本文基于信息熵理论，以股票价格涨跌为信源定义股票价格信息熵，并定义熵比值以避免股票价格趋势性对分析结果的影响。本文通过计算和分析2015年至2016年上证市场和深证市场的11只股票指数和3只个股收盘价分钟序列的信息熵和熵比值，探究中国股票市场资产价格的信息熵特征，从信息熵角度讨论股票市场有效性。本文的结果表明：（1）股票价格信息熵S(n)与符号片段长度n有显著线性关系，股票价格的熵比值随n的增加而递减；（2）（2）观测数据的时间尺度越小，价格的可预测性越强（3）大幅波动行情下，股票价格熵比值低，市场有效性低；（4）大规模市场的熵比值更高，市场有效性强于小规模市场；（5）个股的熵比值高于股票指数的熵比值。

Based on Shannon’s entropy theory, this paper defined stock price entropy taking gain/loss as information source, and then defined entropy ratio to avoid the impact of stock price trend on analysis. Using closing price per minute of 11 stock indexes and 3 stocks in Shanghai Stock Exchange and Shenzhen Stock Exchange to calculate entropy ratio, this paper researched the entropy characteristics of asset price on stock market in China, and discussed stock market efficiency from the aspect of entropy. The result shows that: (1) there is a significant linear relationship between stock price entropy and length of symbol fragment, and a negative correlation between entropy ratio and length of symbol fragment; (2) stock price is easier to be predicted with smaller time scale (3) when market fluctuates strongly, the entropy ratio and stock market efficiency tends to be lower; (4) entropy ratio and stock market effectiveness are better in large-scale market; (5) entropy ratio of single stock is higher than that of stock index.