ECO00032M Investment and Portfolio Management 2022
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ECO00032M
MSc Degree Examinations 2022
DEPARTMENT OF ECONOMICS & RELATED STUDIES
Investment and Portfolio Management
Solutions
1. A portfolio manager summarizes the input to the index model from the macro and micro forecasters in the following table:
Micro Forecasts
Asset Stock A Stock B Stock C Stock D |
Expected |
Return (%) Beta 20 1:3 28 1:8 17 0:7 16 1:0 Macro Forecasts |
Residual Standard Deviation (%) 58 71 60 55 |
|
Passive |
Asset T一bills equity portfolio |
Expected |
Return (%) 4 16 |
Standard Deviation (%) 0 28 |
(a) Calculate expected excess returns and alphas for these stocks.
Answer:
E(ró ) 一 rf
αó = E(ró ) 一 rf 一 βó [E(rM ) 一 rf ]
Asset |
E(ró ) 一 rf |
αó (%) |
Stock A |
16 |
0:4% |
Stock B |
24 |
2:4% |
Stock C |
13 |
4:6% |
Stock D |
12 |
0:0% |
(b) Using the Treynor-Black procedure Önd the optimal weight of the active portfolio.
Answer:
Asset |
αj σ(ej )2 |
wó = |
αj /σ(ej )2 ≥ αj /σ(ej )2 |
Stock A |
0:0119 |
|
6:3492% |
Stock B |
0:0476 |
|
25:4219% |
Stock C |
0:1278 |
|
68:2289% |
Stock D |
0:0000 |
|
0:0000% |
|
0:1873 |
|
100:00% |
αa = β a = g(ea )2 =
wa(0) =
wa(*) =
wó αó = 3:7741%
wó βó = 1:0177
wó(2)g(eó )2 = 0:2015
αa =g(ea )2
= 12:2355%
1 + (1 w一0aβa )wa(0) = 12:2621%
(c) Find the expected return and standard deviation of the optimal risky portfolio. Answer:
E[rp] = rf + wa(*)αa + ((1 一 wa(*)) + wa(*)β a )E[rM 一 rf ]
= 0:04 + 0:1224 × 0:0377 + (0:8773 + 0:1224 × 1:0177) × (0:16 一 0:04) = 0:1649 = 16:49%
gp(2) = ((1 一 wa(*)) + wa(*)β a )2 g M(2) + (wa(*)g(ea ))2
= 0:0817714
gp = ←gp(2) = 28:60%
(d) Show numerically that the squared Sharpe ratio of the optimal risky portfolio, Sp , is equal to:
SM(2) + ╱ 、2
Answer: The Sharpe ratio of the optimal risky portfolio is:
E[rp 一 rf ]
gp
16:49% 一 4%
=
28:60%
= 0:436740 = 43:6740%
and therefore:
Sp(2) = 0:190741
This is the same as:
SM(2) + ╱ 、2 = ╱ 16 2(%)一8%4%、2 + ╱ 、2
= 0:4385712 + 0:0840722
= 0:190741
2. Suppose that there are two independent economic factors, F1 and F2 . The risk-free rate is 1% and all stocks have independent Örm-speciÖc components with a standard deviation of 45%. The following are well-diversiÖed portfolios:
Portfolio Beta on F1 Beta on F2 Expected Return
A
B
1:1
1:8
2:2
一0:4
28%
16%
(a) Calculate risk premia for F1 and F2 . Calculate the factor risk premia RP1 and RP2 in this economy?
Answer: From the above information we have:
28% = 1% + 1:1RP1 + 2:2RP2 ;
16% = 1% + 1:8RP1 一 0:4RP2 :
Solving for the risk premia RP1 and RP2 we obtain:
┐ = 2一 ┐ ┌ ┐
┐ = 2一 ┐ ━1 ┐ = 一1:5 × 0:21一 2:2 × 2:0 ┌ 一(一) 一1 ┐ ┌ ┐ = ┐
Thus, the risk-beta relationship is:
E(r) = rf + β1 × 9:9545% + β2 × 7:2955%:
(b) Suppose that another portfolio, portfolio C, is well diversiÖed with β 1 = 一0:7 and β 2 = 2:6 and expected return of 14%. Would an arbitrage opportunity exist? If so,
propose an arbitrage portfolio. Show that this portfolio is risk-free.
