Limit-hitting exciting effects: Modeling jump dependencies in stock markets adhering to daily price-limit rules

Abstract

Price limits are widely implemented in stock markets worldwide; however, they are rarely considered in financial models. In this study, we propose a model specifically designed for asset prices that adhere to daily price-limit mechanisms. Our model captures the interdependence among limit-hitting events and other small price jumps by using a multivariate mutually-exciting point process. It is applicable to any stock market with a multi-layer price limit mechanism. By analyzing data from all publicly listed A-share stocks in China from 2007 to 2021, we demonstrate that our model outperforms other classic models in terms of goodness of fit. Additionally, we find that limit-hitting jumps, as opposed to inconspicuous small price jumps, have a higher propensity to attract investors' attention and result in subsequent price jumps. We further construct a clustering index based on the model parameters and investigate its determinants.