Classification of flash crashes using the Hawkes(p,q) framework

Wehrli, Alexander1,5; Sornette, Didier1,2,3,4

2021-09-01

10.1080/14697688.2021.1941212

QUANTITATIVE FINANCE   影响因子和分区

1469-7688

1469-7696

We introduce a novel modeling framework-the Hawkes(p, q) process-which allows us to parsimoniously disentangle and quantify the time-varying share of high frequency financial price changes that are due to endogenous feedback processes and not exogenous impulses. We show how both flexible exogenous arrival intensities, as well as a time-dependent feedback parameter can be estimated in a structural manner using an Expectation Maximization algorithm. We use this approach to investigate potential characteristic signatures of anomalous market regimes in the vicinity of 'flash crashes'-events where prices exhibit highly irregular and cascading dynamics. Our study covers some of the most liquid electronic financial markets, in particular equity and bond futures, foreign exchange and cryptocurrencies. Systematically balancing the degrees of freedom of both exogenously driving processes and endogenous feedback variation using information criteria, we show that the dynamics around such events are not universal, highlighting the usefulness of our approach: (i) post-mortem, for developing remedies and better future processes-e.g. improving circuit breakers or latency floor designs-and potentially (ii) ex-ante, for short-term forecasts in the case of endogenously driven events. Finally, we test our proposed model against a process with refined treatment of exogenous clustering dynamics in the spirit of the recently proposed autoregressive moving-average (ARMA) point process.

Flash crash Hawkes process ARMA point process High frequency financial data Market microstructure EM algorithm Time-varying parameters

SCI ; SSCI

英语

其他

Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences

Business, Finance ; Economics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods

WOS:000696443500001

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD

ECONOMICS BUSINESS

Web of Science

1.Swiss Fed Inst Technol, Dept Management Technol & Econ, Zurich, Switzerland
2.Univ Geneva, Swiss Finance Inst, 40 Blvd Pont dArve, CH-1211 Geneva 4, Switzerland
3.Inst Innovat Res, Tokyo Inst Technol, Tokyo Tech World Res Hub Initiat, Tokyo, Japan
4.Southern Univ Sci & Technol SUSTech, Inst Risk Anal Predict & Management RisksX, Acad Adv Interdisciplinary Studies, Shenzhen 518055, Peoples R China
5.Swiss Natl Bank, Boersenstr 15, CH-8001 Zurich, Switzerland

Wehrli, Alexander,Sornette, Didier. Classification of flash crashes using the Hawkes(p,q) framework[J]. QUANTITATIVE FINANCE,2021.

Wehrli, Alexander,&Sornette, Didier.(2021).Classification of flash crashes using the Hawkes(p,q) framework.QUANTITATIVE FINANCE.

Wehrli, Alexander,et al."Classification of flash crashes using the Hawkes(p,q) framework".QUANTITATIVE FINANCE (2021).