The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices.
The authors test for lead-lag effects between the Indian Nifty and Nifty Junior indices using Pesaran–Timmermann tests and Granger-Causality. Then, a simple test on overnight returns is proposed to infer whether the observed predictability is mainly attributable to non-synchronous trading or some form of inefficiency.
The evidence suggests that non-synchronous trading is a better explanation for the observed predictability in the Indian Stock Market.
The indication that non-synchronous trading effects become more pronounced in high-frequency data suggests that prior studies using daily data may underestimate the impacts of non-synchronicity.
The originality of the paper rests on various important contributions: overnight returns is looked at to infer whether predictability is more attributable to non-synchronous trading or to some form of inefficiency; the impacts of non-synchronicity are investigated in terms of lead-lag effects rather than serial correlation; and high-frequency data is used which gauges the impacts of non-synchronicity during less active parts of the trading day.
The authors thank Steve Thomas (Cass), Lawrence Leger (Loughborough), two anonymous referees and participants at the Emerging Markets Finance Conference (2005) and the Portuguese Finance Network Conference (2008) for comments about previous versions of this paper. The authors also thank the National Stock Exchange of India for providing the data.
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