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A large confirmatory dynamic factor model for stock market returns in different time zones

Oliver B. Linton, Haihan Tang and Jianbin Wu

Journal of Econometrics, 2025, vol. 249, issue PB

Abstract: We propose a confirmatory dynamic factor model for a large number of stocks whose returns are observed daily across multiple time zones. The model has a global factor and a continental factor that both drive the individual stock return series. We propose two estimators of the model: a quasi-maximum likelihood estimator (QML-just-identified), and an improved estimator based on an Expectation Maximization (EM) algorithm (QML-all-res). Our estimators are consistent and asymptotically normal under the large approximate factor model setting. In particular, the asymptotic distributions of QML-all-res are the same as those of the infeasible OLS estimators that treat factors as known and utilize all the restrictions on the parameters of the model. We apply the model to MSCI equity indices of 42 developed and emerging markets, and find that most markets are more integrated when the CBOE Volatility Index (VIX) is high.

Keywords: Daily global stock market returns; Time-zone differences; Confirmatory dynamic factor models; Quasi maximum likelihood; EM algorithm (search for similar items in EconPapers)
JEL-codes: C32 C55 C58 G15 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:249:y:2025:i:pb:s0304407625000259

DOI: 10.1016/j.jeconom.2025.105971

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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