energy: (50% − 50%) × 10% = 0.0% 

• Health care: (30% − 20%) × −2.0% = −0.2% 

• Financials: (20% − 30%) × 12% = −1.2% 

• Total allocation effect = –1.4% 

Brinson–Fachler Model 

Allocation effect, A i = (w i − W i )B i > 0 = positive: 

If we o/w a sector i with positive return, even when the sector 

return < overall benchmark return (i.e., B i < B). 

Solves this problem by modifying the asset allocation factor to 

compare returns with the overall benchmark: 

B S − B 

The contribution to arithmetic excess return from sector 

allocation for the portfolio = 6.8% − 8.2% = −1.4%. 

A i = (w i − W i )(B i − B) Energy: (50% - 50%) x (10% - 8.20%) = 0.0% 

Health care: (30% - 20%) x (-2.0% - 8.20%) = -1.02% 

Financials: (20% - 30%) x (12.0% - 8.20%) = - 0.38% 

Total allocation effect = –1.4% 

Impact in 

Health 

care is 

greater 

Impact in 

financials 

is much 

smaller 

Manager is o/w (by 10%) in a negative market = −0.2% 

Penalized by opportunity cost of market 10% × −8.2% = −0.82% 

Total impact 

= −1.02%. 

Portfolio is 10% o/w in a market that is u/performing the overall 

market by −10.2% (−2.0% − 8.2%) and generating a loss of −1.02% 

u/w by 10% in a positive market cost = −1.2% 

Opportunity cost o/w in overall market −10% × −8.2% = 0.82% 

Total impact of 

−0.38%. 

Net effect 

As expected, at the portfolio level, the allocation effect of −1.4% 

remains the same as that calculated with the BHB model.

Interpreting the Results of a BHB Attribution 


C is correct. 

B, C, A, A 

The manager is underweight in APAC, 20% vs a benchmark weight of 30%. 

The APAC portion of the portfolio underperformed, with a −0.50% 

benchmark return versus the total benchmark return of 0.81%. 

3. Which of the following conclusions from the above attribution analysis 

is most correct? 

1. Why is the contribution to selection for Europe, the Middle East, and 

Africa (EMEA) negative? 

A. The total benchmark return is less than the total portfolio return. 

B. The manager selected securities in EMEA that underperformed the 

benchmark. 

C. The manager underweighted an outperforming sector. 

B is correct. 

The manager selected securities that u/performed, with a portfolio return 

for EMEA of 0.7% vs a benchmark return of 1.5%. 

2. Why is the contribution to allocation for APAC equal to +5 bps? 

A. The benchmark weight and the portfolio weight are equal. 

B. The manager has an o/w position in an overperforming region. 

C. The manager has an u/w position in an underperforming region. 

A. The manager’s SS decisions were better in the Americas than in APAC. 

B. The manager’s SS decisions were better in EMEA than in APAC. 

C. The manager’s allocation decisions were better in APAC than in EMEA. 

A is correct. 

As reflected in the contribution to selection, the manager’s security selection 

decisions were better in the Americas (0.48%) than in APAC (–0.30%). 

4. Which of the following conclusions from the above attribution analysis 

is most correct? 

A. Overall, the manager made better allocation decisions than SS decisions. 

B. Overall, the manager made better SS decisions than allocation decisions. 

C. Contribution from interaction was most noticeable in the Americas. 

A is correct. 

Overall, the manager made better allocation decisions (0.20%) than selection 

decisions (–0.14%).

The 

issue 

Equities 

Brinson–Fachler focuses on SS, AA, interaction of SS and AA. How 

about other decisions within the investment process? 

R p − R f = a p + b p1 RMRF + b p2 SMB + b p3 HML + b p4 WML + E p 

35f) Interpret the output from fixed-income attribution analyses. 

A, A 

A is the correct answer. 

The negative coefficient on SMB indicates that the manager had a 

slight large-cap bias relative to the benchmark. 

The slight tilt on WML (+0.02) combined with a positive return to the 

factor resulted in a positive contribution to return. 

The below-benchmark beta of RMRF (–0.05) combined with a 

positive return to the factor resulted in a negative contribution to 

return. 

2. What investment approach, not taken by the portfolio 

manager, could have delivered more value to the portfolio 

during the investment period? 

A. A momentum-based approach 

B. A growth-oriented approach 

C. A small-cap-based approach 

Factor-Based Attribution 

Use the data from Exhibit 5 to answer the following questions. 

1. Which of the following statements is not correct? 

A. The manager’s slight small-cap tilt contributed positively to return. 

B. The manager’s slight momentum tilt contributed positively to return. 

C. The manager’s below-benchmark beta contributed negatively to return. 

A is correct. 

Had the manager overweighted momentum stocks during the period, 

the momentum factor (WML) return of 9.63% would have contributed 

significant positive performance to the portfolio.

Fixed income 

portfolios 

• Exposure 

decomposition 

—duration 

based 

• Yield curve 

decomposition 

—full repricing 

based 

• Yield curve 

decomposition 

—duration 

based 

Durations 

• Short < 5 

• Mid 5 – 10 

• Long > 10 

For instance, a 

bond with a 

duration of 5.5 is 

treated the same as 

a bond with a 

duration of 9.5 in 

terms of its relative 

impact on the 

portfolio versus its 

benchmark 


Inferences 

PDur (8.17) vs Bdur (7.19): 

• Manager bullish on long-term 

bonds (interest rates↓), 

increasing exposure to the 

long end curve (50%) vs 30% 

for the benchmark). 

Corporate sector (60% v 45% 

benchmark weight): 

• Manager expected credit 

spreads to narrow, bet 

produces the 4.94 contribution 

to DUR vs 3.28 for the 

benchmark. 

• Might also have been a yield 

bet. Even if spreads do not 

narrow, the higher-yielding 

corporates are likely to 

outperform the government 

bonds in the portfolio. 

• This allocation makes the 

portfolio more exposed to 

market yield fluctuations in the 

corporate sector. 

Total portfolio return = −5.03% vs 

benchmark return of −4.83%: 

U/performance = −0.20% over the 

period.


Yield curve decomposition—full repricing 

Inferences 

Exhibit 5 

Portfolio’s attribution results (based on Exhibit 4). (Note you are expected to be 

able to interpret, but not calculate, these results.) 

Duration effect 

62 bps lost extending/longduration 

(instead of shortening) 

during a period when yields 

increased (benchmark returns were 

negative in each duration bucket). 

Curve effect 

52 bps gained from changes in the 

shape of the yield curve. Given the 

manager’s o/w in the long-duration 

bucket (50/30), we can infer that 

the yield curve flattened. 

Total Interest 

Allocation 

10 bps lost, net effect of duration + 

curve effect. 

Sector Allocation 

23 bps lost because the manager 

o/w the corporate sector during a 

period when credit spreads 

widened (benchmark corporate 

returns in each duration bucket 

were less than the government 

returns in those same duration 

buckets). 

Bond Selection 

13 bps were added through bond 

selection., holding non benchmark 

bonds. One in long duration bucket. 

Overall 

The portfolio underperformed its 

benchmark by 20 bps.


Exhibit 6 

Yield curve decomposition—duration based 

Provides an example of a sample duration-based yield curve decomposition 

attribution analysis (focus on interpretations, not calculations). 

Shift 

Slope 

Lost 89 bps: O/w of long DUR of 8.17 vs 

benchmark of 7.19 

Gained 39 bps: O/w on long-end, meets a 

flattening curve, long-term yields increase less 

than yields on shorter terms yields. 

Curvature 

Gained 53 bps: U/w government in rising rates 

helped. 

Spread 

Loss 33 bps: O/w the corporate sector and 

corporate spreads widened. 

Specific spread/ 

selection return 

Corporate 5% 30 June 26 bond added 2 bps of 

selection return. 

Corporate (P) 6% 30 June 31 bond added 15 bps 

of selection return. 

Both decisions at +17 bps to active returns. 

Yield 

Inferences 

Gained 11 bps: O/w of corporate bonds and longer-term maturities 

(Exhibit 4/5), which generally offer higher yield than G-bonds and 

short-term maturities. 

Residual 

A residual of −0.14% is unaccounted for because 

duration and convexity can only estimate the 

percentage price variation. 

It is not an accurate measure of the true price 

variation. 

Roll 

Lost 4 bps from o/w of longer maturities (Exhibit 5): The 

flattened yield curve means bonds with longer maturities sit on a 

flatter part of the yield curve, where the roll return is limited. 

The residual becomes more important during 

large yield moves, which is the case here, with a 

+1% yield shift.


C 

Fixed-Income Return Attribution 

1. Which decision had the most 

positive effect on the overall 

performance of the portfolio? 

A. Taking a long-duration position 

B. Security selection of bond issues 

C. Overweighting the long end of the 

yield curve 

C is correct: 

52 bps were gained by 

overweighting the long end of 

the yield curve during a period 

when the slope of the yield 

curve flattened.


