时间序列和统计模型是现代金融资产定价以及金融风险测量和管理的理论和实践的一个基本组成部分。此外，预测是金融和投资决策的一个必要组成部分。本单元介绍了用于分析金融市场中出现的数据的时间序列模型。然后，它考虑在这些模型的背景下进行预测、测试和敏感性分析的方法。主题包括：金融收益数据的属性；资本资产定价模型（CAPM）；金融收益因子模型，在面板数据设置中包含已知和未知因子；通过ARCH和GARCH对条件波动率进行建模和预测；预测市场风险措施，如风险价值。重点是涉及许多真实市场数据集分析的应用。我们鼓励学生使用适当的计算软件包进行实践分析。
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