Testing of Long Memory in Indian Stock Market using ARFIMA model

Naliniprava Tripathy

Journal of Prediction Markets, 2015, vol. 9, issue 3, 23-39

Abstract: This paper examines the presence of long memory property and market cycles in the Indian stock market by using daily closing price of Nifty Index from May 2009 to April 2015. The study has used Unit Root Test, Autocorrelation Test, Rescaled Range (R/S) statistics and ARFIMA Models to determine the long memory property in Indian stock market. The result of the study shows that Indian stock market exhibits a high degree of positive long-term persistence. The results of ARFIMA model also indicates that stock price index exhibits strong evidence of long memory and contradicts the evidence against efficient market hypothesis. This implies that future stock price can be predicted. The study concludes that there is an arbitrage opportunities available for international investors and they can make abnormal profits by investing in Indian stock market.

Keywords: Unit Root Test; Autocorrelation Test; Long Memory; Rescaled Range (R/S) statistics; ARFIMA Mode (search for similar items in EconPapers)
JEL-codes: L83 (search for similar items in EconPapers)
Date: 2015
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