fluctuations in uncertainty with persistence ranging from 32 to 128 months carry a negative price of risk of about -2% annually …. The price of risk for fluctuations with persistence outside of this range and for the raw series of aggregate uncertainty …A single factor that captures assets' exposure to business-cycle variation in macroeconomic uncertainty can explain the …

The relationship between risk and return is one of the most studied topics in finance. The majority of the literature … is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the …-realized variance. We find strong robust evidence of volatility feedback in monthly data. Once volatility feedback is accounted for …

and 4 years is effective in explaining the differences in risk premia across alternative test assets, including recently …

Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions … different frequencies but also due to the preservation of high-frequency features such as time-varying volatility. Temporally … aggregated models misspecify the evolution frequency of the volatility dynamics, resulting in poor volatility timing and worse …

decompositions, derives a network risk model for a portfolio of assets. As a normalized measure of the sum of variance contributions … deriving the network risk model, the portfolio covariance matrix is decomposed to obtain the network-driven component of the … both the variance and covariance decompositions. In a third step, using quantile regressions, the proposed network risk …

12 years of high-frequency data from U.S. and German sovereign bond markets. We detect realized volatility and realized …

This paper reviews the literature on idiosyncratic equity volatility since the publication of “Have Individual Stocks … Become More Volatile? An Empirical Exploration of Idiosyncratic Risk” in 2001. We respond to replication studies by Chiah …, Gharghori, and Zhong and by Leippold and Svaton, and we present volatility estimates through the end of 2021, significantly …

This paper proposes a Skewed Stochastic Volatility (SSV) model to model time varying, asymmetric forecast distributions … to estimate Growth at Risk as introduced in Adrian et al. (2019) seminal paper "Vulnerable Growth". In contrary to their …, I modify the Tempered Particle Filter of Herbst and Schorheide (2019) to account for stochastic volatility and …