1/13/2024 0 Comments Rtm newsflowThe exclusion process, one of Markov interacting processes, is firstly introduced to imitate the trading interactions among the investing agents in this work and to explain various statistical facts found in financial data. In attempt to reproduce and investigate nonlinear dynamics of financial markets, a new random agent-based financial price dynamics is developed and investigated by stochastic exclusion process. The results display that the model is feasible with respect to above volatility analyses. The model has similar complexity behaviors with real markets in terms of monotonic volatility with matching energy analysis, and the proposed financial model and real markets both show multifractal and anti-correlation for average monotonic volatility series by MFDFA method. Further, empirical mode decomposition and multifractal are employed to study the behaviors of monotonic volatility duration. For verifying the rationality of the model, matching energy analysis that can detect chaos and complexity in nonlinear time series is applied to study the new statistics. Meanwhile, average monotonic volatility duration of returns is also investigated, which can reflect the average volatility level. ![]() To measure the volatility of financial return series, a novel statistic called maximum monotonic volatility rate is put forward to measure the speed of monotonic volatility of returns. The exclusion process is a kind of statistical physics system, which is considered as modeling particle Markov motion with conserved number of particles. In order to reproduce the volatility dynamics of financial price changes, the agent-based financial model is established by stochastic finite-range exclusion process. Financial markets have been known to exhibit plentiful nonlinear complex volatility behaviors.
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