Modeling long-range memory trading activity by stochastic differential equations
物理与社会
2009-11-13 v1 统计金融
摘要
We propose a model of fractal point process driven by the nonlinear stochastic differential equation. The model is adjusted to the empirical data of trading activity in financial markets. This reproduces the probability distribution function and power spectral density of trading activity observed in the stock markets. We present a simple stochastic relation between the trading activity and return, which enables us to reproduce long-range memory statistical properties of volatility by numerical calculations based on the proposed fractal point process.
引用
@article{arxiv.physics/0608036,
title = {Modeling long-range memory trading activity by stochastic differential equations},
author = {V. Gontis and B. Kaulakys},
journal= {arXiv preprint arXiv:physics/0608036},
year = {2009}
}
备注
12 pages, 4 figures, APFA5 Proceedings