报告题目：Short term prediction of extreme returns based o the recurrence interval analysis

报告人：蒋志强 华东理工大学商学院博士生导师

报告时间：2018年6月11日（周一）10:30

报告地点：博识楼434室

报告摘要：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(∆t|t). Maximizing the usefulness of extreme forecasts to define an optimized hazard threshold, we indicate 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.

 报告参考文献：

【1】Z.-Q. Jiang, A. Canabarro, B. Podobnik, H. E. Stanley, and W.-X. Zhou*, Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets, Quantitative Finance, 16, 1713-1724 (2016).

【2】Z.-Q. Jiang, G.-J. Wang, A. Canabarro, B. Podobnik, C. Xie, H. E. Stanley, and W.-X. Zhou*, Short term prediction of extreme returns based on the recurrence interval analysis, Quantitative Finance, 18, 3353-3370 (2018).