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Investment Index Construction from Information Propagation Based on Transfer Entropy

Author

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  • Fujio Toriumi

    (The University of Tokyo)

  • Kazuki Komura

    (The University of Tokyo)

Abstract

In recent years, the number of individual investors continues to increase in financial markets. However, the large information gap between individual and institutional investors unduly impairs individual investors, which may negatively influence the market. In this study, we propose a new investment index that focuses on the relationships among stocks to help manage the risk of individual investors. The relationships among stocks have often been analyzed by a cross-correlation matrix method. However, such methods are strongly influenced by irregular events, including drawdowns. Therefore, we employed a transfer entropy method to analyze the relationships among stocks. Transfer entropy is a sequence analysis method proposed by Schreiber that is robust for irregular events. First, we applied the partial correlation and transfer entropy methods to test the data and confirm robustness for unexpected events. Next, we generated stock-networks by transfer entropy that represents the relationships among stocks. Finally, we proposed an investment index that is calculated from stock-networks which are generated from transfer entropy. We compared the proposed investment index with long positions and obtained higher performance investment by our proposed method than with a long position.

Suggested Citation

  • Fujio Toriumi & Kazuki Komura, 2018. "Investment Index Construction from Information Propagation Based on Transfer Entropy," Computational Economics, Springer;Society for Computational Economics, vol. 51(1), pages 159-172, January.
    • Handle: RePEc:kap:compec:v:51:y:2018:i:1:d:10.1007_s10614-016-9618-8
    DOI: 10.1007/s10614-016-9618-8
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    References listed on IDEAS

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    1. Okyu Kwon & Jae-Suk Yang, 2008. "Information flow between stock indices," Papers 0802.1747, arXiv.org.
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    Cited by:

    1. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    2. Xie, Wen-Jie & Yong, Yang & Wei, Na & Yue, Peng & Zhou, Wei-Xing, 2021. "Identifying states of global financial market based on information flow network motifs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

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