A Study of the Machine Learning Approach and the MGARCH-BEKK Model in Volatility Transmission
نویسندگان
چکیده
This study analyzes the volatility spillover effects in US stock market (S&P500) and cryptocurrency (BGCI) using intraday data during COVID-19 pandemic. As potential drivers of portfolio diversification, we measure asymmetric transmission on both markets. We apply MGARCH-BEKK algorithm-based GA2M machine learning model. The negative shocks to returns impact S&P500 more than positive also indicates evidence unidirectional cross-market from research findings show benefit diversification between BGCI.
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ژورنال
عنوان ژورنال: Journal of risk and financial management
سال: 2022
ISSN: ['1911-8074', '1911-8066']
DOI: https://doi.org/10.3390/jrfm15030116