论文标题
基于信息理论的市场效率的统计检验
A statistical test of market efficiency based on information theory
论文作者
论文摘要
我们通过使用信息理论的广泛工具（即香农熵）来确定在给定时间尺度上的时间序列回报中包含的信息量，该信息应用于该时间序列的符号表示。通过在有效的市场假设成立的情况下，通过得出该市场信息指标的确切和渐近分布，我们将对市场效率进行统计检验。我们将其应用于股票指数，单股票和加密货币的真实数据集，为此，我们能够在每个日期确定是否应拒绝有效的市场假设，并就给定的置信度拒绝。
We determine the amount of information contained in a time series of price returns at a given time scale, by using a widespread tool of the information theory, namely the Shannon entropy, applied to a symbolic representation of this time series. By deriving the exact and the asymptotic distribution of this market information indicator in the case where the efficient market hypothesis holds, we develop a statistical test of market efficiency. We apply it to a real dataset of stock indices, single stock, and cryptocurrency, for which we are able to determine at each date whether the efficient market hypothesis is to be rejected, with respect to a given confidence level.
