The　measurement　of　liquidity　is　the　basis　of　research　in　market　microstructure　studies.　Based　on　the　intraday　tick　trading　data　on　Chinese　stock　markets　from　2009　to　2016,　we　run　horseraces　of　monthly　estimates　of　newly　and　widely　employed　low-frequency　liquidity　proxies　in　the　literature　against　three　types　of　bid-ask　spread　high-frequency　benchmarks.　The　empirical　results　reveal　that　the　closing　percent　quoted　spread　estimator　has　the　smallest　estimation　error,　and　the　FHT　estimator　has　the　highest　correlation.　Moreover,　these　two　estimators　win　the　majority　of　horseraces　in　terms　of　estimation　error　and　correlation　comparison　with　the　high-frequency　benchmarks.　Meanwhile,　we　find　that　most　liquidity　estimators　based　on　Roll＇s　model　do　not　perform　well.　Because　the　performance　metrics　of　estimation　precision　or　correlation　performance　on　related　liquidity　issues　differ　depending　on　the　type　of　research,　our　study　offers　appropriate　liquidity　measures　for　different　research　purposes.