Woofun AI reports that the crypto derivatives sector is experiencing unprecedented expansion while simultaneously suffering from a foundational absence of a unified benchmark interest rate. for the first quarter of 2026, the 'traditional asset perpetual' category witnessed weekly trading volume surge from approximately $525.8 million at the end of 2025 to $30.7 billion in mid-March 2026, representing a staggering quarterly increase of about 5,756%. This explosive growth is further evidenced by monthly trading volume skyrocketing from $7.9 billion in November 2025 to $19.91 billion in March 2026, an increase of approximately 25 times within just five months. Despite this massive liquidity influx, the entire ecosystem of leveraged positions, collateralized lending, and yield products operates without a standardized pricing anchor, creating a fragmented financial landscape where each entity sets its own rates in isolation.

Monitored by Woofun AI, the data reveals that Hyperliquid handled approximately $172.63 billion in perpetual transactions over a 30-day snapshot, with open interest amounting to around $9.13 billion. In the first quarter of 2026, commodity-related perpetuals accounted for approximately 30% of Hyperliquid's open interest, a figure driven mainly by the surging demand for 24/7 crude oil trading.

Meanwhile, 币安 launched TradFi perpetual contracts on January 8, 2026, initially offering gold (XAUUSDT) and silver (XAGUSDT). Thanks to this early entry, 币安 secured 62.7% of the TradFi perpetual contract market share, while Hyperliquid followed closely with 29.7%. The index data utilized by Hyperliquid for these traditional asset perpetuals stems from its collaboration with S&P Global, yet this partnership, which directly links crypto perpetuals to traditional indices, is currently under regulatory review by the US CFTC.

The core structural issue remains that while various products report specific 'interest rates' or 'yields,' the industry lacks its own SOFR—a widely recognized benchmark curve capable of serving as a pricing anchor. Perpetuals utilize funding rates, lending agreements rely on annualized borrowing rates (APRs), sUSDe offers staking yields, and tokenized government bonds provide coupon payments.

However, each exchange and protocol functions almost like a miniature financing market, establishing prices without a common, credible reference framework. Woofun AI observes that a qualified benchmark must meet strict criteria: it should be based on real transactions, operate in a market broad and deep enough to prevent manipulation by a single entity, possess independent governance, and preferably include a maturity structure to support medium- and long-term pricing. The basis of SOFR is the actual trading volume of overnight repurchase agreements backed by US Treasury bonds, with a daily average trading volume that often exceeds $1 trillion, a metric completely distinct from the notional volume of futures underpinning Term SOFR.

Applying the logic of SOFR to the crypto sector reveals significant structural similarities. In its research, the BIS compared the on-chain collateralized lending market to a 'crypto-native money market,' noting that its operating mechanism mirrors traditional tripartite repurchase agreements through excess collateral, market-cap-based liquidation, and overnight rollover. Since on-chain lending is essentially a form of repurchase-based secured financing, using the design of SOFR, which is grounded in actual repurchase transactions, serves as an appropriate analogy for the crypto sector. Historically, LIBOR was the cornerstone of global finance, with approximately $3 trillion worth of financial contracts relying on rates from five major currency regions.

However, LIBOR possessed a fatal design flaw: it was not based on real transactions but on estimated borrowing costs voluntarily reported by a few banks daily. This flaw was exposed during the 2008 financial crisis when traders from several major global banks systematically manipulated LIBOR rates to benefit their derivative positions, leading to its abolition and replacement by SOFR.

The design of SOFR essentially represents a 'reverse engineering' of LIBOR's flaws, relying on actual trading volume rather than self-reported estimates. It utilizes the weighted median of trading volumes from three repurchase markets: tripartite repurchases, GCF repurchases, and bilateral repurchases settled through FICC's DVP service. This results in a broad, deep market with minimal risk of manipulation, managed by the New York Fed and adhering to IOSCO benchmark principles to ensure no conflict of interest between managers and the priced market.

However, SOFR has an inherent limitation as an overnight rate lacking a maturity structure. The market requires not only the 'overnight cost today' but also the 'expected funding cost over the next three months' to properly price medium- and long-term loans. Consequently, CME introduced CME Term SOFR, a forward-looking interest rate covering four maturities: 1 month, 3 months, 6 months, and 12 months. By analyzing trading data of SOFR futures, CME infers market expectations regarding the future path of SOFR, constructing a forward-looking maturity curve. In the fourth quarter of 2023, the representative notional volume of SOFR futures used to construct Term SOFR was approximately $2.3 trillion per day.

