This paper examines the implications of pricing errors and factors that are not strong for the Fama-MacBeth two-pass estimator of risk premia and its asymptotic distribution when T is fixed with n → ∞, and when both n and T → ∞, jointly. While the literature just distinguishes strong and...

This paper examines the role of pricing errors in linear factor pricing models, allowing for observed strong and semi-strong factors, and latent weak factors. It focusses on the estimation of ∅k = λk − μk which plays a pivotal role, not only in the estimation of risk premia but also in...

In this paper we are concerned with the role of factor strength and pricing errors in asset pricing models, and their implications for identification and estimation of risk premia. We establish an explicit relationship between the pricing errors and the presence of weak factors that are...

The arbitrage pricing theory (APT) attributes differences in expected returns to exposure to systematic risk factors, which are typically assumed to be strong. In this paper we consider two aspects of the APT. Firstly we relate the factors in the statistical factor model to a theoretically...

This paper decomposes the risk premia of individual stocks into contributions from systematic and idiosyncratic risks. I introduce an affine jump-diffusion model, which accounts for both the factor structure of asset returns and that of the variance of idiosyncratic returns. The estimation is...

Stockholders are faced with both macroeconomic uncertainty and uncertainty that is generated from fears. We develop a financial stress factor as a proxy for pessimism that operates through stockholders' expectations about the elevated market volatility and shocks the cross-section of stock...

We disentangle the risk of time-varying volatility and return in a consumption-based asset pricing model by introducing stochastic volatility of consumption growth to asset prices moving in volatility units instead of moving in time. This time-change approach yields additional insights to risk...

This paper introduces a high-dimensional factor model with time-varying factor loadings. We show that both the factors and the time-varying loadings can be consistently estimated without rotations. We also propose a model-selection approach to determine the constancy of each factor loading for...

This paper develops a rare disaster asset pricing model with EZ preferences, in particular including the impact of macroeconomic consequences of the COVID-19 disaster. I estimate the probability of disaster, disaster states, and the duration of disaster to shed light on the frequency and size of...

We use deep neural networks to estimate time-varying equity risk premia. The key innovations are the nonlinear and non-parametric generalisation of Fama-Macbeth regressions through partial derivatives of an arbitrary estimator function with respect to its input and the introduction of Jacobian...