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Comparative Analysis of Turkish and German Stock-Markets as a Hedge Product Against Inflation by Using Machine Learning Algorithms

Author

Listed:
  • Ibrahim Dikmen

    (Istanbul Technical University)

  • Kaya Tokmakcioglu

    (Istanbul Technical University)

Abstract

Stock markets are places where investors meet the companies who seek capital to expand their business. One of the aims of investors is to hedge their capital against inflation and valuation of reserve currency, US Dollar. In this study, we apply various machine learning algorithms to predict hedge-ability of Turkiye’s and Germany’s stock markets. For this purpose, the automotive industry became subject for both countries. The outcomes of the study indicate machine learning algorithms are promising for prediction. However, they lack consistency and precision. Yet, it is possible to distinguish certain algorithms and try to improve performances with additional inputs, parameter tuning and more data. The algorithms should be combined with other methods for better results. It might also be beneficial if the study is supported by the views of sector experts.

Suggested Citation

  • Ibrahim Dikmen & Kaya Tokmakcioglu, 2025. "Comparative Analysis of Turkish and German Stock-Markets as a Hedge Product Against Inflation by Using Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 66(3), pages 2593-2618, September.
    • Handle: RePEc:kap:compec:v:66:y:2025:i:3:d:10.1007_s10614-024-10810-2
    DOI: 10.1007/s10614-024-10810-2
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    References listed on IDEAS

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    6. Collin Chikwira & Jahed Iqbal Mohammed, 2023. "The Impact of the Stock Market on Liquidity and Economic Growth: Evidence of Volatile Market," Economies, MDPI, vol. 11(6), pages 1-19, May.
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