TITLE:
Comovement of Stock Markets—An Analysis by Nonlinear Cointegration*
AUTHORS:
Kazumi Asako, Zhentao Liu
KEYWORDS:
Booms and Busts, Stock Prices, Nonlinear Cointegration, Bayesian Estimation
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.4 No.5,
May
16,
2016
ABSTRACT: This paper proposes and estimates a statistical
model of nonlinear cointegration, with applications to the stock markets of
Japan and the United States. We define nonlinear cointegration as a long-run
stable relationship between two time series variables even in the presence of
temporary nonlinear divergence from this long-run relationship. More concretely,
extending the bubble model of Asako and Liu (2013) [1] to stock price ratio variables,
both upward and downward divergent bubble processes are estimated at a time. We
conclude that, although two stock price indexes are not linearly cointegrated,
they are considered to be cointegrated nonlinearly.