Institutional investors who are wading, however cautiously, into crypto assets bring familiar tools such as Value-at-Risk (VaR) into uncharted waters. How does VaR, time-tested but not necessarily fit for all purposes, stand up amid cryptocurrency volatility?
Comments and actions like those of BlackRock chief executive Laurence Fink, who has evolved from crypto skepticism to offering a leading bitcoin exchange-traded fund, have stoked mainstream investing interest. According to CoinShares data, digital asset investment-product inflows surged at the end of August before cooling off; the total stood at $86.7 billion as of October 7.
While VaR is used to calculate maximum potential losses in a finite period, given normal market conditions and at a specific confidence level, cryptocurrencies have been subject to far greater volatility and unpredictability than conventional assets. The extreme price swings, 24/7 trading hours, and relatively short history of digital assets such as bitcoin and ether – which are the two biggest in market capitalization – challenge the assumptions underlying traditional VaR models.
Sizing Up Suitability
“We do utilize VaR, but it tends to be a lagging indicator rather than a leading indicator,” said Jeff Dorman, chief investment officer of asset manager Arca.
“Crypto markets tend to have long periods of low, declining volatility, followed by rapid price declines with volatility spikes,” Dorman explained. Any measure of VaR will therefore tend to understate actual risk and then overstate it once most of the risks have been removed, i.e. when the leverage is flushed out.
Jeff Dorman of Arca
Moreover, digital-asset risk comprises both market risk and default risk, and VaR becomes less suitable due to the major impact of the latter.
“VaR, which attempts to forecast percent changes in the price of an asset over a few days, and not a 100% drop, is suitable for assets where market risk is the majority source of risk,” noted Ryo Takei, quantitative modeling director, financial risk analytics at S&P Global Market Intelligence. For digital assets, default risk is still too significant for VaR to be used effectively, Takei added.
On-Chain Analysis
What’s more, VaR is typically calibrated using historical price data, making it “a natural tool” for bonds and equities with stores of readily available data, according to Takei. Bitcoin offers transparency of a different kind:
“If you run a bitcoin node or access a block explorer, you can see every single transaction since the genesis block to the most current block in real time. This transparency enables what is known as on-chain analysis, which allows for real-time tracking of large holders’ trading activities, providing insights that go beyond historical price data.
“Such analyses are much more powerful and actionable when positioning and assessing risks in digital assets in an investment portfolio than simply calibrating to historical prices,” Takei continued. “Platforms for on-chain analysis are growing, used both for investment purposes as well as for criminal investigations.”
Evolution for Crypto
As the cryptocurrency market evolves, so do the tools for managing its risks. In 2022, market data provider Kaiko introduced a VaR estimator tailored for digital assets.
Anne-Claire Maurice Jeancolas
Initially, when holdings were modest, crypto VaR was seen as “nice to have” rather than "must have,” said Anne-Claire Maurice Jeancolas, Kaiko Quant Data managing director. “Now we have more TradFi [traditional finance] actors coming into the space – people are taking this far more seriously.
“Our customers are still applying both [traditional and crypto VaR] methodologies, and that’s normal because they need time to be convinced.”
One significant driver behind the crypto-space adoption of VaR, Jeancolas said, is compliance, given regulators’ recognition of the standard.
Two years ago, when demand for cryptocurrencies picked up, “the approach was to proxy every cryptocurrency holding to bitcoin futures,” said Suhrad Dagli, CEO of data and analytics software company RiskSpan. “So whatever the VaR was for bitcoin futures, that’s what was used . . . But the demand we’re seeing now is much more sophisticated than what we’ve seen in the past.”
Emerging Trends and Research
Dagli emphasized that while VaR is useful in cryptocurrency risk management, it must be complemented with other tools to account for unique characteristics.
Market participants are increasingly exploring hybrid models that combine traditional VaR with approaches like Expected Shortfall (ES), which focuses on average losses in worst-case scenarios beyond the VaR threshold.
“ES considers potential losses that exceed the quantile of interest,” said Fernanda Müller, professor of finance at the Business School of the Federal University of Rio Grande do Sul, Brazil. “In this way, ES provides greater protection than VaR.”
A 2023 study, The Efficiency of Value-at-Risk Models During Extreme Market Stress in Cryptocurrencies, published in the journal Sustainability, highlights that the Historical Simulation VaR model was the most accurate in predicting market stress during such periods as the COVID-19 pandemic and amid geopolitical tensions. In contrast, the Delta Normal and Monte Carlo Simulation VaR models frequently overestimated risk, underscoring the limitations of VaR amid high volatility.
Further Adaptations
As interest in crypto continues to grow, and traditional VaR faces the challenges, the integration of hybrid approaches and advanced methodologies offers a path forward. The emergence of tailored VaR services and adaptations such as with Expected Shortfall will be crucial in risk management’s ability to address the complexities of crypto assets.
As Müller cautions, no risk model is a guarantee of success.
“As the crypto market matures and investor participation increases, changes in this market are expected,” she said. “The main advances in this field will likely involve the development of more sophisticated models that better account for the unique characteristics of cryptocurrencies, such as heavy tails and volatility.”
Topics: Digital Assets
