Nonlinear transmission mechanisms of liquidity shocks and return predictability

Abstract

Changes in stock market liquidity affect transaction costs, price discovery, and risk premium adjustment. When volatility rises or trading depth declines, liquidity deterioration can amplify future return fluctuations through concentrated selling pressure, order book contraction, and investor rebalancing. Focusing on the relationship between liquidity shocks and return predictability, daily public trading data of Shanghai and Shenzhen A share listed companies from 2014 to 2024 are used to construct the Amihud illiquidity measure. Abnormal liquidity shocks are identified through residuals from a rolling AR(1) model. Based on this measurement, two way fixed effects models, threshold regressions, and quantile regressions are applied to examine transmission differences across market states and return distribution regions. The results show that negative liquidity shocks significantly suppress future excess returns. This effect is stronger in high volatility states, small capitalization stocks, and low return quantiles. Nonlinear models also show lower forecast errors and higher directional accuracy under stressed market conditions. These findings indicate that the predictive value of liquidity shocks is mainly concentrated in downside markets and tail risk regions. The evidence provides practical implications for risk warning, asset pricing, and portfolio adjustment.