We examine in this paper the training and test set performance of several equity factor models with a dataset of 20 years of data, 1,200 stocks and 100 factors. First, we examine several models to forecast expected returns, which can be used as baselines for more complex models: linear...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading...

Traditional portfolio optimization models specify placement of capital as rather irrevocably and fully at risk through investment horizon(s) or continuously. Under this constraint, asset class allocation typically serves as primary mode of diversification, pursuing risk moderation by seeking to...

Long-term country equity premium forecasts based on a cross-sectional global factor model (CS-GFM), where factors represent compensation for risks proxied by valuation and financial variables, are superior, statistically and economically, from forecasts based on time-series prediction models...

This paper tests the efficiency of macroeconomic forecasts, contributing to the existing literature using a rolling-event approach. We construct a monthly economic surprises index, aggregating several macroeconomic news surprises for the nine largest economic areas (G9), which we further analyze...

In this paper, we document evidence that downside betas tend to comove more than upside betas during a financial crisis, but upside betas tend to comove more than the downside betas during financial booms. We find that the asymmetry between Downside-Beta Comovement and Upside-Beta Comovement is...

We find out-of-sample predictability of commodity futures excess returns using forecast combinations of 28 potential predictors. Such gains in forecast accuracy translate into economically significant improvements in certainty equivalent returns and Sharpe ratios for a mean-variance investor....