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Some properties of multiple time series Ising model in financial market simulations

机译:金融市场模拟中多个时间序列Ising模型的某些属性

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In this paper we investigate an Ising model which simulates multiple financial time series. The model is called the multiple time series Ising model that introduces the interaction which couples to spins of other systems. We analyze the return time series data simulated by the model and find that several stylized facts such as volatility clustering appear in the model. Non-zero cross correlations between the absolute returns are also present in the model. On the other hand no cross correlations between returns are observed. We also estimate volatility of the return time series by the GARCH model and check the view of the finite-variance mixture of normal distributions for the return data by using the GARCH volatility. The results are found to be consistent with this veiw.
机译:在本文中,我们研究了一个Ising模型,该模型可以模拟多个财务时间序列。该模型称为多重时间序列Ising模型,该模型引入了与其他系统的自旋耦合的相互作用。我们分析了模型模拟的返回时间序列数据,发现模型中出现了一些程式化的事实,例如波动率聚类。模型中还存在绝对收益之间的非零互相关。另一方面,没有观察到收益之间的相互关系。我们还可以通过GARCH模型估算返回时间序列的波动率,并使用GARCH波动率检查返回数据的正态分布的有限方差混合视图。发现结果与此观点一致。

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