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Intelligent finance—an emerging direction

Author

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  • Heping Pan
  • Didier Sornette
  • Kenneth Kortanek

Abstract

Intelligent finance represents a new direction recently emerging from the confluence of several distinct disciplines in financial market analysis, investing and trading, removing any historical or artificial barrier between them. It is conceived as the science, technology and art of the comprehensive, predictive, dynamic and strategic analysis of global financial markets, towards a unification and integration of academic finance and professional finance. As a comprehensive approach, it is a quest for absolute positive and non-trivial returns in investing and trading by exploiting complete information about financial markets from all general perspectives, drawing ideas, theories, models and techniques from many related academic disciplines, such as macroeconomics, microeconomics, academic finance, financial mathematics, econophysics, behavioural finance and computational finance, and from professional schools of thought, such as macrowave investing, trend following, fundamental analysis, technical analysis, mind analysis, active speculation, etc. In terms of risk management, intelligent finance is expected to minimize the very last risk—the incompleteness of an investing or trading method or system. The theoretical framework of intelligent finance consists of four major components: financial information fusion, multilevel stochastic dynamic process models, active portfolio and total risk management, and financial strategic analysis. We first provide the background from which intelligent finance has recently emerged as a new direction in finance research and industry, and then provide a brief theoretical review of the predictability of financial markets since Bachelier. After these background discussions, we clarify the major research directions of intelligent finance.

Suggested Citation

  • Heping Pan & Didier Sornette & Kenneth Kortanek, 2006. "Intelligent finance—an emerging direction," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 273-277.
    • Handle: RePEc:taf:quantf:v:6:y:2006:i:4:p:273-277
    DOI: 10.1080/14697680600760753
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    Citations

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    Cited by:

    1. L. D. Zubkova & S. M. D’yachkov, 2018. "Industry Investment Analysis of Activities of Russian Telecommunications Companies," Studies on Russian Economic Development, Springer, vol. 29(2), pages 182-190, March.
    2. John Fry, 2014. "Bubbles, shocks and elementary technical trading strategies," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(1), pages 1-13, January.
    3. Gabriela Prelipcean & Mircea Boscoianu, 2020. "Risk Analysis of a Hedge Fund Oriented on Sustainable and Responsible Investments for Emerging Markets," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 653-653, August.
    4. Ahmet Duran & Michael Bommarito, 2011. "A profitable trading and risk management strategy despite transaction costs," Quantitative Finance, Taylor & Francis Journals, vol. 11(6), pages 829-848.
    5. Haochen Guo & Petr Polak, 2023. "Intelligent finance and change management implications," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    6. Frank J. Fabozzi & Sergio Focardi & Caroline Jonas, 2007. "Trends in quantitative equity management: survey results," Quantitative Finance, Taylor & Francis Journals, vol. 7(2), pages 115-122.

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