英文标题：
《Short term prediction of extreme returns based on the recurrence
interval analysis》
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作者：
Zhi-Qiang Jiang (ECUST, BU), Gang-Jin Wang (HNU, BU), Askery Canabarro
(BU, UFA), Boris Podobnik (ZSEM), Chi Xie (HNU), H. Eugene Stanley (BU),
Wei-Xing Zhou (ECUST)
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最新提交年份：
2016
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英文摘要：
Being able to predict the occurrence of extreme returns is important in financial risk management. Using the distribution of recurrence intervals---the waiting time between consecutive extremes---we show that these extreme returns are predictable on the short term. Examining a range of different types of returns and thresholds we find that recurrence intervals follow a $q$-exponential distribution, which we then use to theoretically derive the hazard probability $W(\\Delta t |t)$. Maximizing the usefulness of extreme forecasts to define an optimized hazard threshold, we indicates a financial extreme occurring within the next day when the hazard probability is greater than the optimized threshold. Both in-sample tests and out-of-sample predictions indicate that these forecasts are more accurate than a benchmark that ignores the predictive signals. This recurrence interval finding deepens our understanding of reoccurring extreme returns and can be applied to forecast extremes in risk management.
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中文摘要：
能够预测极端回报的发生在金融风险管理中非常重要。利用重复间隔的分布，即连续极值之间的等待时间，我们表明这些极值收益在短期内是可预测的。通过检查一系列不同类型的回报和阈值，我们发现复发间隔遵循$q$-指数分布，然后我们使用该分布从理论上推导出风险概率$W（\\Delta t | t）$。为了最大限度地发挥极端预测的效用，定义一个优化的风险阈值，我们指出，当风险概率大于优化阈值时，第二天就会出现金融极端。样本内测试和样本外预测都表明，这些预测比忽略预测信号的基准更准确。这一重现期发现加深了我们对重复出现极端回报的理解，并可用于预测风险管理中的极端情况。
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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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