We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do...

We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the Efficient Market Hypothesis). We do not...

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with exogenous predictors. Unlike existing Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms, our approach is not based on a structural form representation of the...

In this paper, we extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a...

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...

This paper proposes a novel approach to extracting option-implied equity premia, and empirically examines the information content of these risk premia for forecasting the stock market return. Our approach does not require specifying the functional form of the pricing kernel, and does not impose...

Even in large equity markets, the dividend-price ratio is significantly related with the growth of future dividends. In order to uncover this relationship, we use monthly dividends and a mixed data sampling technique which allows us to cope with within-year seasonality. We reduce the effect of...

Changes in stock returns arise from changes in expected future cash flow growth and expected future discount rates. However, which variables proxy for those changes remains unknown. This paper considers twenty-five variables that are arranged into five groups and examines both in-sample...