Designing and explaining the dynamic model of comprehensive risk transfer of cryptocurrency in the financial markets of the world

The purpose of this article was to provide a dynamic and dynamic model to explain how to transfer the pervasive risk of cryptocurrencies in the world markets. In this regard, the statistical information of the cryptocurrency market index and the data of the Nasdaq, New York, Toronto, London, Frankfort, Madrid, Shanghai, Hong Kong, Tokyo, and Mumbai stock market indices were used. In this research, the data related to the cryptocurrency market and financial markets from July 2012 to July 2022 have been used. In the first part of this study, using the information of the period 2012-2022, based on the frequency of monthly data for the financial markets, the comprehensive risk criterion has been calculated using the method of value at risk, conditional interval and expected loss. In the second part, using multivariate conditional heteroscedastic variance autocorrelation method (MGARCH), the external effects related to pervasive risk related to cryptocurrency were estimated on financial markets. The obtained results indicate that there are spillover effects between financial markets and an increase in pervasive risk in each of the financial markets leads to an increase in pervasive risk in other financial markets. In the second part, using multivariate conditional heteroscedastic variance autocorrelation method (MGARCH), the external effects related to pervasive risk related to cryptocurrency were estimated on financial markets. The obtained results indicate that there are spillover effects between financial markets and an increase in pervasive risk in each of the financial markets leads to an increase in pervasive risk in other financial