Using the high-frequency data of Shanghai Stock Exchange 180 index components, this paper provides insightful studies on the price clustering phenomena of Chinese stock markets. The last decimal points of transaction prices and quoting prices of the sample stocks are found to significantly cluster on digits 0, 5 and 8. The clustering frequency can be explained partly by some trading variables such as transaction price, return standard deviation, market capitalization and liquidity of the stocks. After controlling for variations of these variables, quotes farther away from the best queues display stronger clustering patterns and may carry less information.