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Linton, O. B., Tang, H., Wu, J.

A Structural Dynamic Factor Model for Daily Global Stock Market Returns

JIWP Number: 2214

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

JEL Codes: C55 C58 G15

Author links: Oliver Linton  

PDF: jiwp2214.pdf

Open Access Link: 10.17863/CAM.86222

Theme: empirical