This paper investigates whether the HML, the SMB along with the short-term reversal, the long-term reversal and the momentum factors exhibit both in-sample and out-of-sample forecasting ability for the US stock returns. Our findings suggest that these factors contain significantly more...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

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....

Generating one-month-ahead systematic (beta) risk forecasts is common place in financial management. This paper evaluates the accuracy of these beta forecasts in three return measurement settings; monthly, daily and 30 minutes. It is found that the popular Fama-MacBeth beta from 5 years of...

Analysis with high frequency returns has become a core part of modern financial econometrics. Particularly in the measurement and forecasting of variance, covariance, correlation and Capital Asset Pricing Model (CAPM) beta. This paper studies CAPM beta measurement and forecasting with high...

We provide a short and selected review of the vast literature on cross-section predictability. We focus on the state of art methods used to forecast the cross-section of stock returns with major predictors and are primarily interested in the ideas, methods, and their applications. To understand...

We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the quality of their return forecasts. In the low signal-to-noise environment of a one month horizon, we find that it is preferable to rely on a theory-based approach instead of engaging...

We examine the asymmetric impact of shocks to macroeconomic expectations and their underlying dispersion on equity risk premia across different market regimes. First, we rely on a two-state logit mixture vector autoregressive model and use Consensus Economics survey data on GDP growth,...

We examine the asymmetric impact of shocks to macroeconomic expectations and their underlying dispersion on equity risk premia across different market regimes. First, we rely on a two-state logit mixture vector autoregressive model and use Consensus Economics survey data on GDP growth,...

It is a common wisdom that individual stocks' returns are difficult to predict, though in many situations it is important to have such estimates at our disposal. In particular, they are needed to determine the cost of capital. Market equilibrium models posit that expected returns are...