We build a simple diagnostic criterion for approximate factor structure in large panel datasets. Given observable factors, the criterion checks whether the errors are weakly cross-sectionally correlated or share at least one unobservable common factor (interactive effects). A general version...

This chapter surveys recent econometric methodologies for inference in large dimensional conditional factor models in finance. Changes in the business cycle and asset characteristics induce time variation in factor loadings and risk premia to be accounted for. The growing trend in the use of...

In this article we examine the risk factors that help explain long/short equity (LSE) mutual fund performance. We show that for most LSE mutual funds, 50%-80% of their returns can be explained using common factors such as capitalization, book-to-value ratio, dividend yield, and volatility. The...

In this paper, we present a continuous time Capital Asset Pricing Model where the volatilities of the market index and the stock are both stochastic. Using a singular perturbation technique, we provide approximations for the prices of European options on both the stock and the index. We derive...

The paper describes the specification, estimation, and testing of an unrestricted structural econometric model design to explain and forecast individual returns of securities listed on the Brazilian stock market. The model's explanatory variables include macroeconomic, fundamental and...

This paper is concerned with statistical inference and model evaluation in possibly misspecified and unidentified linear asset-pricing models estimated by maximum likelihood and one-step generalized method of moments. Strikingly, when spurious factors (that is, factors that are uncorrelated with...

Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama-French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In...

We compare major factor models and find that the Stambaugh and Yuan (2016) four-factor model is the overall winner in the time-series domain. The Hou, Xue, and Zhang (2015) q-factor model takes second place and the Fama and French (2015) five-factor model and the Barillas and Shanken (2018)...

We examine which factor model best captures systematic return covariation by focusing on the economic implications for portfolio risk control. The pairwise variance equality test and the model confidence set procedure suggest that the Fama and French (2015) five-factor model, the Barillas and...

We propose a new method, VASA, based on variable subsample aggregation of model predictions for equity returns using a large-dimensional set of factors. To demonstrate the effectiveness, robustness, and dimension reduction power of VASA, we perform a comparative analysis between state-of-the-art...