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Journal of the American Statistical Association Volume 117, 2022 - Issue 538
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Theory and Methods

Learning Latent Factors From Diversified Projections and Its Applications to Over-Estimated and Weak Factors

Jianqing Fana Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ; View further author information
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Yuan Liaob Department of Economics, Rutgers University, New Brunswick, NJCorrespondence[email protected]
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Pages 909-924 | Received 01 Mar 2020, Accepted 25 Sep 2020, Published online: 20 Nov 2020

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Ignace De Vos, Gerdie Everaert & Vasilis Sarafidis. (2024) A method to evaluate the rank condition for CCE estimators. Econometric Reviews 43:2-4, pages 123-155.
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Jianqing Fan & Yihong Gu. (2023) Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression. Journal of the American Statistical Association 0:0, pages 1-15.
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Jianqing Fan, Zhipeng Lou & Mengxin Yu. (2023) Are Latent Factor Regression and Sparse Regression Adequate?. Journal of the American Statistical Association 0:0, pages 1-13.
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Articles from other publishers (3)

Yu-Ning Li, Jia Chen & Oliver Linton. (2023) Estimation of common factors for microstructure noise and efficient price in a high-frequency dual factor model. Journal of Econometrics, pages 105382.
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Jianqing FanKunpeng Li & Yuan Liao. (2021) Recent Developments in Factor Models and Applications in Econometric Learning. Annual Review of Financial Economics 13:1, pages 401-430.
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Stefano Giglio, Dacheng Xiu & Dake Zhang. (2021) Test Assets and Weak Factors. SSRN Electronic Journal.
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