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Weighted multiscale cumulative residual Rényi permutation entropy of financial time series

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  • Zhou, Qin
  • Shang, Pengjian

Abstract

In this paper, based on cumulative residual entropy (CRE) and Rényi permutation entropy (RPE), multiscale cumulative residual Rényi permutation entropy (MCRRRPE) and weighted multiscale cumulative residual Rényi permutation entropy (WMCRRPE) are proposed as novelty measures to quantify the uncertainty of the nonlinear time series. First, the MCRRPE and WMCRRPE methods are performed on the synthetic data, and the impact of the changes to parameters is discussed. Then, the MCRRPE and WMCRRPE methods are applied to the closing prices of the US, European and Chinese stock markets. We analyze the statistics and draw some conclusions from the comparison: the stock markets can be divided into four categories: (1) NASDAQ and FTSE100, (2) S&P500, DJI and HSI, (3) DAX30 and CAC40 and (4) SSE and SZSE. The standard deviation has a certain relationship with WMCRRPE. Compared with the MCRRPE method, the WMCRRPE method can distinguish these financial stock markets effectively and better estimate the complexity of the time series containing amplitude information.

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  • Zhou, Qin & Shang, Pengjian, 2020. "Weighted multiscale cumulative residual Rényi permutation entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    • Handle: RePEc:eee:phsmap:v:540:y:2020:i:c:s037843711931742x
    DOI: 10.1016/j.physa.2019.123089
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    Cited by:

    1. Lahmiri, Salim & Bekiros, Stelios, 2020. "Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Będowska-Sójka, Barbara & Kliber, Agata, 2021. "Information content of liquidity and volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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