C 

Interest rates↑ 

should’ve shortened 

not extended duration 

Curve effect (+37 bps) 

Duration and sector 

allocation effects 

Credit spreads 

Exhibit 4 

The –97 bps duration effect relative return: 

Manager took a longer-than-benchmark-duration 

position in the long-duration bucket, a decision that 

hurt performance because interest rates rose. 

Manager’s specific positioning along the long end 

of the yield curve benefited from changes in the 

shape of the yield curve (flattening). 

This implication is further supported by the positive 

slope effect shown in Ehibit 6 (+0.39 bps) 

Taken together, these accounted for the majority 

of the manager’s underperformance relative to the 

benchmark. 

In the long-duration bucket, the manager o/w 

corporate bonds relative to the benchmark. 

2. Explain the contribution of the long-duration bucket to 

overall portfolio performance. 

This decision penalized returns because credit 

spreads widened, which can be inferred from the 

weaker performance of the long-duration corporate 

segment of the benchmark (–5.42%) relative to the 

long-duration government segment (–4.38%). 

Curve effect, selection effects 

Duration, sector allocation effects 

Long-duration bucket cost the portfolio 

+37 bps, +13 bps 

–125 bps, −22 bps 

–97 bps of relative return 

Selection effect (+0.13) 

Manager’s specific bond selections added to 

return, supported by specific spread contribution 

reflected of +0.17 in Exhibit 6

35g) Discuss considerations in selecting a risk attribution approach. 

A, B, C 

Risk attribution 

Identifies the sources of risk in the investment process. 

1. Which risk attribution approach is most relevant to evaluate Manager A? 

A. Marginal contribution to total risk 

B. Marginal contribution to tracking risk 

C. Factor’s marginal contributions to total risk and specific risk 

A is correct. Manager A is bottom-up manager with an absolute return 

target. B is incorrect because tracking risk is not relevant to an absolute 

return mandate. C is incorrect because, as a market-neutral manager, 

Manager A is not seeking to take different-from-market exposures. 

Risk Attribution 

2. Which risk attribution approach is best to evaluate Manager B? 




Manager A is market-neutral, follows a systematic investment approach, scoring each 

security on a set of risk factors. He seeks to maximize the portfolio score on the basis of the 

factor characteristics of individual securities. He has a hurdle rate of T-bills plus 5%. 

Manager B has a strong fundamental process based on a comprehensive understanding of 

the business model and competitive advantages of each firm. He also uses sophisticated 

models to make explicit three-year forecasts of the growth of free cash flow to determine the 

attractiveness of each security’s current valuation. His objective is to outperform the MSCI 

World ex-US Index by 200 bps. 

Manager C specializes in timing sector exposure and generally avoids idiosyncratic risks 

within sectors. Using technical analyses and econometric methodologies, she produces 

several types of forecasts. The manager uses this information to determine appropriate 

sector weights. The risk contribution from any single sector is limited to 30% of total portfolio 

risk. She hedges aggregate market risk and seeks to earn T-bills plus 300 bps. 

B is correct. Manager B is a bottom-up manager with a relative return 

target. A and C are incorrect because they are best suited to absolute return 

mandates. 

3. Which risk attribution approach is most relevant to evaluate Manager C? 




C is correct. 

Manager C is a top-down manager with an absolute return target. A factorbased 

attribution is best suited to evaluate the effectiveness of the 

manager’s sector decisions and hedging of market risk.

35h) Distinguish between investment results attributable to the asset owner versus those attributable to the investment manager. 

A fund sponsor 

has these total 

equity benchmark: 

Exhibit 10 

Macro Attribution 

• 50% large-cap value equities 

• 25% small-cap value equities 

• 25% large-cap growth equities 

Investment returns by two investment managers hired by 

fund sponsor to manage the equity portion of the fund. 

Hire Value Manager 

Allocation (78% − 75%)[0.32 − (–0.03)] 

= 0.01 

Hire Growth Manager 

(22% − 25%)[–1.08 − (–0.03)] 

= 0.03 

Sponsor decision O/w equity: 78% − 75%) U/w growth : 22% − 25%) 

Perf. Vs. B. O/p : 0.32 − (–0.03) U/p: –1.08 – (−0.03) 

Selection + 

Interaction = 

I i = (w i − W i )(R i − B i ) 

Manager 

performance vs 

benchmark 

Conclusion 

+ [(75%)(0.99 − 0.32)] 

+ [(78% − 75%)(0.99 − 0.32)] 

= 0.52 

The value manager 

outperformed (0.99 − 0.32). 

Sponsor’s manager selection 

decision, independent of the 

decision to overweight value 

equities, added value. 

+ [(25%)(0.82 − (–1.08)] 

+ [(22% − 25%)(0.82 − (–1.08)] 

= 0.42 

The growth manager outperformed 

(+0.82 −−1.08). 

Fund sponsor’s manager selection 

decision, independent of the 

decision to underweight growth 

equities, added value. 

To evaluate the decisions 

of the fund sponsor 

We perform a return Brinson–Fachler attribution 

analysis using the set of weight and return data 

Allocation 

Selection 

TAA decision of the sponsor against its own strategic benchmark. 

A i = (w i − W i )(B i − B) 

Fund sponsor’s manager selection decision: Did the selected 

managers add value relative to their assigned benchmarks?


A fund sponsor has 

these total equity 

benchmark: 

Exhibit 10 

Micro Attribution 

• 50% large-cap value equities 

• 25% small-cap value equities 

• 25% large-cap growth equities 

Investment returns by two investment managers to hired by 

fund sponsor to manage the equity portion of the fund. 

Summing up the segment-level results for each manager: 

• The total outperformance at the overall fund level of 98 bps is almost entirely 

the result of positive security selection decisions (105 bps in total). 

Impact of the PM’s decisions on 

total fund performance 

Allocation (w i − W i )(B i − B) 

Perform a return Brinson–Fachler attribution 

analysis 

Selection + Interaction W i (R i − B i ) + (w i − W i )(R i − B i ) 

Attribution effects for the small-cap value equities 

Allocation (20% − 25%)[1.52 − (–0.03)] = −0.08 

Selection + Interaction [(25%)(2.39 − 1.52)] + [(20% − 25%)(2.39 − 1.52)] = 0.17 

• The decision of the Value Portfolio Manager to underweight small cap in favor 

of large cap detracted from total fund performance because the small-cap value 

benchmark outperformed the total benchmark (1.52% versus −0.03%), leading 

to an allocation effect of −0.10. 

• The large-cap value benchmark underperformed the total benchmark (−0.28% 

versus −0.03%). Because the portfolio was underweight large-cap value, this 

led to a positive allocation effect of 0.03. 

• In total, allocation decisions contributed −7 bps.

Granular 


Micro Attribution 

Attribution analysis extendable down another level and to examine 

the investment manager’s results relative to the investment process 

Stock piker 

–within 

sectors 

Drilling down to the lowest level, the same allocation and selection 

formulas can be used to calculate the contribution of individual 

security decisions within sectors. 

Transaction costs 

If the pricing sources used in the portfolio and the benchmark 

are identical, then any difference in return will be caused by 

transaction activity; because of trading expenses and bid–offer 

spreads will negatively affect returns, but occasionally because 

of timing, the manager may be able to trade at advantageous 

prices during the day and recover all the transaction costs by 

the end of the day, resulting in a positive effect. 

Exhibit 13 

Exhibit 14 

Contradiction 

Good country allocation but ─ SS within countries 

Poor sector allocation but strongly +SS within industrial sectors. 

The importance of an attribution approach around the investment 

decision-making process used by the manager. 

The arithmetic 

allocation effects 

of each security 

Allocation 

measures the 

value added from 

individual SS 

Chevron = (24% − 30%) × (10% − 7.05%) = −0.18% 

ConocoPhillips (21% − 25%) × (8.0% − 7.05%) = −0.04% 

ExxonMobil = (41% − 35%) × (6.0% − 7.05%) = −0.06% 

Marathon Oil = (6% − 5%) × (4.0% − 7.05%) = −0.03% 

Newfield Exploration (8% − 5%) × (–5.0% − 7.05%) = −0.36% 

Transactions occur for only one security during the period— 

ExxonMobil. Therefore, the only selection effects (transaction 

costs and timing) occur for this security: 

ExxonMobil = 41% × (5.0% − 6.0%) = −0.41%


Macro Attribution 

AAA Asset Management runs a fixed-income 

fund of funds. The fund’s benchmark is a 

blended benchmark comprising 80% 

Bloomberg Barclays Global Aggregate Index 

and 20% Bloomberg Barclays Global 

Treasury Index (both in US dollars, 

unhedged). Two internal investment teams 

have been selected to manage the fund’s 

assets. The allocations to the two products 

are determined by the firm’s chief fixedincome 

strategist. 

