Nonparametric regression using linear combinations of basis functions
Statistics and Computing
Consistent variable selection in large panels when factors are observable
Journal of Multivariate Analysis
Efficient Bayesian estimation of multivariate state space models
Computational Statistics & Data Analysis
Penalized factor mixture analysis for variable selection in clustered data
Computational Statistics & Data Analysis
Editorial: Special issue on variable selection and robust procedures
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
Empirical tests of the arbitrage pricing theory using measured variables rely on the accuracy of standard inferential theory in approximating the distribution of the estimated risk premiums and factor betas. The techniques employed thus far perform factor selection and model inference sequentially. Recent advances in Bayesian variable selection are adapted to an approximate factor model to investigate the role of measured economic variables in the pricing of securities. In finite samples, exact statistical inference is carried out using posterior distributions of functions of risk premiums and factor betas. The role of the panel dimensions in posterior inference is investigated. New empirical evidence is found of time-varying risk premiums with higher and more volatile expected compensation for bearing systematic risk during contraction phases. In addition, investors are rewarded for exposure to ''Economic'' risk.