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Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities

Author

Listed:
  • Jules Sadefo-Kamdem

    (MRE - Montpellier Recherche en Economie - UM - Université de Montpellier)

  • Rose Bandolo Essomba

    (African Institute for Mathematical Sciences (AIMS-Cameroon))

  • James Njong Berinyuy

    (African Institute for Mathematical Sciences (AIMS-Cameroon))

Abstract

Over the past few years, the application of deep learning models to finance has received much attention from investors and researchers. Our work continues this trend, presenting an application of a Deep learning model, long-term short-term memory (LSTM), for the forecasting of commodity prices. The obtained results predict with great accuracy the prices of commodities including crude oil price (98.2 price(88.2 on the variability of the commodity prices. This involved checking at the correlation and the causality with the Ganger Causality method. Our results reveal that the coronavirus impacts the recent variability of commodity prices through the number of confirmed cases and the total number of deaths. We then investigate a hybrid ARIMA-Wavelet model to forecast the coronavirus spread. This analyses is interesting as a consequence of the strong causal relationship between the coronavirus(number of confirmed cases) and the commodity prices, the prediction of the evolution of COVID-19 can be useful to anticipate the future direction of the commodity prices.

Suggested Citation

  • Jules Sadefo-Kamdem & Rose Bandolo Essomba & James Njong Berinyuy, 2020. "Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities," Post-Print hal-02921304, HAL.
    • Handle: RePEc:hal:journl:hal-02921304
    DOI: 10.1016/j.chaos.2020.110215
    Note: View the original document on HAL open archive server: https://hal.umontpellier.fr/hal-02921304
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    Cited by:

    1. Capitani, Daniel Henrique Dario & Gaio, Luiz Eduardo, 2023. "Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 11(2), April.
    2. Hong Shen & Qi Pan & Lili Zhao & Pin Ng, 2022. "Risk Contagion between Global Commodities from the Perspective of Volatility Spillover," Energies, MDPI, vol. 15(7), pages 1-21, March.
    3. Pavel Kotyza & Katarzyna Czech & Michał Wielechowski & Luboš Smutka & Petr Procházka, 2021. "Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?," Agriculture, MDPI, vol. 11(2), pages 1-16, January.
    4. Ran Lu & Hongjun Zeng, 2022. "VIX and major agricultural future markets: dynamic linkage and time-frequency relations around the COVID-19 outbreak," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 40(2), pages 334-353, September.
    5. Cao, Yan & Cheng, Sheng, 2021. "Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices," Resources Policy, Elsevier, vol. 74(C).
    6. Frédy Pokou & Jules Sadefo Kamdem & François Benhmad, 2024. "Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1349-1399, April.
    7. Francesco Piccialli & Vincenzo Schiano Cola & Fabio Giampaolo & Salvatore Cuomo, 2021. "The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 23(6), pages 1467-1497, December.
    8. Dorota Zebrowska-Suchodolska & Andrzej Karpio & Krzysztof Kompa, 2021. "COVID-19 Pandemic: Stock Markets Situation in European Ex-Communist Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 1106-1128.
    9. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    10. 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.
    11. Yishun Liu & Chunhua Yang & Keke Huang & Weiping Liu, 2023. "A Multi-Factor Selection and Fusion Method through the CNN-LSTM Network for Dynamic Price Forecasting," Mathematics, MDPI, vol. 11(5), pages 1-20, February.
    12. Juan Antonio Galán-Gutiérrez & Rodrigo Martín-García, 2022. "Fundamentals vs. Financialization during Extreme Events: From Backwardation to Contango, a Copper Market Analysis during the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(4), pages 1-23, February.
    13. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    14. Iuga, Iulia Cristina & Mudakkar, Syeda Rabab & Dragolea, Larisa Loredana, 2024. "Agricultural commodities market reaction to COVID-19," Research in International Business and Finance, Elsevier, vol. 69(C).
    15. Daniel Stefan Armeanu & Stefan Cristian Gherghina & Jean Vasile Andrei & Camelia Catalina Joldes, 2023. "Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets," Energy & Environment, , vol. 34(5), pages 1433-1470, August.
    16. Hachmi Ben Ameur & Sahbi Boubaker & Zied Ftiti & Wael Louhichi & Kais Tissaoui, 2024. "Forecasting commodity prices: empirical evidence using deep learning tools," Annals of Operations Research, Springer, vol. 339(1), pages 349-367, August.
    17. Jin, Lifu & Zheng, Bo & Ma, Jiahao & Zhang, Jiu & Xiong, Long & Jiang, Xiongfei & Li, Jiangcheng, 2022. "Empirical study and model simulation of global stock market dynamics during COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    18. Maghyereh, Aktham & Abdoh, Hussein & Awartani, Basel, 2022. "Have returns and volatilities for financial assets responded to implied volatility during the COVID-19 pandemic?," Journal of Commodity Markets, Elsevier, vol. 26(C).

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