120 citations · 145 across the 8 of their papers we have counts for
8 papers
Panel Coupled Matrix-Tensor Clustering Model with Applications to Asset Pricing
Liyuan Cui, Guanhao Feng, Yuefeng Han +1
We tackle the challenge of estimating grouping structures and factor loadings in asset pricing models, where traditional regressions struggle due to sparse data and high noise. Exi…
Growing the Efficient Frontier on Panel Trees
Lin William Cong, Guanhao Feng, Jingyu He +1
We introduce a new class of tree-based models, P-Trees, for analyzing (unbalanced) panel of individual asset returns, generalizing high-dimensional sorting with economic guidance a…
Factor Investing: A Bayesian Hierarchical Approach
Guanhao Feng, Jingyu He
This paper investigates asset allocation problems when returns are predictable. We introduce a market-timing Bayesian hierarchical (BH) approach that adopts heterogeneous time-vary…
Deep Learning in Characteristics-Sorted Factor Models
Guanhao Feng, Jingyu He, Nicholas G. Polson +1
This paper presents an augmented deep factor model that generates latent factors for cross-sectional asset pricing. The conventional security sorting on firm characteristics for co…
Deep Learning for Predicting Asset Returns
Guanhao Feng, Jingyu He, Nicholas G. Polson
Deep learning searches for nonlinear factors for predicting asset returns. Predictability is achieved via multiple layers of composite factors as opposed to additive ones. Viewed i…
Sparse Regularization in Marketing and Economics
Guanhao Feng, Nicholas Polson, Yuexi Wang +1
Sparse alpha-norm regularization has many data-rich applications in Marketing and Economics. Alpha-norm, in contrast to lasso and ridge regularization, jumps to a sparse solution.…
Regularizing Bayesian Predictive Regressions
Guanhao Feng, Nicholas G. Polson
We show that regularizing Bayesian predictive regressions provides a framework for prior sensitivity analysis. We develop a procedure that jointly regularizes expectations and vari…
The Market for English Premier League (EPL) Odds
Guanhao Feng, Nicholas G. Polson, Jianeng Xu
This paper employs a Skellam process to represent real-time betting odds for English Premier League (EPL) soccer games. Given a matrix of market odds on all possible score outcomes…