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Are frontier stock markets more inefficient than emerging stock markets?

Prakash L. Dheeriya and Erdost Torun

International Journal of Monetary Economics and Finance, 2013, vol. 6, issue 4, 271-284

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. (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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