IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxxviiy2024i3p1069-1082.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://ersj.eu/journal/3766/download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ndaïrou, Faïçal & Area, Iván & Nieto, Juan J. & Torres, Delfim F.M., 2020. "Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Đorđević, J. & Papić, I. & Šuvak, N., 2021. "A two diffusion stochastic model for the spread of the new corona virus SARS-CoV-2," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    2. Masum, Mohammad & Masud, M.A. & Adnan, Muhaiminul Islam & Shahriar, Hossain & Kim, Sangil, 2022. "Comparative study of a mathematical epidemic model, statistical modeling, and deep learning for COVID-19 forecasting and management," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    3. Basnarkov, Lasko, 2021. "SEAIR Epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    6. Mishra, A.M. & Purohit, S.D. & Owolabi, K.M. & Sharma, Y.D., 2020. "A nonlinear epidemiological model considering asymptotic and quarantine classes for SARS CoV-2 virus," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    7. Memon, Zaibunnisa & Qureshi, Sania & Memon, Bisharat Rasool, 2021. "Assessing the role of quarantine and isolation as control strategies for COVID-19 outbreak: A case study," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    8. Amaral, Marco A. & Oliveira, Marcelo M. de & Javarone, Marco A., 2021. "An epidemiological model with voluntary quarantine strategies governed by evolutionary game dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    9. Ullah, Mohammad Sharif & Higazy, M. & Kabir, K.M. Ariful, 2022. "Dynamic analysis of mean-field and fractional-order epidemic vaccination strategies by evolutionary game approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    10. Rafiq, Danish & Suhail, Suhail Ahmad & Bazaz, Mohammad Abid, 2020. "Evaluation and prediction of COVID-19 in India: A case study of worst hit states," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    11. Faïçal Ndaïrou & Iván Area & Delfim F. M. Torres, 2020. "Mathematical Modeling of Japanese Encephalitis under Aquatic Environmental Effects," Mathematics, MDPI, vol. 8(11), pages 1-14, October.
    12. Swapnarekha, H. & Behera, Himansu Sekhar & Nayak, Janmenjoy & Naik, Bighnaraj, 2020. "Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    13. Li, Tingting & Guo, Youming, 2022. "Optimal control and cost-effectiveness analysis of a new COVID-19 model for Omicron strain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    14. Florian Dorn & Sahamoddin Khailaie & Marc Stoeckli & Sebastian C. Binder & Tanmay Mitra & Berit Lange & Stefan Lautenbacher & Andreas Peichl & Patrizio Vanella & Timo Wollmershäuser & Clemens Fuest & , 2023. "The common interests of health protection and the economy: evidence from scenario calculations of COVID-19 containment policies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(1), pages 67-74, February.
    15. Aldila, Dipo & Khoshnaw, Sarbaz H.A. & Safitri, Egi & Anwar, Yusril Rais & Bakry, Aanisah R.Q. & Samiadji, Brenda M. & Anugerah, Demas A. & GH, M. Farhan Alfarizi & Ayulani, Indri D. & Salim, Sheryl N, 2020. "A mathematical study on the spread of COVID-19 considering social distancing and rapid assessment: The case of Jakarta, Indonesia," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    16. Simón A. Rella & Yuliya A. Kulikova & Emmanouil T. Dermitzakis & Fyodor A. Kondrashov, 2021. "Rates of SARS-COV-2 transmission and vaccination impact the fate of vaccine-resistant strains," Working Papers 2129, Banco de España.
    17. Rabih Ghostine & Mohamad Gharamti & Sally Hassrouny & Ibrahim Hoteit, 2021. "Mathematical Modeling of Immune Responses against SARS-CoV-2 Using an Ensemble Kalman Filter," Mathematics, MDPI, vol. 9(19), pages 1-13, September.
    18. Koutsellis, Themistoklis & Nikas, Alexandros, 2020. "A predictive model and country risk assessment for COVID-19: An application of the Limited Failure Population concept," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    19. Ahumada, M. & Ledesma-Araujo, A. & Gordillo, L. & Marín, J.F., 2023. "Mutation and SARS-CoV-2 strain competition under vaccination in a modified SIR model," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    20. Usama H. Issa & Ashraf Balabel & Mohammed Abdelhakeem & Medhat M. A. Osman, 2021. "Developing a Risk Model for Assessment and Control of the Spread of COVID-19," Risks, MDPI, vol. 9(2), pages 1-15, February.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ers:journl:v:xxvii:y:2024:i:3:p:1069-1082. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.