三级CFA考试SS6复习笔记.pdf

2011年年CFA三级基础班讲义三级基础班讲义 SS6 Capital Market Expectations in Portfolio Management 讲师 薛隽讲师 薛隽 CFA CPA 日期 日期 2011年年3月 地点 上海 北京 深圳 月 地点 上海 北京 深圳 上海金程国际金融专修学院上海金程国际金融专修学院上海金程国际金融专修学院上海金程国际金融专修学院 2 2 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Topic in CFA Level III SS 1 2ETHICS MONITORING AND REBALANCING SS 17PERFORMANCE EVALUATION AND ATTRIBUTION SS 18GLOBAL INVESTMENT PERFORMANCE STANDARDS 3 3 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Framework ORGANIZING THE TASK FRAMEWORK AND CHALLENGES 1 A Framework for Developing Capital Market Expectations 2 Challenges in Forecasting TOOLS FOR FORMULATING CAPITAL MARKET EXPECTATIONS 1 Formal Tools 2 Survey and Panel Methods 3 Judgment ECONOMIC ANALYSIS 1 Business Cycle Analysis 2 Economic Growth Trends 3 International Interactions 4 Economic Forecasting 5 Using Economic Information in Forecasting Asset Class Returns 4 4 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Framework What s CME Investors expectation concerning the risk and return prospects of asset classes Why we need CME Input to formulating a strategic asset allocation 5 5 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formulate capital market expectations The analyst should use a seven step process 1 Determine the capital market expectations that are needed given the investor s objectives 2 Investigate assets historical performance and their determinants 3 Identify the valuation model used and its requirements 4 Collect the best data possible 5 Use experience and judgment to interpret current investment conditions 6 Formulate capital market expectations and 7 Monitor actual performance and use it to refine the process Other concepts Alpha research active including building CME Beta research passive 23 a 6 6 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting High quality forecasts are consistent unbiased objective well supported and have a minimum amount of forecast error 9 problems encountered in producing forecasts 1 Limitations to using economic data Time lag Revision Change in definition or calculation method Re based 23 b 7 7 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 2 Data measurement errors and biases transcription errors These are errors in gathering and recording data Such errors are most serious if they reflect a bias survivorship bias arises when a data series reflects only entities that have survived to the end of the period Without correction statistics derived from series subject to survivorship bias can be misleading in the forward looking context of expectations setting Return is overestimated appraisal smoothed data for certain assets without liquid public markets appraisal data are used in lieu of market price transaction data Appraised values tend to be less volatile than market determined values for the identical asset would be Risk is underestimated 23 b 8 8 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 3 Limitation of historical estimates Nonstationarity meaning informally that different parts of a data series reflect different underlying statistical properties 4 Ex Post risk as a biased risk measure of Ex Ante risk Looking backward we are likely to underestimate ex ante risk and over estimate ex ante aniticipated returns Only the ex ante risk premium is important in decision making 23 b 9 9 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 5 Biases in analyst s methods Data mining bias is introduced by repeatedly drilling or searching a dataset until the analyst finds some statistically significant pattern time period bias relates to results that are time period specific Research findings are often found to be sensitive to the selection of starting and or ending dates How to avoid check for economic rationales between the variables split into 2 sub periods 6 Failure to account for conditioning information 7 Misinterpretation of correlations 23 b 1010 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 8 6 Psychological traps 1 the anchoring trap the tendency of the mind to give disproportionate weight to the first information it receives on a topic Initial impressions estimates or data anchor subsequent thoughts and judgments 2 the status quo trap the tendency for forecasts to perpetuate recent observations that is to predict no change from the recent past f inflation has been rising at a double digit rate for several recent periods it is a natural tendency to forecast a similar increase in the next period May be overcome with rational analysis used within a decision making process 23 b 1111 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 8 6 Psychological traps 3 the confirming evidence trap the bias that leads individuals to give greater weight to information that supports an existing or preferred point of view than to evidence that contradicts it The tendency to seek out information that supports an existing point of view also reflects this bias Avoidance Equality to all evidences Involve of independent person Honest to motives 23 b 1212 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 8 6 Psychological traps 4 the overconfidence trap the tendency of individuals to overestimate the accuracy of their forecasts would be reflected in admitting too narrow a range of possibilities or scenarios in forecasting A good practice to prevent this trap from undermining the forecasting endeavor is to widen the range of possibilities around the primary target forecast 5 the prudence trap the