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Evaluation of the association between cryptocurrencies with oil and gold prices using the BEKK multivariate GARCH model | ||
International Journal of Nonlinear Analysis and Applications | ||
مقاله 162، دوره 14، شماره 1، فروردین 2023، صفحه 2061-2078 اصل مقاله (455.8 K) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.27155.3523 | ||
نویسندگان | ||
Behrouz Shakeri1؛ Artin Beytari* 2؛ Mohammadreza Ghorbanian2؛ Rouhollah Javadi3 | ||
1Department of Humanities, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran | ||
2Department of Accounting, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran | ||
3Department of Accounting, Payame Noor University, Tehran, Iran | ||
تاریخ دریافت: 24 آبان 1400، تاریخ بازنگری: 01 اسفند 1400، تاریخ پذیرش: 10 اسفند 1400 | ||
چکیده | ||
Due to the emergence of cryptocurrencies in the world, many people save their capital and assets like cryptocurrencies. Cryptocurrencies are associated with prices of gold and oil, and stock market indices. On this basis, the present study aimed to evaluate the association between cryptocurrencies with oil and gold prices. To this end, the study performed an evaluation using the BEKK multivariate GARCH method. Therefore, two regression models were estimated to evaluate the association between cryptocurrencies and oil and gold prices. Based on the results, the mutual relationship between cryptocurrency volatility and gold and oil prices was confirmed. In general, volatility in oil and gold prices has a positive effect on cryptocurrency volatility. Given that volatility in oil and gold prices has a positive effect on cryptocurrency volatility, and these effects will be more manifested in future periods, cryptocurrency investors are recommended to examine oil and gold prices, especially oil prices in the last 10 years, before purchasing cryptocurrencies. | ||
کلیدواژهها | ||
cryptocurrencies؛ oil price؛ gold price؛ multivariate GARCH model | ||
مراجع | ||
[1] S.S. Adebola, L. Gil-Alana and G. Madigu, Gold prices and the cryptocurrencies: Evidence of convergence and cointegration, Phys. A: Statist. Mech. Appl. 523 (2019), 1227–1236. [4] L. Catania, S. Grassi and F. Ravazzolo, Predicting the volatility of cryptocurrency time series, Centre for Applied Macro and Petroleum Economics, CAMP, CAMP Working Paper, Series 3, 2018. [27] A. Turk and S. Rubino, The collapse of the Dollar and how to profit from it, Crown Pub. Group 272 (2008), no. 19. | ||
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