Evaluation of Multi-Asset Investment Strategies with Digital Assets

Abstract

The drastic growth of the cryptocurrencies market capitalization boosts investigation of their diversification benefits in portfolio construction. In this paper with a set of classical and modern measurement tools, we assess the out-of-sample performance of eight portfolio allocation strategies relative to the naive 1=N rule applied to traditional and crypto-assets investment universe. Evaluated strategies include a range from classical Markowitz rule to the recently introduced LIBRO approach, Trimborn et al. (2019). Furthermore, we also compare three extensions for strategies with respect to input estimators applied. The results show that in the presence of alternative assets, such as cryptocurrencies, Mean-Variance strategies under-perform the benchmark portfolio. In contrast, CVaR optimization tends to outperform the benchmark as well as geometric optimization. Furthermore, we find evidence that liquidity-bounded strategies tend to perform very well. Thus, our findings underscore the non-normal distribution of returns as well as the necessity to control for liquidity constraints at alternative assets markets.

Keywords: Portfolio Management, Asset Allocation, Investments, Alternative Assets, Bitcoin, Cryptocurrencies, LIBRO

JEL Classification: C01, C58, G11