Long-range memory model of trading activity and volatility

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dc.creatorGontis, V.
dc.creatorKaulakys, B.
dc.date2006-06-14
dc.date.accessioned2026-07-07T12:07:46Z
dc.date.available2026-07-07T12:07:46Z
dc.descriptionEarlier we proposed the stochastic point process model, which reproduces a variety of self-affine time series exhibiting power spectral density S(f) scaling as power of the frequency f and derived a stochastic differential equation with the same long range memory properties. Here we present a stochastic differential equation as a dynamical model of the observed memory in the financial time series. The continuous stochastic process reproduces the statistical properties of the trading activity and serves as a background model for the modeling waiting time, return and volatility. Empirically observed statistical properties: exponents of the power-law probability distributions and power spectral density of the long-range memory financial variables are reproduced with the same values of few model parameters.
dc.description12 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/physics/0606115
dc.identifierhttp://arxiv.org/abs/physics/0606115
dc.identifierJ. Stat. Mech. (2006) P10016
dc.identifierdoi:10.1088/1742-5468/2006/10/P10016
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/209085
dc.subjectPhysics and Society
dc.subjectStatistical Finance
dc.titleLong-range memory model of trading activity and volatility
dc.typetext

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