Analyzing current market candidates reveals why many are unsuitable as benchmarks. The perpetual funding rate is an implicit price of leverage determined by the spread between spot prices and perpetual contract prices, functioning essentially as an overnight rate without a maturity structure. When spot markets for TradFi assets are closed, such as on weekends for stocks and precious metals, exchanges cannot obtain real spot prices to calculate the funding rate. 币安 addresses this by freezing the index price at the last available spot price and using an EWMA marker price with a ±3% upper limit, while Hyperliquid also switches to EWMA on weekends and sets volatility upper limits for different assets. During closed periods, the 'anchor' for perpetual contract prices is a predicted value rather than an actual trading price. When the market reopens and actual prices deviate significantly from these limits, limit-up or limit-down orders occur, proving that prices during closed periods are predictions, not real arbitrage anchors.

On May 29, 2026, the US CFTC approved KalshiEX's Bitcoin perpetual contract (BTCPERP), marking the first truly regulated Bitcoin perpetual contract in the United States. Simultaneously, the CFTC issued policy statements regarding perpetual contracts, staff guidelines for 24/7 trading and liquidation, and a no-action decision regarding Coinbase's provision of perpetual contracts through Deribit. This development is significant because a regulated perpetual contract cleared by a central counterparty generates funding rates and spreads in a compliant and liquidated environment, making it an ideal candidate for a future 'crypto SOFR.' Together with the CFTC's review of the Hyperliquid–S&P Global index collaboration, this indicates that regulation is moving closer to establishing crypto benchmarks. In contrast, the native dollar-denominated financing market in the crypto world, exemplified by Bitfinex, operates as a peer-to-peer secured financing market where lenders provide funds to margin traders in exchange for interest.

A key aspect of Bitfinex's design is that the financing period ranges from 2 to 120 days, commonly 2 days, 7 days, or 30 days, requiring both the interest rate and financing period to match when a transaction is executed. This results in Bitfinex's financing market naturally forming a real lending curve spanning short to long maturities, where money with a 30-day maturity and money with a 120-day maturity have different prices determined by actual supply and demand. This is one of the few real lending markets in the crypto world that naturally possesses a maturity structure. The Flash Return Rate (FRR) serves as the reference interest rate for this market, calculated by weighting all active fixed-rate financings based on their scale and updated hourly. Essentially, FRR is the 'Bitfinex version of the benchmark reference rate,' reflecting the current average lending cost. Lenders can choose to offer loans at the FRR rate, allowing their interest rates to automatically reflect market conditions. Bitfinex charges approximately 15% in fees on lending earnings, or 18% for hidden orders, with a minimum order amount of $150.

FRR is quoted on a daily basis and annualized accordingly; the FRR rate for Bitfinex USD is approximately 0.0136% per day, or 5.1% annually, roughly on par with other candidates such as tokenized government bonds, Aave, and SSR. The critical factor is FRR's volatility, with the historical range of USD lending rates fluctuating dramatically from 3% to 20% APR, strongly correlated with leverage demand. This daily interest rate curve, spanning maturities from 2 to 120 days, forms the native dollar financing curve in the crypto world with a real maturity structure.

However, Bitfinex and Tether both belong to the same parent company, iFinex, with overlapping management teams. As a result, Bitfinex boasts the highest liquidity of USDT in the entire crypto world, contributing to the depth of its financing market. Yet, this structure concentrates counterparty risks and stablecoin issuer risks within the same entity. Borrowing money through Bitfinex, using its matchmaking services, pricing in USDT, and having the same parent company provide backing in extreme situations creates a highly self-contained structure. Although Bitfinex's financing market is the oldest and deepest native dollar financing market in the crypto world, its absolute scale remains much smaller compared to the trillions of dollars in trading volume of the aforementioned perpetual markets.

When comparing FRR with LIBOR and SOFR, FRR is cleaner in terms of being based on real transactions, calculated by weighting all actual fixed-rate financings based on their scale.

However, FRR originates from the trading activities of a single exchange operated by the same parent company, iFinex, which also controls the largest stablecoin, Tether, creating a conflict of interest.

Moreover, this same operator acts as the lender of last resort for this market, further increasing concentration and potential for conflicts. Therefore, in terms of concentration and conflict of interest, FRR faces the same problems that SOFR aimed to address. Other mechanisms include pricing based on algorithmic utilization, where interest rates are automatically calculated based on the utilization rate of the fund pool using a predefined formula. On Aave's mainnet, the USDC deposit interest rate varies between approximately 3.5% and 6% depending on the utilization rate, while on Morpho, USDC vaults managed by curators yield approximately 5% to 7% after deducting curator fees. These are 'policy-like interest rates' directly set by protocol governance. DAI's DSR and USDS's SSR function similarly to a policy interest rate set by a central bank, decided through governance votes on Sky's platform rather than market matching or algorithmic utilization.

