We use 92,632,873 daily returns for 33,010 US firms to establish the best forecasting model for realized idiosyncratic variances. Comparing forecasts from 10 different models, we find that the most popular models, the martingale and GARCH type models, perform worst. Using the...

Using a time-varying spillover approach, we investigate volatility spillovers between natural alternative investments, i.e. timber and water, and a battery of traditional instruments comprising equities, bonds, crude oil, gold, real estate, shipping and currency, for the period...

According to recent research, diversification across risk factors (or investment styles) proves to be more efficient than traditional asset class diversification. In this paper, we take the next step and show that it is economically worthwhile to combine risk factors in a dynamic manner, in a...

Motivated by standard portfolio theory, this paper incorporates ex-ante volatility estimates in the construction of winner-minus-loser stock momentum portfolio. I find that over the 1927-2015 period this leads to an increase in the Sharpe ratio from 0.34 to 1.14 and strongly reduced crash risk....

This paper investigates how the two technical drivers, volatility and correlation, influence the algorithm of the investment strategy pairs trading. We model and empirically prove the connection between the rule-based pair selection, the trading algorithm, and the total return. Our insights...

Momentum is one of the largest and most pervasive market anomalies. However, despite a high mean and Sharpe ratio, momentum suffers from large negative skewness that comes from momentum crash periods. These crashes occur in times of both market stress and market rebound and thus variables that...

Our study provides further insights into the evidence of excess returns of low volatility enhanced portfolios. Based on the framework presented by Campbell and Vuolteenaho (2003), we analyze through-the-cycle as well as stress periods to provide an insight into which portfolio construction...

Due to arbitrage risk asymmetries, the relationship between idiosyncratic risk and expected returns is positive (negative) among overpriced (underpriced) stocks. We offer a new active anomaly-selection strategy that capitalizes on this effect. To this end, we consider eleven equity anomalies in...

We examine the impact of tail risk on the return dynamics of size, book-to-market ratio, momentum, and idiosyncratic volatility sorted portfolios. Our time-series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value,...

In this paper we document that at the aggregate stock market level the unexpected volatility is negatively related to expected future returns and positively related to future volatility. We demonstrate how the predictive ability of unexpected volatility can be utilized in dynamic asset...