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Fractional cumulative residual Kullback-Leibler information based on Tsallis entropy

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  • Mao, Xuegeng
  • Shang, Pengjian
  • Wang, Jianing
  • Yin, Yi

Abstract

The cumulative residual Kullback-Leibler information was recently proposed as a suitable generalization of Kullback-Leibler information to the survival function. In this paper, we extend the traditional cumulative residual Kullback-Leibler information to fractional orders by combining it with Tsallis entropy, called fractional CRKL. Some properties of the proposed measure are studied and proved. It can be estimated by generalized Fisher information. In addition, we also define discrete fractional CRKL for calculation. Some distributions are enumerated to verify the validity of the new measure. Finally, it is applied to financial time series to detect the dissimilarities between different stock indices and to identify the significant events in specific periods.

Suggested Citation

  • Mao, Xuegeng & Shang, Pengjian & Wang, Jianing & Yin, Yi, 2020. "Fractional cumulative residual Kullback-Leibler information based on Tsallis entropy," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920306883
    DOI: 10.1016/j.chaos.2020.110292
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    References listed on IDEAS

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