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Hedge Fund Monthly
 
Equity Market Neutral Hedge Fund Return Drivers
By D. Stephen Foerster, Ivey Business School, University of Western Ontario November 2006
 

In this study, I focus on trying to better understand what drives the returns of the "classic" hedge fund style: equity market neutral strategies. If such strategies are able to exploit market inefficiencies, then these strategies should provide significant outperformance after adjusting for risk. Measures of market beta should not be significantly different from zero. Similarly, any other betas relative to various "exposures" or factors should not be significantly different from zero. In order to test these propositions, one needs to identify various risk factors beyond the traditional market that might explain returns.

Researchers have identified various factors that relate to portfolio strategies such as going long in small stocks and short in large stocks, going long in value stocks and short in growth stocks, and going long in stocks that have experience large price increases and short in those that have not. As such, investors may be better off simply replicating such long/short strategies directly rather than through hedge fund investments. While much attention has been placed on these portfolio strategies as risk factors, less attention has been placed on economic factors that may impact on performance. Examination of economic factors as explanatory variables for equity market neutral hedge funds may shed light on the ability of such funds to act as a counter-balance during depressed economic times.

Methodology

I create and examine the properties of four asset-based style factors based on equity market neutral market strategies. The strategies are based on rankings and monthly updates of equal-weighted portfolios of S&P 500 stocks and involve going long (short) on the highest (lowest) ranked quintile sorted on earning/price (EP), price/book (PB), price momentum (PRM) and market capitalis ation (MKT). I then examine the CSFB/Tremont equity market neutral index return series to explain what drives average equity market neutral hedge fund return performance, measured in excess of T-bill returns (EMNE). Finally, I extend the analysis to other hedge fund styles, as a robustness check and to examine whether style factors and economic variables also explain returns from other styles. 

Returns are regressed on a number of style-based and economic variable factors as indicated in the following equation:
     t = 1,…, T                                                      (1)
where ai is an intercept term, Fj,t represent the j = 1,…,n factor returns in period t, bi,j are the coefficients or betas for each factor and εi,t is an error term for time t.

I use the Fama-French factors including the market risk premium (RmRf), small-minus-big market capitali sation portfolios (SMB), value (high book/price) -minus-growth (low book/price) portfolios (HML), as well as the (up-minus-down) momentum variable (UMD).

I create a number of economic-based variables. YLD is the difference between the 10-year treasury note yield and the three-month T-bill yield, while PREM is the difference between the Moody’s seasoned Aaa and Baa bond yields. The inflation change variable INFCHG represents changes in the all-item urban consumer price index year-over-year series. For the volatility measure VIX, 1980-1985 data represent trailing 250-day annualis ed standard deviations of S&P 500 returns and the 1986-2005 data are annuali sed implied volatility measures from the (old) VIX S&P 100 volatility index.

Results

I first examine the long/short strategies. All strategies except PRM show positive and significant returns. The PRM strategy (while still positive) is most volatile while the MKT strategy is the least volatile. EP shows the largest Sharpe ratio. Among the style strategies, PB and MKT are most highly correlated (0.69), followed by EP and PB (0.45). Many of the style strategies are significantly negatively related to inflation changes. RmRf is significantly negatively related to the volatility measure.

Table 1 presents results of regressions of the monthly style factor excess returns (i e , above T-bill returns) on the various Fama-French factors as well as the economic variables (coefficient significance is indicated by p-values in parentheses). Much of the EP strategy returns can be explained by the Fama-French factors. The EP strategy is driven by the performance of value stocks versus growth stocks and by larger stocks. These factors combine to subsume any market effects. EP excess returns are negatively related to the momentum factor. The addition of economic variables as explanatory factors does not impact on the results. While the intercept term was significant in the initial CAPM regression with one market factor, once additional factors are included the intercept is no longer significant, suggesting no positive alpha.

The PB strategy shows a somewhat similar pattern compared with EP. The intercept or alpha relative to the market factor is positive although not significant. The results suggest a small cap effect. The market effect is also significant. PB excess returns are negatively related to the momentum factor. The strategy performs well when markets are more volatile.

For the PRM strategy, the initial alpha based on the CAPM regression is virtually zero. With the inclusion of the Fama-French factors, the price momentum strategy is significantly negatively related to the market factor and the SMB factor. The addition of the UMD factor is significantly positive as expected. The price momentum strategy tends to perform better in economic expansions which are associated with an upward sloping yield curve and a lower default premium.

Finally, the MKT strategy shows a positive alpha in the CAPM regression but one that is not significant. The strategy is significantly positively related to the three Fama-French factors. Results suggest small stocks do better when momentum is not as strong. The strategy tends to do better in volatile markets.

I also consider results related to the equity market neutral index. Average monthly returns of 0.80% are significantly positive. The standard deviation is much lower than that of the U S market risk premium or the world index excess return. EMN is positively and significantly related to the U S market risk premium and the world market risk premium and is negatively and significantly related to the yield curve.

