Modeling market crashes by assuming similarities with earthquakes in occurrence behavior

I investigate similarities in the occurrences of earthquakes and financial market crashes, specifically their self-exciting behavior. This paper revolves around the Hawkes process, as it accounts for this behavior. Residual analysis of the maximum likelihood estimated model for an S&P 500 dataset shows the self-enforcing characteristic of financial market crashes, leading to the conclusion that financial market crashes follow a Hawkes process. Furthermore, I confirm that this model is suitable for the investigation of earthquake occurrences by estimating it for a dataset consisting of data about earth- quakes in the vicinity of Japan. Evaluation of simulated data series that are created using the estimated Hawkes process, is inconclusive in determining whether the data contains the characteristics of the original datasets because of an error in the simulation procedure.