Long Memory in Stock Trading Volume: Evidence from Indian Stock Market

44 Pages Posted: 23 Jun 2004

See all articles by Alok Kumar

Alok Kumar

Indira Gandhi Institute of Development Research (IGIDR) - Economics

Date Written: June 21, 2004

Abstract

In this paper, we have examined the long memory property of Indian stock market by analyzing the trading volume series. Given the absence of trading volume index data, we have constructed trading volume series for the Indian stock market. We used maximum likelihood method to analyze the constructed trading volume index. The estimation of ARFIMA model, obtained a significant parameter for the order of fractional integration, and this could be consistent with the long autocorrelations observed in the trading volume series. The finding that stock-trading volume is a long memory process is robust, given different estimating methods, different sub samples, temporal aggregation and tests on individual stocks. Because of the conditional heteroscedasticity in the series, we have also carried out ARFIMA-GARCH procedures to check whether long persistence was robust in the presence of conditional heteroscedasticity.

Keywords: Trading volume, Detrending, Long memory process, ARFIMA, ARFIMA-GARCH, Periodogram regression

JEL Classification: C1, C22, G10

Suggested Citation

Kumar, Alok, Long Memory in Stock Trading Volume: Evidence from Indian Stock Market (June 21, 2004). Available at SSRN: https://ssrn.com/abstract=557681 or http://dx.doi.org/10.2139/ssrn.557681

Alok Kumar (Contact Author)

Indira Gandhi Institute of Development Research (IGIDR) - Economics ( email )

Film City Road, Santosh Nagar
Mumbai 400065 Maharashtra
India
91 982 025 7651 (Phone)
91 222 840 2752 (Fax)

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