Predicting tail events in a RIA-EVT-Copula framework

Wei-Zhen Li, Jin-Rui Zhai, Zhi-Qiang Jiang, Gang-Jin Wang and Wei-Xing Zhou

Physica A: Statistical Mechanics and its Applications, 2022, vol. 600, issue C

Abstract: Predicting the occurrence of tail events is of great importance in financial risk management. By employing the method of peak-over-threshold (POT) in extreme value theory (EVT) to identify the financial extremes, we perform a recurrence interval analysis (RIA) on these extremes. We find that the waiting time between consecutive extremes (recurrence interval) follows a q-exponential distribution, and the sizes of extremes above the thresholds (exceeding size) conform to a generalized Pareto distribution. We also find that there is a significant correlation between recurrence intervals and exceeding sizes. We thus model the joint distribution of recurrence intervals and exceeding sizes through connecting the two corresponding marginal distributions with the Frank and Ali-Mikhail-Haq (AMH) copula functions, and apply this joint distribution to estimate the hazard probability to observe another extreme in Δt time since the last extreme happened t time ago. Furthermore, an extreme predicting model based on RIA-EVT-Copula is proposed by applying a decision-making algorithm on the hazard probability. Both in-sample and out-of-sample tests reveal that this new extreme forecasting framework has better predicting performance than the forecasting model based on the hazard probability only estimated from the distribution of recurrence intervals. Our results not only shed a new light on understanding the occurring pattern of extremes in financial markets, but also improve the accuracy of predicting financial extremes for risk management.

Keywords: Recurrence interval analysis; Peaks over threshold; Copula; Hazard probability; Extreme forecasting (search for similar items in EconPapers)
JEL-codes: C51 C53 G01 G17 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437122003703
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
Working Paper: Predicting tail events in a RIA-EVT-Copula framework (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:600:y:2022:i:c:s0378437122003703

DOI: 10.1016/j.physa.2022.127524

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().