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Short term prediction of extreme returns based on the recurrence interval analysis

發布時間:2018-06-05瀏覽次數:823

講座名稱

Short term prediction of extreme returns based on the recurrence interval analysis

開設部門

統計與信息學院

時間地點

2018年6月15日;信息樓407室

面向對象

全校

主講人

蔣志強

講座類型

全校性講座

內容簡介

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.


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