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A Structural Dynamic Factor Model for Daily Global Stock Market Returns

Oliver B. Linton, Haihan Tang and Jianbin Wu

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: Most stock markets are open for 6-8 hours per trading day. The Asian, European and American stock markets are separated in time by time-zone differences. We propose a statistical dynamic factor model for a large number of daily returns across multiple time zones. Our model has a common global factor as well as continental factors. Under a mild fixed-signs assumption, our model is identified and has a structural interpretation. We propose several estimators of the model: the maximum likelihood estimator-one day (MLE-one day), the quasi-maximum likelihood estimator (QMLE), an improved estimator from QMLE (QMLE-md), the QMLEres (similar to MLE-one day), and a Bayesian estimator (Gibbs sampling). We establish consistency, the rates of convergence and the asymptotic distributions of the QMLE and the QMLE-md. We next provide a heuristic procedure for conducting inference for the MLE-one day and the QMLE-res. Monte Carlo simulations reveal that the MLE-one day, the QMLE-res and the QMLE-md work well. We then apply our model to two real data sets: (1) equity portfolio returns from Japan, Europe and the US; (2) MSCI equity indices of 41 developed and emerging markets. Some new insights about linkages among different markets are drawn.

Keywords: Daily Global Stock Market Returns; Expectation Maximization Algorithm; Minimum Distance; Quasi Maximum Likelihood; Structural Dynamic Factor Model; Time-Zone Differences (search for similar items in EconPapers)
JEL-codes: C55 C58 G15 (search for similar items in EconPapers)
Date: 2022-06-15
New Economics Papers: this item is included in nep-dem, nep-ecm, nep-ets, nep-ifn and nep-sea
Note: obl20
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2237

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