International audienceThis paper investigates empirically whether uncertainty about volatility of the market portfolio can explain the performance of hedge funds both in the cross-section and over time. We measure uncertainty about volatility of the market portfolio via volatility of aggregate volatility (VOV) and construct an investable version of this measure by computing monthly returns on lookback straddles on the VIX index. We find that VOV exposure is a significant determinant of hedge fund returns at the overall index level, at different strategy levels, and at an individual fund level. After controlling for a large set of fund characteristics, we document a robust and significant negative risk premium for VOV exposure in the cross-section of hedge fund returns. We further show that strategies with less negative VOV betas outperform their counterparts during the financial crisis period when uncertainty was at its highest. On the contrary, strategies with more negative VOV betas generate superior returns when uncertainty in the market is less. Finally, we demonstrate that VOV exposure-return relationship of hedge funds is distinct from that of mutual funds and is consistent with the dynamic trading of hedge funds and risk-taking incentives arising from performance-based compensation of hedge funds

The authors examine whether volatility risk is a priced risk factor in securities returns. Zero-beta at-the-money straddle returns of the S&P 500 index are used to measure volatility risk. It is demonstrated that volatility risk captures time variation in the stochastic discount factor. The results suggest that straddle returns are important conditioning variables in asset pricing, and investors use straddle returns when forming their expectations about securities returns. One interesting finding is that different classes of firms The authors are indebted to Joel M. Vanden for his valuable comments and suggestions. They would also like to thank to participants in presentations at the Central Bank of Republic of Turkey, Bilkent University, and the EFMA 2006 Annual Meeting in Madrid for their comments and suggestions. The usual disclaimer applies.

International audienceUsing firm-level option and stock data, we examine the predictive ability of option-implied volatility measures proposed by previous studies and recommend the best measure using up-to-date data. Portfolio-level analysis implies significant non-zero risk-adjusted returns on arbitrage portfolios formed on the call -- put implied volatility spread, implied volatility skew, and realized -- implied volatility spread. Firm-level cross-sectional regressions show that the implied volatility skew has the most significant predictive power over various investment horizons. The predictive power persists before and after the 2008 Global Financial Crisi

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We propose a volatility-based capital asset pricing model (V-CAPM) in which asset betas change discretely with respect to changes in investors' expectations regarding near-term aggregate volatility. Using a novel measure to proxy uncertainty about expected changes in aggregate volatility, i.e. monthly range of the VIX index (RVIX), we find that portfolio betas change significantly when uncertainty about aggregate volatility expectations is beyond a certain threshold level. Due to changes in their market betas, small and value stocks are perceived as riskier than their big and growth counterparts in bad times, when uncertainty about aggregate volatility expectations is high. The proposed model yields a positive and significant market risk premium during periods when investors do not expect significant uncertainty in near-term aggregate volatility. Our findings support a volatility-based time-varying risk explanation. © 2015 Elsevier Inc