The fund has underperformed its benchmark 

in each of the last three years. You are a 

member of the board of directors, which is 

meeting to determine what action should be 

taken. Based solely on the data in the table 

below, which of the following courses of 

action would you recommend? 

C is correct. 

Based solely on the information 

provided, the chief fixed-income 

strategist’s allocation decision 

was the main driver of the fund’s 

underperformance. Product A 

modestly underperformed its 

benchmark over the three-year 

period (−16 bps). Product B 

outperformed its benchmark 

(+39 bps). The strategist’s 

allocation decisions were 

strongly negative in Years 1 and 

2, when he overweighted the 

Treasury allocation and the 

Treasury index underperformed 

the aggregate fund benchmark. 

The results of the attribution 

analysis are shown below: 

Justify your response. 

A. Terminate the manager of Product A. 

B. Terminate the manager of Product B. 

C. Remove the chief fixed-income strategist 

as manager of the fund of funds.

Benchmark ≠ 

Index 

Liabilitybased 

benchmarks 

A market index may be considered for use as a benchmark. 

However, the most appropriate benchmark is not necessarily 

a market index. 

Many active managers follow specific investment disciplines 

that cannot be adequately described by a security market 

index 

Used when the assets are required to pay a specific future 

liability (e.g., DBP plan), so must focus on cash flows 

required to defease the liabilities. 

Tracks the fund’s progress toward fully funded status or 

tracks the performance of assets relative to the changes in 

liabilities. 

Crucial because it would possible for the portfolio to 

outperform a market index but still not meet its liabilities. 

Furthermore, a market-value-weighted index would likely be 

an inappropriate benchmark because the liability often has a 

targeted asset allocation and risk exposures that are 

different from those of the index. 

A more recent innovation is LDI indexes. The Bloomberg 

Barclays LDI Index Series is a series of six investible 

indexes designed specifically for portfolios intended to 

hedge pension liabilities. However, they may not describe 

a plan’s liability structure as accurately as a benchmark 

constructed specifically for the plan. 

35i) Discuss uses of liability-based benchmarks. 

35j) Describe types of asset-based benchmarks. 

Absolute 

(including target) 

return 

Broad market 

Style 

Factor-modelbased 

Returns-based 

(Sharpe style 

analysis) 

Manager 

universes (peer 

groups) 

Custom securitybased 

(strategy) 

Asset-Based Benchmarks 

Minimum target return that the manager is expected to beat: 

20% per annum return for a private equity investment. 

Measures of broad asset class performance, such MSCI 

World Index for global developed market equities. 

Natural grouping of investment disciplines that has some 

predictive power in explaining the future dispersion of returns 

across portfolios 

Constructed to more closely capture the investment decisionmaking 

process (e.g., Cahart Model) 

Factors are the returns for various style indexes (e.g., smallcap 

value, small-cap growth, large-cap value, and large-cap 

growth). The style analysis produces a benchmark of the 

weighted average of these asset class indexes that best 

explains or tracks the portfolio’s returns. 

Broad group of managers with similar investment disciplines. 

Although not a benchmark, per se, a manager universe 

allows investors to make comparisons with the performance 

of other managers following similar investment disciplines 

Built to more precisely reflect the investment discipline of an 

investment manager. Such benchmarks are developed 

through discussions with the manager and an analysis of past 

portfolio exposures. After identifying the manager’s 

investment process, the benchmark is constructed by 

selecting securities and weightings consistent with that 

process and client restrictions.

35i) Discuss uses of liability-based benchmarks. 

35j) Describe types of asset-based benchmarks. 

Liability-Based Benchmarks 

1. Which of the following portfolios is most likely to use a 

liability-based benchmark? 

A. A portfolio managed for a private client with a goal of 

capital appreciation 

B. An intermediate-duration fixed-income portfolio 

managed for a defined benefit pension fund 

2. Which of the following most accurately describes a liability-based 

benchmark? 

A. It focuses on the cash flows that the benchmarked asset must 

generate. 

B. It represents the performance of a specific security market, 

market segment, or asset class. 

C. It is a collection of securities that represents the pool of assets 

available to the portfolio manager. 

C. The total portfolio for a defined benefit pension fund 

with an asset allocation of 80% fixed income/20% 

equity 

A is correct. A liability-based benchmark is constructed according to the cash 

flows that the benchmarked asset must generate. 

C is correct. A liability-based benchmark is most likely to be used 

for the total pension fund portfolio as the plan sponsor tracks its 

funded status.

35k) Discuss tests of benchmark quality. 

35m) Describe the impact of benchmark misspecification on attribution and appraisal analysis. 

Unambiguous 

Investable 

Measurable 

Appropriate 

Reflective of current 

investment opinions 

Specified in advance 

Accountable 

Characteristics of a valid benchmark 

The individual securities and their weights should 

be clearly identifiable. 

It must be possible to replicate and hold the 

benchmark to earn its return (at least gross of 

expenses). 

It must be possible to measure the benchmark’s 

return on a reasonably frequent and timely basis. 

The benchmark must be consistent with the 

manager’s investment style or area of expertise. 

The manager should be familiar with the securities 

that constitute the benchmark and their factor 

exposures. 

Must be constructed prior to the evaluation period so 

that the manager is not judged against benchmarks 

created after the fact. 

The manager should accept ownership of the 

benchmark and its securities and be willing to be held 

accountable to the benchmark. The benchmark should 

be fully consistent with the manager’s investment 

process, and the manager should be able to 

demonstrate the validity of his or her benchmark. 

Through acceptance of the benchmark, the sponsor 

assumes responsibility for any discrepancies between 

the targeted portfolio for the fund and the benchmark. 

The manager becomes responsible for differences 

between the benchmark and her performance. 

Benchmarks 

1. You have hired a bond manager to run an intermediate-duration government fixedincome 

portfolio. Which type of benchmark is most suitable for this portfolio? 

A. A broad market index 

B. A liability-based benchmark 

C. A factor-model-based benchmark 

A is correct. A broad market index is a suitable benchmark for a government bond 

portfolio provided the maturity and duration characteristics of the benchmark align with 

those of the investment mandate. 

2. You have hired a top-down quantitative equity manager who has built a 

proprietary process based on timing the fund’s exposures to systematic risks. 

Which type of benchmark is most suitable for this portfolio? 




C is correct. Factors represent systematic risks. The manager’s approach attempts to 

create alpha by timing the portfolio’s exposure to factors. A factor-model-based 

benchmark can be constructed to represent the manager’s investment approach.



3. You are on the board of a pension fund that is seeking to close the gap 

between its assets and its liabilities. What is the most appropriate benchmark 

against which to measure the performance of the plan’s outsourced chief 

investment officer? 




B is correct. The primary investment objective of the pension portfolio is to close the 

gap between assets and liabilities. The performance of the pension fund’s manager 

should be evaluated relative to this objective. 

You are a portfolio manager at JEMstone Capital. Your firm has been hired to run a 

global small-cap developed market equity portfolio. The agreement with the client sets a 

minimum market cap of US$500 million and a liquidity constraint that states that a 

portfolio holding is capped at 5 times its average daily liquidity over the past 12 months. 

Most portfolios managed by the firm are managed without constraint against the MSCI 

ACWI Small Cap Index, which has an average market cap of approximately $1.2 billion 

and a median market cap of approximately $650 million. A stock is eligible for inclusion 

in the index if the shares traded over the prior three months are equal to at least 20% of 

the security’s free-float-adjusted market capitalization. Your team is discussing the 

suitability of the MSCI ACWI Small Cap Index for this portfolio. 

Discuss the validity of this benchmark using the Richards and Tierney framework. 

Unambiguous 

Investable 

Measurable 

Does not meet 

the criteria 

of appropriate. 

Reflective of 

current 

investment 

opinions 

Specified in 

advance 

Accountable 

The individual securities and their weights 

are clearly identifiable. 

The shares in the index are freely tradeable. 

Index returns are published daily. 

The liquidity and capitalization constraints 

imposed by the client are not consistent with 

the manner in which the manager runs other 

portfolios managed by the firm. 

The benchmark was selected by the 

manager and is presumed to be 

representative of the manager’s investment 

process. 

The benchmark is not created after the fact. 

The manager may choose to 

be accountable to this index if the liquidity 

and capitalization constraints are not 

expected to interfere with the ability to 

execute the investment strategy. 

The client should be made aware of the 

discrepancies between the portfolio 

constraints and the benchmark.



Evaluating Benchmark Quality: 

Analysis Based on a Decomposition of Portfolio Holdings and Returns 

Portfolio’s return (P) = itself P = P 13 

Incorporate Benchmark, B P = B + (P − B) 14 

P – B = Active return = A P = B + A 15 

Enter market index return (M) P = M + (B – M) + A 16 

B – M = manager’s style return = S 

P = M + S + A 

If the manager’s portfolio is a broad market index where S = 0 and A = 0 P = M 

If the benchmark is a broad market index, then S = 0 P = M + A. 

