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Realized volatility prediction of the US Commodity futures during the Global Financial Crisis (GFC) and COVID-19 pandemic

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Warianty tytułu
PL
Prognoza zrealizowanej zmienności kontraktów terminowych na towary w USA podczas globalnego kryzysu finansowego (GFC) I pandemii COVID-19
Języki publikacji
EN
Abstrakty
EN
This research aims to inspect the predictability of the realized volatility (RV) of the US Commodity futures market during the economic crisis period for the last 20 years. The economic crisis period includes the Global Financial Crisis (GFC) and the financial crisis during COVID-19. This study extends its aim to show the forecasting comparison during the financial crisis period and the normal economic period. A standard predictive regression model from the weekly RV data is used to test the certainty of next week’s RV of the commodity futures. This study uses data from Q1 of 2000 to Q3 of 2020. It finds that platinum, palladium, gold, and crude oil have significant predictability for the RV forecast during the global financial crisis, whereas sugar, silver, and platinum have high and significant predictability to forecast the RV during the pandemic. In addition, a comparison of RV predictability between normal economic periods and economic crisis periods shows a significant difference in predictability between different economic periods.
PL
Niniejsze badanie ma na celu zbadanie przewidywalności zrealizowanej zmienności (RV) na amerykańskim rynku kontraktów terminowych na towary w okresie kryzysu gospodarczego w ciągu ostatnich 20 lat. Okres kryzysu gospodarczego obejmuje globalny kryzys finansowy (GFC) i kryzys finansowy podczas COVID-19. Niniejsze badanie rozszerza swój cel, aby pokazać porównanie prognoz w okresie kryzysu finansowego i normalnego okresu gospodarczego. Standardowy model regresji predykcyjnej z tygodniowych danych RV jest wykorzystywany do testowania pewności przyszłotygodniowej RV kontraktów terminowych na towary. W badaniu wykorzystano dane z okresu od 1. kwartału 2000 r. do 3. kwartału 2020 r. Stwierdzono, że platyna, pallad, złoto i ropa naftowa mają znaczną przewidywalność prognozy RV podczas globalnego kryzysu finansowego, podczas gdy cukier, srebro i platyna mają wysoką i znaczącą przewidywalność w prognozowaniu RV podczas pandemii. Ponadto porównanie przewidywalności RV między normalnymi okresami gospodarczymi a okresami kryzysu gospodarczego pokazuje znaczną różnicę w przewidywalności między różnymi okresami gospodarczymi.
Rocznik
Strony
260--277
Opis fizyczny
Bibliogr. 66 poz., rys., tab.
Twórcy
autor
  • John von Neumann University, Kecskemét, Hungary
  • College of Business and Economics, University of Johannesburg, Johannesburg 2006, South Africa
autor
  • Department of Economics, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
autor
  • Department of Finance and Banking, Begum Rokeya University, Rangpur 5400, Bangladesh
Bibliografia
  • 1. Adämmer, P., Schüssler, R. A., (2020). Forecasting the Equity Premium: Mind the News! Review of Finance, 24(2).
  • 2. Aït-Youcef, C., (2019). How index investment impacts commodities: A story about the financialization of agricultural commodities. Economic Modelling, 80(February), 23-33.
  • 3. Andersen, T. G., Bollerslev, T., Diebold, F. X. and Ebens, H., (2001). The distribution of realized stock return volatility. Journal of Financial Economics, 61(1).
  • 4. Azar, S. A., Chopurian, N. A., (2018). Commodity indexes and the stock markets of the GCC countries. Arab Economic and Business Journal, 13(2), 134-142.
  • 5. Bakas, D., Triantafyllou, A., (2018). The impact of uncertainty shocks on the volatility of commodity prices. Journal of International Money and Finance, 87, 96-111.
  • 6. Bakas, D., Triantafyllou, A., (2020). Commodity price volatility and the economic uncertainty of pandemics. Economics Letters, 193, 109283.
