Hedge Funds.ppt

1、CHAPTER 26,Hedge Funds,26-2,Hedge Funds vs. Mutual Funds,Hedge Fund,Transparency: Limited Liability Partnerships that provide only minimal disclosure of strategy and portfolio composition No more than 100 “sophisticated”, wealthy investors,Mutual Fund,Transparency: Regulations require public disclos

2、ure of strategy and portfolio composition Number of investors is not limited,26-3,Hedge Funds vs. Mutual Funds,Hedge Fund,Investment strategy: Very flexible, funds can act opportunistically and make a wide range of investments Often use shorting, leverage, options Liquidity: Often have lock-up perio

3、ds, require advance redemption notices,Mutual Fund,Investment strategy: Predictable, stable strategies, stated in prospectus Limited use of shorting, leverage, options Liquidity: Can often move more easily into and out of a mutual fund,26-4,Hedge Funds vs. Mutual Funds,Hedge Fund,Compensation struct

4、ure: Typically charge a management fee of 1-2% of assets and an incentive fee of 20% of profits,Mutual Fund,Compensation structure: Fees are usually a fixed percentage of assets, typically 0.5% to 1.5%,26-5,Hedge Fund Strategies,Directional Bets that one sector or another will outperform other secto

5、rs Non-directional Exploit temporary misalignments in relative valuation across sectors Buy one type of security and sell another Strives to be market neutral,26-6,Table 26.1 Hedge Fund Styles,26-7,Statistical Arbitrage,Uses quantitative systems that seek out many temporary and modest misalignments

6、in prices Involves trading in hundreds of securities a day with short holding periods Pairs trading: Pair up similar companies whose returns are highly correlated but where one is priced more aggressively Data mining to uncover systematic pricing patterns,26-8,Portable Alpha,Invest wherever you can

7、find alpha. Hedge the systematic risk of the investment to isolate its alpha. Establish exposure to desired market sectors by using passive products such as indexed mutual funds or ETFs. Transfer alpha from the sector where you find it to the asset class in which you ultimately establish exposure.,2

8、6-9,Pure Play Example,You manage a $1.2 million portfolio. You believe alpha is 0 and that the market is about to fall. So you establish a pure play on the mispricing. The return on your portfolio is:,26-10,Pure Play Example,Suppose beta is 1.2, alpha is 2%, the risk-free rate is 1%, and the S Hedge

9、d Position,26-14,Style Analysis: Factor Exposure,Many hedge funds have directional strategies in which the fund makes an outright bet. A directional fund will have significant betas on the factors on which it bets.,26-15,Style Analysis: Factor Exposure,Market-neutral funds have insignificant betas.

10、Dedicated short bias funds exhibit substantial negative betas on the S&P index. Distressed firm funds have significant exposure to credit conditions. Global macro funds show negative exposure to a stronger U.S. dollar.,26-16,Liquidity and Hedge Fund Performance,Hedge funds tend to hold more illiquid

11、 assets than other institutional investors. Aragon: Typical alpha may actually be an equilibrium liquidity premium rather than a sign of stock-picking ability. Hasanhodzic and Lo: Hedge fund returns have serial correlation, a sign of liquidity problems. This biases the Sharpe ratios upward.,26-17,Fi

12、gure 26.2 Hedge Funds with Higher Serial Correlation in Returns,26-18,Liquidity and Hedge Fund Performance,Sadka: Unexpected declines in market liquidity are an important determinant of average hedge fund returns. Santa effect: Hedge funds report average returns in December that are substantially gr

13、eater than their average returns in other months. The December spike in returns is stronger for lower-liquidity funds, suggesting that illiquid assets are more generously valued in December.,26-19,Figure 26.3 Average Hedge Fund Returns as a Function of Liquidity Risk,26-20,Hedge Fund Performance and

14、 Survivorship Bias,Backfill bias: Hedge funds report returns only if they choose to and they may do so only when their prior performance is good. Survivorship bias: Failed funds drop out of the database Hedge fund attrition rates are more than double those for mutual funds.,26-21,Hedge Fund Performa

15、nce and Changing Factor Loadings,Hedge funds are designed to be opportunistic and may frequently change their risk profiles.,If risk is not constant, alphas will be biased if a standard, linear index model is used.,26-22,Figure 26.4 Characteristic Line of a Perfect Market Timer,26-23,Figure 26.4 Cha

16、racteristic Lines of Stock Portfolio with Written Options,26-24,Conclusions,The ability to perfectly time the market give the fund a nonlinear characteristic line, similar to holding a call option. The fund has greater sensitivity to the market when it is rising. Funds that write options have greate

17、r sensitivity to the market when it is falling than when it is rising. Nonlinear characteristic lines suggest many hedge funds are implicit option writers.,26-25,Figure 26.6 Monthly return on hedge fund indexes versus return on the S&P 500,26-26,Black Swans and Hedge Fund Performance,Nassim Taleb: M

