THE CRYPTO-EQUITY NEXUS: A ROLLING LINEAR REGRESSION ANALYSIS OF BITCOIN’S PREDICTIVE POWER ON MICROSTRATEGY AND BLACKROCK - Andreas Widjaja; Benny Budiawan Tjandrasa; Andrew Sebastian Lehman (ZILLZELL MEDIA PRIMA, 2025)
This study analyzes the differing dynamics within the crypto-equity nexus by examining the influence of Bitcoin (BTC) on the valuation of MicroStrategy (MSTR), an active leveraged balance sheet adopter, and BlackRock (BLK), a passive institutional conduit. The objective is to assess the predictive effectiveness of BTC across these various corporate archetypes. We utilized Rolling Linear Regression (RLR) with both growing-window and fixed-window methodologies to evaluate the time-varying correlation and forecast accuracy for MSTR and BLK from 2020 to late 2025. This comparative analysis identified parameter instability due to changes in corporate strategy. The findings indicate that the RLR model for MSTR demonstrated considerable forecast bias, as reflected by a notably high Mean Absolute Percentage Error (MAPE), especially with the growing window. This failure indicates that MSTR functions as a non-linear, high-beta instrument, enhanced by a speculative leverage premium. The BLK model exhibited high accuracy and stability, evidenced by a low MAPE, which confirms a systematic second-order correlation based on institutional fee revenue. In conclusion, the findings indicate that BTC serves as a significant determinant for both equities, necessitating a tailored predictive modeling approach. Simple linear models are adequate for stable conduits such as BLK; however, they fail to accurately represent MSTR, where price movements are influenced by non-linear corporate financing and active leverage dynamics.