1. Joint Estimation of Conditional Mean and Covariance for Unbalanced Panels
- Author
-
Filipovic, Damir and Schneider, Paul
- Subjects
Statistics - Methodology ,Computer Science - Machine Learning ,Quantitative Finance - Statistical Finance ,Statistics - Machine Learning ,(primary) 62G05 (secondary) 62G20, 46E40, 46E22 - Abstract
We propose a nonparametric, kernel-based joint estimator for conditional mean and covariance matrices in large unbalanced panels. Our estimator, with proven consistency and finite-sample guarantees, is applied to a comprehensive panel of monthly US stock excess returns from 1962 to 2021, conditioned on macroeconomic and firm-specific covariates. The estimator captures time-varying cross-sectional dependencies effectively, demonstrating robust statistical performance. In asset pricing, it generates conditional mean-variance efficient portfolios with out-of-sample Sharpe ratios that substantially exceed those of equal-weighted benchmarks.
- Published
- 2024