英文标题：
《Are news important to predict large losses?》
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作者：
Mauro Bernardi, Leopoldo Catania and Lea Petrella
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最新提交年份：
2014
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英文摘要：
In this paper we investigate the impact of news to predict extreme financial returns using high frequency data. We consider several model specifications differing for the dynamic property of the underlying stochastic process as well as for the innovation process. Since news are essentially qualitative measures, they are firstly transformed into quantitative measures which are subsequently introduced as exogenous regressors into the conditional volatility dynamics. Three basic sentiment indexes are constructed starting from three list of words defined by historical market news response and by a discriminant analysis. Models are evaluated in terms of their predictive accuracy to forecast out-of-sample Value-at-Risk of the STOXX Europe 600 sectors at different confidence levels using several statistic tests and the Model Confidence Set procedure of Hansen et al. (2011). Since the Hansen\'s procedure usually delivers a set of models having the same VaR predictive ability, we propose a new forecasting combination technique that dynamically weights the VaR predictions obtained by the models belonging to the optimal final set. Our results confirms that the inclusion of exogenous information as well as the right specification of the returns\' conditional distribution significantly decrease the number of actual versus expected VaR violations towards one, as this is especially true for higher confidence levels.
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中文摘要：
在本文中，我们研究了新闻对使用高频数据预测极端财务回报的影响。我们考虑了几种不同的模型规格，它们分别针对基础随机过程和创新过程的动态特性。由于新闻本质上是定性指标，因此首先将其转化为定量指标，然后将其作为外生回归引入条件波动动力学。从历史市场新闻反应和判别分析定义的三个词列表出发，构建了三个基本情绪指数。利用几个统计测试和Hansen等人（2011）的模型置信集程序，评估模型的预测精度，以预测不同置信水平下斯托克欧洲600个行业的样本外风险值。由于Hansen的过程通常提供一组具有相同VaR预测能力的模型，因此我们提出了一种新的预测组合技术，该技术可以动态地对属于最优最终集的模型所获得的VaR预测进行加权。我们的结果证实，包含外部信息以及正确说明收益的条件分布显著减少了实际与预期VaR违规的数量，因为对于更高的置信水平尤其如此。
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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：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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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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