This paper studies portfolio optimization through improvements of ex-ante conditional covariance estimates. We use the cross-section of stock returns over a 52-year sample to analyze trading performance by implementing the machine learning algorithm of hierarchical clustering. We find that...

Conventional financial theory considers ex-ante that risk, generally measured by the volatility, has to be appropriately rewarded by expected returns. In modern financial markets, there are countless quantitative and systematic strategies which may test and eventually lead to excess returns when...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....

We derive a model-free option-based formula to estimate the contribution of market frictions to expected returns (CFER) within an asset pricing setting. We estimate CFER for the U.S. optionable stocks. We document that CFER is sizable, it predicts stock returns and it subsumes the effect of...

I build a price-ratio model based on the Campbell and Shiller (1988) decomposition to test which components of investor expectations best explains cross-sectional price differences. I evaluate the in- and out-of-sample performance of my model, which uses a higher-order expansion with an added...

Intuition suggests that constraint investment strategies will result in losses due to a limited portfolio allocation. Two types of constrained assets have been particularly growing over the last few decades: Islamic Mutual Funds and Socially Responsible Mutual Funds. Although research regarding...

With continued strong inflows into hedge fund strategies, it is imperative for researchers to study if hedge funds are still worth their high fees. In an updated and comprehensive study covering both North American and Asian hedge funds, we find market risk factors explain up to 81% of hedge...

The risk of infrastructure investments is driven by unique factors that cannot be well described by standard asset class factor models. We thus create a nine-factor model based on infrastructure-specific risk exposure, i.e., market risk, size, value, momentum, cashflow volatility, leverage,...

We find that when measured in terms of dollar-turnover, and once beta-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of 5.1, the “Cold-Minus-Hot” (CMH) anomaly is certainly not less significant than other well-known factors such as Value or...

Assuming a symmetric relation between returns and innovations in implied market volatility, Ang, Hodrick, Xing, and Zhang (2006) find that sensitivities to changes in implied market volatility have a cross-sectional effect on firm returns. Dennis, Mayhew, and Stivers (2006), however, find an...