Our paper reexamines whether 29 variables from 26 papers published after Goyal and Welch (2008), as well as the original 17 variables, were useful in predicting the equity premium in-sample and out-of-sample. Our samples include the original periods in which these variables were identified, but...

A 'lost decade' for the Eurozone is looming on the horizon. Under these circumstances, stable indicators for future economic activity are especially valuable to decision makers. This paper examines the predictive power of the yield spread, one of the most reliable indicators for gross domestic...

An OLS and probit framework is used to examine the predictive power of yield spreads with respect to GDP growth and recessions in the Eurozone from the 1990s to the recent past. Credit default swap (CDS) data on sovereign bonds, which provide a direct measure of default risk, are employed as...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies - momentum. We find that momentum has earned abnormally high risk-adjusted returns - a...

The literature on excess return prediction has considered a wide array of estimation schemes, among them unrestricted and restricted regression coefficients. We consider bootstrap aggregation (bagging) to smooth parameter restrictions. Two types of restrictions are considered: positivity of the...

The predictability of a high-dimensional time series model in forecasting with large information sets depends not only on the stability of parameters but also depends heavily on the active covariates in the model. Since the true empirical environment can change as time goes by, the variables...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies — momentum. We find that momentum has earned abnormally high risk-adjusted returns — a...

This paper presents an innovative approach to extracting factors which are shown to predict the VIX, the S&P 500 Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we extract factors from panels of filtered volatilities - in...

This paper explores the variance risk premium in option returns across twenty different futures, including equities, bonds, currencies, and commodities (energy, metals, and grains). We implement a novel model-free methodology that constructs tradable option portfolios, which replicate realized...

We survey recent methodological contributions in asset pricing using factor models and machine learning. We organize these results based on their primary objectives: estimating expected returns, factors, risk exposures, risk premia, and the stochastic discount factor, as well as model comparison...