  • 7. Blot, C., Creel, J., Hubert, P., Labondance, F. and Saraceno, F., (2015). Assessing the link between price and financial stability. Journal of Financial Stability, 16, 71-88.
  • 8. Bouteska, A., Hajek, P., Fisher, B. and Abedin, M. Z., (2023). Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network. Research in International Business and Finance, 64, 101863
  • 9. Bouteska, A., Sharif, T. and Abedin, M. Z., (2023). COVID-19 and stock returns: Evidence from the Markov switching dependence approach. Research in International Business and Finance, 64, 101882
  • 10. Campbell, J. Y., Thompson, S. B., (2008). Predicting excess stock returns out of sample: Can anything beat the historical average? Review of Financial Studies, 21(4), 1509-1531.
  • 11. Chai, S., Chu, W., Zhang, Z., Li, Z. and Abedin, M. Z., (2022). Dynamic nonlinear connectedness between the green bonds, clean energy, and stock price: the impact of the COVID-19 pandemic. Annals of Operations Research.
  • 12. Chen, Y., Zhou, W. and Liu, M., (2020). Impact of Economic Policy Uncertainty shocks on China ’ s Stock Market Development. In 4th International Symposium on Business Corporation and Development in South-East and South Asia under BandR Initiative (ISBCD 2019) (pp. 380-384). Atlantis Press.
  • 13. Combes, J. L., Guillaumont, P., (2002). Commodity price volatility, vulnerability and development. Development Policy Review, 20(1), 25-39.
  • 14. Corbet, S., Larkin, C. and Lucey, B., (2020). The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters, 35(May), 101554.
  • 15. Dharani, M., Hassan, M. K., Huda, M. and Abedin, M. Z., (2022). Covid-19 pandemic and stock returns in India. Journal of Economics and Finance, 47(1), 251-266
  • 16. Ederington, L. H., Guan, W., (2010). How asymmetric is U.S. stock market volatility? Journal of Financial Markets, 13(2), 225-248.
  • 17. Engle, R. F., Ghysels, E. and Sohn, B., (2013). Stock Market Volatility and Macroeconomic Factor Volatility. The Review of Economics and Statistics, 95(3), 776-797.
  • 18. Fernandez, V., (2019). A readily computable commodity price index: 1900–2016. Finance Research Letters, 31(1170037), 448-457.
  • 19. Fleming, J., Ostdiek, B. and Whaley, R. E., (1995). Predicting stock market volatility: A new measure. Journal of Futures Markets, 15(3), 265-302.
  • 20. Frost, J., (2013). Multiple Regression Analysis: Use Adjusted R-Squared and Predicted R- Squared to Include the Correct Number of Variables. Minitab Blog.
  • 21. Gao, L., Han, Y., Zhengzi Li, S. and Zhou, G., (2018). Market intraday momentum. Journal of Financial Economics, 129(2), 394-414.
  • 22. Gao, X., Ren, Y. and Umar, M., (2022). To what extent does COVID-19 drive stock market volatility? A comparison between the U.S. and China. Economic Research-Ekonomska Istrazivanja , 35(1), 1686-1706.
  • 23. Gilbert, C. L., (2011). Commodity Price Volatility. AgroParisTech-CEPII-INRA Seminar.
  • 24. Giot, P., Laurent, S., (2007). The information content of implied volatility in light of the jump/continuous decomposition of realized volatility. Journal of Futures Markets, 27(4), 337-359.
  • 25. Goodell, J. W., (2020). COVID-19 and finance: Agendas for future research. Finance Research Letters, 35(April).
  • 26. Goodell, J. W., Huynh, T. L. D., (2020). Did Congress trade ahead? Considering the reaction of US industries to COVID-19. Finance Research Letters, 36, 101578.
  • 27. Hasan, M. M., Khan, S., (2019). Stock volatility tests with the CAPM and Fama-french three- factor model: particular reference world’s top 10 largest companies. Torun Business Review, 19(1), 2019-2020.
  • 28. Hasan, M. M., Popp, J. and Oláh, J., (2020). Current landscape and influence of big data on finance. Journal of Big Data, 7(1), 21.
