Long memory in the Portuguese stock market
AbstractPurpose – This paper's aim is to test for the presence of fractional integration, or long memory, in the daily returns of the Portuguese stock market using autoregressive fractionally integrated moving average (ARFIMA), generalised autoregressive conditional heteroskedasticity (GARCH) and ARFIMA-FIGARCH models. Design/methodology/approach – The data cover two periods: 4 January 1993-13 January 2006 (full sample), and 1 February 2002-13 January 2006 (that is, data are considered after the merger of the Portuguese Stock Exchange with Euronext). Findings – The results from the full sample show strong evidence of long memory in stock returns. When data after the merger are considered, weaker evidence of long memory is found. It is concluded that the Portuguese stock market is more efficient after the merger with Euronext. Originality/value – The findings of this paper are helpful to financial managers and investors dealing with Portuguese stock indices.
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Bibliographic InfoArticle provided by Emerald Group Publishing in its journal Studies in Economics and Finance.
Volume (Year): 24 (2007)
Issue (Month): 3 (September)
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- Hiremath, Gourishankar S & Bandi, Kamaiah, 2011. "Testing Long Memory in Stock Returns of Emerging Markets: Some Further Evidence," MPRA Paper 48517, University Library of Munich, Germany.
- Christos Floros, 2011. "On the relationship between weather and stock market returns," Studies in Economics and Finance, Emerald Group Publishing, vol. 28(1), pages 5-13, March.
- Hiremath, Gourishankar S & Bandi, Kamaiah, 2010. "Long Memory in Stock Market Volatility:Evidence from India," MPRA Paper 48519, University Library of Munich, Germany.
- Adnan Kasman & Erdost Torun, 2007. "Long Memory in the Turkish Stock Market Return and Volatility," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 7(2), pages 13-27.
- Pilar Iglesias & Jaime San Martín & Soledad Torres & Frederi Viens, 2011. "Option pricing under a Gamma-modulated diffusion process," Annals of Finance, Springer, vol. 7(2), pages 199-219, May.
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