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Cryptocurrency Risks

J. Benson Durham
The Journal of Investing June 2020, joi.2020.1.128; DOI: https://doi.org/10.3905/joi.2020.1.128
J. Benson Durham
is head of quantitative global policy analytics at Cornerstone Macro LLC in New York, NY
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Abstract

Optimizations given historical data unsurprisingly produce sizeable allocations to Bitcoin (XBT). But further analyses of risks raise questions, even abstracting from expected returns. GARCH-based measures of dynamic XBT volatility and covariance suggest that optimal weights change over time. Also, quantile regressions indicate that conditional XBT returns with respect to the S&P 500 are modestly positively skewed. Yet benevolent symmetry is hardly stable or consistent along the distribution. Spectral analysis shows that the XBT volatility primarily owes to higher-frequency cycles. Nonetheless, XBT betas are substantially greater, and notably positive, over longer cycles compared with shorter cycles, which implies that XBT has been a much less effective strategic hedge. Dynamic principal components analysis indicates that individual coins’ exposures to the “crypto market factor” have likely increased meaningfully enough over time to diminish diversification benefits.

TOPIC: Currency

Key Findings

  • • Standard mean-variance portfolio optimizations given historical data unsurprisingly produce sizeable allocations to Bitcoin (XBT). But further analyses of risks raise questions, especially for passive investors and abstracting from expected returns. For example, GARCH-based measures of dynamic XBT volatility and covariance suggest that optimal portfolio weights change substantially over time.

  • • Quantile regressions indicate that conditional XBT returns with respect to the S&P 500 are modestly positively skewed, arguably unlike even safe-haven assets such as US Treasuries. However, this comparatively benevolent symmetry is hardly stable or consistent along the distribution.

  • • Spectral analysis shows that the XBT volatility primarily owes to higher-frequency cycles, much like common asset classes. Nonetheless, XBT betas are substantially greater, and notably positive, over longer cycles compared with shorter cycles, which implies that XBT has been a much less effective strategic hedge. Also, dynamic principal components analysis indicates that individual coins’ exposures to the “crypto market factor” have likely increased meaningfully enough over time to diminish diversification benefits for passive investors.

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The Journal of Investing: 30 (1)
The Journal of Investing
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December 2020
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Cryptocurrency Risks
J. Benson Durham
The Journal of Investing Apr 2020, joi.2020.1.128; DOI: 10.3905/joi.2020.1.128

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Cryptocurrency Risks
J. Benson Durham
The Journal of Investing Apr 2020, joi.2020.1.128; DOI: 10.3905/joi.2020.1.128
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  • Article
    • Abstract
    • MEAN-VARIANCE OPTIMIZATIONS: UNCONDITIONAL TO CONDITIONAL VARIANCE-COVARIANCE MATRICES
    • THE CONDITIONAL DISTRIBUTION OF XBT RETURNS: POSITIVELY OR NEGATIVELY SKEWED?
    • SPECTRAL ANALYSIS: SINES, COSINES, AND CRYPTOS
    • FACTORS AND INDIVIDUAL CRYPTOCURRENCIES: DYNAMIC PCA
    • DISCUSSION
    • ACKNOWLEDGMENTS
    • ADDITIONAL READING
    • ENDNOTES
    • REFERENCES
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