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Academics find hedge funds are passive


A new paper 'Passive Hedge Funds' from Mikhail Tupitsyn and Paul Lajbcygier from the Department of Banking and Finance and the Department of Econometrics & Business Statistics, at the Faculty of Business and Economics, Monash University, Australia finds that most hedge fund managers are passive.

The academics write: “Active management should be manifest through nonlinear exposure to the systematic risk factors that drive hedge fund returns.” They posit that in order to demonstrate managerial skill enhanced performance should accrue as a consequence of active management. “Using generalised additive models we find that approximately two-thirds of hedge funds exhibit only linear factor exposures and hence are ‘passive’. What’s more such ‘passive’ managers tend to outperform ‘active’ managers. Finally, we also show that many ‘active’ managers, despite initial nonlinear risk exposures, eventually become ‘passive’.”
The paper explains that the issue of nonlinear risk exposures is crucial for understanding the many aspects of hedge fund performance. “The standard decomposition of hedge fund returns into alpha and beta components relies on the assumption that the exposures to risk factors are linear” the study says. “We challenge this assumption and perform analyses of nonlinearities in hedge fund style portfolios and individual funds using a nonparametric methodology based on Generalized Additive Models (GAMs). GAMs impose no functional form on risk exposures, preserve the additivity of the model, perform variable selection, and allow for automatic or manual control of the smoothness of risk exposure functions. To address potential data over fitting issues, we conduct out-of-sample tests of the GAMs and linear models from the literature, including the seven-factor Fung and Hsieh (2004) model, the linear model with Hasanhodzic and Lo (2007) factors, and a stepwise linear model with 14 factors from Giannikis and Vrontos (2011).”
Their findings are that at the portfolio level, overall a GAM using loess smoothers has a lower tracking error out-of-sample than all linear models, though the result is stronger in styles implementing arbitrage strategies (Fixed Income Arbitrage, Convertible Arbitrage, and Event Driven) than in directional styles (Long-Short Equity, Dedicated Short Bias, and Emerging Markets). “This is consistent with the conjecture in Agarwal and Naik (2004) of arbitrage styles providing financial insurance through short-put-like exposures. Also, the Fung and Hsieh (2004) model does not perform well out-of-sample compared to a linear model with Hasanhodzic and Lo (2007) factors. This suggests that primitive trend-following factors do not capture nonlinearities in hedge fund strategies well.”
At the fund level, the authors find one-fifth of funds exhibiting significant nonlinear patterns in risk exposures over the long run. “Around two-thirds of funds maintain linear risk exposures. The rest of the funds do not have significant linear or nonlinear exposures. These results mean that while in the short term hedge funds may engage in dynamic trading strategies involving complex securities, over the long run many of them behave like alternative beta portfolios.”
Finally, the academics examined performance of nonlinear funds and persistence of their nonlinear form of exposures. “It is found that nonlinear funds on average underperform linear and market-neutral funds on a risk-adjusted basis. Nonlinear funds also tend to have higher negative tail risk. However, these results may be time-varying and are influenced by major financial events such as the LTCM crisis in 1998 and financial crisis in 2007-2008. Also, we observed that many nonlinear funds that survive over a long term alter their risk exposures and are classified as linear funds in the next period. On the other hand, linear exposures exhibit much higher persistence.”

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