 An Enhanced Factor Model for Portfolio Selection in High Dimensions*Fangquan Shi, Lianjie Shu and Xinhua Gu Journal of Financial Econometrics, 2024, vol. 22, issue 1, 94-118 Abstract: This article extends Fama and French (FF) models of observed factors by introducing latent factors (LFs) to further extract information from FF residual returns. A diagonally dominant (DD) rather than a diagonal or sparse matrix structure is adopted in this study to estimate remaining covariance between disturbance terms. Such an enhanced factor (EF) model provides a more comprehensive analysis for portfolio selection in high dimensions and also has certain advantages of estimation stability and computational efficiency. It is shown that the proposed EF–DD approach achieves overall better performance than competing models in terms of portfolio variance and the net Sharpe ratio. Keywords: covariance matrices; diagonally dominant structures; factor models; Fama and French models; latent factors; minimum variance portfolios (MVPs) (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:22:y:2024:i:1:p:94-118. Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.