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Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory

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  • Daniel Štifanić
  • Jelena Musulin
  • Adrijana Miočević
  • Sandi Baressi Šegota
  • Roman Šubić
  • Zlatan Car

Abstract

COVID-19 is an infectious disease that mostly affects the respiratory system. At the time of this research being performed, there were more than 1.4 million cases of COVID-19, and one of the biggest anxieties is not just our health, but our livelihoods, too. In this research, authors investigate the impact of COVID-19 on the global economy, more specifically, the impact of COVID-19 on the financial movement of Crude Oil price and three US stock indexes: DJI, S&P 500, and NASDAQ Composite. The proposed system for predicting commodity and stock prices integrates the stationary wavelet transform (SWT) and bidirectional long short-term memory (BDLSTM) networks. Firstly, SWT is used to decompose the data into approximation and detail coefficients. After decomposition, data of Crude Oil price and stock market indexes along with COVID-19 confirmed cases were used as input variables for future price movement forecasting. As a result, the proposed system BDLSTM + WT-ADA achieved satisfactory results in terms of five-day Crude Oil price forecast.

Suggested Citation

  • Daniel Štifanić & Jelena Musulin & Adrijana Miočević & Sandi Baressi Šegota & Roman Šubić & Zlatan Car, 2020. "Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory," Complexity, Hindawi, vol. 2020, pages 1-12, July.
    • Handle: RePEc:hin:complx:1846926
    DOI: 10.1155/2020/1846926
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    Cited by:

    1. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2022. "The COVID-19 pandemic, policy responses and stock markets in the G20," International Economics, Elsevier, vol. 172(C), pages 77-90.
    2. Caporale, Guglielmo Maria & Gil-Alana, Luis Alberiko & Poza, Carlos, 2022. "The COVID-19 pandemic and the degree of persistence of US stock prices and bond yields," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 118-123.
    3. María del Carmen Valls Martínez & Pedro Antonio Martín Cervantes, 2021. "Testing the Resilience of CSR Stocks during the COVID-19 Crisis: A Transcontinental Analysis," Mathematics, MDPI, vol. 9(5), pages 1-24, March.
    4. Jelena Musulin & Sandi Baressi Šegota & Daniel Štifanić & Ivan Lorencin & Nikola Anđelić & Tijana Šušteršič & Anđela Blagojević & Nenad Filipović & Tomislav Ćabov & Elitza Markova-Car, 2021. "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review," IJERPH, MDPI, vol. 18(8), pages 1-39, April.
    5. Xinyu Wang & Liang Zhao & Ning Zhang & Liu Feng & Haibo Lin, 2022. "Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network," Papers 2204.06692, arXiv.org.
    6. Si, Deng-Kui & Li, Xiao-Lin & Xu, XuChuan & Fang, Yi, 2021. "The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China," Energy Economics, Elsevier, vol. 102(C).
    7. Piotr Korneta & Katarzyna Rostek, 2021. "The Impact of the SARS-CoV-19 Pandemic on the Global Gross Domestic Product," IJERPH, MDPI, vol. 18(10), pages 1-12, May.
    8. Yang, Qu & Yu, Yuanyuan & Dai, Dongsheng & He, Qian & Lin, Yu, 2024. "Can hybrid model improve the forecasting performance of stock price index amid COVID-19? Contextual evidence from the MEEMD-LSTM-MLP approach," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    9. Anqiang Huang & Xinjun Liu & Changrui Rao & Yi Zhang & Yifan He, 2022. "A New Container Throughput Forecasting Paradigm under COVID-19," Sustainability, MDPI, vol. 14(5), pages 1-20, March.

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