If the benchmark is a broad market index and the manager does have style 

differences from the benchmark, the analysis using the broad market 

benchmark is incorrect. 

Do manager’s active selection decisions align with the style currently 

favored by the market (systematic biases) 

Likewise, we define the difference between the portfolio and the broad 

market index as E = (P – M). 

P = M + S + A 

Style return (S) will be lumped together with the measured active management component (A), 

manager’s true added value will be obscured. 

A = (P – B), S = (B – M) 

A good benchmark should not reflect any biases, where the correlation between A and S should 

not be statistically different from zero. 

When a manager’s style (S) is in (out of) favor relative to the market, we expect both the 

benchmark and the account to outperform (underperform) the market. Therefore, a good 

benchmark will have a statistically significant positive correlation coefficient between S and E.



Decomposition of Portfolio Return 

The return due to style is the style-specific benchmark return of 7.85% minus 

the broad market return of 8.92%: −1.07%. 

1. Assume that the Courtland account has a return of −5.3% in a given 

month, during which the portfolio benchmark has a return of −5.5% 

and the market index has a return of −2.8%. 

A. Calculate the Courtland account’s return due to the manager’s style. 

The return due to style is S = B – M = −5.5% − (–2.8%) = −2.7%. 

B. Calculate the Courtland account’s return due to active management. 

A = P – B = −5.3% − (–5.5%) = 0.2%. 

2. Assume that Mr. Kuti’s account has a return of 5.6% in a given month, 

during which the portfolio benchmark has a return of 5.1% and a 

market index has a return of 3.2%. 

A. Calculate the return due to the manager’s style for Mr. Kuti’s account. 

S = B – M = 5.1% − 3.2% = 1.9%. 

B. Calculate the return due to active management for Mr. Kuti’s account. 

A = P – B = 5.6% − 5.1% = 0.5%. 

3. An actively managed mid-cap value equity portfolio has a return of 

9.24%. The portfolio is benchmarked to a mid-cap value index that has 

a return of 7.85%. A broad equity market index has a return of 8.92%. 

Calculate the return due to the portfolio manager’s style. 

4. A US large-cap value portfolio run by Anderson Investment 

Management returned 18.9% during the first three quarters of 2019. 

During the same time period, a US large-cap value index had a return of 

21.7% and a broad US equity index returned 25.2%. 

A. Calculate the return due to style. 

The return due to style is the difference between the benchmark and the 

market index, or S = (B − M) = (21.7% − 25.2%) = −3.5%. 

B. Calculate the return due to active management. 

The return due to active management is the difference between the portfolio 

and the benchmark, or A = (P − B) = (18.9% − 21.7%) = −2.8%. 

C. Using your answers to A and B, discuss Anderson’s performance 

relative to the benchmark and relative to the market. 

Anderson’s underperformance relative to the broad US equity index is partly 

a function of style and partly a function of the manager’s weak performance 

within the style. Given that the US large-cap value index underperformed 

the US market index by 3.5%, we can infer that large-cap value was out of 

favor during the period measured. Provided the US large-cap value index is 

an appropriate benchmark for Anderson, the manager’s underperformance 

bears further investigation. The client would want to understand the specific 

drivers of the underperformance and relate those decisions to the 

manager’s stated investment process.

Impact of benchmark 

mis-specification 

A manager invests in 

Japanese stocks, thus, the 

MSCI Japan Index more 

closely represents the 

manager’s normal portfolio. 

The 2018 returns are as 

follows: 



Importance of Choosing the Correct Benchmark 

Lead to mismeasurement of the value added by 

the portfolio managers. 

The sponsor evaluates the manager using 

the MSCI Pacific Index comprised mostly 

Japanese stocks, but the index also 

includes Australia, New Zealand, Hong 

Kong SAR, and Singapore. 

• Manager return: 24.5% 

• MSCI Japan (normal portfolio) return: 

24.0% 

• MSCI Pacific (investor’s benchmark) 

return: 25.0% 

Implications • Fundamentally, any further performance attribution 

against the investor’s benchmark will also be useless. 

Peer group 

comparisons or 

benchmarking 

• By using the incorrect benchmark, the attribution 

would attempt to explain an underperformance, 

rather than the true active return, which contributed 

positively to the investor’s return. 

• Using a broad market index, as most fund sponsors 

do, typically misses the manager’s style (i.e., creates 

style bias). This decomposition is useful for 

understanding the impact of a mis-specified 

benchmark on performance appraisal. 

This is particularly susceptible to selection problems. 

Practitioners must select peers without suggesting to the 

PM that median peer group performance is the target. 

Performance vs MSCI Japan 

Performance vs MSCI Pacific 

24.5 – 24.0% = +0.5% (O/performed) 

24.5 – 25.0% = – 0.5% (U/performed) 

In summary, • the manager’s “true” active return is 

24.5% − 24.0% = + 0.5%, and 

• the manager’s “misfit” active return is 

24% − 25% = −1.0%. 

Motive for 

benchmark 

Investment decisions of the fund manager is then 

incentivized to not underperform the peer group median, 

often leading to herding around the median return. 

Sometimes, benchmarks are chosen for the wrong 

reasons. Underperforming managers change benchmarks 

to improve their measured excess return, which is both 

inappropriate and unethical.

Not an asset 

class such as 

equities and 

fixed income 

Use leverage, 

sell assets short, 

take positions in 

derivatives 

Transparency 

Arbitrage-based 

hedge fund 

strategies 

35l) Describe problems that arise in benchmarking alternative investments. 

Benchmarking Hedge Fund Investments 

Diverse characteristics make it difficult to create 

a single standard against; varied types of 

strategies unlimited investment universe, vary 

substantially from one to another; 

Some hedge funds lever many times their capital 

base, which increases their expected return and 

risk. A manager’s use of style, leverage, short 

positions, and derivatives may change over time. 

Hedge funds also typically lack transparency, 

are difficult to monitor, and are often illiquid. 

R F + spread (3- 6%) is advocated as benchmark, 

as arbitrage strategies are risk free, with the 

spread reflecting the active management return 

and management costs. 

However, most, even EMN strategies, are not 

completely free of systematic risk, and the use of 

leverage could magnify that systematic risk, so 

spread rate should be adjusted upward. 

Both broad market indexes and the R F rate will 

be weakly correlated or uncorrelated with hedge 

fund returns, thus failing the benchmark quality 

test: that states that portfolio and benchmark 

factor sensitivities should be similar. 

Hedge 

fund peer 

universes 

and 

limitations 

Benchmarking Hedge Fund Investments 

Because of the shortcomings of broad market indexes and the 

risk-free rate, hedge fund manager universes are often used 

as hedge fund benchmarks. 

Key limitations of such HF peer universes include: 

1. The risk and return characteristics of a strategy peer group 

is unlikely to be representative of the approach taken by a 

single fund. 

2. HF peer groups suffer from survivorship and backfill bias - 

when the index provider adds a manager to the index and 

imports the manager’s entire return history. 

3. HF performance data are often self-reported and typically 

not confirmed by the index provider. A fund’s reported net 

asset value may be a managed value. Even if the manager 

has no intention to misreport the data, hedge funds hold 

illiquid assets that require some subjectivity in pricing. If 

the previous period’s price is used as the current price or 

an appraisal is used, then the data will be smoothed. The 

presence of stale pricing will result in downward-biased 

standard deviations and temporal instability in correlations, 

with hedge funds potentially given larger portfolio 

allocations as a result.


Unrepresentative 

Large fund 

dominance 

Bias 

Weighting system 

Infrequent valuations 

Leverage 

Transparency 

Different measures 

of appropriate return 

measure. 

Benchmarking Real Estate Investments 

The benchmarks are based on a subset of the real 

estate opportunity set, not fully representative. 

Index performance is likely to be highly correlated with 

the returns of the largest fund data contributors. 

Benchmark returns are based on manager-reported 

performance and may be inherently biased. 

Benchmarks weighted by fund or asset value may 

place a disproportionate emphasis on the most 

expensive cities and asset types. 

Valuations based on appraisals, often infrequent and 

smooths changes in property values, and lag 

underlying property performance. Transaction-based 

indexes are becoming more readily available. 

Some benchmark returns are unlevered, whereas 

others contain varying degrees of leverage based on 

the structure used by the investor that contributed the 

data. 

Real estate indexes do not reflect the high transaction 

costs, limited transparency, and lack of liquidity that 

drive performance for actual real estate investments. 

Open-end funds, generally use time-weighted rates of 

return. Closed-end funds, however,, generally report 

using internal rates of return. 

Valuation 

methodology 

Time Value of 

Money 

Life cycle 

issues 

Choice of public 

market 

equivalent 

(PME) 

methodology 

Benchmarking Private Equity 

The valuation methodology used by the managers may 

differ. 

