Multiscale Effects of Macroeconomic News on the Dynamic Correlations between Bitcoin and the US Stock Markets

This study investigates how the rhythm of fourteen major US macroeconomic surprises resonates within the bitcoin–stock multiscale dynamic correlations. To do so, we use the Maximum overlap discrete wavelet transform to decompose the daily bitcoin and DJIA return series. The next step in the analysis involves generating the multiscale correlation series from the ADCC-GARCH model. We find that the influence of macro surprises on these correlations unfolds elegantly across distinct economic dimensions and across the market states. That is, most of real-activity indicators such as industrial production, durable goods, and business inventories bind bitcoin more closely to equities in the medium investment horizon during the COVID-19 pandemic, as growth signals ignite synchronized optimism. In contrast, Inflation and policy news (CPI and Fed announcements) amplify this comovement over longer horizons, reflecting shared repricing of risk premia and the chance for other variables to drive the correlations. These results remain the same after replacing the DJIA with the S&P500 and controlling for time-trends, bitcoin volume and the global policy uncertainty. The results bring important implications for both investors and policymakers that bitcoin no longer remains in isolation and its comovmenet with traditional assets must be determined by the macroeconomic surprises and the market state. JEL : C58, D89, E00, G12, G15.