  • 29. Hasan, M. M., Yajuan, L. and Khan, S., (2020). Promoting China’s Inclusive Finance Through Digital Financial Services. Global Business Review, 23(4), 984-1006.
  • 30. He, F., Wang, Z. and Yin, L., (2020). Asymmetric volatility spillovers between international economic policy uncertainty and the U.S. stock market. North American Journal of Economics and Finance, 51, 101084.
  • 31. Ismail, A., Ihsan, H., Khan, S. A. and Jabeen, M., (2017). Price volatility of food and agricultural commodities: A case study of Pakistan. Journal of Economic Cooperation and Development, 38(3), 77-120.
  • 32. Joëts, M., Mignon, V. and Razafindrabe, T., (2017). Does the volatility of commodity prices reflect macroeconomic uncertainty? Energy Economics, 68, 313-326.
  • 33. Khan, M. A., Ahmed, M., Popp, J. and Oláh, J., (2020). Us policy uncertainty and stock market nexus revisited through dynamic ardl simulation and threshold modelling. Mathematics, 8(11), 1-20.
  • 34. Kirikkaleli, D., (2020). The effect of domestic and foreign risks on an emerging stock market: A time series analysis. North American Journal of Economics and Finance, 51(November 2018), 100876.
  • 35. Kristöfel, C., Strasser, C., Morawetz, U. B., Schmidt, J. and Schmid, E., (2014). Analysis of woody biomass commodity price volatility in Austria. Biomass and Bioenergy, 65(2014), 112-124.
  • 36. Kurowska-Pysz, J., (2021). Selected conditions of developing inter-organizational cooperation in innovation processes on the Polish capital market. [in:] A. Ujwary-Gil and B. Godlewska-Dzioboń (Eds.), Challenges in Economic Policy, Business, and Management in the COVID-19 era. Institute of Economics, Polish Academy of Sciences.
  • 37. Li, G., Wang, S., (2020). Research on the Relationship Between the Volume of Shenzhen Stock Market and Economic Growth. In 6th International Conference on Humanities and Social Science Research (ICHSSR 2020) (pp. 154-158). Atlantis Press.
  • 38. Li, W., Chien, F., Kamran, H. W., Aldeehani, T. M., Sadiq, M., Nguyen, V. C. and Taghizadeh-Hesary, F., (2022). The nexus between COVID-19 fear and stock market volatility. Economic Research-Ekonomska Istrazivanja, 35(1), 1765-1785.
  • 39. Li, Z., Zhong, J., (2019). Impact of economic policy uncertainty shocks on China’s financial conditions. Finance Research Letters, 35, 101303.
  • 40. Liang, C., Ma, F., Li, Z. and Li, Y., (2020a). Which types of commodity price information are more useful for predicting US stock market volatility? Economic Modelling, 93, 642-650.
  • 41. Mahmud, A., Ding, D. and Hasan, M. M., (2021). Corporate Social Responsibility: Business Responses to Coronavirus (COVID-19) Pandemic. SAGE Open, 11(1).
  • 42. Makhlouf, Y., Kellard, N. M. and Vinogradov, D., (2017). Child mortality, commodity price volatility and the resource curse. Social Science and Medicine, 178, 144-156.
  • 43. Marvasti, A., Lamberte, A., (2016). Commodity price volatility under regulatory changes and disaster. Journal of Empirical Finance, 38, 355-361.
  • 44. McMillan, D. G., Speight, A. E. H., (2007). Weekly volatility forecasts with applications to risk management. Journal of Risk Finance, 8(3), 214-229.
  • 45. Monteiro, A. P., Vale, J., Leite, E., Lis, M. and Kurowska-Pysz, J., (2022). The impact of information systems and non-financial information on company success. InternationalJournal of Accounting Information Systems, 45, 100557.
  • 46. Naik, P. K., Shaikh, I. and Huynh, T. L. D., (2022). Institutional investment activities and stock market volatility amid COVID-19 in India. Economic Research-Ekonomska Istrazivanja , 35(1), 1542-1560.
