The PERACS Alpha - Finance Magazin

Neuvermessung einer Anlageklasse:
Wie Rendite und Risiko bei
Investments in verschiedene Private-
Equity-Fonds korrelieren
Prof. Oliver Gottschalg of HEC Paris
Founder and Head of Research,
PERACS Independent PE Track Record Analytics and Certification

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve and Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
2

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
3

Consideration of Risk in PE
Typical Approach : Top Down based on aggregate times series data
1 Use of listed PE Proxies (e.g. LPX50, as used for Solvency II/QIS Studies)
Challenges:
• Listed Private Equity vehicles not necessarily representative for typical unlisted PE, which
leads to possible overstatement of volatility and correlation
2
Use of times series performance data from Private Equity Funds (e.g. Thomson One, preqin)
Challenges :
• Autocorrelation of performance data needs to be eliminated
• Available databases consist largely of rather old funds (15+ years) for which NAVs were not
systematically marked to market as they are today
• Generally aggregate treatment of vintage years
• No consideration of individual transactions and hence no specific treatment of different
investment years, industry segments or deal sizes
Existing Methods provide limited insights into risk-return relationship and are
unsuitable to assess/compare riskiness of different fund managers and strategies
4

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
5

Number of Variables
The Data-Driven Approach
of the HEC PE Observatory
Number of Datapoints
1
Commercially Available Data
(performance data on >5,000 PE funds
with >100,000 underlying investments
2
3
4
Proprietary Survey&PPM data
(>15,000 deals with deal IRR,
target characteristics and
investor information)
Survey&PPM data
(over 200 deals with detailed
management & accounting
information)
Case
Studies
Access to unique data
made possible through
partnership with buyout
firms, institutional
investors, database
vendors and industry
associations during
>10-year research effort.
For more information, please visit www.buyoutresearch.org
6

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
7

Measuring Returns:
The « PERACS Alpha »
Real-World Client Example
KKR European Fund I (Vintage 1999)
Duration =
4.55 years
2.85x
2.15x 18.35%
TVPI
Variable-Rate
Profitability Index
PERACS
Alpha
Performance is measured in the excess of the cost of the forgone opportunity investing capital elsewhere, which is approximated by the MSCI World index,
both in absolute multiple terms based on the PERACS Profitability Index and on an annualized basis through the PERACS Alpha, based on the duration of the
investment.
NAV at Par; Gross; All 41 Deals; Version 2.1.31; 11 Feb 2013, 4:00 PM; Page 13
8

Measuring Returns:
The « PERACS Alpha »
Generic Example
Linking PERACS Alpha to IRR
36%
Effect of IRR Bias due to
reinvestment hypothesis
26%
18%
8%
A GP's "PERACS Alpha" is a
measures of pure value
generation that is corrected
for the biases of standard
IRR and expresses returns
relative to the 'opportunity
cost' of not investing in the
public market. It is based on
a refinement of the method
developed by Acharya,
Gottschalg et al. (Review of
Financial Studies, 2012)
GP IRR
PERACS
Rate of
Return
PERACS
Alpha
Market
Returns
9

Focus: PE Performance
during economic Cycles
Three-Year Joint Research Effort with Golding Capital Partners
10

Focus: PE Performance
during economic Cycles
• Deal-level analysis based on HEC/GCP research database: 4822 realized buyouts
• Aggregate equity investment: 112.376.083.822,98 €
• Representative Distribution across geographies, industries, size-categories
• Inherent upward biases: data source ‘PPM’ ~ Top Quartile/Upper Half
11 * Source: Research Project 2011 ‘Finding Alpha’ in Collaboration with Golding Capital Partners

Focus: PE Performance during the
Great Financial Crisis
Alpha
2.7%
5,1%
-2.4%
Market Alpha Absolute
Alpha M-IRR*
Returns
Rate of Return
Vergleichbare
Aktienrendite
Commentary
• This analysis is based on 345 crisisdeals,
which were invested in before
the collapse of Lehman‘s in
September 2008 and realised post
September 2008
• The Alpha of these transactions is
5.1% (gross of fees)
• The absolute return of these
transactions executiedin a difficult
investment climate still continues to
be positive on an average long-term
basis
Positive Alpha even on private equity deals
which were directly affected by the crisis
* Source: Research Project 2013 ‘Finding Alpha’ in Collaboration with Golding Capital Partners
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Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
13

