Open AccessSimulation of non-stationary event flow with a nested stationary component
Author(s) -
Ruslan V. Pleshakov
Publication year - 2020
Publication title -
discrete and continuous models and applied computational science
Language(s) - English
Resource type - Journals
eISSN - 2658-7149
pISSN - 2658-4670
DOI - 10.22363/2658-4670-2020-28-1-35-48
Subject(s) - stationary sequence , series (stratigraphy) , event (particle physics) , sequence (biology) , poisson distribution , flow (mathematics) , random variable , mathematics , variable (mathematics) , statistical physics , stationary process , statistics , mathematical analysis , physics , geometry , geology , paleontology , quantum mechanics , biology , genetics
A method for constructing an ensemble of time series trajectories with a nonstationary flow of events and a non-stationary empirical distribution of the values of the observed random variable is described. We consider a special model that is similar in properties to some real processes, such as changes in the price of a financial instrument on the exchange. It is assumed that a random process is represented as an attachment of two processes - stationary and non-stationary. That is, the length of a series of elements in the sequence of the most likely event (the most likely price change in the sequence of transactions) forms a non-stationary time series, and the length of a series of other events is a stationary random process. It is considered that the flow of events is non-stationary Poisson process. A software package that solves the problem of modeling an ensemble of trajectories of an observed random variable is described. Both the values of a random variable and the time of occurrence of the event are modeled. An example of practical application of the model is given.