Answer: The equilibrium expected return on portfolio C is:
1% 一 0:7 × 9:9545% + 2:6 × 7:2955% = 13%:
Thus, portfolio C is underpriced (has too high expected return). The arbitrage strategy could be constructed as follows:
● sell 1 unit (dollar) of portfolio A
● buy 1 unit (dollar) of portfolio B
● buy 1 units (dollar) of portfolio C
● borrow 1 unit (dollar) at the risk-free rate
The risk exposure of this portfolio is:
(一1.1 + 1.8 一 0.7) × RP1 + (一2.2 一 0.4 + 2.6) × RP2 = 0. Thus, the arbitrage portfolio is risk-free. The expected return is:
一28% + 16% + 14% 一 1% = 1%.
Since the portfolio is well-diversiÖed with no exposure to the systematic risk it o§ers the risk-free return of 1%.
(c) Is it possible, hypothetically, to build an arbitrage portfolio if short selling is not allowed? Explain and give an example.
Answer: To build an arbitrage portfolio we need to eliminate the systematic risk by combining assets in proper quantities. Generally, if some portfolios are mispriced, we would buy the underpriced one (with higher than fair expected return) and sell the that is overpriced (with lower than fair expected return) with the same risk exposure (betas). Thus, if short selling is not allowed it might be di¢ cult to perform arbitrage. However, there might be some assets that have opposite betas than others. If such assets are underpriced, we might be able to construct long-only arbitrage portfolio.
[There might be other examples.] For example, imagine an asset D with β 1 = 一0.9 and β 2 = 0.2 and expected return 一6%, while the fair rate of return should be:
1% 一 0.9 × 9.95% + 0.2 × 7.3% = 一6.5%.
We would then:
● buy 1 unit (dollar) of portfolio B
● buy 2 units (dollar) of portfolio D
● borrow 3 units (dollar) at the risk-free rate
The risk exposure of this portfolio is:
(1.8 一 2 × 0.9) × RP1 + (一0.4 + 2 × 0.2) × RP2 = 0; while the expected return is:
16% 一 2 × 6% 一 3 × 1% = 1%.
(d) If the Arbitrage Pricing Theory is to be a useful theory, the number of systematic factors in the economy must be small. Why?
Answer: Any pattern of returns can be explained if we are free to choose an indeÖnitely large number of explanatory factors. If a theory of asset pricing is to have value, it must explain returns using a reasonably limited number of explanatory variables (i.e., systematic factors such as unemployment levels, GDP, and oil prices).
3.
(a) Describe the 2一step Fama-MacBeth (1973) test of the Capital Asset Pricing Model test. Answer: In the Örst step estimate a security characteristic line (SCL) for each security (portfolio) in a time-series regression:
ró,t 一 rf,t = aó + bó (rM,t 一 rf,t ) + eó,t :
Then, the stocks are sorted into 20 portfolios created according to their betas. The portfoliosíbetas are less noisy measures of betas than betas of individual securities.
In the second step we use the portfolios betas estimates from the Örst step regression as the independent variable in the cross-sectional regression:
rp,t 一 rf,t = y0 + y1 βp :
The squared betas and the estimates of the variance of the residuals, g(eó )2 , can be added as a variable:
rp,t 一 rf,t = y0 + y1 βp + y2 βp(2) + y2 g(eó )2 : The time series of the estimates of gammas allow us to test the hypotheses:
y0 = 0;
y 1 = rM 一 rf ;
y2 = 0;
y3 = 0:
(b) Explain the Rollís (1977) critique of the tests of the Capital Asset Pricing Model.
Answer: Roll pointed out that:
. There is a single testable hypothesis associated with the CAPM: the market port- folio is mean-variance e¢ cient.
. All other implications of the model, such as the linear relation between expected
return and beta, follow from the market portfolioís e¢ ciency and therefore are not independently testable.
. In any sample there will be an inÖnite number of ex post mean-variance e¢ cient portfolios using the sample-period returns and covariances. Sample betas calculated between each such portfolio and individual assets will be exactly linearly related to sample average returns. I.e. if betas are calculated against such portfolios, they will satisfy the SML relation exactly whether or not the true market portfolio is mean-variance e¢ cient in an ex ante sense.
. The CAPM is not testable unless we know the exact composition of the true market portfolio and use it in the tests. This implies that the theory is not testable unless all individual assets are included in the sample.
