Authors: Prakash L. Dheeriya; Erdost Torun
Addresses: Department of Finance and Accounting, California State University-Dominguez Hills, 1000 E Victoria St, Carson, CA 90747, USA ' Faculty of Business, Department of International Business & Trade, Dokuz Eylul University, Kaynaklar Campus, Tinaztepe 35160, Buca-Izmir, Turkey
Abstract: This paper investigates the presence of long memory in MSCIs Frontier and Emerging Market Indices, using autoregressive fractionally integrated moving average (ARFIMA) and fractionally integrated generalised autoregressive conditional heteroscedasticity (FIGARCH) models. The concept of 'long memory' has become important recently in financial academic research. Long memory tests are carried out both for the returns and volatilities of these series. Results of the ARFIMA models indicate the existence of long memory in Frontier markets return series. Presence of long memory properties in return series is indicative of inefficiency or efficiency in stock markets, and therefore, are useful to investors interested in diversifying their portfolios. On a risk return basis, frontier and emerging markets may provide a better outcome for portfolio managers.
Keywords: ARFIMA; autoregressive fractionally integrated moving average; FIGARCH; fractionally integrated GARCH; autoregressive conditional heteroscedasticity; frontier markets; emerging markets; efficiency; long memory; diversification; portfolio management.
International Journal of Monetary Economics and Finance, 2013 Vol.6 No.4, pp.271 - 284
Received: 17 May 2013
Accepted: 01 Aug 2013
Published online: 21 Mar 2014 *