A fund’s IRR can be meaningfully influenced by an early 

loss or an early win in the portfolio. 

The data are from a specific point in time, and the 

companies in a fund can be at different stages of 

development. 

The PME methodology has been developed to allow 

comparisons of private equity IRRs with returns of 

publicly traded equity indexes. 

The methodology uses cash flow data to replicate the 

general partner’s capital calls and distributions, 

assuming these same cash flows were invested in the 

chosen equity index. 

Comparing the performance of the PME index with the 

net IRR of the fund reveals the extent of over- or 

underperformance of the PME index relative to the 

public index. 

Several PME methodologies exist; It is important to 

choose the appropriate PME for each private equity 

fund; a poorly chosen PME raises the risk of leading the 

investor to an incorrect conclusion.

Indexes use futures, 

rather than actual 

assets 

Some major groups 

are investable. 

Benchmarking of 

commodity 

investments 

presents similar 

challenges to other 

AIs, including 


Benchmarking Commodity Investments 

Commodity benchmarks attempt to replicate the returns 

available to holding long positions in commodities rather than 

the actual commodity. 

Because the cost-of-carry model ensures that the return on a 

fully margined position in a futures contract mimics the return 

on an underlying spot deliverable, futures contract returns are 

often used as a surrogate for cash market performance. 

The major indexes contain some common groups of 

underlying assets, including energy (oil and gas), metals 

(industrial and precious), grains (corn, soybeans, and wheat), 

and soft commodities (cocoa, coffee, cotton, sugar). 

However, beyond these basic groupings, commodity indexes 

vary greatly in their composition and weighting schemes. A 

market-cap-weighting scheme, so common for equity and 

bond market indexes, cannot be carried over to indexes of 

commodity futures. Because every long futures position has a 

corresponding short futures position, the market capitalization 

of a futures contract is always zero. 

1. the use of derivatives to represent actual commodity 

assets, 

2. varying degrees of leverage among funds, and 

3. the discretionary weighting of exposures within the index. 

Market 

indexes do 

not exist for 

managed 

derivatives 

peer group– 

based 

benchmarks, 

including 

survivorship 

bias. 

Difficult to find 

suitable 

benchmarks 

Use market 

indexes, such 

as the Barclay 

Distressed 

Securities 

Index. 

Benchmarking Managed Derivatives 

Benchmarks are typically specific to a single 

investment strategy. For example, the Mount 

Lucas Management Index takes both long and 

short positions in many futures markets based on 

a technical (moving-average) trading rule that is, 

in effect, specific to an active momentum strategy. 

Other derivative benchmarks are based on peer 

groups. For example, the BarclayHedge. These 

indexes suffer from the known limitations of peer 

group–based benchmarks, including survivorship 

bias. 

Benchmarking Distressed Securities 

Takes long time for this strategy to play out; thus, 

valuing the holdings may be a challenge. It is 

difficult to estimate the true market values, and 

stale pricing is almost inevitable. 

This can help but as index is constructed from 

multiple strategies, it is difficult to discern whether 

the index is suitable for a given investment 

approach. In addition, because the valuations for 

the member funds are calculated at random 

intervals, it doesn’t necessarily correct for the 

valuation issues noted previously.

35n) Calculate and interpret the Sortino ratio, the appraisal ratio, upside/downside capture ratios, maximum drawdown, and drawdown duration. 

35o) Describe limitations of appraisal measures and related metrics. 

Skill 

Luck 

Distinguishing Investment Skill from Luck 

Active investment management skill as the ability of a 

portfolio manager to add value on a risk-adjusted basis 

through investment analysis and insights. 

Performance reflects good luck (unanticipated good 

developments) and bad luck (unanticipated bad 

developments). 

The paradox of skill says as people become more 

knowledgeable about an activity, the difference between the 

worst and the best performers becomes narrower. 

Thus, the ever-increasing aggregate skill level of investment 

managers, supplemented by massive computing power and 

access to “big data,” may lead to narrower investment 

performance differentials and a greater likelihood that these 

differentials can be explained by luck. 

Perhaps we gain additional insight into 

skill by examining the consistency of 

performance over time. But the 

hypothesis that the manager’s underlying 

mean return exceeds the benchmark’s 

mean return may require many years of 

observations to confirm with a 

reasonably high degree of confidence 

One problem faced in 

investment performance 

appraisal is that many 

investment management 

performance records are only a 

few years long, making it 

difficult to distinguish between 

luck and skill. 

Sharpe ratio 

Appraisal Measures 

E(R P ) – R F /σ p 

Additional (excess) return for bearing risk above the risk-free 

rate, stated per unit of return volatility. 

Performance appraisal = excess return. 

Performance attribution = return in excess of a R B . 

Advantage 

Can be compared among different funds without the explicit 

choice of a market benchmark. 

Weakness 

• SD assumes investors are indifferent between upside and 

downside volatility. For example, for an investor looking 

for a potentially high-rewarding investment, volatility on 

the upside is not necessarily a negative. 

• Similarly, risk-averse investors concerned about the 

preservation of capital are clearly most concerned with 

downside risk.

Treynor 

ratio 



E(R P ) – R F /β p 

Measures the excess return per unit of systematic risk. We 

must carefully choose an efficient market benchmark against 

which to measure the systematic risk of the manager’s fund. 

The 

Appraisal 

Ratio (AR) 

Appraisal Measures 

Measures the reward of active management relative to the 

risk of active management (alpha from a factor model): 

AR = α / σε 

The 

Information 

Ratio (IR) 

Advantage 

Usefulness depends on whether systematic risk or total risk is 

most appropriate in evaluating performance. 

Shows performed in relation not to its own volatility (σ p ) but to 

the volatility it would bring to a well-diversified portfolio (β p ) 

Ranking is most useful if the portfolios whose performance is 

being evaluated are being combined in a broader, fully 

diversified portfolio. 

The ratio is most informative when the portfolios being 

evaluated are compared with the same benchmark index. 

E(R P ) – E(R B )/σ(r p – r B ) = Active return / Active risk (TE) 

Assess performance relative to the benchmark, scaled by risk 

The ratio implicitly assumes the chosen benchmark is well 

matched to the risk of the investment strategy. 

where 

σ ε equals the standard deviation of ε t , commonly denoted as 

the “standard error of regression,” which is readily available 

from the output of commonly used statistical software. 

AR is a returns-based measure, like the IR. It is the 

annualized alpha divided by the annualized residual risk. 

In the appraisal ratio, both the alpha and the residual risk are 

computed from a factor regression. Although the AR can be 

computed using any factor model appropriate for the 

portfolio, the measure was first introduced by Treynor and 

Black (1973) using Jensen’s alpha and the standard 

deviation of the portfolio’s residual or non-systematic risk. 

Treynor and Black argued that security selection ability 

implies that deviations from benchmark portfolio weights can 

be profitable and showed that the optimal deviations from the 

benchmark holdings for securities depend on “appraisal 

ratio.” The appraisal ratio is also referred to as the Treynor– 

Black ratio or the Treynor–Black appraisal ratio.



Sortino 

Ratio 

Sharpe ratio = [E(R P ) – R F /σ p ] : 

Equally penalizes both upside and downside volatility. 

Sortino ratio = E(R P ) – R T /σ D 

A measure of return per unit of downside risk. 

Modifies Sharpe ratio to penalize only those returns that 

are lower than a user-specified return, being R T, the 

minimum acceptable return (MAR) [target rate of return). 

Example 

Replaces SD with downside risk as target semi-standard 

deviation or target semi-deviation, σ D; hence it penalizes 

managers only for “harmful” volatility. 

Assume a portfolio has an MAR of 4.0%. The portfolio’s 

returns over a 10- year period are given in Exhibit 14. 

And the numerator is E(R P ) – R T = 6.0% − 4.0% = 2.0% 

Target semi-Standard deviation is reported in Exhibit 14. 

Not a risk 

premium 

Based on the information in the table, the Sortino ratio is 

approximately 2.0% / 3.07% = 0.65. 

It is return that is greater than what is minimally 

acceptable to the investor. It penalizes a manager when 

portfolio return is lower than the MAR.



Sortino 

Ratio 

Advantages 

Better than Sharp Ratio when return distributions are not symmetrical, 

due to the underlying assumption of normally distributed returns inherent 

in the standard deviation used for Sharpe ratio. 

Sharp ratio will not effectively distinguish between strategies with 

greater-than-normal upside volatility (positively skewed strategies, such 

as trend following) and strategies with greater-than-normal downside 

volatility (negatively skewed strategies, such as option writing). Both 

types of volatility are penalized equally in the Sharpe ratio. 

The Sortino ratio is arguably a better performance metric for such assets 

as hedge funds or commodity trading funds, whose return distributions 

are purposefully skewed away from the normal. 

The Sortino ratio it is most relevant when one of the investor’s primary 

objectives is capital preservation. 

