Dynamic network and own effects on abnormal returns: evidence from China's stock market.

This paper addresses the question of how to model the process of abnormal returns on individual stocks. It postulates a framework, where abnormal returns are generated by a process which features two autoregressive components, one stock-specific and one related to network effects. This process deviates from customary ones in that the parameters are specific to each stock/firm, that the autoregressive process is explicitly modelled instead of using cumulative abnormal returns over a pre-specified window, and that network effects are present. Abandoning either one of those deviations is rejected by data on Chinese stocks in 2018 and 2019, an episode which is significant for an abnormal stock-market returns analysis, as it was characterized by numerous tariff-setting events related to the "trade war" between the USA and China.