We show how to build a cross-section of asset returns, that is, a small set of basis or test assets that capture complex information contained in a given set of stock characteristics and span the Stochastic Discount Factor (SDF). We use decision trees to generalize the concept of conventional...

Based on a novel high-frequency data set for a large number of firms, I estimate the time-varying latent continuous and jump factors that explain individual stock returns. The factors are estimated using principal component analysis applied to a local volatility and jump covariance matrix. I...

A Simple Method for Predicting Covariance Matrices of Financial Returns makes three contributions. It proposes a new method for predicting the time-varying covariance matrix of a vector of financial returns and a new method for evaluating a covariance predictor. The third contribution is an...