Theory & Methods: Estimation of the Stochastic Volatility Model by the Empirical Characteristic Function Method
Theory & Methods: Estimation of the Stochastic Volatility Model by the Empirical Characteristic Function Method
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理论
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Jun Yu
中科院分区：
文献类型：
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作者：
J. Knight;S. Satchell;Jun Yu
随机波动率模型的似然没有封闭形式，因此最大似然估计方法难以实现。然而，可以证明该模型具有已知的特征函数。因此，该模型可通过经验特征函数进行估计。本文推导了模型的特征函数并讨论了估计过程。考虑申请每日澳元/新西兰元汇率回报。模型检查表明随机波动率模型与经验特征函数估计值很好地拟合了数据。
The stochastic volatility model has no closed form for its likelihood and hence the maximum likelihood estimation method is difficult to implement. However, it can be shown that the model has a known characteristic function. As a consequence, the model is estimable via the empirical characteristic function. In this paper, the characteristic function of the model is derived and the estimation procedure is discussed. An application is considered for daily returns of Australian/New Zealand dollar exchange rate. Model checking suggests that the stochastic volatility model together with the empirical characteristic function estimates fit the data well.