Using the data of Chinese listed firms from 2003-2020, this study applies a System GMM estimation approach to document that high local government ecological concerns increase a firm’s stock price crash risk. This finding remains consistent after addressing endogeneity issues and undergoing robustness checks. This study also reveals that the implementation of the new environmental protection law in 2015 mitigates the relationship between local government ecological concerns and stock price crash risk. Further analyses indicate that stricter environmental regulation and high subsidies, as well as enhanced corporate social responsibility and governance, can effectively alleviate the adverse effect of local government ecological concerns on stock price crash risk. In addition, we note that the influence of local government ecological concerns on stock price crash risk is more significant in the eastern region, heavily polluting industries, and non-SOEs. Lastly, the research identifies two potential channels through which local government ecological concerns can impact stock price crash risk by reducing the quality of information disclosure and intensifying investor disagreement.

This paper contributes to the development of recent literature on the explanation power and calibration issue of heterogeneous asset pricing models by presenting a simple stochastic market fraction asset pricing model of two types of traders (fundamentalists and trend followers) under a market maker scenario. Statistical analysis based on Monte Carlo simulations shows that the long-run behaviour and convergence of the market prices, long (short)-run profitability of the fundamental (trend following) trading strategy, survivability of chartists, and various under and over-reaction autocorrelation patterns of returns can be characterized by the stability and bifurcations of the underlying deterministic system. Our analysis underpins mechanism on various market behaviour (such as under/over-reactions), market dominance and stylized facts in high frequency financial markets.