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Performance Attribution

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

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Performance Attribution

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  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 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! Source: regressions using CFSB/Tremeont indices at hedgeindex.com, idea from Asness et al JPM

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

  12. Monthly returns on Global Macro HF and US market • “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

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

  14. Option-like return example: Merger “arbitrage”. Price • 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!

  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 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%! (Includes 3 lags) • Many near, or above 1. These are big betas! • Many HF styles are much more sensitive to down markets = write puts = “short volatility.” • Source: my regressions using hegefundindex.com data; following Asness et al JPM

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

  19. Additional benchmarks matter too! • 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 • Source: my regressions using hegefundindex.com data

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