Abstract
This a summary to introduce the composite multiscale entropy analysis and the multivariate multiscale entropy analysis as two new attempts to measure the overall complexity of the stock market, and the results will also be new input dimensions to measure financial risk. According to the combined results of the ensemble empirical mode decomposition and the composite multiscale entropy analysis the investment risk in the Chinese stock market may be relatively low, possibly because of the Chinese government’s supervision of the stock market. And the multivariate multiscale sample entropy is improved to quantify the complexity of multi-channel data over different time scales. Due to the expanded application of this method in the financial field, the complexity of the four ternary return sequences generated by each stock trading time in the Chinese stock market was quantified for the first time. We find that as the stock trading time increases, the complexity of the three-variable return series per hour shows a significant downward trend. As another new attempt, the complexity of the global stock market (Asia, Europe and the United States) is quantified by analyzing the multiple returns of the global stock market.
Published Version
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