Scaling analysis of price by multi-scale Shannon entropy

Mohammad Osoolian, Mohammad Esmaeeil Fadaeinejad, Mobina Bagheri and Jamshid Ardalankia
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Mohammad Osoolian: Department of Finance, Shahid Beheshti University, G. C. Evin, Tehran 19839, Iran
Mohammad Esmaeeil Fadaeinejad: Department of Finance, Shahid Beheshti University, G. C. Evin, Tehran 19839, Iran
Mobina Bagheri: Department of Finance, Shahid Beheshti University, G. C. Evin, Tehran 19839, Iran
Jamshid Ardalankia: ��Department of Economics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0316, USA

International Journal of Modern Physics C (IJMPC), 2023, vol. 34, issue 03, 1-17

Abstract: Multi-scale behaviors emerge in financial markets as complex systems. In this study, we intended to employ multi-scale Shannon entropy to trace the information transition of these phenomena, at different levels of Tehran stock market index (TEDPIX). The obtained results show that, in various magnitude scales and time scales, entropy Granger-causes TEDPIX index in terms of linear and nonlinear aspects. The results revealed that Granger causalities exist between entropy and TEDPIX. The causalities were linear in monthly (noise), quarterly (noise), semi-yearly (noise) and yearly (useful information) time spans; on the other hand, in quarterly (useful information) time span, the causalities were nonlinear. In this regard, one can conclude that entropy would be able to predict the market’s behavior.

Keywords: Multi-scale behavior; financial markets; price prediction (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0129183123500389

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