We propose a modeling framework which allows for creating probability predictions on a future market crash in the medium term, like sometime in the next five days. Our framework draws upon noticeable similarities between stock returns around a financial market crash and seismic activity around earthquakes. Our model is incorporated in an Early Warning System for future crash days. Testing our EWS on S&P 500 data during the recent financial crisis, we find positive Hanssen–Kuiper Skill Scores. Furthermore our modeling framework is capable of exploiting information in the returns series not captured by well known and commonly used volatility models. EWS based on our models outperform EWS based on the volatility models forecasting extreme price movements, while forecasting is much less time-consuming.

Additional Metadata
Keywords Financial crashes, Hawkes process, Self-exciting process, Early Warning System
JEL Estimation (jel C13), Simulation Methods; Monte Carlo Methods; Bootstrap Methods (jel C15), Forecasting and Other Model Applications (jel C53), Financial Forecasting (jel G17)
Persistent URL dx.doi.org/10.1016/j.jbankfin.2015.03.003, hdl.handle.net/1765/78172
Series ERIM Top-Core Articles , Econometric Institute Reprint Series
Journal Journal of Banking & Finance
Gresnigt, F, Kole, H.J.W.G, & Franses, Ph.H.B.F. (2015). Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes. Journal of Banking & Finance, 56, 123–139. doi:10.1016/j.jbankfin.2015.03.003