Although there are arguments in favor of both the Sharpe ratio and the 

Sortino ratio, the Sharpe ratio has been much more widely used. In 

some cases, this preference may reflect a certain comfort level 

associated with the use of standard deviation, which is a more traditional 

measure of volatility. 

Also, cross-sectional comparisons of Sortino ratios are difficult to make 

applicable to every investor, because the MAR is investor-specific. 

Performance Appraisal Measures 

1. Portfolio B delivered 10.0% annual returns on average over 

the past 60 months. Its average annual volatility as measured 

by standard deviation was 14.0%, and its downside volatility 

as measured by target semi-standard deviation was 8.0%. 

Assuming the target rate of return is 3.0% per year, the 

Sortino ratio of portfolio B is closest to: 

A. 0.66. 

B. 0.77. C is correct. 

C. 0.88. 

2. Why might a practitioner use the Sortino ratio, rather than the 

Sharpe ratio, to indicate performance? 

A. He is measuring option writing. 

B. The return distributions are not symmetrical. 

C. The investor’s primary objective is capital preservation. 

D. All of the above 

D is correct, because the Sortino ratio is more relevant when return 

distributions are not symmetrical, as with option writing. The Sortino 

ratio is also preferable when one of the primary objectives is capital 

preservation.



Performance Appraisal Measures -continued 

3. Portfolio Y delivered an average annualized return of 9.0% over the past 

60 months. The annualized SD over this same time period was 20.0%. 

The market index returned 8.0% per year on average over the same 

time period, with an annualized standard deviation of 12.0%. Portfolio Y 

has an estimated beta of 1.40 versus the market index. Assuming the 

risk-free rate is 3.0% per year, the appraisal ratio (AR) is closest to: 

A. ‒0.8492. 

B. ‒0.0922. 

C. ‒0.0481. 

AR = α / σε 

B is correct. 

Jensen’s alpha, α p = 9.0% – [3.0% + 1.40(8.0% – 3.0%)] = –1.0% = –0.01. 

Non- systematic risk, σ 2 εp = = 0.202 – 1.402(0.122) = 0.011776. 

4. The AR is the ratio of the portfolio’s alpha to the standard deviation of its: 

A. total risk. 

B. systematic risk. 

C. non-systematic risk. 

4. Portfolio C delivered an average annualized return of 11.0%, with an 

annualized SD of 14.0% based on the past 60 months of data. The 

market index returned 12.0% per year over the same time period, 

with an annualized standard deviation of 16.0%. A market model 

regression estimates beta of 0.90 for Portfolio C, with an R 2 of 0.64. 

Assuming the R F is 3.0% per year, the appraisal ratio is closest to: 

A. ‒0.1701. 

B. ‒0.1304. 

C. ‒0.0119. 

C is correct. 

αp = 11.0% − [3.0% + 0.90(12.0% − 3.0%)] = −0.10% 

Non-systematic risk , σ 2 εp = (1 − 0.64)0.14 2 = 0.007056. 

AR = α / σε = −0 001 /√0.007056 = −0.0119. 

5. Assume a target return of 3.0%. Annual returns over the past four 

years have been 6.0%, −3.0%, 7.0%, and 1.0%. The target semistandard 

deviation is closest to: 

A. 1.33%. 

B. 3.16%. 

C. 4.65%. 

B is correct. 

C is correct. It is ratio of the portfolio’s alpha to the standard deviation of the 

portfolio’s non-systematic risk. Allows an investor to evaluate whether excess 

returns warrant the additional non-systematic risk in actively managed portfolios.

Capture 

ratios & 

draw downs 

Capture 

Ratios 



CR (m, B, t) = UC (m, B, t)/ DC (m, B , t) 

Large losses require proportionally greater gains to reverse or offset. 

Performance measures used to monitor this aspect of manager 

performance include capture ratios and drawdowns. 

Measure manager’s participation in up and down markets—that is, the 

manager’s % return relative to that of the benchmark. 

UC(m,B,t) = R(m,t)/R(B,t) if R(B,t) ≥ 0 

DC(m,B,t) = R(m,t)/R(B,t) if R(B,t) < 0 

Capture 

Ratios 

Exhibit 17 

Where: CR(m, B, t) = capture ratio for 

manager m relative to benchmark B for time t 

CR measures the asymmetry of return and, as such, is 

like bond convexity and option gamma. 

Where: 

• UC(m,B,t) = UC for manager m relative to benchmark B for time t 

• DC(m,B,t) = DC for manager m relative to benchmark B for time t 

• R(m,t) = Return of manager m for time t 

• R(B,t) = Return of benchmark B for time t 

Upside capture (UC) ratio: Measures capture when the benchmark 

return is positive. UC greater (less) than 100% suggests o/performance 

(u/performance) relative to the benchmark, and 

Downside capture (DC) ratio: measures capture when the 

benchmark return is negative. DC less (greater) than 100% suggests 

o/performance (u/performance) relative to the benchmark. 

Practitioners should note that when the manager and benchmark 

returns are of the opposite sign, the ratio will be negative—for example, 

a manager with a 1% return when the market is down 1% will have a 

downside capture ratio of −100%. 

CR > 1 = positive asymmetry, 

or a convex return profile 

CR < 1 = negative asymmetry, 

or a concave return profile. 

As benchmark returns increase, 

portfolio returns increase—but at 

a increasing rate. 

Concave CR: As benchmark returns 

increase, portfolio returns 

increase—but at a decreasing rate.

Exhibit 18 



Consider the following return series for the manager, R(m), and 

the benchmark, R(B). 

During up 

markets 

During 

down 

markets 

Geometric avg return is 0.51% for the manager and 0.70% 

for the benchmark, giving an upside capture of 72.8%., 

Geometric avg return is −0.70% for the manager and 

−1.17% for the benchmark, giving a downside capture of 

59.8%. The manager’s capture ratio is 1.217, or 121.7%

Drawdown 



The cumulative peak-to-trough loss during a continuous 

period. 

Drawdown duration is the total time from the start of the 

drawdown until the cumulative drawdown recovers to zero, 

which can be segmented into the drawdown phase: 

• Start to trough and 

• Recovery phase (trough-to-zero cumulative return). 

Maximum DD(m,t) = min([V(m,t) – V(m,t*)]/V(m,t*), 0) 

Exhibit 20 

Observation 

where 

V(m,t) = portfolio value of manager m at time t 

V(m,t*) = peak portfolio value of manager m 

t > t* 

Consider the return on the S&P 500 Index from January 

2011 to February 2012. 

The drawdown is 0% until May 2011, when the return is 

−1.13% and the drawdown continues to grow, reaching a 

maximum of −16.26% in September 2011. 

The strong returns from October 2011 to February 2012 

reverse the drawdown. 

The total duration of the drawdown was 10 months, with a 

5-month recovery period.



Principle 

An asymmetrical return profile or avoiding large drawdowns, 

particularly during periods when the market is not trending 

strongly upward, can result in higher risk-adjusted returns. 

Exhibit 22 

Four trading strategies to illustrate the potential effects of the 

capture ratio and drawdown on return performance. 

This arises from basis drift, the change in the denominator 

when calculating returns, or from the practical problem of 

recovering from a smaller asset base after a large loss. 

Exhibit 21 

A portfolio decline of 90% needs a 900% gain to recover 

Experiment 

Each strategy’s allocation to the S&P 500 Total Return (TR) 

Index and to 90-day T-bills (assuming monthly rebalancing) 

is based on the realized monthly return from January 2000 

to December 2013. 

Time period chosen to encompasses the extreme 

drawdown of 2008–2009.) 

Long-only 

100% allocated to S&P 500 throughout the period. 

Low-beta 

50% allocated to the S&P 500 throughout the period. 

Positive 

asymmetry 

75% to the S&P 500 for months when the S&P 500 return is 

positive and 25% when S&P 500 is negative. 

Negative 

asymmetry 

25% to the S&P 500 for months when the S&P 500 return is 

positive and 75% when S&P 500 is negative. 

Exhibit 23 

Each profile’s cumulative monthly return.



Long only vs 

low beta 

Observations 

1. Long-only outperformed from the strong up market of 

2013. 

2. Low-beta outperformed for most of the period, with lower 

realized volatility (7.79% vs 15.64%) and higher riskadjusted 

returns during the entire period (0.14 vs 0.10). 

3. Low-beta profile declined only 18.8% (vs 42.5%), from 

January 2000 to September 2002; hence it had higher 

cumulative performance from January 2000 to October 

2007 despite markedly lagging the long-only profile (56.0% 

to 108.4%) from October 2002 to October 2007. 

Positive vs 

negative 

asymmetry 

4. Low-beta approach may sacrifice performance, but it 

shows that limiting drawdowns (-28.3% vs -50.9%) can 

result in better absolute and risk-adjusted returns in certain 

markets (Sharpe ratio, 0.14 vs 0.10). 

