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Detecting market pattern changes: A machine learning approach

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  • Mustafa, Andy Ali
  • Lin, Ching-Yang
  • Kakinaka, Makoto

Abstract

We train an artificial neural network (ANN) model to recognize the pattern of the financial market and use this model to detect whether and when the market pattern has changed. Over 2000–2021, we find that the market has experienced five significant changes. The timings of these changes coincide with critical historical events (e.g. Great Recession and COVID-19) and changes in the monetary policy regime.

Suggested Citation

  • Mustafa, Andy Ali & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Detecting market pattern changes: A machine learning approach," Finance Research Letters, Elsevier, vol. 47(PA).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321005572
    DOI: 10.1016/j.frl.2021.102621
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    References listed on IDEAS

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    2. Oliveira, Alexandre Silva de & Ceretta, Paulo Sergio & Albrecht, Peter, 2023. "Performance comparison of multifractal techniques and artificial neural networks in the construction of investment portfolios," Finance Research Letters, Elsevier, vol. 55(PA).
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    4. Kristian Gundersen & Timothée Bacri & Jan Bulla & Sondre Hølleland & Antonello Maruotti & Bård Støve, 2024. "Testing for time‐varying nonlinear dependence structures: Regime‐switching and local Gaussian correlation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(3), pages 1012-1060, September.

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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other

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