The subprime crisis was quite damaging for hedge funds. Using the local projection method (Jordà 2004, 2005, 2009), we forecast the dynamic responses of the betas of hedge fund strategies to macroeconomic and financial shocks-especially volatility and illiquidity shocks-over the subprime crisis...

In this study, we propose a set of covariates that exploit information content of hedge funds' relative size, performance, growth, tail risk, and past liquidation rate, in predicting their liquidation. Empirical results show that our proposed covariates exhibit significant predictive power for...

We use a holdings-based attribution model to disaggregate the benchmark-adjusted returns to U.S. equity mutual funds into components that reflect persistent segment tilts, the timing of segment returns, and stock selection relative to their benchmarks. We find that large-cap funds add value by...

This paper provides evidence of the impact of hedge funds on asset markets. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average first order autocorrelation coefficient of hedge fund returns, and show that it has strong and...

Using a novel equity lending dataset, this paper is the first to show that expected returns strongly and negatively predict future equity lending fees. In comparing two expected return measures, I find that a rational expected return has stronger predictive power of future short selling activity...

We propose and test a methodological framework to examine the relation between mutual fund fees and return predictability. Gil-Bazo and Ruiz-Verdu (2009) drew attention to the puzzling fact that funds with worse before-fee performance charge higher fees. We make another contribution to the...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...