We propose a new measure of the expected variance risk premium that is based on a forecast of the conditional variance from a GARCH-MIDAS model. We find that the new measure has strong predictive ability for future U.S. aggregate stock market returns and rationalize this result by showing that...

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

The aim of this research is to analyze a short-term risk premium in Poland between 2005 and 2015. In particular one-day periods are considered. It is studies whether the same GARCH type model can be applied for the whole period, or whether the estimated parameters differ significantly for...

I generalize the long-run risks (LRR) model of Bansal and Yaron (2004) by incorporating recursive smooth ambiguity aversion preferences from Klibanoff et al. (2005, 2009) and time-varying ambiguity. Relative to the Bansal-Yaron model, the generalized LRR model is as tractable but more flexible...

This paper provides empirical evidence that volatility markets are integrated through the time-varying term structure of variance risk premia. These risk premia predict the returns from selling volatility for different horizons, maturities, and products, including variance swaps, straddles, and...