tendency to temper forecasts so that they do not appear extreme or the tendency to be overly cautious in forecasting Avoidance widen the range In addition the most sensitive estimates affecting a forecast should be carefully reviewed in light of the supporting analysis 23 b 1313 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 8 6 Psychological traps 6 the recallability trap the tendency of forecasts to be overly influenced by events that have left a strong impression on a person s memory Often forecasts are overly influenced by the memory of catastrophic or dramatic past events To minimize the distortions of the recallability trap analysts should ground their conclusions on objective data and procedures rather than on personal emotions and memories 23 b 1414 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Challenges in Forecasting 9 problems encountered in producing forecasts 9 Model and input uncertainty model uncertainty uncertainty concerning whether a selected model is correct input uncertainty uncertainty concerning whether the inputs are correct 23 b 1515 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Framework ORGANIZING THE TASK FRAMEWORK AND CHALLENGES 1 A Framework for Developing Capital Market Expectations 2 Challenges in Forecasting TOOLS FOR FORMULATING CAPITAL MARKET EXPECTATIONS 1 Formal Tools 2 Survey and Panel Methods 3 Judgment ECONOMIC ANALYSIS 1 Business Cycle Analysis 2 Economic Growth Trends 3 International Interactions 4 Economic Forecasting 5 Using Economic Information in Forecasting Asset Class Returns 1616 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Forecasting Tools The tools for formulating capital market expectations formal tools statistical tools discounted cash flow models the risk premium approach financial market equilibrium models Survey and panel methods Analyst judgment 23 c 1717 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal Tools Statistical tools i Statistical tools Historical statistical approach sample estimators geometric arithmetic Shrinkage estimators reduce the influence of historical outliers through the weighting process and useful when data set is small and historical values are not reliable Time series estimators Multifactor models 23 c 1818 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal Tools Statistical tools 3 Time Series Estimators Time Series Estimators involve forecasting a variable on the basis of lagged values of the variable being forecast and often lagged values of other selected variables Volatility clustering is the tendency for large small swings in prices to be followed by large small swings of random direction Volatility clustering captures the idea that some markets represent periods of notably high or low volatility 22 1 2 1 ttt iiiii FFR 22 11 23 c 1919 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal Tools Statistical tools Multifactor models two factor multifactor model 2 212 1 22 2 22 1 2 2 21 iiiFiFii FFCov 211 2 2 1 2 2 2 2 1 1 21 FFCovjiCov jijiFjiFji 23 c 2020 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal Tools Statistical tools 23 c 2121 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal tools DCF models Discounted cash flow models correct emphasis on the future on the future cash flows of an asset and the ability to back out a required return do not account for current marker conditions such supply and demand so these models are viewed as being more suitable for LT valuation Earning growth rate g GDP growth rate excess corporate growth g P Div i g i Div PR R 0 11 0 23 c 2222 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism where the expected rate of return on equity Div1 P0 the expected dividend yield S the expected percent change in number of shares outstanding the expected inflation rate Grinold and Kroner step further by including a variable that adjusts for stock repurchases and changes in market valuations as represented by P E ratio E P Sgi P Div Ri 0 1 iR Formal tools DCF models 23 c 2323 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Grinold and Kroner g the expected real total earnings growth rate not identical to the EPS growth rate in general with changes in shares outstanding P E the per period percent change in the P E multiple The term S is negative in the case of net positive share repurchases is a positive repurchase yield in such cases Equation consists of three components an expected income return an expected nominal earnings growth return and an expected repricing return from expected P E ratio expansion or contraction 1 Expected income return D P S 2 Expected nominal earnings growth return i g 3 Expected repricing return P E The expected nominal earnings growth return and the expected repricing return constitute the expected capital gains Example 13 2 a risk premium based on the asset s sensitivity to the world market portfolio 3 expected return on the world market portfolio in excess of the risk free rate 23 c 2828 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism ICAPM E Ri RF i E RM RF where E Ri the expected return on asset i given its beta RF the risk free rate of return E RM the expected return on the world market portfolio i the asset s sensitivity to returns on the world market portfolio equal to Cov Ri RM Var RM ERP asset class risk premium RPi equal to E Ri RF is a simple function of the world market risk premium RPM equal to E RM RF iM ii mMii m mM RP RPRP M M iMii ERP ERP Formal tools Financial Market Equilibrium