18、any hedge funds rack up fame through strategies that make money most of the time, but expose investors to rare but extreme losses Examples: The October 1987 crash Long Term Capital Management,26-27,Fee Structure in Hedge Funds,2% of assets plus an incentive fee equal to 20% of investment profits: In

19、centive fees are effectively call options on the portfolio with: X =(portfolio value)* (1 + benchmark return) The manager gets the fee if the portfolio value rises sufficiently, but loses nothing if it falls.,26-28,Figure 26.7 Incentive Fees as a Call Option,26-29,Fee Structure in Hedge Funds,High w

20、ater mark: The fee structure can give incentives to shut down a poorly performing fund. If a fund experiences losses, it may not be able to charge an incentive unless it recovers to its previous higher value. With deep losses, this may be too difficult so the fund closes.,26-30,Funds of Funds,Funds

21、that invest in one or more other hedge funds. Also called “feeder funds”. A way to diversify across many hedge funds.,Supposed to provide due diligence in screening funds for investment worthiness. Madoff scandal showed that these advantages are not always realized in practice.,26-31,Funds of Funds,

22、Optionality can have a big impact on expected fees. Fund of funds pays an incentive fee to each underlying fund that outperforms its benchmark even if the aggregate performance is poor. Diversification can actually hurt the investor in this case.,26-32,Funds of Funds,Spread risk across several diffe

23、rent funds Investors need to be aware that these funds of funds operate with considerable leverage. If the various hedge funds in which these funds of funds invest have similar investment styles, diversification may illusory.,26-33,Example 26.6 Incentive Fees in Funds of Funds,A fund of funds has $1

24、 million invested in three hedge funds Hurdle rate for the incentive fee is a zero return Each fund charges an incentive fee of 20% The aggregate portfolio of the fund of funds is -5% Still pays incentive fees of $.12 for every $3 invested,CHAPTER 27,The Theory of Active Portfolio Management,26-35,O

25、verview,Treynor-Black model The optimization uses analysts forecasts of superior performance. The model is adjusted for tracking error and for analyst forecast error. Black-Litterman model,26-36,Table 27.1 Construction and Properties of the Optimal Risky Portfolio,26-37,Spreadsheet 27.1 Active Portf

26、olio Management,26-38,Spreadsheet 27.1,An active portfolio of six stocks is added to the passive market index portfolio. Table D shows: Performance increases are very modest. M-square increases by only 19 basis points.,26-39,Table 27.2 Stock Prices and Analysts Target Prices for June 1, 2006,Lets ad

27、d these new forecasts to the spreadsheet model and re-calculate Table D.,26-40,Figure 27.1 Rates of Return on the S&P 500 (GSPC) and the Six Stocks,26-41,Table 27.3 The Optimal Risky Portfolio,26-42,Results,The Sharpe ratio increases to 2.32, a huge risk-adjusted return advantage. M-square increases

28、 to 25.53%.,26-43,Results,Problems: The optimal portfolio calls for extreme long/short positions that may not be feasible for a real-world portfolio manager. The portfolio is too risky and most of the risk is nonsystematic risk. A solution: Restrict extreme positions. This results in a lack of diver

29、sification.,26-44,Table 27.4 The Optimal Risky Portfolio with Constraint on the Active Portfolio (wA 1),26-45,Figure 27.2 Reduced Efficiency when Benchmark is Lowered,Benchmark risk is the standard deviation of the tracking error, TE = RP-RM. Control it by restricting WA.,26-46,Table 27.5 The Optima

30、l Risky Portfolio with the Analysts New Forecasts,26-47,Adjusting Forecasts for the Precision of Alpha,How accurate is your forecast? Regress forecast alphas on actual, realized alphas to adjust alpha for the accuracy of the analysts previous forecasts.,26-48,Figure 27.4 Organizational Chart for Por

31、tfolio Management,26-49,The Black-Litterman Model,The Black-Litterman model allows portfolio managers to incorporate complex forecasts (called “views”) into the portfolio construction process.,Historical returns, even over long periods, have very limited power to infer expected returns for the next

32、month. The business cycle and other macroeconomic variables may be better forecasters of expected returns. Historical variance is a good predictor of expected future variance.,26-50,Steps in the Black-Litterman Model,Estimate the covariance matrix from recent historical data. Determine a baseline fo

33、recast. Integrate the managers private views.,Develop revised (posterior) expectations. Apply portfolio optimization.,26-51,Figure 27.5 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level,26-52,Figure 27.6 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level,

34、26-53,BL Conclusions,The Black-Litterman (BL) model and the Black-Treynor (TB) model are complements. The models are identical with respect to the optimization process and will chose identical portfolios given identical inputs. The BL model is a generalization of the TB model that allows you to have

35、 views about relative performance that cannot be used in the TB model.,26-54,BL vs. TB,Black-Litterman Model,Optimal portfolio weights and performance are highly sensitive to the degree of confidence in the views. The validity of the BL model rests largely upon the way in which the confidence about views is developed.,Treynor-Black Model,TB model