This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have...

Simple regression tests that have power against the alternatives that. asset prices and expected future asset returns are excessively volatile are developed and performed for the foreign exchange and stock markets. These tests have a number of advantages over alternative, variance hounds...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a...

Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this, a voluminous literature has emerged for modeling the...

We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine...

We develop a flexible semiparametric time series estimator that is then used to assess the causal effect of monetary policy interventions on macroeconomic aggregates. Our estimator captures the average causal response to discrete policy interventions in a macro-dynamic setting, without the need...

We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous...

This paper uses simulations to explore the properties of the HP filter of Hodrick and Prescott (1997), the BK filter of Baxter and King (1999), and the H filter of Hamilton (2018) that are designed to decompose a univariate time series into trend and cyclical components. Each simulated time...

The purpose of this paper is to characterize the changes in risk premium in the 1980s. A five-variable vector autoregressive model (VAR) is constructed to calculate a risk premium series in the foreign exchange market. The risk premium series is volatile and time-varying. The hypothesis of no...