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Modelling and Detecting Long Memory in Stock Returns

  • Ciprian Necula

    (Faculty of Finance and Banking, Bucharest University of Economics)

In this paper we revisit this issue of long memory in stock returns by applying a range of parametric and semi-parametric techniques to daily, weekly and monthly index return data on nine countries, namely the USA, Japan, France, Great Britain, Taiwan, Singapore and Romania. We also discuss a continuous trading model based on the fractional Brownian motion (a stochastic process that exhibit long memory) and pricing derivative securities under this model.

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File URL: http://www.dofin.ase.ro/Working%20papers/Ciprian%20Necula/diz.pdf
File Function: First version, 2008
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Paper provided by Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB in its series Advances in Economic and Financial Research - DOFIN Working Paper Series with number 9.

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Date of creation: Jun 2008
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Handle: RePEc:cab:wpaefr:9
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