We analyze the recursive, out-of-sample performance of asset allocation decisions based on financial ratio-predictability under single-state linear and regime-switching models. We adopt both a statistical perspective to analyze whether models based on the dividend-price, earning-price, and...

We investigate whether it is possible to find a Stochastic Discount Factor (SDF) that jointly prices the cross-section of eight U.S. portfolios of stocks, Treasuries, corporate bonds, and commodities and replicates their observed moments, and especially correlations. We use the first three...

Using data on international, on-line media coverage and tone of the Brexit referendum, we test whether it is media coverage or tone to provide the largest forecasting performance improvements in the prediction of the conditional variance of weekly FTSE 100 stock returns. We find that versions of...

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 analyze the time-varying nature of the price discovery process in the sovereign debt market over the sample period January 2006 – September 2015. In particular, we test whether the cointegration relationship that should tie bond and CDS spreads together holds over the entire sample. In...

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 investigate the out-of-sample, recursive predictive accuracy for (fully hedged) commodity future returns of two sets of forecasting models, i.e., hidden Markov chain models in which the coefficients of predictive regressions follow a regime switching process and stepwise variable selection...

We test whether three well-known commodity-specific variables (basis, hedgingpressure, and momentum) may improve the predictive power for commodity futuresreturns of models otherwise based on macroeconomic factors. We compute recursive,out-of-sample forecasts for fifteen monthly commodity...

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 study the recursive, out-of-sample realized predictive performance of a rich set of predictor choices and models, spanning linear and Markov switching frameworks when the forecast target is represented by excess NCREIF and equity NAREIT returns. We find considerable pockets of predictive...