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[转载]【统计学】【2012】金融时间序列的统计分析与风险管理

已有 1030 次阅读 2021-4-19 17:24 |系统分类:科研笔记|文章来源:转载

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本文为美国北卡罗来纳大学(作者:Hongyu Ru)的博士论文,共80页。

 

本文研究了金融收益的波动性、偏度和风险价值的动态变化。它包含三个主题。

 

第一个是资产定价条件偏态模型的渐近性质。我们从一个简单的基于消费的资产定价模型入手,将资产定价模型与分位数回归的正则性条件联系起来。在一定的假设条件下,我们证明了分位数回归估计是渐近一致的正态分布。

 

第二个是风险管理的动态分位数模型。我们提出了一个基于动态分位数回归的金融风险模型,该模型允许我们联合估计条件波动率和偏度。通过仿真,将该方法与ARCHtype模型进行了比较。我们还提出了一种密度拟合方法,通过匹配条件分位数和参数密度来获得收益的条件分布。

 

第三部分是基于消费的资产定价模型的仿真研究。我们证明了在资产定价模型中引入条件不对称可以获得更大的收益率和更高的比率。

 

The dissertation studies the dynamic of volatility, skewness, and value at risk for financial returns. It contains three topics. The first one is the asymptotic properties of the conditional skewness model for asset pricing. We start with a simple consumption-based asset pricing model, and make a connection between the asset pricing model and the regularity conditions for a quantile regression. We prove that the quantile regression estimators are asymptotically consistent and normally distributed under certain assumptions for the asset pricing model. The second one is about dynamic quantile models for risk management. We propose a financial risk model based on dynamic quantile regressions, which allows us to estimate conditional volatility and skewness jointly. We compare this approach with ARCHtype models by simulation. We also propose a density fitting approach by matching conditional quantiles and parametric densities to obtain the conditional distributions of returns. The third one is a simulation study of a consumption based asset pricing model. We show that larger returns and Sharp ratio can be obtained by introducing conditional asymmetry in the asset pricing model.

 

1.        基于分位数的资产定价条件偏态模型的渐近性质

2. 风险管理的动态分位数模型

3. 资产定价的长期偏态模拟研究


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