英文标题：
《Quantile Dependence between Stock Markets and its Application in
  Volatility Forecasting》
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作者：
Heejoon Han
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最新提交年份：
2016
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英文摘要：
  This paper examines quantile dependence between international stock markets and evaluates its use for improving volatility forecasting. First, we analyze quantile dependence and directional predictability between the US stock market and stock markets in the UK, Germany, France and Japan. We use the cross-quantilogram, which is a correlation statistic of quantile hit processes. The detailed dependence between stock markets depends on specific quantile ranges and this dependence is generally asymmetric; the negative spillover effect is stronger than the positive spillover effect and there exists strong directional predictability from the US market to the UK, Germany, France and Japan markets. Second, we consider a simple quantile-augmented volatility model that accommodates the quantile dependence and directional predictability between the US market and these other markets. The quantile-augmented volatility model provides superior in-sample and out-of-sample volatility forecasts.
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中文摘要：
本文考察了国际股票市场之间的分位数相关性，并评估了其在改进波动率预测方面的应用。首先，我们分析了美国股市与英国、德国、法国和日本股市之间的分位数依赖性和方向可预测性。我们使用交叉分位数图，这是分位数命中过程的相关统计。股票市场之间的详细相关性取决于具体的分位数范围，这种相关性通常是不对称的；负溢出效应强于正溢出效应，从美国市场到英国、德国、法国和日本市场存在很强的方向性可预测性。其次，我们考虑一个简单的分位数增加波动率模型，该模型考虑了美国市场和这些其他市场之间的分位数依赖性和方向可预测性。分位数增加波动率模型提供了卓越的样本内和样本外波动率预测。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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