Bitcoin as a Portfolio Diversifier within Institutional Mean Variance Frameworks

Abstract

This thesis investigates whether the integration of digital assets, specifically Bitcoin and <br/>Ethereum, into a traditional multi-asset institutional portfolio can produce superior out-of<br/>sample risk-adjusted performance relative to the conventional 60/40 equity-bond benchmark. <br/>Using a Mean-Variance Optimization (MVO) framework enhanced by Ledoit-Wolf <br/>covariance shrinkage, the study evaluates seven distinct portfolio configurations across an <br/>empirical window spanning January 2016 to May 2026, covering multiple market regimes <br/>including the 2020 COVID-19 liquidity shock, the 2022 inflationary spike, and the 2024 <br/>institutional crypto adoption phase. <br/>The empirical design employs a dual-mode out-of-sample validation strategy: a fixed-weight <br/>stability test and a rolling realism test with systematic rebalancing. Results suggest that <br/>portfolios enriched with Bitcoin tended to achieve superior Sharpe and Sortino ratios relative <br/>to the baseline within this sample period and asset universe. The Master Portfolio (Case 7), <br/>combining equities, bonds, Bitcoin, Ethereum, Gold, and Silver, attains a static Sharpe Ratio <br/>of 1.62, a static Sortino Ratio of 3.23 and a Maximum Drawdown of only −6.40%. These <br/>findings are consistent with the primary hypothesis (H₁) that, within this empirical setting, <br/>Bitcoin can improve out-of-sample risk-adjusted performance, while also providing evidence <br/>consistent with the secondary hypothesis (H₂) that Bitcoin acts primarily as a portfolio <br/>diversifier rather than a consistent safe haven. All results should be interpreted as conditional <br/>on the sample period, the chosen asset universe, and the rebalancing assumptions. All asset <br/>price data was sourced from Investing.com and the risk-free rate from the FRED 3-Month <br/>Treasury Bill series (TB3MS).