In the context of an international portfolio diversification problem, we find that small capitalization equity portfolios become riskier in bear markets, i.e. display negative co-skewness with other stock indices and high co-kurtosis. Because of this feature, a power utility investor ought to...

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean-variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968-2016, we find evidence...

We report systematic, out-of-sample evidence on the benefits to an already well diversified investor that may derive from further diversification into various hedge fund strategies. We investigate dynamic strategic asset allocation decisions that take into account investors' preferences as well...

This paper studies the predictive performance of multivariate models at forecasting the (excess) returns of portfolios mimicking the Market, Size, Value, Momentum, and Low Volatility factors isolated in asset pricing research. We evaluate the accuracy of the point forecasts of a number of linear...

We test whether the unconventional monetary policy (UMP) announcements by the Federal Reserve and the European Central Bank represent a risk factor for the hedge fund industry as a whole and for ten commonly used strategies in particular. Using modified event studies and Markov switching models,...

This paper has a twofold objective. First, we contribute to the stream of literature that investigates whether traditional asset pricing factors show any predictive power for the cross-section of Real Estate Investment Trust (REIT) returns. In particular, we investigate the existence of a...

In this paper we take an empirical asset pricing perspective and investigate the dominant view (possibly, an instinctive reflection of the media hype surrounding the surge of Bitcoin valuations) that cryptocurrencies represent a new asset class, spanning risks and payoffs sufficiently...

We investigate the potential role of Exchange Traded Products (Notes) as vehicles to trade volatility (here proxied by the VIX index) as an asset class in a fully optimizing asset allocation framework, subject to long-only constraints. In back-testing, recursive exercises based on an expanding...

We test the performance of two ESG score-driven quantitative signals on a large, multi-national crosssection of European stock returns. In particular, we ask whether in the cross-section, the cost of equity capital is more strongly affected by the (upward) “slope” (identified as momentum...

We present a structured portfolio optimization framework with sparse inverse covariance estimation and an attention-based LSTM network that exploits machine learning (deep learning) techniques. We shrink Wishart volatility towards a Graphical Lasso initial covariance estimator and solve the...