A Structural Dynamic Factor Model for Daily Global Stock Market Returns

Oliver 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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: A Structural Dynamic Factor Model for Daily Global Stock Market Returns (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2237

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