Models 23 c 2929 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Formal tools Financial Market Equilibrium Models Use the Singer Terhaar approach to estimate expected return 1 Estimate the perfectly integrated and the completely segmented risk premiums for the asset class using the ICAPM 2 Add the applicable illiquidity premium if any to the estimates from the prior step 3 Estimate the degree to which the asset market is perfectly integrated 4 Take a weighted average of the perfectly integrated and the completely segmented risk premiums using the estimate of market integration from the prior step 23 c 3030 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example ERP Suppose an analyst is valuing two markets A and B what is the ERP for the two markets their expected returns and the covariance between them given the following Sharpe ratio of the global portfolio 0 29 Standard deviation of the global port 8 Risk free rate 4 5 Degree of market integration for market A 80 Degree of market integration for market B 65 Standard deviation of Market A 18 Standard deviation of Market B 26 Correlation of Market A with global port 0 87 Correlation of Market B with global port 0 63 Estimated illiquidity premium for A 0 Estimated illiquidity premium for B 2 4 3131 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example Justifying Capital Market Forecasts Samuel Breed CIO of a university endowment is presenting the capital market expectations shown in Exhibit 1 to the end endowment t board of trustees 3232 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example Capital Market Projections Asset ClassProxyProjected 5 Year Annual Return Projected Standard Deviation Equities Large Cap U S equity S P 5008 80 16 50 2 Small mid cap U S equity Russell 25009 80 22 00 3 Ex U S equityMSCI EAFE9 20 20 00 Fixed Income 4 Domestic fixed income LB Aggregate4 70 4 50 5 Non U S fixed income Citi Non U S Govt 4 60 9 50 Other Assets 6 U S real estate NCREIF7 60 14 00 7 Private equityVE Post Venture Cap 12 00 34 00 8 Cash equivalents90 day T bill3 30 1 00 InflationCPI U2 60 1 40 3333 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Exhibit1 Correlations 12345678 Large Cap U S equity1 Small mid cap U S equity0 851 Ex U S equity0 740 611 Domestic fixed income0 270 20 211 Non U S fixed income0 03 00 220 321 U S real estate 0 640 520 470 20 031 Private equity0 630 570 630 20 10 451 Cash equivalents 0 1 0 2 0 250 3 0 05 0 060 071 3434 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example Assume the following The Sharpe ratio of the global investable market portfolio GIM is 0 28 and its standard deviation is 7 percent The beta of private equity with respect to the GIM is 3 3 and the beta of small mid cap U S equity is 2 06 William Smyth a trustee questions various projections for private equity as follows A I have seen volatility estimates for private equity based on appraisal data that are much smaller than the one you are presenting in which the volatility of private equity is much larger than that of small mid cap U S equity Your volatility estimate for private equity must be wrong Evaluate whether Smyth s Comment A is accurate 3535 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example Solution Smyth s Comment A is not accurate Although private equity and small cap stocks both represent ownership interests private equity is not traded and appraisal data will tend to underestimate volatility B The premium of private equity over small mid cap U S equity is not justifiable because they both represent ownership interests in U S business Evaluate whether Smyth s Comment B is accurate Solution Smyth s Comment B is not accurate One justification for a higher expected return for private equity is that it has a lockup period and should therefore bear an illiquidity premium 3636 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example C Using the ICAPM the forecast correlation between private equity returns and small mid cap U S equity returns is lower than your estimate indicates Evaluate whether Smyth s Comment C is accurate Solution Smyth s Comment C is accurate According to elementary portfolio theory the correlation between two assets Thus the correlation between private equity and small mid cap U S equity is equal to 3 3 2 06 7 2 34 22 0 45 which is lower than the estimate of 0 57 3737 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example for Setting CME Using the Singer Terhaar approach Zimmerman Capital Management ZCM is developing a strategic asset allocation for a small U S foundation that has approved investment in the following five asset classes U S equities U S fixed income non U S equities non U S fixed income and U S real estate the foundation limits nondomestic assets to no more than 12 percent of invested assets The final set of expectations needed consists of the expected returns standard deviations and all distinct pairwise covariances of U S equities U S fixed income non U S equities non U S fixed income and U S real estate The investment time horizon is 10 years A risk premium approach will be taken to developing expected return estimates following the methodology of Singer and Terhaar Historical estimates of standard deviations will be used and ICAPM betas will be used to develop estimates of covariances 3838 8989 100 Contribution Breeds Professionalism100 Contribution Breeds Professionalism Example Exhibit 4 supplies the standard deviation estimates and gives relevant in