. The market proxy, such as S&P500, might be mean-variance e¢ cient even when the true market portfolio is not. Conversely, the proxy may be ine¢ cient but it implies nothing about the true market portfolioís e¢ ciency. Furthermore, most reasonable market proxies will be very highly correlated with each other and with the true market portfolio whether or not they are mean-variance e¢ cient. Such high degree of correlation will make is seem that the exact composition of the market portfolio is unimportant, whereas the use of di§erent proxies can lead to quite di§erent con- clusions. This problem is referred to as benchmark error, because it refers to the use of an incorrect benchmark (market proxy) portfolio in the tests of the theory.
(c) Why would an advocate of the e¢ cient market hypothesis believe that even if many investors exhibit behavioural biases, security prices might still be set e¢ ciently?
Answer: Even if many investors exhibit behavioral biases, security prices might still be set e¢ ciently if the biases are idiosyncratic. In this case, biases of di§erent investors could cancel out on average. However, even if the biases are systematic, e.g. due to a shared sentiment, waves of optimism or pessimism, or herd behaviour, prices might be e¢ cient if the actions of arbitrageurs move prices to their intrinsic values. Arbitrageurs who observe mispricing in the securities markets would buy underpriced securities (or possibly sell short overpriced securities) in order to proÖt from the anticipated subsequent changes as prices move to their intrinsic values. Consequently, securities prices would
still exhibit the characteristics of an e¢ cient market.
(d) Brieáy describe a typical industry life cycle. Answer:
● start-up, characterized by extremely rapid growth;
● consolidation stage, characterized by growth that is less rapid but still faster than that of the general economy
● maturity stage, characterized by growth no faster than the general economy
● relative decline, in which the industry grows less rapidly than the rest of the economy or actually shrinks.
4.
(a) The average returns for the mutual fund Steady Investments has been 12%. From re- gression of the fundís excess returns over the risk free rate on the excess returns of the market portfolio you found the fundís beta equal to 0:6 with residual standard deviation equal to 30% and adjusted R一squared equal to 75%. The risk-free rate over the period was 2%, and the marketís average return was 10% with standard deviation equal to 25%.
Find fundís:
. Total standard deviation
. Information ratio
. Sharpeís measure
. Treynorís measure
. M2 measure
Answer: The total variance of the fundís returns can be found from the adjusted R一squared:
g2 (e)
R = 1 一
g2 (r) ;
which gives
g2 (r) = 1(g)2 (一 = 1 0一 = 0:36
g(r) = 0:60 = 60%
The fundís alpha:
α = (r 一 rf ) 一 β(rM 一 rf )
= (12 一 2) 一 0:6 × (10 一 2)
= 0:052 = 5:20%:
The performance measures are:
IR = = = 0:1733 = 17:33%
S = 一r) rf = 126(%)一0%2% = 0:1667
T = E(r一 rf = 0:12一0:60:02 = 0:1667
M2 = (S 一 SM ) × gM = ╱0:1667 一 、0:25 = 一3:83%
(b) You have also been given the following information on another fund Xtreme Performance:
Based on your calculations from (a), which fund would you choose:
. as the entire investment fund?
Alpha Beta Information ratio Sharpe Treynor M2 T2 |
0.0440 1.2 0.1257 0.0.2530 0.1167 一0.0168 0.0367 |
. as one of a number of subportfolios?
. as an addition to the passive market portfolio?
Explain.
Answer: Since Xtreme has higher Sharpe and M2 measures it would be preferable to hold as the entire investment fund. However, it should be noted that both funds have lower Sharpe ratios than the market portfolio. As an addition to a well diversiÖed portfolio the appropriate risk measure is based on systematic risk (as opposed to total risk) and in this scenario Steady would be preferable, since it has higher Treynor and T2 measures. If one of the portfolios would be added to the market portfolio the appropriate performance measure is the information ratio, and therefore Steady would be a better choice.
(c) How many observations do we need before we can be 95% conÖdent that the realised
alpha for Steady Investments from (a) is down to skill, not to luck? Answer: The standard deviation of the estimator for α is approximately:
(α) ≈ ) =
^T
this equation for T gives:
= 127.86; 2
so the sample should include at least 128 observations.
(d) What is the basic trade-o§ when departing from pure indexing in favour of an actively managed portfolio?
Answer: The trade-o§ entailed in departing from pure indexing in favor of an ac
2023-01-09