Sequential Information Arrival Hypothesis: More Evidence from the Indian Derivatives Market

Sangram K. Jena

Vision, 2016, vol. 20, issue 2, 101-110

Abstract: The study attempts to gather additional evidence on the sequential information arrival hypothesis by examining the dynamic relationship between the trading volume and the volatility of CNX Nifty index futures traded on the National Stock Exchange of India. The documented result using a linear Granger causality model shows a unidirectional causality from volatility to trading volume, thus rejecting the theory of sequential arrival of information in Nifty index futures. Further, under a non-linear GARCH framework of analysis, it is reinforced that a lagged trading volume has no explanatory power of current conditional volatility, even in the presence of market depth surrogated by open interest in the Nifty futures market. Consequently, given the trading volume, the possibility of forecasting the price variability of Nifty futures is rejected.

Keywords: Nifty index futures; Granger causality; GARCH (1, 1); Linear and Non-linear causality; Volatility and sequential arrival of Information hypothesis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:vision:v:20:y:2016:i:2:p:101-110

DOI: 10.1177/0972262916637259

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