5. Not surprisingly, positive asymmetry results in better 

performance relative to long only, low beta, and negative 

asymmetry. It lags lags in up markets, this lag is more than 

offset by the lower participation in down markets. 

6. Not surprisingly, the negative asymmetry profile lags, with 

lower participation in up markets insufficient to offset the 

greater participation in down markets.



Key point 

Is strategy inherently 

convex or convexity 

relies on manager skill? 

Consistency between 

the stated investment 

process and reported 

performance? 

What is the strategy’s 

robustness and 

potential risks? 

How does Manager 

responds to a large 

drawdown? 

Positive asymmetry is a desirable trait, only some 

strategies are convex. 

A hedging strategy that rolls forward OTM put 

options will return many small losses as more 

options expire worthless than are compensated for 

by the occasional large gain during a large market 

downturn. This strategy will exhibit consistent 

positive asymmetry because it depends more on the 

nature of the strategy than on investment skill. 

An inconsistency could indicate issues with the 

strategy’s repeatability and implementation or more 

serious reporting and compliance concerns. Capture 

ratios can be useful in evaluating consistency issues. 

For example, the expected benefits of 

diversification—in particular, mitigating downside 

capture—might not be realized in a crisis if 

correlations converge toward 1. 

These provide evidence of the robustness and 

repeatability of the investment, portfolio construction, 

and risk management processes, as well as insight 

into the people implementing the processes. 

How does 

Manager 

responds to a 

large 

drawdown? 

Investment 

horizon and its 

relationship 

with risk 

capacity. 

Drawdowns are stress tests of the investment 

process and provide a natural point to evaluate and 

improve processes, which is particularly true of firmspecific 

drawdowns. 

An investor closer to retirement, with less time to 

recover from losses, places more emphasis on 

absolute measures of risk. In addition, even if the 

manager maintains her discipline during a large 

drawdown, the investor may not. 

This dynamic arises if the investor’s perception of risk 

is path dependent or the drawdown changes risk 

tolerance. If there has been no change to investment 

policy and no change in the view that the manager 

remains suitable, the temptation to exit should be 

resisted to avoid exiting at an inauspicious time. 

Investors with shorter horizons, with lower risk 

capacity, or who are prone to overreact to losses may 

bias selection toward managers with shallower and 

shorter expected drawdowns. 

This requires understanding of the source of the 

drawdown and the potential principal–agent risk, 

operational risk, and business risk that it entails.



Capture Ratios and Drawdown 

1. Do losses require proportionally greater 

gains to reverse or offset? Choose the 

best response. 

A. Yes, because in investing, it is easier to 

lose than to gain. 

B. No, gains should reflect losses. 

C. Yes, because we calculate percentage 

gains/losses on the basis of the starting 

amount of portfolio holdings. 

C is the correct response. If the denominator 

of the gain calculation is lower, a higher 

percentage gain is required to offset the loss. 

E.G, if you lose 10% of $100, your new holding 

is $90. To earn back the $10 loss, you must 

earn 10/90, or 11%. 

A is not correct because the “ease” of gaining 

or losing is not relevant. 

B is not correct because proportionally higher 

gains are required. 

2. Using the return information in the 

table below, what is the manager’s 

downside capture ratio? 

A. 103% 

B. 108% 

C. 115% 

A is the correct answer. See the table below.

35p) Evaluate the skill of an investment manager. 

Context 

Performance 

Attribution 

Analysis 

Over a five-year period, Manager A’s performance is 

9.42%, versus the benchmark performance of 9.25%. 

So, we know that the manager added 17 bps (9.42 − 

9.25) of outperformance. 

But did the manager earn the 17 bps through skill, or 

was she the beneficiary of luck? 

In Exhibit 25, we present the sample attribution analysis 

(for simplicity, we have combined the interaction effect 

with stock selection). 

Overall country 

allocation 

decisions 

Impacts Portfolio Managers decisions 

Portfolio manager lost 43 bps. 

O/w Australia (30% to 25%) lost 24 bps, as 

Australia underperformed (4.10% versus 9.25%). 

U/W Japan (51% to 60%) lost 21 bps, because 

Japan outperformed (12.4% versus 9.25%). 

Summary: manager did not make good weighting 

decisions over the five-year period. 

Stock selection 

decisions. 

Portfolio manager gained 59 bps 

Selecting Australian stocks added 31 bps 

Selecting Japanese stocks added 47 bps 

Selecting Hong Kong SAR lost 18 bps. 

Summary: Manager is a good stock picker, 

especially for Japanese and Australian stocks.; not 

successful in choosing the markets to allocate 

assets. 

Risks incurred 

to achieve 

performance 

Lets consider Manager A relative to other 

managers, using a sample appraisal ratio analysis 

over the same five-year period (Exhibit 26)


Volatility vs Benchmark 

(two-sided deviation) 

Sharp ratio vs Benchmark 

(total risk-adjusted returns) 

Trevor ratio vs Benchmark 

(systematic risk-adjusted returns) 

Information ratio vs Benchmark 

(active risk-adjusted returns) 

Sortino ratio vs Benchmark 

(one-sided deviation) 

< B, 2 nd < B, 3 rd > B, 1 st In the end 

Sample Evaluation of Skill 

Summary 

Risk 

Finding 

Country 

allocation: 

Manager A 

made incorrect 

A B C 

bets in Japan 

> B, 2 nd < B, 1 st > B, 3 rd 

and Australia. 

A long track 

< B, 2 nd > B, 1 st < B, 3 rd 

record is 

necessary to 

have any 

< B, 1 st < B, 2 nd < B, 3 rd 

statistical 

certainty in a 

> B, 1 st > B, 2 nd > B, 3 rd 

conclusion of 

skill or no skill. 

Reinforced Exhibit 25, Manager A has generated excess 

return over the benchmark through stock selection 

Did so without incurring significant excess risk relative to 

the benchmark and two similar managers. 

Within the limits of these analyses, Manager A has 

exhibited some level of skill worthy of further analysis. 

• What beliefs about country selection are embedded in 

Manager A’s investment philosophy? 

• Are country allocations integral to her investment 

approach, or they a by-product of her stock selection? 

• Answers to these will determine whether her skill 

should be penalized by the poor outcomes of the 

country selection decisions in this period. 

Additional analyses to increase confidence could include: 

• Risk attribution; 

• Ex ante analyses 

• Qualitative analyses of the manager (e.g., direct 

interviews with management to assess abilities), 

assessment of investment goals and management 

fees, and so on. 

We must understand and acknowledge the limits of all 

tools, being careful to qualify any conclusions regarding 

investment skill with the appropriate level of prudence.


Investment Manager Skill 

1. Which statement best describes Manager A’s performance during this fiveyear 

period? 

A. On an absolute basis, Manager A performed better than either B or C. 

B. Relative to systematic risk, A performed better than either B or Manager C. 

C. Manager C incurred the least risk. 

B is correct. Manager A’s Treynor ratio was better than that of both Manager B 

and Manager C for the period. 

A is not correct because A’s return for the period was less than C’s return. 

C is not correct because C’s annualized SD (volatility) was highest. 

2. Which of the following best provides evidence of manager skill? 

A. Security selection attribution effect of 47 bps 

B. Annualized performance equal to 9.42% 

C. Annualized standard deviation equal to 12.34% 

A is correct. Performance attribution can be indicative of manager skill, 

especially over longer historical time periods. 

Neither B nor C is correct because neither performance nor standard deviation, 

on their own, is necessarily indicative of manager skill.


Investment Manager Skill 

3. How can a practitioner best distinguish manager skill from luck? 

A. Run thousands of analyses of the same manager over an extended period. 

B. Avoid making broad-based judgments without statistical evidence. 

C. Use multiple analysis tools to jointly infer conclusions, sensitive to the limits 

of those tools. 

C is correct. 

Practitioners should use multiple analyses with different tools to find multiple 

sources that agree on evidence of skill. 

A is not correct, because thousands of analyses, especially the same types of 

analyses, may not necessarily lead to more conclusive results. 

B is not correct because it states best practice but not necessarily techniques 

to distinguish skill from luck.





Learning Outcome Statements 

Covered 

• a, b, c, d, e, f, g, h, i 

Not Covered 

• None 

36a) Describe the components of a manager selection process, including due diligence. 

36b) Contrast Type I and Type II errors in manager hiring and continuation decisions. 

36c) Describe uses of returns-based and holdings-based style analysis in investment manager selection; 

36d) Describe uses of the upside capture ratio, downside capture ratio, maximum drawdown, drawdown duration, and up/down 

capture in evaluating managers; 

36e) Evaluate a manager’s investment philosophy and investment decision-making process; 

36f) Evaluate the costs and benefits of pooled investment vehicles and separate accounts; 

36g) Compare types of investment manager contracts, including their major provisions and advantages and disadvantages; 

36h) describe the three basic forms of performance-based fees; 

36i) Analyze and interpret a sample performance-based fee schedule.

