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Macro Factors: The Next Layer of a Digital Asset-Specific Risk Model

A few months ago we wrote our first article in a series that attempts to build the framework for a digital asset specific risk factor model. In that piece, we proposed a foundational risk factor in the model – “crypto beta” – which represents broad crypto market risk in portfolios. The next step in this journey is to see whether it makes sense to include risks in the model that impact traditional asset classes in addition to crypto markets. Here is a summary of our findings:

 

  • This is the second in a series of posts about the construction of a crypto-specific risk factor model. The first post proposed a foundational risk factor in the model – “crypto beta” – which represents broad crypto market risk in portfolios. The objective of this post is to determine whether it makes sense to add certain macro factors to a crypto-specific risk factor model alongside crypto beta.
  • Historically, it was the case that digital assets had little relationship with the largest asset classes in investor portfolios, stocks and bonds. Over more recent periods though, that story may have changed. For example, Bitcoin’s correlation with the NASDAQ is at all time highs.
  • Six of the nine traditional asset classes we tested exhibited statistically significant relationships with crypto over a multi-year period.
  • To avoid material collinearity and an excessive number of factors in the model, we selected two macro factors to add to our model: Equities and Inflation.
  • We believe this risk model that includes macro factors brings value to those managing digital asset portfolios, as they can understand the significance of macro versus crypto-specific risk drivers in their portfolio. There is also an application for the multi-asset class investor that has (or is seeking to add) crypto exposure to their portfolio.
If you want to learn more, please watch the 7 minute video here or read the full report here.