We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense...

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 contemporaneous relationship between market excess...

The DCF (Discounted Cash flow) Model provides the theoretical background for the possible impact of interest rate changes on equity prices. This paper examines the spillover effects from the movement of short term interest rates to equity markets within the Euro area. The empirical study is...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...

I propose a friction measure of bond round-trip liquidity costs that is robust to outliers and accounts for the idiosyncratic information behind trading decisions. Particularly effective with investment-grade bonds, the proposed measure displays properties consistent with the credit risk puzzle....

We develop a Bayesian Markov chain Monte Carlo algorithm for estimating risk premia in dynamic stochastic general equilibrium (DSGE) models with stochastic volatility. Our approach is fully Bayesian and employs an affine solution strategy that makes estimation of large-scale DSGE models...

March 2020 packed 2 ½ years of normal U.S. stock market volatility into one month, making it the most volatile month on record. Daily variability clocked in at 6%, six times higher than the average over the past 90 years. How should an investor respond to such volatility? In this article we...

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized measures to the latent conditional variance. A...

Many consumption-based models succeed in matching long lists of asset price moments. We propose an alternative, full-information Bayesian evaluation that decomposes the price-dividend ratio (p/d) into contributions from long-run risks, habit, and a residual. We find that long-run risks account...

Unexpected shifts in the realized stock market volatility, often associated with financial crises, carry a significantly negative risk premium across stocks and Treasuries, which suggests the existence of a unified pricing model. Investors require a premium for holding the risky assets (stocks),...