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Simple and Effective Portfolio Construction with Crypto Assets

Kasper Johansson, Stephen Boyd

arXiv 3 Dec 2024 · Econometrics · 1 citations (OpenAlex)

arXiv:2412.02654 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We consider the problem of constructing a portfolio that combines traditional financial assets with crypto assets. We show that despite the documented attributes of crypto assets, such as high volatility, heavy tails, excess kurtosis, and skewness, a simple extension of traditional risk allocation provides robust solutions for integrating these emerging assets into broader investment strategies. Examination of the risk allocation holdings suggests an even simpler method, analogous to the traditional 60/40 stocks/bonds allocation, involving a fixed allocation to crypto and traditional assets, dynamically diluted with cash to achieve a target risk level.

Citation extraction

66
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1D. Palomar (2024) Portfolio Optimization1.00053100%
2O. Holovatiuk (2020) Cryptocurrencies as an asset class in portfolio optimisation0.81142100%
3K. Johansson, G. Ogut, M. Pelger, T. Schmelzer, and S. Boyd (2023) A simple method for predicting covariance matrices of financial returns0.81142100%
4I. Ruiz Roque da Silva, E. Junior, and P. Balbi (2022) Cryptocurrencies trading algorithms: A review0.81142100%
5E. Qian (2011) Risk parity and diversification0.64422100%
6A. Brauneis and R. Mestel (2019) Cryptocurrency-portfolios in a mean-variance framework0.64422100%
7T. Burggraf (2019) Risk-based portfolio optimization in the cryptocurrency world0.64422100%
8A. Hu, C. Parlour, and U. Rajan (2019) Cryptocurrencies: Stylized facts on a new investible instrument0.64422100%
9Y. Hu, S. Rachev, and F. Fabozzi (2019) Modelling crypto asset price dynamics, optimal crypto portfolio, and crypto option valuation0.64422100%
10Z. Jiang and J. Liang (2017) Cryptocurrency portfolio management with deep reinforcement learning0.64422100%

Showing the top 10 of 66 scored citations.