The governance-based setting of DSR/SSR, the market-weighted calculation of FRR, and the algorithmic utilization-based calculation of Aave's interest rates represent three completely different mechanisms, each with credibility issues and manipulation risks. A mature market benchmark should ideally come from the mechanism least susceptible to manipulation: a market-weighted average of real transactions from a broad and deep market. Currently, in April 2026, the SSR rate was lowered by governance from 4.75% to approximately 3.6% to 3.75%, following the path set by the Federal Reserve. The circulation volume of USDS is approximately $11 billion, representing a 'risk-free component' with a yield of approximately 4% to 5%, making it a viable candidate for a 'crypto risk-free benchmark.' Platforms like BlackRock's BUIDL and Franklin Templeton's BENJI bring the coupon income of US Treasury bonds onto the blockchain. Currently, the main tokenized government bond tokens, such as BUIDL, USDY, USDM, and USYC, are paying approximately 4.1% to 4.7% in annualized yields in April 2026, closely mirroring the yield of 3-month US Treasury bonds. Their yields can almost directly be compared to traditional risk-free interest rates.

The secondary market pricing of these tokenized government bonds is very tight. For example, during the period from February to April 2026, the trading prices of Ondo's tokenized government bonds deviated from the median by only approximately 2 basis points, and 95% of the trades fell within 5 basis points of the median. This demonstrates that when underlying assets are standard and virtually risk-free, price discovery on the blockchain can be highly accurate. In contrast, high-risk products like perpetuals have highly predictive prices during closed periods; the lower the risk, the more accurate the price, while the higher the risk, the more speculative the pricing becomes. Another category includes securitization products combining the perpetual funding rate with returns from collateral. Their annualized yield depends heavily on the funding rate level in the perpetual market, making them essentially a repackage of the implied interest rate rather than a benchmark in itself.

If we consider these seven candidates, each measures something different: leverage sentiment, real lending activities, algorithmic utilization, governance policies, risk-free coupon income, and institutional arbitrage opportunities. They carry different types of risks, including liquidation risks, counterparty risks, smart contract risks, governance risks, and credit risks, and are all priced by different entities. None of them meets all three criteria of 'broad scope, maturity structure, and independent governance.' The current state of crypto benchmark interest rates is that none can serve as a single, reliable anchor. If we place these candidate interest rates on the same or comparable maturities and compare them side by side, we can get a snapshot of their values at a specific point in time. Let us take Bitfinex's FRR as an example. Currently, its annualized rate is approximately 5%, which is roughly on par with tokenized government bonds (~4.5%), Aave (~4% to 5.5%), and SSR (~3.6%), with a very narrow spread. At first glance, FRR seems unremarkable and similar to other candidates.

However, the real danger with FRR lies not in its high volatility but in its behavior during stress. The historical range of USD lending rates has fluctuated drastically, ranging from 3% to 20% APR. During periods of stability, FRR converges towards the risk-free interest rate, but during times of high leverage, high demand, or market stress, it can soar rapidly.

Using such an interest rate as the pricing anchor for the entire market means that the anchor itself will experience significant fluctuations at exactly the times when stability is most needed. In traditional finance, if two instruments reflect the same risk but have different interest rates, arbitrageurs will quickly enter the market to narrow the spread.

However, in the crypto world, the spread itself represents a structural risk determined by market forces. A working paper by the BIS pointed out that the carry amount in the crypto market can become extremely large, sometimes exceeding 40% per year, and can fluctuate dramatically over time. During periods of stress, this carry amount can reverse sharply. For example, during the collapse of FTX, the carry amount associated with CME's products once dropped below -50%. Crypto exhibits negative carry benefits, where investors prefer holding futures rather than spot assets, which is the exact opposite of the commodity market. This phenomenon is similar to what happens in some government bond markets where balance sheet constraints make derivatives more attractive than holding spot assets. The reason crypto carry benefits are large and not eliminated by arbitrage is that regulated capital finds it difficult to hold spot assets and can only participate in the market through futures.

Additionally, arbitrage capital is scarce due to margin and liquidation risks.

Woofun AI analysis suggests that judging from regulatory trends and capital flows, the possible future combinations could involve tokenized government bonds serving as the foundation for the risk-free component, combined with a maturity curve formed by CME's spreads, Bitfinex's maturity structure, or on-chain interest rate swaps. Alternatively, a governance-neutral aggregate index could emerge. The logic behind the first approach is that the risk-free component should naturally be anchored by assets that are closest to being risk-free, while the maturity curve should be constructed by combining existing sources with a maturity structure. The logic behind the second approach is that instead of relying on a single source, it is better to create a neutral aggregate index that avoids concentration. This marks a critical juncture where the industry must decide whether to consolidate around a single, potentially flawed entity or build a composite standard that reflects the true diversity and depth of the crypto financial ecosystem. The path forward will likely require a hybrid model that leverages the regulatory clarity of CFTC-approved instruments, the liquidity depth of established exchanges like 币安, and the risk-free nature of tokenized Treasuries offered by institutions like BlackRock. Without such a unified framework, the trillions of dollars in leveraged positions will remain exposed to the whims of fragmented, non-standardized pricing mechanisms, perpetuating the systemic risks that have plagued the sector since its inception.