Table 2 examines the drivers of equity market neutral hedge fund excess returns (EMNE). I begin with a simple CAPM regression using RmRf. The intercept term can be interpreted as alpha. In this first regression, the beta is significantly positive but very low (0.07) as expected in such a market neutral strategy. Thus equity market neutral strategies are not truly neutral, but do exhibit very little pure market exposure. The alpha is positive and significant (0.44) and represents an annuali sed return of 5.4%. Thus in a CAPM world, it appears that such strategies offer superior performance.

The second regression examines the impact of the addition of the four style factors. The market beta now increases slightly to 0.10. The EP coefficient is significant (positive) as is the PB variable (but negative), while the PRM variable is significant (negative). The alpha decreases slightly to 0.43 or 5.3% on an annualis ed basis. The adjusted R-square increases substantially. Thus equity market neutral fund performance captures a value effect as measured by the price-earnings ratio, but a growth effect as captured by the price-to-book ratio. With the negative price momentum coefficient, this suggests that equity market neutral captures some price reversal effects rather than continuation of strong 12-month performance. The MKT variable is not significant suggesting size is not a relevant factor driving equity market neutral performance.

The third and fourth equations add the economic variables. In both regressions the adjusted R-square increases to over 27% and the alpha becomes small or negative and insignificant. If we consider these economic factors as reflective of risks for which one expects to be compensated, then the equity market neutral strategies, on average, are not providing superior performance. The RmRF, EP, PB, PRM and MKT coefficients are a similar order of magnitude and significance as in the previous regressions, suggesting an orthogonal impact of the economic variables. The dominant style factors continue to be RmRf, EP, PB, and to a lesser extend PRM. The yield variable is significant and negative, and the volatility variable is significant and positive. This it appears that, in addition to the factors described above, the equity market neutral excess return alpha can be explained by the shape of the yield curve and market volatility.

The remaining regressions examine the other hedge fund style excess returns. There is a clear dichotomy with five of the styles less than 8% of the variability is explained – convertible arbitrage (CAE), fixed-income arbitrage (FIAE), global macro (GME), managed futures (MFE), and multi-strategy (MSE), yet all have significant world market premium betas. For the remaining seven styles – dedicated short bias (DSBE), emerging markets (EME), event-driven (EDE), event-driven distressed (EDDE), event-driven multi-strategy (EDMS), event-driven risk arbitrage (EDRA), long /short equity (LSE) – more than 35% of the variability is explained, and for the overall index (HFIE) 41% is explained. Most of the event-driven strategies have significant and negative VIX coefficients, suggesting lower volatility is better for these types of strategies.

Conclusions

For the most part, equity market neutral funds show very little market exposure. Performance appears to be superior when measured against a variety of long/short style factors, but not with the addition of economic factors. The “good news” is that equity market neutral returns are negatively related to the shape of the yield curve and positively related to market volatility, suggesting an important counter-cyclical role for such a strategy.

This article is the winner of the 2006 AIMA Cannada Research Award and first appeared in AIMA Journal Autumn 2006.

Table 1
Style Factor Regression Analysis (1980-2005)

 

Int

RmRf

SMB

HML

UMD

YLD

PREM

INFCH

VIX

Adj R2

EPE

0.51
(0.032)
-0.35
(0.000)
0.121

EPE

-0.02
(0.915)
-0.02
(0.639)
-0.12
(0.051)
0.83
(0.000)
0.428

EPE

0.08
(0.712)
-0.04
(0.480)
-0.12
(0.071)
0.81
(0.000)
-0.10
(0.030)
0.435

EPE

-0.35
(0.686)
-0.03
(0.571)
-0.11
(0.080)
0.81
(0.000)
-0.09
(0.037)
0.05
(0.741)
0.19
(0.683)
0.09
(0.478)
0.01
(0.809)
0.429

PBE

0.06
(0.773)
-0.02
(0.73)
-0.003

PBE

-0.62
(0.003)
0.33
(0.000)
0.26
(0.000)
1.04
(0.000)
0.467

PBE

-0.17
(0.176)
0.27
(0.000)
0.31
(0.000)
0.94
(0.000)
-0.44
(0.000)
0.713

PBE

-1.31
(0.015)
0.30
(0.000)
0.31
(0.000)
0.96
(0.000)
-0.44
(0.000)
0.07
(0.487)
-0.02
(0.932)
0.01
(0.913)
0.05
(0.007)
0.717

PRME

0.00
(0.997)
0.18
(0.014)
0.016

PRME

0.23
(0.509)
-0.31
(0.003)
0.03
(0.801)
0.35
(0.007)
0.039

PRME

-0.99
(0.000)
-0.17
(0.000)
-0.10
(0.040)
-0.08
(0.135)
1.21
(0.000)
0.839

PRME

-0.16
(0.791)
-0.19
(0.000)
-0.10
(0.022)
-0.10
(0.054)
1.20
(0.000)
0.24
(0.023)
-0.65
(0.041)
-0.09
(0.316)
-0.03
(0.174)
0.844