Cumulative Income Share
Measuring Risk:
The PERACS Risk Curve
Inspired by Lorenz curve in Macroeconomics
Approach used to assess Income Inequality across countries
100
80
60
40
20
0
0 20 40 60 80 100
Cumulative Population Share
Brazil China Perfect
Calculation and plotting of the
aggregate performance (= Alpha)
for any percentage of 'worst'
deals in the portfolio. The
corresponding 'PERACS Risk
Curve' captures cumulative
distribution function of the
distribution of performance in a
PE portfolio. Similar to the 'Gini
Coefficient' for wealth
distribution, we capture the
distribution of performance in a
single measure, the 'PERACS Risk
Coefficient', which makes it
possible to compare and
benchmark the risk of different
PE portfolios in a measure that is
independent of the performance
of these portfolios.
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1
5
9
13
17
21
25
29
33
37
41
45
49
53
57
61
65
69
73
77
% of value creation
The "PERACS Risk Curve"
of a Typical PE Fund
Generic Example
100%
80%
60%
40%
20%
0%
-20%
Alpha Drags
Vertex
Alpha Contributors
Break Even
Point
Insight
Overall assessment
of the distribution
(uniform vs. exponential)
of returns
in the portfolio as a
new risk measure
for PE portfolios.
Benchmarking
Comparison with
average performance
distribution
from HEC PE
database, based on
different portfolio
characteristics.
Number of transactions
15

Metric 5a – PERACS
Risk Curve by % of Deals
Real-World
Client Example
Nordic Capital Fund V versus Fund VI
PERACS Risk Coefficient
100%
80%
60%
40%
20%
0%
-20%
-40%
Benchmark EU
Since 2005 Large-Cap
Nordic Capital Fund V
Nordic Capital Fund VI
0.90
0.91
0.59
0.45
-60%
0% 20% 40% 60% 80% 100%
0 0.5 1
The PERACS Risk Curve illustrates the portion of the cumulative PERACS Alpha generated by the poorest-performing x% of the portfolio (as measured by %
of deals). The PERACS Risk Coefficient expresses the skewedness of returns from 0 (perfectly uniform) to 1 (perfectly concentrated Alpha).
16

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
17

Adjusted PERACS Risk Coefficient
Negative (!) Link Between
Risk and Return across GPs
Across 152 PE GPs with >9 realized deals in Track record
1.1
1.0
0.9
0.8
0.7
0.6
0.5
R 2 Linear = 0,273
0.4
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Aggregate Alpha
18

Adjusted PERACS Risk Coefficient
Negative (!) Link Between
Risk and Return across PE Funds
Across 263 PE Funds with >9 realized deals
1.1
1.0
0.9
0.8
0.7
0.6
0.5
R 2 Linear = 0,193
0.4
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Aggregate Alpha
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Adjusted PERACS Risk Coefficient
Negative (!) Link Between Risk and
Return across Segments of the PE Universe
Across 600 PE sectors (geography, industry, size, period)
with >9 realized deals
1.1
1.0
0.9
0.8
0.7
0.6
0.5
R 2 Linear = 0,271
0.4
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Aggregate Alpha
20

Agenda
• The Challenge
• Combining unique data with advanced methods
• Accurate Performance Measure: The PERACS Alpha
• Insightful Risk Metric: The PERACS Risk Curve & Coefficient
• Empirical Evidence on the Risk and Return Relationship
• Towards a Bottom-Up Risk Model for Private Equity
21

Consideration of Risk in PE
Towards a Bottom-Up Risk Model for Private Equity
• Monte Carlo simulation on an annual basis.
• An company is purchased at a point in time (year 0) and is then either sold (exit case) or kept in the
portfolio in the subsequent years.
• NAV(n) denotes the current value of an individual investment in year n. We calculate NAV(n) on the
basis of empirical data. In the Monte Carlo model, NAV(n) depends on the prior year figure, NAV(n-1).
The distribution of ratio NAV(n)/NAV(n-1) varies depending on whether or not an exit takes place at
time n.
• In the event of an exit in year n, exit-NAV(n)/NAV(n-1) is assumed to be gamma distributed, with the
parameters of this transitional distribution depending on the age and other characteristics (segment,
etc.) of the investment and derived from empirical data.
• In the event of no exit in year n, gamma distribution of NAV(n)/ NAV(n-1) is also assumed, with the
parameters calculated in the same way as the exit case but generally resulting in different values
(both the return and the standard deviation are usually higher in the case of exit than in the case of
no exit).
Existing Methods provide limited insights into risk-return relationship and are
unsuitable to assess/compare riskiness of different fund managers and strategies
22

Towards a Bottom-Up Risk
Model for Private Equity
…
NAV(3)
NAV(2)
…
NAV(1)
Exit-NAV(3)
NAV(0)
Exit-NAV(2)
Exit-NAV(1)
Jahr 0 Jahr 1 Jahr 2 Jahr 3 Jahr 4
YEAR EXIT PROBABILITY EXIT MULTIPLE
1 3.9% 1.45
2 5.6% 2.02
3 12.0% 2.43
4 13.1% 2.72
5 13.3% 2.53
6 10.5% 2.34
7 10.1% 2.21
8 9.9% 2.32
9 6.2% 2.00
10 4.8% 1.98
11 3.5% 2.08
* Source: joint Research Project with Dr. Bernd Kreuter, Palladio Partners

