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This thesis investigates the dynamic correlation between the S&P 500 and Bitcoin returns from 2018 to 2024. To capture potential regime-specific dynamics, a Markov Switching Model is employed to segment each return data into two distinct states characterized by high or low volatility, using a LASSO regression to find the appropriate explanatory variables for the returns. Univariate GARCH(1,1)
