Realtime estimation of the degree of market efficiency using variable weighted Sample Entropy

Recently, the complex features of financial time series have been studied using a variety of methods developed in econophysics. These analyses of extensive financial data have empirically pointed to the breakdown of the efficient market hypothesis (EMI), in particular the weak-form of EMI. Sample entropy (SampEn) can be used to quantify the randomness in the time series. In the financial time series analysis, the SampEn can quantify the degree of market efficiency. In this paper, we investigated the degree of market efficiency of the US market and Asian market around the epoch of Black Monday and Asian Currency Crisis respectively by using variable weighted SampEn algorithm.