Home  Journals  Financial Analytics: Science and Experience  13(37) - 2010 October

On the methods of evaluating the long memory of the financial time series

Available online: 8 October 2010

Subject Heading: MATHEMATICAL METHODS OF ANALYSIS IN THE ECONOMY

JEL Classification: 

This paper deals with several aspects in time series modeling concerning estimation and tests of long memory, fractional integration, and co integration, as well as applications to financial data. The aim of the paper is to develop new and improved estimation and testing techniques, in particular to extend existing work concerning fractional processes and also to introduce new areas of application. The formulation allows the widely used rational autoregressive integrated moving average ARFIMA models and our asymptotic results provide a theoretical justification of the findings in simulations that the local Whittle estimator is robust to deterministic polynomial trends. Finally, we explore the existence of long memory in some financial time series and conclude using a novel approach in their exploration.

Keywords: long memory, fractionally integrated auto regression models, periodogram, Whittle method

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ISSN 2311-8768 (Online)
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