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...

We develop a new approach for evaluating performance across hedge funds. Our approach allows for performance comparisons between models that are misspecified – a common feature given the numerous factors that drive hedge fund returns. The empirical results show that the standard models used in...

On the tracking and replication of hedge fund optimal investment portfolio strategies in global The hedge fund represents a unique investment opportunity for the institutional and private investors in the diffusion-type financial systems. The main objective of this condensed article is to...

We propose a Markov regime-switching approach accounting for false discoveries in order to measure hedge fund performance. It enables us to extract information from both time-series and cross-sectional dimensions of panels of individual hedge fund returns in order to distinguish between skilled,...

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 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...

This paper mainly focuses on the correlation between live hedge funds return and their value at risk (VaR), which is based on the historical data from May 2000 to April 2010. The authors adopt portfolio level analyses and fund level cross-sectional regression, and find that there is significant...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...

The profitability of a trading system based on the momentum-like effects of price jumps was tested on the time series of 7 assets (EUR/USD, GBP/USD, USD/CHF and USD/JPY exchange rates and Light Crude Oil, E-Mini S&P 500 and VIX Futures), in each case for 7 different frequencies (ranging from...

This paper compares various machine learning models to predict the cross-section of emerging market stock returns. We document that allowing for non-linearities and interactions leads to economically and statistically superior out-of-sample returns compared to traditional linear models. Although...