  • 47. Okorie, D. I., Lin, B., (2020). Stock markets and the COVID-19 fractal contagion effects. Finance Research Letters, 38, 101640.
  • 48. Ortmann, R., Pelster, M. and Wengerek, S. T., (2020). COVID-19 and investor behavior. Finance Research Letters, 37, 101717.
  • 49. Osborne, J. W., (2001). Prediction in multiple regression. Practical Assessment, Research and Evaluation, 7(2), 2000-2001.
  • 50. Patton, A. J., Sheppard, K., (2015). Good volatility, bad volatility: signed jumps and the Persistence of volatility. Review of Economics and Statistics, 97(3), 683-697.
  • 51. Popp, J., Oláh, J., Fekete, M. F., Lakner, Z., and Máté, D., (2018). The relationship between prices of various metals, oil and scarcity. Energies, 11(9).
  • 52. Qiao, T., Han, L., (2023). COVID-19 and tail risk contagion across commodity futures markets. Journal of Futures Markets, 43(2), 242-272.
  • 53. Rahman, M. M., Guotai, C., Das Gupta, A., Hossain, M., and Abedin, M. Z., (2022). Impact of early COVID-19 pandemic on the US and European stock markets and volatility forecasting. Economic Research-Ekonomska Istrazivanja, 35(1), 3591-3608.
  • 54. Razmi, S. F., Ramezanian Bajgiran, B., Behname, M., Salari, T. E. and Razmi, S. M. J., (2020). The relationship of renewable energy consumption to stock market development and economic growth in Iran. Renewable Energy, 145, 2019-2024.
  • 55. Rizvi, S. K. A., Itani, R., (2022). Oil market volatility: comparison of COVID-19 crisis with the SARS outbreak of 2002 and the global financial crisis of 2008. Economic Research- Ekonomska Istrazivanja, 35(1), 1935-1949.
  • 56. Salisu, A. A., Ebuh, G. U. and Usman, N., (2020). Revisiting oil-stock nexus during COVID-19 pandemic: Some preliminary results. International Review of Economics and Finance, 69, 280-294.
  • 57. Salisu, A. A., Vo, X. V., (2020). Predicting stock returns in the presence of COVID-19 pandemic: The role of health news. International Review of Financial Analysis, 71, 101546.
  • 58. Schwert, G. W., (1989). Why Does Stock Market Volatility Change Over Time? The Journal of Finance, 44(5), 1115-1153.
  • 59. Schwert, G. W., (2011). Stock Volatility during the Recent Financial Crisis. European Financial Management, 17(5), 789-805.
  • 60. Siami-Namini, S., Hudson, D. and Trindade, A., (2017). Commodity Price Volatility and U.S. Monetary Policy: Commodity Price Overshooting Revisited. Agribusiness, 35(2), 200-218.
  • 61. Suzuki, K., Ikushima, Y. and Murayama, Y., (2023). Changes in Cargo Movement due to the Effects of COVID-19. Production Engineering Archives, 29(2) 147-154.
  • 62. Tarpey, T. (2000). A Note on the Prediction Sum of Squares Statistic for Restricted Least Squares. American Statistician, 54(2), 116-118.
  • 63. Wang, Y., Wei, Y., Wu, C. and Yin, L., (2018). Oil and the short-term predictability of stock return volatility. Journal of Empirical Finance, 47, 90-104.
  • 64. Zhang, D., Hu, M. and Ji, Q., (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 101528.
  • 65. Zhang, N., Wang, A., Haq, N. U. and Nosheen, S., (2022). The impact of COVID-19 shocks on the volatility of stock markets in technologically advanced countries. Economic Research-Ekonomska Istrazivanja , 35(1), 2191-2216.
  • 66. Zhang, Y., Wang, R., (2022). COVID-19 impact on commodity futures volatilities. Finance Research Letters, 47, 102624.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a206ac38-4718-43cc-8ac9-b7cf201ce17b
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