Hedging stock price risk with gold during the outbreak of the covid pandemi
محورهای موضوعی : Business ManagementAli Baghani 1 , Mojtaba Karimi 2 , Azin Sadat OstadRamadan 3
1 - Assistant Professor, Department of Accounting and Finance, South Tehran Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3 - Research Expert of Kowsar Insurance Company, Tehran, Iran.
کلید واژه: risk hedging, stock price, gold, COVID disease,
چکیده مقاله :
Risk contagion refers to the transmission of information across financial markets. However, for investors, minimizing risk is crucial, and one way to achieve this is by diversifying their investment portfolio across different markets. In this research, the focus is on managing investor risk in the capital market by hedging stock price risk with gold, particularly during the COVID-19 outbreak. The DCC (Dynamic Conditional Correlation) and ADCC (Asymmetric Dynamic Conditional Correlation) models were employed for this purpose. The data used for analysis encompasses the monthly prices of Bahar Azadi gold coin and company stocks from 2017 to 2022. The research findings indicate an asymmetric correlation between the price of Bahar Azadi gold coin and the stock price of selected chemical and basic metals companies during the research period. The optimal risk hedging ratios have significantly increased in all companies during the COVID period, implying higher risk hedging costs. The research also reveals that F_khas (Khorasan steel company) exhibits the highest risk hedging efficiency, indicating its effectiveness in using gold for risk hedging. On the other hand, the symbol of Sh_iran (Iran Chemical Industries Company) demonstrates the lowest efficiency in using gold for risk coverage. These results offer an opportunity for investors to optimize their risk hedging and asset allocation strategies.
Risk contagion refers to the transmission of information across financial markets. However, for investors, minimizing risk is crucial, and one way to achieve this is by diversifying their investment portfolio across different markets. In this research, the focus is on managing investor risk in the capital market by hedging stock price risk with gold, particularly during the COVID-19 outbreak. The DCC (Dynamic Conditional Correlation) and ADCC (Asymmetric Dynamic Conditional Correlation) models were employed for this purpose. The data used for analysis encompasses the monthly prices of Bahar Azadi gold coin and company stocks from 2017 to 2022. The research findings indicate an asymmetric correlation between the price of Bahar Azadi gold coin and the stock price of selected chemical and basic metals companies during the research period. The optimal risk hedging ratios have significantly increased in all companies during the COVID period, implying higher risk hedging costs. The research also reveals that F_khas (Khorasan steel company) exhibits the highest risk hedging efficiency, indicating its effectiveness in using gold for risk hedging. On the other hand, the symbol of Sh_iran (Iran Chemical Industries Company) demonstrates the lowest efficiency in using gold for risk coverage. These results offer an opportunity for investors to optimize their risk hedging and asset allocation strategies.
• Abdoh Tabrizi, H., & Radpour, M. (2009). Measuring and managing market risk: A value-at-risk approach. Tehran: Aghaz Publications.
• Abdoh Tabrizi, H., & Khabeiri, A. (2018). Future market. Tehran: Ba'athat Publications.
• Arago, V., & Fernandez, M. A. (2007). Influence of structural changes in transmission of information between stock markets: A European empirical study. Journal of Multinational Financial Management, 17(1), 112-124.
• Bahrami, J., & Mirzapour, A. (2013). Optimal risk hedging ratio in Bahar Azadi coin futures contracts traded in Iran Commodity Exchange. Economic Research and Policy Quarterly, 20(64), 175-206.
• Baillie, R. T., & Myers, R. J. (1991). Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics, 6(2), 109-124.
• Basher, S. A., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235-247.
• Bazraei, M., Qavidel, S., Imam Verdi, Q., & Mahmoudzadeh, M. (2020). Hedging stock price of listed industries with exchange rate (Multidisciplinary industry, banking and investment). Financial Economics Quarterly, 15(54), 106-183.
• Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24.
• Bollerslev, T. (1990). Modeling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. Review of Economics and Statistics, 72.
• Chang, C.-L., McAleer, M., & Tansuchat, R. (2011). Crude oil hedging strategies VAR-DCC-GARCH. Energy Economics, 33(5), 912-923,
• Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20, 339-350.
• Elmi, Z., Abu Nouri, I., Raskhi, S., & Shahrazi, M. M. (2014). Effects of structural failures in volatility on momentum transfer and volatility spillover between gold and stock markets of Iran. International Economic Modeling Research Quarterly, 8(26), 57-73.
• Eskandari, H., Rostami, A. A., & Hosseinzadeh, K. (2014). The optimal ratio of currency risk hedging using gold futures in the financial market of Iran. Journal of Financial Engineering and Securities Management, 6(25), 21-40.
• Falahi, F., Haqit, J., Sanobar, N., & Jahangiri, K. (2014). Investigating the correlation between stock, currency and coin market volatility in Iran using the DCC-GARCH model. Economic Research Quarterly, 14(52), 123-147.
• Gorton, G., & Rouwenhorst, K. G. (2006). Facts and fantasies about commodity futures. Financial Analysts Journal, 62, 47-68.
• Hatami, A., Mohammadi, T., Khodadad Kashi, F., & Abolhasani Hestiani, A. (2019). Dynamics of optimal risk hedging ratio in stock and gold markets: VAR-DCC-GARCH approach. Financial Economics Quarterly, 12(45), 73-92.
• Huisman, R., Mahieu, R., & Schlichter, F. (2009). Electricity portfolio management: Optimal peak/offpeak allocations. Energy Economics, 31(1), 169-174.
• Inclan, C., & Tiao, G. C. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical Association, 89(427), 913-923.
• Jahangiri, K., & Hekmati Farid, S. (2015). Study of spillover effects of stock, gold, oil and currency market turbulence. Economic Research Quarterly, 15(56), 159-179.
• Kang, S. H., Cheong, C., & Yoon, S. M. (2011). Structural changes and volatility transmission in crude oil markets. Physica A: Statistical Mechanics and its Applications, 390(4), 4317-4324.
• Kroner, K. F., & Sultan, J. (1993). Time-varying distributions and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis, 28(4), 535-551.
• Ku, Y. H. H., Chen, H. C., & Chen, K. H. (2007). On the application of the dynamic conditional correlation model in estimating optimal time-varying hedge ratios. Applied Economics Letters, 14(7), 503-509.
• Lee, Y. H., Huang, Y. L., & Wu, C. Y. (2014). Dynamic correlations and volatility spillovers between crude oil and stock index returns: The implications for optimal portfolio construction. International Journal of Energy Economics and Policy, 4(3), 327-336.
• Malik, F., Ewing, B. T., & Payne, J. E. (2005). Measuring volatility persistence in the presence of sudden changes in the variance of Canadian stock return. Canadian Journal of Economics, 38(4), 1037-1056.
• Nikumram, H., Pourzmani, Z., & Dehghan, A. M. (2014). Contagion of Turbulence in Iran's Capital Market. Investing Knowledge Quarterly, 3(11), 179-199.
• Sanso, A., Arago, V., & Carrion, J. L. (2003). Testing for changes in the unconditional variance of financial time series. Revista de Economía Financiera, 4(4), 32-53.
• Shahzad, S. J. H., Bouri, E., Roubaud, D., & Kristoufek, L. (2020). Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin. Economic Modelling, 87, 212-224.
• Yao, Z., & Wu, H. (2012). Financial engineering estimation of minimum risk hedge ratio. Systems Engineering Procedia, 3, 187-193.
• Yousaf, I., & Ali, S. (2021). Linkages between stock and cryptocurrency markets during the COVID-19 outbreak: An intraday analysis. The Singapore Economic Review, Advance online publication.