Liquidity and realized volatility prediction in Chinese stock market: A time-varying transitional dynamic perspective

Abstract

Basing on the features of emerging Chinese stock market, this article discusses whether sharply deteriorating liquidity propels the stock market into a “crisis” state and investigates the dynamic impacts of the market liquidity on volatility forecasting. We construct the Markov-switching (MS) liquidity-adjusted HAR models with liquidity from the perspective of time-varying transition probabilities (TVTP). Empirical evidence suggests that a sharp deterioration in liquidity increases the probability of a “crisis” state for China's stock market. Out-of-sample forecasting results demonstrate that our proposed TVTP-MS-HAR-CJ-LIQ model, combining TVTP and MS-HAR-CJ with liquidity, substantially improves the predictive performance. Considering liquidity's impact from the TVTP perspective is suggested for the emerging but attention-attracting Chinese stock market.