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Application of Technical Analysis Stochastic Oscillator for Early Detection of Epidemiological Changes Based on Covid-19 Data in Poland

Author

Listed:
  • A. Szepeluk
  • D. Tomczyszyn
  • A. Cyburt

Abstract

Purpose: The aim of the research was to test the possibility of using a type of technical analysis indicator – the stochastic oscillator – to predict the progression of an epidemic based on the Polish COVID-19 epidemic data. Design/Methodology/Approach: Data on active COVID-19 cases in Poland in 2020/22 were used as a research material. The stochastic oscillator was used to determine turning points in the prediction of epidemiological changes. Findings: It was demonstrated that the best performance is achieved with the slow, smoothed version of the oscillator and the following parameters: %K14 and %D7. Despite a few erroneously generated changes in the incidence trend, most signals were verified correctly. Practical Implications: The stochastic oscillator, most commonly used in finance to predict market trends, may also find application in research related to predicting disease progression. Originality/Value: Studies such as those in this article, based on epidemiological data, have not been conducted before.

Suggested Citation

  • A. Szepeluk & D. Tomczyszyn & A. Cyburt, 2024. "Application of Technical Analysis Stochastic Oscillator for Early Detection of Epidemiological Changes Based on Covid-19 Data in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 1069-1082.
    • Handle: RePEc:ers:journl:v:xxvii:y:2024:i:3:p:1069-1082
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    References listed on IDEAS

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    2. Adak, Debadatta & Majumder, Abhijit & Bairagi, Nandadulal, 2021. "Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
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    More about this item

    Keywords

    Simulation Methods; Simulation Modeling; Public Health.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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