1. Performance Attribution These characteristics of returns are well known. Known “styles” of returns. –don’t give credit to a passive value manager for beating the S&P500 – that’s too easy! Evaluation now is relative to a “style” or benchmark portfolio –Growth-- Value –Small-Cap-- Large-Cap –Industry-- International –Momentum-- Emerging markets

2. Finding Alpha Word of caution: finding historical alpha is easy! –Suppose you could sell historical alpha? –Measurement of alpha is difficult: the market is very volatile: S&P500 = 20% per year, individual stocks 50% per year. –This has a significant effect on the reliability of estimates of alpha.

3. Finding Skill High past returns: –Risk? –Return to active management: skill? –Luck? Do returns persist? –Yes if manager always takes positions with known high returns: do a style correction. –Yes because of momentum in stock returns.

4. Example: Carhart (1997) Realized returns from declared holdings or net asset value corrected for distributions Regression of returns on – the market –small cap versus large cap factor (SMB) –value versus growth factor (HML) –momentum factor (PR1YR) Similar to a style-based evaluation of performance.

5. Table III of Carhart 1997

6. Implications of these studies Mutual funds tend to generate negative alpha when evaluated relative to sophisticated benchmarks There is persistence in performance, but –It is driven by momentum –It is mostly due to luck –Loads and fees chew up any gains There is persistence in poorly performing funds, –These are the funds with large expense ratios and large turnover

7. Spectacular growth in HF

8. Strategy composition HF do lots of different things. Strategy gobbledygook. Who knows what any of this means? Obscure strategies seems an important part of HF marketing

9. Returns Not astronomical, but if beta really = 0, these aren’t bad returns! Is beta 0?

10. Hedge fund alphas and betas – lags and stale prices StyleER (%/mo)aba3b3 Index0.640.460.280.360.44 Std. errors0.200.170.04 Short-0.530.10-0.940.13-0.99 Emerg mkts0.390.000.58-0.070.69 Event0.610.460.220.380.37 Global Macro0.930.820.170.740.31 Long/Short Eqty0.730.420.470.320.65 Source: regressions using CFSB/Tremeont indices at hedgeindex.com, idea from Asness et al JPM Not zero! Bigger with lags Smaller with lags Really not zero. “Alternative asset?” Long-short doesn’t mean zero beta! Lags are important – stale prices or lookback option Betas are big!

11. Correlation with the market is obvious. Getting out in 2000-2003 was smart! (Mostly due to Global/Macro group)

12. “Global macro” yet you see the correlation with US market Lagged market effect is clear in 1998. Is Nov/Dec 1998 unrelated to Oct? Dramatic stabilization / change of strategy in mid 2000 Monthly returns on Global Macro HF and US market

13. “Emerging markets diversify away from US investments, give us access to a new asset class?” Names: yes. Betas: no. Names don’t mean much! Monthly returns on Emerging Market HF and US market

14. Option-like return example: Merger “arbitrage”. Cash offer. Borrow, buy target. Large chance of a small return if successful. (Leverage: a large return) Small chance of a large loss if unsuccessful. The strategy seems unrelated to the overall market, “beta zero” But…offer is more likely to be unsuccessful if the market falls! Payoff is like an index put! Price

15. Merger arb returns Source: Mark Mitchell and Todd Pulvino, Journal of Finance Line: like the payoff of writing index puts!

16. Source: Mitchell and Pulvino, using CFSB/Tremont merger-arb index News: 1) “occasional catastrophes’’ 2) catastrophes more likely in market declines

17. Hedge fund up/down betas Styleb3b upb down Index0.440.080.77 Short-0.99-0.22-1.82 Emerg mkts0.690.081.16 Event0.370.180.47 Global Macro0.31-0.080.66 Long/Short Eqty0.650.191.18 Example: if the market goes up 10%, the HF index goes up 0.8%. But if the market goes down 10%, the HF index goes down 7.7%! Source: my regressions using hegefundindex.com data; following Asness et al JPM Many near, or above 1. These are big betas! Many HF styles are much more sensitive to down markets = write puts = “short volatility.” (Includes 3 lags)

18. Implications of option-like payoffs Need option-return benchmarks for risk management (investing in HF) and compensation benchmarks.

19. Additional benchmarks matter too! StyleRm+Rm-Term+Term-Corp+Corp- Index0.070.720.270.551.010.94 Conv arb0.250.200.100.35-0.221.03 Short-0.32-1.75-0.050.190.62-0.66 Emerg mkts0.131.03-0.440.200.732.48 Event0.210.390.150.320.301.43 BondArb0.080.12-0.020.350.441.40 Global Macro-0.090.66 1.172.291.53 Long/Short Eqty0.161.050.090.220.380.84 Source: my regressions using hegefundindex.com data Term = long term gov’t bond return – t bill rate Corp = corporate bond return – long term gov’t Big betas, especially on corp (default spread) Often much more for bad news than for good news Market up/down has moderated since 1998, but term, corp up/down still strong Most HF strategies amount to “providing liquidity”, “disaster insurance” in some market