Balancing Cryptoassets and Gold: A Weighted-Risk-Contribution Index for the Alternative Asset Space

  • Aikaterini KoutsouriEmail author
  • Francesco Poli
  • Elise Alfieri
  • Michael Petch
  • Walter Distaso
  • William J. Knottenbelt
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


Bitcoin is foremost amongst the emerging asset class known as cryptoassets. Two noteworthy characteristics of the returns of non-stablecoin cryptoassets are their high volatility, which brings with it a high level of risk, and their high intraclass correlation, which limits the benefits that can be had by diversifying across multiple cryptoassets. Yet cryptoassets exhibit no correlation with gold, a highly-liquid yet scarce asset which has proved to function as a safe haven during crises affecting traditional financial systems. As exemplified by Shannon’s Demon, a lack of correlation between assets opens the door to principled risk control through so-called volatility harvesting involving periodic rebalancing. In this paper we propose an index which combines a basket of five cryptoassets with an investment in gold in a way that aims to improve the risk profile of the resulting portfolio while preserving its independence from mainstream financial asset classes such as stocks, bonds and fiat currencies. We generalise the theory of Equal Risk Contribution to allow for weighting according to a desired level of contribution to volatility. We find a crypto–gold weighting based on Weighted Risk Contribution to be historically more effective in terms of Sharpe Ratio than several alternative asset allocation strategies including Shannon’s Demon. Within the crypto-basket, whose constituents are selected and rebalanced monthly, we find an Equal Weighting scheme to be more effective in terms of the same metric than a market capitalisation weighting.


Cryptoassets Index Volatility Rebalancing premium Risk management Asset allocation Equal risk contribution Weighted risk contribution Bitcoin Gold 



Imperial College of London gratefully acknowledges the support given mutually by CoinShares and Elwood Capital Management. Their funding provides Imperial with the support needed to conduct the research found within this paper.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Aikaterini Koutsouri
    • 1
    Email author
  • Francesco Poli
    • 2
  • Elise Alfieri
    • 3
  • Michael Petch
    • 4
  • Walter Distaso
    • 2
  • William J. Knottenbelt
    • 1
  1. 1.Department of ComputingImperial College LondonLondonUK
  2. 2.Department of FinanceImperial College LondonLondonUK
  3. 3.University Grenoble AlpesGrenobleFrance
  4. 4.CoinShares, Octagon PointLondonEngland

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