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Exam in TIØ4317 – Empiriske og kvantitative metoder i finans, 2009

Exam in TIØ4317 – Empiriske og kvantitative metoder i finans, 2009

Exam in TIØ4317 – Empiriske og kvantitative metoder i finans, 2009

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Norges teknisk-naturvitenskapelige universitet<br />

Institutt for <strong>in</strong>dustriell økonomi <strong>og</strong> teknol<strong>og</strong>iledelse<br />

Contacts dur<strong>in</strong>g exam:<br />

1. Alexei Gaivoronski, tlf: 48243742<br />

2. Sjur Westgaard, tlf. 97122019<br />

Sensurer<strong>in</strong>gsfrist: 05.06.<strong>2009</strong><br />

<strong>Exam</strong> <strong>in</strong> <strong>TIØ4317</strong> <strong>–</strong> <strong>Empiriske</strong> <strong>og</strong> <strong>kvantitative</strong><br />

<strong>metoder</strong> i f<strong>in</strong>ans, <strong>2009</strong><br />

All types of calculators are admitted to exam<br />

Exercise 1<br />

Portfolio manager of pension fund Trygg Havn have to make decision about<br />

distribution of funds wealth between two classes of assets. One is governmental bonds<br />

which give 6% yearly return and are considered to be risk free. Another is <strong>in</strong>dex fund<br />

which follows the overall <strong>in</strong>dex of Rosenborg Stock Exchange. Dur<strong>in</strong>g the last 200<br />

trad<strong>in</strong>g days this <strong>in</strong>dex has shown the follow<strong>in</strong>g daily returns:<br />

return -5% -4% -3% -2% -1% 0% 1% 2% 3%<br />

Number of 3 7 9 15 22 38 72 29 5<br />

days<br />

The pension fund manager uses these data as the empirical distribution of future<br />

returns of the <strong>in</strong>dex. In order to serve his liabilities the manager has to construct<br />

portfolio with at least 8% yearly return.<br />

At the same time <strong>in</strong> order to fulfill requirements of regulatory bodies the daily 95%<br />

VaR of his portfolio should not exceed 1%.<br />

1. Is it possible for manager to reach both return and risk targets?<br />

2. What will be the answer if 1% risk bound is expressed <strong>in</strong> CVaR <strong>in</strong>stead of VaR?<br />

Please give detailed answer.<br />

Exercise 2<br />

Portfolio revision when the assets can be bought and sold <strong>in</strong> lots.<br />

There are many types of assets that can be bought and sold only <strong>in</strong> fixed amounts<br />

called lots. You are <strong>in</strong>vited to formulate portfolio rebalanc<strong>in</strong>g problem similar to<br />

those described <strong>in</strong> the book of Zenios, chapter 3, when portfolio is composed from<br />

such assets. Let us denote:<br />

yi <strong>–</strong> current hold<strong>in</strong>g of asset i, i=1:n<br />

p0i <strong>–</strong> current price of one unit of asset i<br />

pi - random future price of one unit of asset i<br />

These assets can be bought and sold <strong>in</strong> fixed lots of two sizes: smaller lot of asset i<br />

consists of k1i units and larger lot consists of k2i units. Buy<strong>in</strong>g or sell<strong>in</strong>g of one smaller<br />

lot entails transaction cost c1i. Buy<strong>in</strong>g or sell<strong>in</strong>g of one larger lot entails transaction<br />

cost c2i.<br />

1


1. Please formulate portfolio revision model with these assets<br />

2. Discuss its properties and possibilities for implementation.<br />

Exercise 3<br />

In this analysis we study credit spreads <strong>in</strong> the UK bond market. That is the difference<br />

between long term yields on corporate AAA rated bonds and government bonds. We<br />

have run an ADF test and confirmed that the spread is stationary. Then we model the<br />

credit spread with 2 ARMA models:<br />

• ARMA(2,2)<br />

• ARMA(2,0)<br />

The results from these 2 models t<strong>og</strong>ether with residual diagnostics are given below:.<br />

2


a) Write down the two models with their parameters. Give comments to the<br />

parameter values and their significance. Test formally if the MA(1) term and<br />

the MA(2) term <strong>in</strong> the ARMA(2,2) are significant. Choose a significance<br />

level at 5%.<br />

b) Describe and perform a test for normality and serial-correlation of the<br />

residuals for the two models. How are the results compare the assumptions we<br />

usually apply to l<strong>in</strong>ear regression models and ARMA models?<br />

c) Describe a criterion for model selection that can be applied. Accord<strong>in</strong>g to this<br />

criterion, which model will you choose?<br />

Exercise 4<br />

In this exercise we analyze volatility <strong>in</strong> the FX market. We are look<strong>in</strong>g at daily returns<br />

for USDJPY <strong>in</strong> the period 7/11 1984 to 31/8 2007. We estimate a GARCH(1,1)<br />

model, a GJR(1,1) model and an EGARCH(1,1) model for the volatility equation. For<br />

the mean equation we just assume a constant. The results for the models are given<br />

below:<br />

4


a) Write down the different models with their parameter estimates and <strong>in</strong>tepret<br />

the models. Give comments to the parameter significance. What type of<br />

restrictions should be apply to the parameters?<br />

b) Calculate the unconditional variance and standard-deviation for the<br />

GARCH(1,1) model.<br />

c) Discuss if asymmetry <strong>in</strong> volatility should be modeled for USDJPY.<br />

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