Key Takeaways
- The Fed paper urges adding a new “crypto” risk class to properly capture the extreme and unique volatility of cryptocurrencies in uncleared derivatives markets.
- It recommends splitting crypto into floating (volatile) and pegged (stablecoin) buckets because their risk behaviors differ sharply.
- Initial margin weights should be calibrated using crypto-specific stress periods and proxy indexes to avoid underestimation.
A new paper from the Federal Reserve examines the risks associated with digital assets that aren’t cleared through central systems.
The paper points out that current risk measurement methods may not work well for crypto and suggests adding special safety measures, such as initial margins, for crypto derivatives.
Why Current Risk Models Fall Short for Crypto?
The paper titled “Initial Margin for Crypto-Currencies: Risks in Uncleared Markets” calls for treating crypto differently from traditional stocks or regular currencies because its price swings can be wild and unpredictable.
The paper argued that traditional risk tools assume all asset classes behave similarly, but crypto breaks that assumption. It highlights that price jumps in crypto are larger and more clustered than in commodities.
The International Swaps and Derivatives Association (ISDA) developed a standard model to determine the amount of collateral, or initial margin, required. It looks at possible losses over 10 days in bad scenarios.
But this model was built for traditional investments and doesn’t yet include crypto.
The Fed researchers say crypto acts more like its own thing, powered by blockchain tech, and shouldn’t be lumped in with commodities or foreign exchange.
They picked 12 big cryptos to study: half float freely like Bitcoin, and the other half are tied to stable currencies like the U.S. dollar.
The paper uses indexes such as Bloomberg’s to track overall crypto movements, comparing them with commodity indexes. What stands out is that crypto’s tough times, when prices crash hard, don’t align with the stresses in other markets.
This mismatch means using old models could underestimate dangers, leaving traders exposed.
For instance, during certain quarters, crypto losses were way higher than what models predict if you treat it like oil or gold.
The researchers used a method to pick out the worst periods by scoring volatility across coins, avoiding overlaps to get a clear picture.
Federal Reserve’s Push for Better Crypto Safeguards
To address issues related to crypto tokens, the Fed paper recommended creating a new category for crypto in the standard model. This would let traders account for hedges across crypto deals, reducing unnecessary margins while covering real risks.
The researchers split crypto into two groups: floating, volatile ones, and stable ones pegged to real money. For floating ones, risk levels could be over twice as high as under commodity rules.
The analysis found Stable ones stay low, around 1% or so, but still need their own handling.
Looking at the correlations, or how prices move together, there is a strong correlation within each group, where over 70% of floaters move similarly, but there is almost zero correlation between groups, as links to other markets, like stocks or bonds, are weak, at under 15%.
The paper describes a consistent calibration method matching how SIMM already works for other classes:
- Use four years of historical price data overall.
- Include 25% from a continuous stress period specific to the crypto algorithm to pick the worst volatility clusters, which works well for crypto’s concentrated market.
- Fill in the rest with the most recent 3 years, adding extra-stress quarters if needed.
- Build proxy indexes: an equal-weighted index for floating coins and one for pegged coins
Recommendations include keeping things simple so anyone can use it without needing tons of data. Since a few coins dominate, such as Bitcoin and Ethereum, calibrating around them works fine.
It’s the first deep dive into how to fit crypto into these rules, balancing innovation with caution. In the end, better models mean stronger markets, protecting everyone from surprise losses.
If adopted by ISDA and regulators, this framework would require higher upfront collateral for most crypto-linked derivatives, especially floating-rate ones, than if shoehorned into the commodities framework.
Prashant Jha is a seasoned crypto journalist based in Delhi, India, with a Bachelor’s Degree in Computer Science Engineering. Passionate about the evolving world of blockchain and cryptocurrencies, he has been a dedicated voice in the industry since 2018. Prashant’s expertise lies in regulatory reporting, where he unravels complex legal and financial developments with clarity and precision. Before joining CCN in 2024, he honed his craft at Cointelegraph, establishing himself as a trusted name in crypto journalism.
His coverage spans major industry events, including the high-profile collapses of FTX, Three Arrows Capital (3AC), and LUNA, offering readers insightful analyses of their regulatory and market implications. Prashant’s technical background enables him to bridge the gap between intricate blockchain technology and its real-world applications, making his work accessible to novices and experts.
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