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Computational Global Macro:Game Theory, Machine Learning, and Causal Inference

Author

Listed:
  • Joseph Simonian

    (Autonomous Investment Technologies, USA)

Abstract

Computational Global Macro offers investors a new paradigm for the analysis of geopolitical risk. By drawing on game theory, machine learning, and causal inference, the book provides investors with a novel framework for analyzing the political and economic interactions between global actors. In doing so, it presents a counterpoint to the often informal and speculative approach to geopolitical analysis that is prevalent in the research produced by investment firms. The book will thus serve as a valuable reference for investment professionals, students, and academics seeking to apply sophisticated quantitative tools to the development of their macro views.

Suggested Citation

  • Joseph Simonian, 2025. "Computational Global Macro:Game Theory, Machine Learning, and Causal Inference," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 13860, August.
    • Handle: RePEc:wsi:wsbook:13860
    as

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    File URL: https://www.worldscientific.com/worldscibooks/10.1142/13860
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    More about this item

    Keywords

    Machine Learning; Game Theory; Causality; Investing; Portfolio Management; Global Macro; Geopolitics; Macroeconomics; Finance; Reinforcement Learning;
    All these keywords.

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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