Volume 4 • Issue 2 • PP: 09–15 • 2024
Regime-Aware Digital-Asset Allocation: Balancing Participation and Downside Risk
Open Access & Copyright
© 2024 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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The exposure of cryptocurrencies has been so easy to make a part of the digital-asset platforms, but the risk engines that come with these products are frequently based on static allocations or unconditional correlation estimates. The problem is that the states that allow participation in upside potential are different from the states that allow protection against sudden drawdowns; solving both optimization problems as a single problem can lead to a portfolio that retains too much crypto risk or to a portfolio with a zero digital asset exposure. In this paper, we introduce a participation constrained, regime aware allocation framework which allocates Bitcoin and Ether alongside gold and the S&P 500. A pre-specified volatility signal separates out the normal period from the stress period, and normal period minimum variance optimization enforces a significant crypto allocation during the normal period, whereas the stress period has an explicit ceiling on the amount of crypto invested. The design is tested without look-ahead bias over 2020–2023, assuming that there is a 10 basis points per unit of turnover charge for the design. Importance of the framework for FinTech investment platforms is that it converts a qualitative risk setting into allocation rules that are easily explainable, auditable, and repeatable. The volatility of the static crypto portfolio was 64.7%, the maximum drawdown was 72.1%, and the conditional loss at 5% monthly was 34.6% for the portfolio. A crypto-only strategy had an annualized return of 12.0% and reduced volatility to 16.3% and the 5% conditional loss to 20.1%, while a regime-aware strategy had an annualized return of 14.9% and reduced volatility to 25.9% and the 5% conditional loss to 14.5%.
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