CHAPTER 27 The Theory of Active Portfolio Management

CHAPTER 27 The Theory of Active Portfolio Management

CHAPTER 27 The Theory of Active Portfolio Management Investments, 8th edition Bodie, Kane and Marcus

Slides by Susan Hine McGraw-Hill/Irwin Copyright 2009 by The McGraw-Hill Companies, Inc. All Overview Treynor-Black model Optimization using analysts forecasts of

superior performance Adjusting model for tracking error Adjusting model for analyst forecast error Black-Litterman model 27-2 Table 27.1 Construction and Properties

of the Optimal Risky Portfolio 27-3 Table 27.2 Stock Prices and Analysts Target Prices for June 1, 2006 27-4

Figure 27.1 Rates of Return on the S&P 500 (GSPC) and the Six Stocks, June 2005 May 2006 27-5 Table 27.3 The Optimal Risky Portfolio

with the Analysts New Forecasts 27-6 Table 27.4 The Optimal Risky Portfolio with Constraint on the Active Portfolio (WA < 1)

27-7 Figure 27.2 Reduced Efficiency when Benchmark is Lowered 27-8 Table 27.5 The Optimal Risky Portfolio

with the Analysts New Forecasts (benchmark risk constrained to 3.85%) 27-9 Adjusting Forecasts for the Precision of Alpha How accurate is your forecast

How should you adjust your position to take account of forecast imprecision Must quantify the uncertainty by examining the forecasting record of previous forecasts by same forecaster The adjusted alpha: f

(T ) a0 a1 (T ) 27-10 Figure 27.3 Histogram of the Alpha Forecast 27-11

Figure 27.4 Organizational Chart for Portfolio Management 27-12 Steps in the Black-Litterman Model Step 1: Estimate the covariance matrix from historical data

Step 2: Determine a baseline forecast Step 3: Integrating the managers private views Step 4: Developing revised (posterior) expectations Step 5: Apply portfolio optimization 27-13

Figure 27.5 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level (view is correct) 27-14 Figure 27.6 Sensitivity of Black-Litterman Portfolio Performance to Confidence

Level (view is false) 27-15 The BL Model as Icing on the TB Cake Suppose that you have two portfoliosone for the US and one for Europe The model would be run as two separate

divisions Each division would compile values of alpha relative to their own passive portfolio Relative performance of the two markets can be expected to add information to the independent macro forecasts for the two economies Portfolios need to be optimized separately

27-16 Value of Active Management Model for estimation of potential fees Kane, Marcus, and Trippi derive an annuitized value of portfolio performance measured as a percent of funds under management The percentage fee that investors would be

willing to pay for active services can be related to the difference between the square of the portfolio Sharpe ratio and that of the passive portfolio Source of the power of the active portfolio is the additive value of the squared information ratios 27-17

Table 27.6 M-Square for the Portfolio, Actual Forecasts 27-18 Table 27.7 M-Square of Simulated Portfolios

27-19 Concluding Remarks The gap between theory and practice has been narrowing in recent years The CFA is expanding knowledge base in the industry Specific lack of application of the TreynorBlack model may be related to lack of

application of adjusting for analysts errors 27-20

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