Estimation of constrained factor models for high-dimensional time series
Liu, Yitian and Pan, Jiazhu and Xia, Qiang (2024) Estimation of constrained factor models for high-dimensional time series. Journal of Forecasting. ISSN 0277-6693 (In Press)
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Abstract
This article studies the estimation of the constrained factor models for high-dimensional time series. The approach is based on the eigenanalysis of a non-negative definite matrix constructed from the auto-covariance matrices. The convergence rate of the estimator for loading matrix and the asymptotic normality of the estimated factor score are explored under regularity conditions set for the proposed model. Our estimation for the constrained factor models can achieve the optimal rate of convergence even in the case of weak factors. The finite sample performance of our approach is examined and compared with the existing methods by Monte Carlo simulations. Our methodology is illustrated and supported by a real data example.
ORCID iDs
Liu, Yitian, Pan, Jiazhu ORCID: https://orcid.org/0000-0001-7346-2052 and Xia, Qiang;-
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Item type: Article ID code: 91565 Dates: DateEvent11 December 2024Published11 December 2024AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 12 Dec 2024 15:49 Last modified: 12 Dec 2024 15:49 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/91565