Information Flows across Markets: Evidence from China–Backed Stocks Dual–Listed in Hong Kong and New York

Abstract

Using a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model, we examine patterns of information flows for China–backed stocks that are cross–listed on exchanges in Hong Kong and New York. Results analyzing the dual–listed stocks indicate significant mutual feedback of information between domestic (Hong Kong) and offshore (New York) markets in terms of pricing and volatility. Stocks listed on the domestic market appear to play a more significant role of information transmission in the pricing process, whereas stocks listed on the offshore market play a bigger role in volatility spillover.

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