This paper introduces a new methodology to estimate time‐varying alphas and betas in conditional factor models, which allows substantial flexibility in a time‐varying framework. To circumvent problems associated with the previous approaches, we introduce a Bayesian time‐varying parameter...

This paper suggests a novel approach for predicting aggregate stock returns at quarterly and annual frequencies. Weak return predictability is consistent with the view that a stationary component of stock prices is highly persistent. In such cases, expected returns are time-varying but also...

Several academics have studied the ability of hybrid models mixing univariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models and neural networks to deliver better volatility predictions than purely econometric models. Despite presenting very promising results, the...

We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a...

We build a novel macro-finance model that combines a semi-structural macroeconomic module with arbitrage-free yield-curve dynamics. We estimate it for the United States and the euro area using a Bayesian approach and jointly infer the real equilibrium interest rate (r*), trend inflation (π*),...

We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a...

Incorporating arbitrage-free term-structure dynamics into a semi-structural macro-model, we jointly estimate the real equilibrium interest rate (r*), trend inflation, and term premia for the United States and the euro area, using a Bayesian approach. The natural real rate and trend inflation are...

We use the Bayesian method introduced by Gallant and McCulloch (2009) to estimate consumption-based asset pricing models featuring smooth ambiguity preferences. We rely on semi-nonparametric estimation of a flexible auxiliary model in our structural estimation. Based on the market and aggregate...

Under an assumption of normality, we explore a non-orthogonal Bayesian technique in which redundant information can in principle be filtered out of the posterior distribution by the explicit coupling of the prior and likelihood functions. The Black-Litterman forecasting model widely used by...

In light of the power problems of statistical tests and undisciplined use of alpha-based statistics to compare models, this paper proposes a unified set of distance-based performance metrics, derived as the square root of the sum of squared alphas and squared standard errors. The Bayesian...