Aquanow Announces New Tools to Evaluate Risk and Return in Decentralized Finance
We are pleased to announce the launch of the Aquanow DeFi Funding Index (ADFI) and Rate (ADFR) as new benchmarks available on the Bloomberg terminal. As institutional adoption of digital assets grows, more sophisticated tools are required to effectively communicate sources of risk and return. These yardsticks are the latest in Aquanow’s suite of solutions to help institutions operate in the digital economy. The Index and Rate are liquidity-pool-value-weighted composites designed to measure the performance and state of major decentralized lending protocols. By capturing an aggregate yield of stablecoin lending to selected DeFi pools, the standards can be used in performance attribution for active investment funds, spread analysis and more. As the time series grows, it will be interesting to evaluate trends and compare funding rates in decentralized pools against traditional marketplaces over the course of economic cycles.
What problems are solved by the Index?
In traditional financial markets, benchmarks provide a standard measure of an asset class’s risk and return against which similar securities are compared. Aggregations of benchmark assets with common features are called indices. There are several composites designed to measure the aggregate bond market and its various sectors (government, municipal, corporate, etc.). Widely known fixed income indexes include the Bloomberg Barclays U.S. Aggregate Bond Index, which tracks the largest debt issuers in the U.S., and the Bloomberg Barclays Global Aggregate Bond Index, which tracks the largest borrowers globally. New composites are often created as novel asset classes arise and investor interests evolve. For example, as demand for developing market securities grew, J.P. Morgan created its Emerging Markets Bond Index in 1992 to provide a standard for portfolios of developing country debt. (Source) The Aquanow DeFi Funding Index is an innovation to capture the subtleties of protocol-based lending markets.
Because indexes are unmanaged, they track returns on a buy-and-hold basis. While rebalancing occurs formulaically, no trades are made to reallocate to securities that may be more attractive over different market cycles or other price-changing events. As such, indexes represent a “passive” investment and can provide a good yardstick against which to measure the performance of a portfolio that is actively managed. The difference between the investment return of a portfolio and its benchmark is known as tracking error (TE). When a portfolio is actively managed, TE typically reflects the investment choices made by the capital allocator attempting to improve performance. If they are successful, tracking error is positive and the portfolio outperforms the benchmark; if not, the fund is said to have underperformed. Similar assessments are frequently carried out to evaluate risk by comparing a fund’s standard deviation of returns to that of the corresponding index. For such assessments to be useful in fixed income, the benchmark and the asset or fund being measured against it should have similar duration, liquidity, issue size, and coupon. Currently, there isn’t a well-established term structure for decentralized loans, which prevents duration matching, but as the market matures we look forward to expanding our analytical tools.
With the proliferation of new hedge funds focused on decentralized markets, standards like the DeFi Funding Index will provide superior attribution evaluations. The returns earned from lending to a decentralized pool of digital assets will fluctuate based on supply/demand in those protocols and flows will be affected by idiosyncrasies that aren’t present in fiat markets. While it might be interesting to evaluate results of DeFi funds relative to traditional composites, the explanatory power of such an assessment would be weak. For example, many bond funds have suffered some of the worst returns in ages as interest rates have increased in 2022 due to central bank policy guidance and inflation concerns. Meanwhile, the popularity of algorithmic stablecoin lending has increased as token prices for most projects are lower and yields for these assets tend to be higher (more on this below). This causes an imbalance where the supply of asset-backed capital in lending pools is abundant, but demand for loans is weak, so protocols decrease rates to bring balance. Returns in both markets are trending lower, but for completely different reasons. Aquanow’s DeFi Funding Index is now available to institutional investors through Bloomberg and captures the idiosyncrasies of the appropriate market for accurate risk/return attribution.
What about the Rate?
In addition to the Index, we believe it’s important to publish the weighted-average spot rate across the decentralized pools for lending non-algorithmic stablecoins. While the former serves as an important tool for evaluating the performance of assets & portfolio managers engaged in DeFi lending, the prevailing rate helps inform in other ways. Benchmark or reference rates are most often used to reflect the cost of borrowing money in different markets. For example, they might reflect how much it costs for banks to borrow from each other (LIBOR or now SOFR). Alternatively, they might indicate the cost of debt in a decentralized pool of capital.
To illustrate, in fiat markets, the on-the-run 10-year US Treasury is typically used as a yardstick for bonds of comparable maturity. An investor that wants to gauge the return for holding a 10-year corporate bond, which most likely has more risk than a government bond, will compare the yields of both assets. If the yield on a 10-year T-bond is going for 2.85%, the investor will demand a risk premium above 2.85% from corporate issuers. Stablecoin advances in protocol-based lending forums are protected by overcollateralization through risky, but established cryptocurrencies pledged as security. Rates tend to be variable and as mentioned reflect the supply and demand of capital and borrowing. We believe this represents the baseline level of risk in the digital system since the pools selected are of institutional size, have proven track records, and the loans relate to non-algorithmic stablecoins as well. The interest charges of loans with other features can be assessed against the Aquanow benchmark to conceptualize their unique risks. Like the Treasury example, if a lender is providing unsecured credit of stablecoins, they would likely expect a spread above the Aquanow DeFi Funding Rate to account for the higher probability of loss in a default.
