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Managing a Crypto-Currency Portfolio Via Minmax Drawdown Control

Author

Listed:
  • Sylvain Chassang

    (New York University)

Abstract

Crypto-currencies and other innovative asset classes present a fundamental challenge for quantitative asset-allocation. Because the track record of innovative assets is by definition short, it is difficult to form reliable estimates of expected returns and covariance matrices needed as inputs for standard portfolio optimization. Even if such estimates are available, they may be useless to investors if the behavior of underlying assets changes over time. Building on the MinMax Drawdown Control framework of Chassang (2018), this paper proposes a conceptually attractive and empirically successful approach to build benchmark portfolios of crypto-currencies and other innovative assets.

Suggested Citation

  • Sylvain Chassang, 2019. "Managing a Crypto-Currency Portfolio Via Minmax Drawdown Control," Working Papers 2019-1, Princeton University. Economics Department..
    • Handle: RePEc:pri:econom:2019-1
    as

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    File URL: https://www.sylvainchassang.org/assets/papers/crypto_portfolio_management.pdf
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    References listed on IDEAS

    as
    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
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    More about this item

    Keywords

    crypto-currencies; MinMax Drawdown Control; prior-free asset allocation; agnostic asset allocation; innovative assets;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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