J-curve effect in the early investment phase
High returns and moderate risk in years 3 to 6
Moderate returns and high risk from year 7 onwards
Invested capital (as % of fund commitment), performance
and value at risk of an average individual fund
70%
60%
50%
40%
30%
20%
10%
0%
-10%
1 2 3 4 5 6 7 8 9 10 11 12 13
-20%
-30%
-40%
-50%
* Source: joint Research Project with Dr. Bernd Kreuter, Palladio Partners
Investiertes Kapital Erwartete Jahresrendite (realisiert und unrealsiert) 99,5% VaR bei gut diversifiziertem Fonds 99,5% VaR bei weniger gut diversifiziertem Fonds

Invested capital (as % of total commitment),
performance and value at risk of a portfolio
50%
40%
30%
20%
10%
0%
-10%
1 2 3 4 5 6 7 8 9 10 11 12 13
-20%
-30%
-40%
Investiertes Kapital
Erwartete Jahresrendite (realisiert und unrealsiert)
99,5% VaR bei gut diversifiziertem Fonds 99,5% VaR bei weniger gut diversifiziertem Fonds
* Source: joint Research Project with Dr. Bernd Kreuter, Palladio Partners

Summary and Conclusions
• The PERACS Alpha accurately measures what LP (should) care about:
annualized returns relative to the “opportunity cost” of PE investing
• Alpha has been found to be concentrated in difficult economic times
• Based on 345 realized PE deals around the Great Financial Crisis, we still
document a positive Alpha of over 500 Basis Points
• The PERACS Risk Curve/Coefficients traces relevant aspects of PE Risk in an
intuitive fashion
• Risk and Return in PE seem to be negatively correlated: Better GPs deliver
greater Alpha at lower volatility
• Bottom-up Risk Modeling for PE Portfolio makes more accurate risk
budgeting possible
26

Thank you for your attention !
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About Professor Oliver Gottschalg
Current Positions
• Director of the HEC PE Observatory
• Academic Director of the TRIUM
Global Executive MBA Program
• Founder and Head of Research,
Peracs, PE Track Record Analytics
Research
• Published in the Review of Financial Studies, Harvard Business
Review, Academy of Management Review, Strategic
Management Journal, Journal of Banking and Finance, etc.
• Featured over 100 times in the business media (press, radio,
TV and online) in the past 2 years, including The Economist,
Financial Times, Wall Street Journal, Financial News, Les Echos,
etc.
Consulting
• Tailored projects for leading sponsors, institutional investors
and advisors. Repeatedly served as advisor to policy makers at
the national and European level in questions related to the
possible regulation of private equity.
Education
• Dipl. Wirtschaftsingenieur (TU Karlsruhe)
• MBA (Georgia State University)
• MSc. of Management (INSEAD)
• Ph.D. (INSEAD)
Work Experience
• Federal Reserve Bank, US
• Bain & Company – Private Equity Practice
Teaching
• HEC MBA Program
• HEC Grande Ecole Program
• HEC Executive Education
• TRIUM Global EMBA Program
• INSEAD Executive Education
• LBS Executive Education
• Tsinghua University Executive Education
• Company-Specific Executive Programs
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About PERACS
• PERACS is not just another performance benchmark, but it provides
customized and insightful metrics to quantify relevant elements of past
performance, risk attributes and strategic differentiators
• Independent, credible, trustworthy, global, conflict-free, and singularly
focused
• Granular analysis built up from company by company portfolio analysis
• Formulaic and transparent. Trusted standardized comparisons
• Dynamic quarterly updates and annual reviews
• Methodology of leading industry academics and investors
• Value added service provided by GPs to their LPs
• Used in GP marketing materials with success
PERACS: The Global Standard for PE Performance Analytics
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Five PERACS Metrics
A
B
C
D
E
Measuring Returns based on the PERACS Alpha and the PERACS Rate of Return
• Enhanced Performance Measurement, avoiding issues with IRR Methodology
• Public-Market Benchmarking (PME) Perspective
• Quantification of different components of GP's added value
Benchmarking Returns
• Objective and data-driven identification of 'Relevant Peer Funds'
Documenting Value Creation Components based on PERACS Value Driver Bridge
• Growth, efficiency gains, multiple expansion, debt reduction, currency fluctuation
Strategic Distinctiveness
• Measures of distinctive strategy, unique deal flow, and strategic consistency/drift
Measuring Return Volatility based on the PERACS Risk Curve and Coefficient
• Assessment of portfolio risk based on historical return distribution
• Graphical representation based on intuitive curve inspired by "Lorenz Curve"
Detailed video tutorials in all PERACS methods are available on
Youtube and on PERACS.com
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PERACS in the ILPA Newsletter
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