Realizing stock market crashes: stochastic cusp catastrophe model of returns under the time-varying volatility

Jozef Baruník and Jiri Kukacka

Papers from arXiv.org

Abstract: This paper develops a two-step estimation methodology, which allows us to apply catastrophe theory to stock market returns with time-varying volatility and model stock market crashes. Utilizing high frequency data, we estimate the daily realized volatility from the returns in the first step and use stochastic cusp catastrophe on data normalized by the estimated volatility in the second step to study possible discontinuities in markets. We support our methodology by simulations where we also discuss the importance of stochastic noise and volatility in deterministic cusp catastrophe model. The methodology is empirically tested on almost 27 years of U.S. stock market evolution covering several important recessions and crisis periods. Due to the very long sample period we also develop a rolling estimation approach and we find that while in the first half of the period stock markets showed marks of bifurcations, in the second half catastrophe theory was not able to confirm this behavior. Results suggest that the proposed methodology provides an important shift in application of catastrophe theory to stock markets.

Date: 2013-02, Revised 2013-05
New Economics Papers: this item is included in nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/1302.7036 Latest version (application/pdf)

Related works:
Journal Article: Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility (2015)
Working Paper: Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility (2014)
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:arx:papers:1302.7036

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().