In traditional finance, Interest Rate Swaps (IRS) are some of the most transacted derivatives. In very broad terms these are transactions involving two parties, where each agrees to cover the other’s interest payments. In IRS, the benchmark rate may determine at least one of the interest rates being exchanged. This creates transparency for all parties involved, brings some standardisation to the agreement and, as a result, makes it easier for all parties to negotiate (Source). While there are some protocols that offer IRS-like characteristics, we believe that by focusing on non-algorithmic stablecoin lending rates from well-established decentralized pools of capital, the Aquanow Rate captures the institutional cost of capital in DeFi and can serve as a future reference rate in derivatives or for discounting cash flows earned in the emerging ecosystem. In the schema below, the ADFR would replace LIBOR (which incidentally has also been phased out in favour of SOFR):
Currently, the supply and demand of capital in digital assets are affected by different variables than the ebbs and flows in traditional markets. As such, fluctuations in the lending rates from decentralized, institutional-grade money markets provide more insightful analysis and superior conversation points. With the passage of time, studies of how the Aquanow DeFi Funding Rate has changed and its correlation with other variables can inform a more rigorous study of the digital economy.
How can we frame the Aquanow benchmarks in the context of the Terra/Luna collapse?
Last week, we witnessed a systemic event in digital asset markets, when the $20B market cap UST broke its peg, and by way of its stability mechanism minted trillions of the Terra blockchain’s governance token, Luna. Hundreds of billions of dollars were lost across the space and many investors were wiped out entirely.
As mentioned, the ADFR is meant to represent the opportunity cost of capital or a baseline level of return for minimal risk in DeFi. In recent weeks, the ADFR had been trading around 3%, which compares to the rate offered on the Terra lending protocol (Anchor) of 20%. While we don’t have a lot of historical precedent, interest rates in decentralized pools tend to be pro-cyclical, meaning they rise with demand (or risk appetite) in digital markets. The 1,700 basis point spread that Anchor was offering over ADFR is significant and may have been interpreted as a warning sign. In traditional markets, credit spreads widen when participants begin to fear an economic slowdown. Investors require a higher rate of return to take the risk that the issuer of the bond they’re buying could come under financial hardship during, say, a recession. To be clear, the UST debacle was more related to its design, but investors may have gleaned an additional signal from the spread blowing out.
As a participant in the ecosystem, I often hear of funds claiming to provide their unitholders with “stable yields in the mid-teens.” Such results have been possible, but as we’ve been tracking the ADFI our opinion of such proclamations has turned skeptical — specifically with respect to “stability.” While the Aquanow DeFi Funding Rate is a snapshot of prevailing returns from asset-backed stablecoin lending in institutional-grade protocols, the ADFI is meant to represent the cumulative total return from a passive investment in the Index. As the performance has moderated with the general ebullience in crypto markets, achieving returns over 10 percentage points higher than the ADFI would require a portfolio manager to take on considerably more risk. Some examples include:
· It’s possible that many were using the Anchor yields to achieve their return targets.
· Alternatively, the PM could be dabbling in lesser-know protocols where a significant portion of the return is paid in the native token, which has probably lost significant value in the recent rout.
· Finally, the fund may employ high amounts of leverage and with borrowing rates moving higher in traditional markets, the cost of margin can be expected to erode returns as well.
For some, taking on more risk to grow their capital faster is desirable and that’s totally acceptable. However, we believe that well-constructed benchmarks can help inform an investor’s analysis when trying to understand the risks involved across their allocations. Such tools have been available for decades in traditional markets and we’re pleased to be introducing them to the digital asset landscape.
How does Aquanow select constituents for these benchmarks?
For a complete description of the Aquanow DeFi Funding Index and Rate, please see our whitepaper here.
To summarize, eligible pools for inclusion in the Aquanow DeFi Funding benchmarks must satisfy the following criteria:
· Size of the pool, measured by the total liquidity supplied, must exceed $100M USD.
· The lending pool’s utilization ratio should be greater than 50%.
· The pool should constitute non-crypto asset backed stablecoins (e.g., USDT and USDC). In other words, no algorithmic stablecoin pools will be included presently.
· The DeFi protocol associated with the pool should have been vetted by third-party auditors.
· There should be no history of protocol breaches, or if such an issue has occurred, there is a reason to believe the problem has been resolved completely.
Selected constituents are initially weighted by their liquidity-pool-size, measured by the total US dollar value of liquidity supplied. However, no single constituent pool will weigh more than 30% or less than 0.5% of the total value.
To account for the rapid pace of change in digital asset markets, a committee internal members and external experts will rebalance the index and rate monthly. The weights will fluctuate as the total value locked in each protocol changes and the constituents will be adjusted as new eligible pools are identified, or existing pools fail to meet the necessary criteria for inclusion. No constituents will be added or removed from the index intra-month, except by special Index Committee decision. For example, in the case of an exploit, it will be treated as a standard counterparty default and the recovery value will be used to update the index value upon the final decision of the index committee.
The current composition of the index is as follows:
The benchmark rate at launch is show below:
We welcome your feedback on this new initiative. We also look forward to providing related case studies in time and updating you on subsequent innovations to help the institutionalization of digital asset markets.