文献类型：期刊文献

英文题名：Extreme value statistics and recurrence intervals of NYMEX energy futures volatility

作者：Xie, Wen-Jie[1,2,3];Jiang, Zhi-Qiang[1,2];Zhou, Wei-Xing[1,2,3,4]

机构：[1]E China Univ Sci & Technol, Sch Business, 130 Meilong Rd,POB 114, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China;[4]E China Univ Sci & Technol, Key Lab Coal Gasificat & Energy Chem Engn MOE, Shanghai 200237, Peoples R China

年份：2014

卷号：36

起止页码：8

外文期刊名：ECONOMIC MODELLING

收录：;WOS:【SSCI(收录号:WOS:000329887800002)】；

语种：英文

外文关键词：Extreme volatility; Risk estimation; Recurrence interval; Distribution; Memory

摘要：Energy markets and the associated energy futures markets play a crucial role in global economies. It is of great theoretical and practical significance to gain a deeper understanding of extreme value statistics of the volatility of energy futures traded on the New York Mercantile Exchange (NYMEX). We investigate the statistical properties of the recurrence intervals of daily volatility time series of four NYMEX energy futures, which are defined as the waiting times tau between consecutive volatilities exceeding a given threshold q. We find that the recurrence intervals are distributed as a stretched exponential P-q(tau)similar to e((a tau)-gamma), where the exponent gamma decreases with increasing q, and there is no scaling behavior in the distributions for different thresholds q after the recurrence intervals are scaled with the mean recurrence interval (tau) over bar. These findings are significant under the Kolmogorov-Smimov test and the Cramer-von Mises test. We show that the empirical estimations are in nice agreement with the numerical integration results for the occurrence probability W-q(Delta t vertical bar t) of a next event above the threshold q within a (short) time interval after an elapsed time t from the last event above q. We also investigate the memory effects of the recurrence intervals. It is found that the conditional distributions of large and small recurrence intervals differ from each other and the conditional mean of the recurrence intervals scale as a power law of the preceding interval (tau) over bar(tau(0))/(tau) over bar similar to(tau(0)/(tau) over bar)(beta), indicating that the recurrence intervals have short-term correlations. Detrended fluctuation analysis and detrending moving average analysis further uncover that the recurrence intervals possess long-term correlations. We confirm that the "clustering" of the volatility recurrence intervals is caused by the long-term correlations well known to be present in the volatility. Our findings shed new lights on the behavior of large volatilities and have potential implications in risk management of energy futures. (C) 2013 Elsevier B.V. All rights reserved.