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...

Extensive research literature has shown that equity factor premia is not constant over time. With the broad adoption of factor investing among active managers, to generate differentiated market views and returns, factor or style timing remains as one attractive means. We present an adaptive...

We estimate the latent factors in high-dimensional panel non-Gaussian data using Higher-order multi-cumulant Factor Analysis (HFA). HFA consists of an eigenvalue ratio test to select the number of non-Gaussian factors and uses alternating regressions to estimate both Gaussian and non-Gaussian...

This paper studies the performance of a sample of funds of hedge funds (FoHFs) from January 1994 to August 2009. We apply the false discoveries (FD) technique of Barras, Scaillet and Wermers (2010) to separate the FoHFs into skilled, zero-alpha and unskilled. We measure the alpha of the FoHFs...

We confront prominent asset pricing models with the classical out-of-sample cross-sectional test of Fama and MacBeth (1973). For all models, we uncover three main findings: (i) the intercept coefficients are economically large and highly statistically significant; (ii) the cross-sectional factor...

Equity analysts conceptualize the Fama-French framework as a tool for studying the size and value characteristics of equity portfolios along with the market return. But the market return is not the return to market beta. In fact, commercial providers of equity risk models typically include both...

We propose a high dimensional minimum variance portfolio estimator under statistical factor models, and show that our estimated portfolio enjoys sharp risk consistency. Our approach relies on properly integrating l1 constraint on portfolio weights with an appropriate covariance matrix estimator....

We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental factor models (FFMs). FFMs are the typical benchmark in the asset management industry and depart from the usual statistical factor models and the factor models with observed...

Models based on factors such as size, value, or momentum are ubiquitous in asset pricing. Therefore, portfolio allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a standard tool for liquid individual assets, this measure is...

A value investing strategy consists of purchasing stocks relatively undervalued to their funda-mental values and selling those relatively overvalued. Finding this kind of companies has been one of the most challenging goals for investors throughout the history. The main objective of this paper...