Abstract
This study examines 8 liquidity measures estimated from low-frequency data, taking high-frequency price impact as benchmark and making use of the tick data and daily data of the component stock of SH180 from CCER. The result shows that: among these low-frequency liquidity measures, the correlation of Hui-Heubel liquidity ratio with the benchmark is the best, and that of Martin index and the effective liquidate speed follow. This result also tell us that, in order to reflecting price variation, the information of highest and lowest price dominates that of open and close price; reflecting trade size, the information of turnover-rate in shares or in money dominates that of trading volume, when we design low-frequency liquidity measures. All coefficients of correlation are not high enough, especially linear coefficients of correlation. This shows that the low-frequency measures can be improved in a large extent.
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