Trading activity as driven Poisson process: comparison with empirical data

Abstract

We propose the point process model as the Poissonian-like stochastic sequence with slowly diffusing mean rate and adjust the parameters of the model to the empirical data of trading activity for 26 stocks traded on NYSE. The proposed scaled stochastic differential equation provides the universal description of the trading activities with the same parameters applicable for all stocks.

9 pages, 5 figures, proceedings of APFA6

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• Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets
• Nonlinear GARCH model and 1/f noise
• Interplay between endogenous and exogenous fluctuations in financial markets
• Understanding the nature of the long-range memory phenomenon in socioeconomic systems
• Agent-based Versus Macroscopic Modeling of Competition and Business Processes in Economics and Finance
• Nonlinear Stochastic Model of Return matching to the data of New York and Vilnius Stock Exchanges
• Modeling non-stationarities in high-frequency financial time series