The article focuses on forecasting idiosyncratic hedge fund return volatility using a non-linear Markov switching GARCH (MS-GARCH) framework in which the conditional mean and volatility of systematic and idiosyncratic hedge fund return components may exhibit dynamic Markov switching behaviour....

This paper investigates hedge funds' exposures to various risk factors across different investment strategies through models with both linear and second-order factors. We extend the analysis from an augmented linear model based on Fama and French (1993) and Fung and Hsieh (2001) to second-order...

This study has 4 contributions to the literature. First, the authors analyze the risk characteristics for 11 Relative Value hedge fund strategies. Second, the authors introduce 3 families of behavioral factors, the D family, the L family, and the R family. In contrast to previous hedge fund...

This paper empirically decomposes hedge fund excess return into factor timing, security selection, and risk premium using Lo (2008)'s performance measure. Portfolio-level tests show that security selection explains most of the excess return generated by hedge funds during 1994-2009, and the...

By studying 81 countries over a period of up to 144 years, with different classes of predictor variables and various forecast specifications, we conduct the most comprehensive equity premium predictability analysis to date. We find that excess returns are more predictable in Emerging and...

Recent research suggests that machine learning models dominate traditional linear models in predicting cross-sectional stock returns. We confirm this finding when predicting one-month forward-looking returns based on a set of common stock characteristics, including predictors such as short-term...

This paper introduces a new out-of-sample forecasting methodology for monthly market returns using the variance risk premium (VRP) that is both statistically and economically significant. This methodology is motivated by the `beta representation,' which implies that the market risk premium is...

We use economic policy uncertainty (EPU) shocks in combination with the mixed data sampling (MIDAS) approach to investigate long-run stock market variances and correlations, primarily for the US and the UK. The US long-run stock market variance depends significantly on US EPU shocks but not on...

The risk premium of stocks due to priced variance risk is summarized to two variables -- the stock-specific price of variance risk (the difference between realized and option-implied variance) and the quantity (i.e., how stock prices respond to their variance shocks) of variance risk....