Long-term memory in the Irish market (ISEQ): evidence from wavelet analysis

dc.creatorSharkasi, Adel
dc.creatorRuskin, Heather J.
dc.creatorCrane, Martin
dc.date2006-07-20
dc.date.accessioned2026-07-07T12:07:47Z
dc.date.available2026-07-07T12:07:47Z
dc.descriptionResearchers have used many different methods to detect the possibility of long-term dependence (long memory) in stock market returns, but evidence is in general mixed. In this paper, three different tests, (namely Rescaled Range (R/S), its modified form, and the semi-parametric method (GPH)), in addition to a new approach using the discrete wavelet transform, (DWT), have been applied to the daily returns of five Irish Stock Exchange (ISEQ) indices. These methods have also been applied to the volatility measures (namely absolute and squared returns). The aim is to investigate the existence of long-term memory properties. The indices are Overall, Financial, General, Small Cap and ITEQ and the results of these approaches show that there is no evidence of long-range dependence in the returns themselves, while there is strong evidence for such dependence in the squared and absolute returns. Moreover, the discrete wavelet transform (DWT) provides additional insight on the series breakdown. In particular, in comparison to other methods, the benefit of the wavelet transform is that it provides a way to study the sensitivity of the series to increases in amplitude of fluctuations as well as changes in frequency. Finally, based on results for these methods, in particular, those for DWT of raw (or original), squared and absolute returns, it can be concluded that there is strong indication for persistence in the volatilities of the emerging stock market returns for the Irish data.
dc.description10 pages. Presented at International Conference "Applications of Physics in Financial Analysis", 29 June- 1 July 2006, Torino, Italy
dc.identifierhttps://arxiv.org/abs/physics/0607182
dc.identifierhttp://arxiv.org/abs/physics/0607182
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/209094
dc.subjectData Analysis, Statistics and Probability
dc.subjectStatistical Finance
dc.titleLong-term memory in the Irish market (ISEQ): evidence from wavelet analysis
dc.typetext

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