Market Value and Stock Liquidity Risk Premium: Break-adjustment under Long Memory Data Characteristics

Abstract

The reform of non-tradable shares caused the break of liquidity in China stock, which made the measures of illiquidity biased. We use real-time adjustment method and stochastic detrending approach to smooth the index and compare the predictive ability of raw measures and break-adjustment measures. Besides, the relationship between stock illiquidity and future excess return in different market value groups is studied. Monte Carlo simulation and ARFIMA model are used to evaluate the regression bias caused by long memory and contemporaneous correlation between shocks, and bootstrap method is used to adjust the slope. The results show that liquidity shock has a relatively large impact on the future excess returns of stocks in the low-market group. The stock returns of low-market companies are more sensitive to liquidity shocks, which indicates the important role of illiquidity indexes in liquidity risk pricing.