MKTE

0.24
(0.273)
0.21
(0.000)
0.058

MKTE

-0.71
(0.000)
0.36
(0.000)
0.87
(0.000)
0.68
(0.000)
0.423

MKTE

0.35
(0.020)
0.32
(0.000)
0.72
(0.000)
0.61
(0.000)
-0.35
(0.000)
0.582

MKTE

-2.47
(0.000)
0.36
(0.000)
0.72
(0.000)
0.63
(0.000)
-0.34
(0.000)
0.08
(0.469)
0.44
(0.194)
0.04
(0.637)
0.07
(0.001)
0.595


Table 2
Equity Market Neutral Index versus Other Style Regression Analysis
(1994-2005)

 

Int

RmRf

EP

PB

PRM

MKT

YLD

PREM

INFCH

VIX

Adj R2

EMNE
0.44
(0.000)
0.07
(0.00)
0.131
EMNE
0.43
(0.000)
0.10
(0.000)
0.07
(0.000)
-0.09
(0.010)
-0.02
(0.082)
0.02
(0.424)
0.218
EMNE
0.02
(0.938)
0.11
(0.000)
0.06
(0.000)
-0.09
(0.006)
-0.02
(0.107)
0.02
(0.429)
-0.09
(0.129)
0.02
(0.008)
0.279
EMNE
-0.18
(0.532)
0.11
(0.000)
0.08
(0.000)
-0.09
(0.006)
-0.02
(0.105)
0.02
(0.548)
-0.13
(0.095)
0.53
(0.190)
0.09
(0.192)
0.02
(0.124)
0.287
HFIE
0.55
(0.441)
0.32
(0.000)
0.01
(0.740)
-0.09
(0.278)
0.13
(0.000)
0.13
(0.040)
-0.16
(0.434)
0.63
(0.533)
0.20
(0.246)
-0.02
(0.454)
0.408
CAE
-0.09
(0.871)
0.05
(0.169)
0.02
(0.524)
-0.04
(0.516)
0.01
(0.806)
0.06
(0.185)
-0.28
(0.063)
1.05
(0.166)
0.282
(0.028)
0.00
(0.920)
0.068
DSBE
2.02
(0.050)
-0.96
(0.000)
-0.07
(0.260)
0.39
(0.001)
-0.06
(0.191)
-0.45
(0.000)
0.05
(0.860)
-1.94
(0.182)
-0.20
(0.410)
-0.02
(0.678)
0.751
EME
-1.73
(0.270)
0.61
(0.000)
0.12
(0.166)
-0.28
(0.111)
0.12
(0.099)
0.37
(0.009)
0.41
(0.348)
3.11
(0.162)
0.74
(0.049)
-0.07
(0.285)
0.357
EDE
0.83
(0.096)
0.22
(0.000)
0.05
(0.094)
-0.06
(0.027)
0.04
(0.103)
0.13
(0.005)
-0.15
(0.292)
1.38
(0.052)
0.25
(0.036)
-0.06
(0.005)
0.449
EDDE
0.97
(0.108)
0.24
(0.000)
0.05
(0.180)
-0.03
(0.611)
0.04
(0.205)
0.12
(0.025)
-0.12
(0.462)
1.31
(0.126)
0.23
(0.109)
-0.06
(0.019)
0.390
EDMSE
0.68
(0.230)
0.21
(0.000)
0.05
(0.142)
-0.08
(0.210)
0.04
(0.094)
0.13
(0.010)
-0.13
(0.425)
1.35
(0.094)
0.30
(0.030)
-0.05
(0.019)
0.362
EDRAE
1.18
(0.003)
0.12
(0.000)
0.05
(0.044)
-0.10
(0.016)
0.01
(0.731)
0.15
(0.000)
-0.25
(0.024)
0.46
(0.405)
0.10
(0.291)
-0.04
(0.010)
0.368
FIAE
0.06
(0.888)
0.01
(0.614)
0.02
(0.445)
0.00
(0.940)
0.02
(0.217)
0.01
(0.816)
-0.01
(0.918)
1.20
(0.052)
0.18
(0.088)
-0.04
(0.035)
0.045
GME
0.75
(0.557)
0.27
(0.002)
0.09
(0.221)
-0.08
(0.578)
0.12
(0.046)
0.10
(0.370)
-0.25
(0.470)
1.02
(0.570)
0.04
(0.887)
-0.03
(0.620)
0.071
LSEE
0.11
(0.068)
0.52
(0.000)
-0.03
(0.395)
-0.13
(0.067)
0.20
(0.000)
0.21
(0.000)
-0.30
(0.102)
0.61
(0.510)
0.23
(0.136)
0.01
(0.738)
0.713
MFE
-2.22
(0.111)
-0.00
(0.961)
0.05
(0.500)
-0.00
(0.983)
0.11
(0.088)
0.12
(0.325)
0.37
(0.335)
-1.17
(0.552)
-0.12
(0.707)
0.12
(0.034)
0.042
MSE
-0.16
(0.753)
0.03
(0.352)
-0.05
(0.084)
0.07
(0.180)
0.03
(0.252)
-0.01
(0.865)
0.12
(0.405)
-0.54
(0.449)
0.11
(0.361)
0.03
(0.102)
0.003

 

 

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