This paper calibrates a class of jump-diffusion long-run risks (LRR) models to quantify how well they can jointly explain the equity risk premium and the variance risk premium in the U.S. financial markets, and whether they can generate realistic dynamics of riskneutral and realized...

Traditional tests of conditional asset pricing models are performed under the assumption of rational expectations and presume that the use of realized returns as a proxy for expected returns is acceptable. This paper turns the tables and asks what realized returns we would observe, given the...

We present new evidence on the predictability of aggregate market returns by developing two new prediction models, one risk-based, and the other purely statistical. The pricing kernel model expresses the expected return as the covariance of the market return with a pricing kernel that is a...

Four new prominent asset pricing factors have recently been proposed. We test whether these factors fulfill necessary conditions for qualifying those as risk factors. We show that the investment and betting-against-beta factors fulfill these conditions. However, the profitability and quality...

We document a strong relation between aggregate corporate investment and direct stock market risk measures. Consistent with the investment-based asset pricing model, the comovement with the proxies for conditional equity premium fully accounts for aggregate investment's predictive power for...

This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...