Multifractal Properties of the Ukraine Stock Market

Simple item page
dc.creatorGanchuk, A.
dc.creatorDerbentsev, V.
dc.creatorSoloviev, V.
dc.date2006-08-01
dc.date.accessioned2026-07-07T12:07:49Z
dc.date.available2026-07-07T12:07:49Z
dc.descriptionRecently the statistical characterizations of financial markets based on physics concepts and methods attract considerable attentions. We used two possible procedures of analyzing multifractal properties of a time series. The first one uses the continuous wavelet transform and extracts scaling exponents from the wavelet transform amplitudes over all scales. The second method is the multifractal version of the detrended fluctuation analysis method (MF-DFA). The multifractality of a time series we analysed by means of the difference of values singularity stregth as a suitable way to characterise multifractality. Singularity spectrum calculated from daily returns using a sliding 1000 day time window in discrete steps of 1-10 days. We discovered that changes in the multifractal spectrum display distinctive pattern around significant "drawdowns". Finally, we discuss applications to the construction of crushes precursors at the financial markets.
dc.descriptionLaTeX, 9 pages, 6 eps figure; Proc. APFA5 Conference, Torino, 2006
dc.identifierhttps://arxiv.org/abs/physics/0608009
dc.identifierhttp://arxiv.org/abs/physics/0608009
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/209105
dc.subjectData Analysis, Statistics and Probability
dc.subjectStatistical Finance
dc.titleMultifractal Properties of the Ukraine Stock Market
dc.typetext

Files

Collections

arXiv