Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Feng, Guanhao"'
Autor:
Doh, Hyun Soo, Feng, Guanhao
Publikováno v:
Journal of Derivatives and Quantitative Studies: 선물연구, 2024, Vol. 32, Issue 3, pp. 182-199.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JDQS-01-2024-0003
Autor:
Feng, Guanhao1 (AUTHOR) gavin.feng@cityu.edu.hk, He, Jingyu1 (AUTHOR) jingyuhe@cityu.edu.hk, Polson, Nicholas G.2 (AUTHOR) ngp@chicagobooth.edu, Xu, Jianeng2 (AUTHOR) jianeng.xu@chicagobooth.edu
Publikováno v:
Journal of Financial & Quantitative Analysis. Nov2024, Vol. 59 Issue 7, p3001-3036. 36p.
Autor:
Feng, Guanhao, He, Jingyu
This paper investigates asset allocation problems when returns are predictable. We introduce a market-timing Bayesian hierarchical (BH) approach that adopts heterogeneous time-varying coefficients driven by lagged fundamental characteristics. Our app
Externí odkaz:
http://arxiv.org/abs/1902.01015
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 constructing long-short factor portfolio weights is nonlinear modeling,
Externí odkaz:
http://arxiv.org/abs/1805.01104
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 in this way, asset pricing studies can be revisited using multi-layer d
Externí odkaz:
http://arxiv.org/abs/1804.09314
Autor:
Feng, Guanhao, He, Jingyu
Publikováno v:
In Journal of Econometrics September 2022 230(1):183-200
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. This feature is attractive for ultra high-dimensional problems that oc
Externí odkaz:
http://arxiv.org/abs/1709.00379
Akademický článek
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Publikováno v:
The Journal of Finance, 2020 Jun 01. 75(3), 1327-1370.
Externí odkaz:
https://www.jstor.org/stable/45286293
Autor:
Feng, Guanhao, Polson, Nicholas G.
We show that regularizing Bayesian predictive regressions provides a framework for prior sensitivity analysis. We develop a procedure that jointly regularizes expectations and variance-covariance matrices using a pair of shrinkage priors. Our methodo
Externí odkaz:
http://arxiv.org/abs/1606.01701