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Mathematica 10 的新功能 › 扩展的时间序列过程 ›

条件异方差的判定 

TimeSeriesModelFit 对于在数据中的条件异方差进行自动检测，并对数据拟合 ARCH/GARCH 模型.

创建星巴克公司股票的日收益时间序列.

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计算自相关函数.

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在收益序列中验证自相关性.

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返回的时间序列不是自相关的，但其平方是自相关.

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TimeSeriesModelFit 判定 GARCH 系列是对数据的最佳拟合.

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求拟合过程.

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模型的残差表现为不相关.

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用 TimeSeriesModel 计算未来预测的置信区间.

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Related Examples

Decide Time Series Process Family and Order from Data Automatically » Identify Conditional Heteroscedacity » Airline Passengers » Constrain the Model Selection Set »
Use Different Criteria for Model Selection » Investigate Time Series Model Residuals » Study Significance of Parameters in Fitted Model » Use Fitted Model to Forecast Time Series »
Model Multiple Exchange Rates » Vector Joint Model versus Univariate Component Models » Use Vector Models with Multiple Strongly Correlated Time Series » Vector Autoregressive Process as Discretized Vector Ornstein–Uhlenbeck Process »
Time Series Processes with Nonzero Mean » Time Series Processes with Initial Conditions » Study Non-weakly Stationary Autoregressive Process » Compute Expectation of Autoregressive Moving-Average Process from Its Definition »
Use Spectral Estimator to Find FARIMA Parameters » Volatility Clustering in a GARCHProcess » Slice Distribution of GARCH(1,1) » Moments of GARCH(1,1) »
Model the Conditional Value at Risk with an ARCHProcess » Expanded Estimation Methods » Broad Performance Improvements »
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