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TERRA ECONOMICUS

GRANGER CAUSALITY AMONG WORLD STOCK MARKETS: MULTIPLE SOLUTIONS

TERRA ECONOMICUS, , Vol. 17 (no. 3),

Detection of causality among indicators of various stock markets located in different time zones is a rather typical task in financial econometrics. However, the variety of lag variable modifications shows that the classical models cannot comprehensively and correctly consider the causal effects that take into account the distribution of the moments of financial institutions indicators’ value recording time within each observation. In this regard, the article, first, presents a summary of lag variable modifications in models with correction of non-synchronism problem; second, shows that the virtual time shift method induces one of the time series to shift one observation and restructures the equations specification, similar to the non-synchronism corrected models; third, theoretically summarizes the existence of multiple solutions of the classical models by proposing two alternative solutions of Granger’s equations under the shift of one of the time series in data set and it’s empirical testing; fourth, summarizes the mechanism of occurrence of alternative scenarios of multivariate autoregression model solutions under non-synchronous data formed exclusively by the Greenwich time line. In general, the work consistently reveals the problems of applicability of the classical models theoretically substantiating the existence of the specter of alternative solutions and the existence of the specter of econometric hypotheses proving other regularities, different from those revealed exclusively on the basis of non-synchronous data under the Greenwich time line condition.
Citation: Grigoryev, R. А. (2019). Granger causality among world stock markets: multiple solutions. Terra Economicus, 17(3), 146–168. DOI: 10.23683/2073-6606-2019- 17-3-146-168


Keywords: prime meridian; prime meridian bias; starting point bias; Granger causality; instantaneous causality; contemporaneous causality; exogenous; autoregression; data set; time series; nonsychronous; time quantum; time zone

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Publisher: Southern Federal University
Founder: Southern Federal University
ISSN: 2073-6606