36a) Describe the components of a manager selection process, including due diligence. 

Manager Selection Process Components 

Defining the Manager Universe 

• Attribution/Appraisal 

• Capture ratio 

• Maximum drawdown 

Qualitative Investment Due Diligence 

• Financial stability/Process 

• Vehicle/Terms 

• Monitoring 

1 

2 

3 

4 

• Suitability 

• Style 

• Active vs. passive 

Quantitative Analysis 

• Philosophy/Process 

• People 

• Portfolio construction vs. philosophy 

Qualitative Operational Due Diligence

Hiring and Continuation Errors 


H 0 : Manager has no skill 

H 1 : Manager has skill 

Decision 

No Skill 

Realization 

Skill 

Hire/Retain Type I Correct 

Not hire/ 

Fire 

Correct 

Type II 

Monitoring should involve both managers that were hired (to uncover Type I 

errors) and managers who were fired (to uncover Type II errors).

Performance Implications 

Firing a skilled 

manager 

Holding an 

unskilled manager 

• Size 

• Shape 

• Mean 

• Dispersion

Practice Question 

As a uptrending market becomes more efficient, the difference between Type I 

and Type II errors will most likely: 

A. Increase. 

B. Decrease. 

C. Remain the same. 

36b) Contrast Type I and Type II errors in manager hiring and continuation decisions.


As a uptrending market becomes more efficient, the difference between Type I 

and Type II errors will most likely: 

A. Increase. 

B. Decrease. 

C. Remain the same. 


Correct answer: B (LOS 36b; easy) 

Explanation: The possibility of earning excess economic returns decreases as 

the market becomes more efficient. Bad managers find it more difficult to 

make mistakes and good managers find it more difficult to gain an edge. 

Therefore, making Type I and Type II errors will become less costly.

36c) Describe uses of returns-based and holdings-based style analysis in investment manager selection; 

Style Analysis—Determining Sources of Risks and Return 

RETURNS-BASED 

HOLDINGS-BASED 

Top-down approach 

Bottom-up approach 

Estimates portfolio 

sensitivities to indexes 

representing specific factors. 

Estimates risk factor 

sensitivities to securities in 

the portfolio. 

Data is easy to acquire but 

the outcome is imprecise. 

Allows estimating current risk 

factors but is computationally 

intensive.

36d) Describe uses of the upside capture ratio, downside capture ratio, maximum drawdown, drawdown duration, and up/down capture in evaluating managers. 

Evaluation Using Drawdown and Capture 

A manager with large drawdowns may be less suitable as an investor nears the end of an investment 

horizon. 

Up 

capture 

96% 

Capture ratios help assess manager compatibility with an investor’s IPS in the context of the current 

market environment, especially as an investor nears the end of an investment horizon. 

Upside capture ratio is when the benchmark return is positive. 

Upside capture > 100% outperformance 

Downside capture ratio is when the benchmark return is negative. 

Downside capture < 100% outperformance 

Down 

capture 

40% 

Capture ratio is upside capture divided by downside capture. 

Drawdown is the cumulative peak-to-trough loss during a particular continuous 

period. 

Drawdown duration is the total time from the start of the drawdown until the 

cumulative drawdown recovers to zero.

Active Share 

36e) Evaluate a manager’s investment philosophy and investment decision-making process. 

AS = 0.5 w −W 

where 

n 

i= 

1 

i 

i 

w , W = portfolio weight and benchmark weight for asset 

i 

i 

 

i 

Tracking Risk 

Low 

High 

Low 

Closet indexer 

Sector rotator 

Active Share 

High 

Diversified 

stock picker 

Concentrated 

stock picker

Philosophy 

Passive 

Active 


Manager Due Diligence—Investment Philosophy 

Manager must 

determine 

whether market 

inefficiencies 

exist and can be 

exploited. 

Exposure to 

systematic risks 

Generate return 

greater than 

costs of 

exploiting 

inefficiencies. 

Structural 

Behavioral 

Structural



With regard to the capacity to exploit a market inefficiency, an active manager 

will least likely be concerned with: 

A. Dependence of the strategy on unique information. 

B. Whether the source of the inefficiency is repeatable. 

C. Whether the inefficiency will allow exploitation while covering costs.



With regard to the capacity to exploit a market inefficiency, an active manager 

will least likely be concerned with: 

A. Dependence of the strategy on unique information. 

B. Whether the source of the inefficiency is repeatable. 

C. Whether the inefficiency will allow exploitation while covering costs. 

Correct answer: A (LOS 36e; moderate) 

Explanation: Information advantages are a concern in establishing an 

investment philosophy rather than an evaluation of the capacity of an 

inefficiency.


Manager Due Diligence—Investment Decision-Making Process 

Idea Generation 

• Unique information 

• Unique 

interpretation 

• Timing advantages 

Idea Implementation Portfolio Construction Portfolio Monitoring 

• Ideas to investments 

• Strategy consistency 

• Repeatable 

• Approval chain 

• SAA/tactical basis 

• Manager convictions 

• Long/short methods 

• Stop losses/Risk 

• Hedges/derivatives 

• External 

considerations 

• Internal considerations


Manager Due Diligence—Operational Due Diligence 

• Trading/soft dollar 

• Unauthorized trading 

• Personal investment 

• Order of transactions 

• Third-party providers 

Operational 

Due Diligence 

• Fee calculation and 

collection 

• Reporting standards 

• Trade allocations 

RISK MANAGEMENT 

Contingencies 

• Offsite backup capabilities 

• Portfolio/firm position risk 

• Cybersecurity capabilities


Manager Due Diligence—Investment Vehicle 

POOLED 

SEPARATE 

Investor funds pooled. 

Trades made for the benefit of the 

pool; no customization. 

Liquidity demands of other 

investors influence manager 

actions. 

May pay taxes on other investor 

transactions. 

Potential lack of transparency or 

delayed reporting. 

Investor funds held in specific 

account for investor. 

Trades made for the benefit of the 

SMA investor; customization. 

Liquidity demands of other 

investors does not directly affect 

SMA investor. 

Tax efficiency possible. 

Position-level detail provided. 

Lower COST Higher



Which of the following is most likely an advantage of a separately managed 

account (SMA) over a pooled investment vehicle? 

A. Lower cost 

B. Potential tax efficiency 

C. Lower tracking risk to a published benchmark



Which of the following is most likely an advantage of a separately managed 

account (SMA) over a pooled investment vehicle? 

A. Lower cost 

B. Potential tax efficiency 

C. Lower tracking risk to a published benchmark 

Correct answer: B (LOS 36f; easy) 

Explanation: An SMA has the potential to customize accounts to the investor, 

including when taxable gains are harvested and losses are realized.


Manager Due Diligence—Investment Manager Contracts 

Lower Liquidity Higher 

• Venture funds 

• Private equity 

• Open-end funds 

• CTAs 

• ETFs 

• Closed-end funds 

• Hedge funds 

Subject to: 

• Hard locks 

• Soft locks


Manager Due Diligence—Performance-Based Fees 

Symmetrical 

Exposure to both gains and losses. 

Fee = Base + % of upside/downside 

performance 

Upside-Full 

Full upside exposure; downside protection 

Fee = Base + % of Positive performance 

Upside-Cap 

Capped upside exposure; downside protection 

Fee = Base + % of positive performance, capped

NAV 


Performance-Based Fee Calculations 

High-Water Marks and Hurdle Rates 

Highwater 

mark 

F 

R 

M 

Application of 

performance 

fee 

Hurdle 

rate 

 

( % ) 

HWM 

M 

0, % 

P ( Gross M ) 

Fees = AUM F + Max F R − F − Hurdle 

 

where 

, F = Fees for management and performance (incentives) 

P 

HWM 

Gross 

= Gross return in excess of the high-water mark 

Hurdle = in currency terms, after HWM and AUM-based fee



Which type of fee structure has the least incentive to assume greater risk to achieve 

higher return, assuming all are subject to high-water marks and the same hurdle rate? 

A. 1.5% of AUM plus 20% of net return 

B. 1% of AUM plus 20% of net gains 

C. 0.75% of AUM plus 20% of net gains, subject to a limitation that the performance 

fee may not exceed the management fee



Which type of fee structure has the least incentive to assume greater risk to achieve 

higher return, assuming all are subject to high-water marks and the same hurdle rate? 

A. 1.5% of AUM plus 20% of net return 

B. 1% of AUM plus 20% of net gains 

C. 0.75% of AUM plus 20% of net gains, subject to a limitation that the performance 

fee may not exceed the management fee 

Correct answer: A (LOS 36i; easy) 

Explanation: This fund structure provides an incentive through the management fee of 

1.5% to protect AUM from losses as well as a performance fee that would discourage 

risk-taking past the fund mandate to avoid loss sharing.



Reading 36: Manager Selection

CFA III, Session 14 2022

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?