Adaptive Bitcoin Accumulation using Multi-Strategy Regime-Based Approach

Описание: In this video, I present my UBC Master of Data Science capstone project on Adaptive Bitcoin Accumulation, completed in partnership with the Trilemma Foundation.

The project explores how traditional dollar-cost averaging, or DCA, can be improved using a multi-strategy regime-based approach. Instead of buying the same amount of Bitcoin every period, the strategy first classifies the current market condition using signals such as BTC trend, MVRV, realized cap growth, and market cap growth. It then applies the strategy that performed best in similar historical regimes.

The goal is not to predict Bitcoin’s exact future price, but to improve accumulation timing and maximize satoshis earned per dollar within a long, buy-only investment framework.

This presentation covers:

The limitations of uniform DCA
Key Bitcoin market metrics
Rule-based market regimes
Candidate strategies such as Momentum, MVRV, and Custom Simple Moving Average
Performance comparison against uniform DCA
Key takeaways from the backtest

Note: This project is for educational and research purposes only and should not be considered financial advice.