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This study investigates the spillover effects between exchange rate changes and stock returns in China. The authors find that no significant interconnections exist between stock returns and exchange rates changes.

Although the conventional structural VAR (SVAR) approach fails to examine the contemporaneous effects, the Markov switching SVAR model captures the volatile structure of the Chinese financial market. The regime-switching estimates indicate that volatile structure tends to be significant during two financial crisis periods.

Notwithstanding the fact that exchange rate changes cannot Granger-cause stock returns in the long run, its contemporaneous spillover effects on stock returns are found to be statistically significant.

This study aims to shed light on the spillover effects between exchange rate changes and stock returns in China, as the Chinese currency is becoming flexible and China’s stock market has undertaken important reforms. The spillovers between the two markets are of topical importance due to the increasing connections between China and the global economy.

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.