Original Title: 432 Hours of Hyperliquid Oil Market Data: A Microstructure Comparison with CME WTI Futures

Original Source: Castle Labs
Original Compilation: Golem, Odaily Planet Daily

Editor’s Note: This article systematically studies the differences in crude oil contract trading data between Hyperliquid and CME during weekday and weekend sessions, and draws several important conclusions. As of now, Hyperliquid indeed cannot match CME on absolute metrics such as liquidity depth or slippage; overall liquidity is less than 1%, which is consistent with the fact that the main users of RWA trading platforms are still crypto-native retail traders.

What makes Hyperliquid different is that the trading volume of crude oil contracts on Hyperliquid increases noticeably during weekend sessions. This suggests that besides retail traders with speculative demand, there are also traders who want to obtain crude oil trading exposure before Monday and carry out hedging who are trading on Hyperliquid during weekends. And this trend is becoming increasingly evident, meaning Hyperliquid already has price discovery capabilities for commodities.

However, for institutional investors, Hyperliquid’s high trading costs compared with CME remain the main obstacle to its expansion in the commodities trading space. If Hyperliquid does not improve its ability to handle institutional-grade orders in time, then it can only serve as a temporary trading venue for traditional traders on weekends, and ultimately can only become a minor supplement to the traditional financial landscape. The following is the original article content:

Research Methodology and Data Sources

This analysis evaluates the microstructure of the crude oil market through two studies, covering both weekday and weekend markets. It uses trade-by-trade execution data from two trading venues: Hyperliquid’s xyz:CL perpetual contract and the Chicago Mercantile Exchange (CME) contract CLJ6 (April 2026 NYMEX WTI crude oil futures).

CME data comes from Databento’s trade data feed. This data captures trade-by-trade execution data rather than order book snapshots. Therefore, all CME depth and slippage estimates are based on actual traded volume, not quoted depth. Hyperliquid data comes from Hyperliquid’s publicly available S3 database, which contains complete on-chain execution records.

Therefore, analysis for both trading venues is based on actual traded volume. All depth data represents visible liquidity: the traded volume within specific basis-point ranges in a 5-minute window around the VWAP mid price, rather than the full resting depth on the order book.

Research Period and Market Background

The research period runs from February 27, 2026 to March 16. This time frame coincides with geopolitical turmoil after Iran launched an attack on February 28, 2026.

· Market close before the attack: The last CME trading day before the attack event occurred.

· Monday open: There is huge reopening pressure; CME’s stock price gaps up significantly at the open, while the Hyperliquid xyz:CL market is constrained by the discovered boundary.

· The following weekends: With oil prices staying high, market volatility has kept crude oil trading volume on the Hyperliquid platform elevated.

xyz:CL was launched at the start of 2026, which means that these three weekends of observation cover Hyperliquid’s early maturation stage. The observed trends—including improving liquidity depth, increasing trading volume, and growing user numbers—partly reflect market maturity. But we believe that on-chain trading venues still cannot compare favorably with traditional trading venues on absolute metrics such as liquidity depth or slippage.

Our goal is to track directional trends: whether the spread between the two is narrowing, how quickly it is narrowing, and under what conditions it narrows.

Data Analysis

The data analysis is divided into two parts by time period:

· Weekday sessions: Covering three full weeks of time, comparing liquidity depth, slippage, and the premium/discount of trades executed on the two trading platforms during overlapping weekday sessions. For Hyperliquid, we also analyze its funding rates over the entire time period.

· Weekend sessions: Within a given time period, including three weekends, we analyze price discovery and the deviation of the price gap between Hyperliquid and the CME opening price.

Weekday Session Data Analysis

This analysis covers three full weeks of time and focuses on the time periods when the two trading platforms are simultaneously active.

Liquidity depth is measured as the dollar trading volume within ±2, ±3, and ±5 basis-point ranges around the VWAP mid price in each 5-minute interval, and then summarized as the median across all weekday intervals. As described above, this reflects trading volume within the interval rather than the resting quoted order-book depth. This method may underestimate the liquidity depth of CME and Hyperliquid.

Execution slippage is estimated using a synthetic order book constructed by sorting trades by execution price. Within each 5-minute time interval, the observed aggressive-side execution records are sorted in ascending order by price (simulating taking sell orders), and then walk through sell orders sequentially until the target order size is reached. The arrival price is set as the lowest execution price observed within that time interval (representing the best sell price at the time the order arrived). Slippage is calculated as the difference between the execution volume-weighted average price (VWAP) and the arrival price, expressed in basis points. This method is applied to incremental order sizes ranging from $10k to $1M.

Weekday-session Hyperliquid–CME basis: track the signed price difference between the Hyperliquid mid price and CME’s latest price within every 5-minute window of all weekday sessions. This can reflect any structural premium or discount that Hyperliquid exhibits relative to the CME reference price during active trading periods. The Hyperliquid mid price comes from the volume-weighted average price (VWAP) of trades within each 5-minute trading interval, not from real-time order book quotes.

Hyperliquid funding rates are quoted hourly, with funding rates expressed in basis points per hour.

Weekend Session Data Analysis

This analysis focuses on three distinct CME weekend exchange closures:

· W1: February 28, 2026 to March 1, 2026

· W2: March 7, 2026 to March 8, 2026

· W3: March 14, 2026 to March 15, 2026

During W1 and W2, Hyperliquid perpetual contracts are constrained, so the mark price cannot exceed the “range limit boundary” (DB). When the oracle price is frozen (e.g., when CME is closed and external price data sources stop updating), the protocol effectively confines the price within a narrow interval.

For each weekend window, we report key metrics for Hyperliquid xyz:CL, including price, volume, and number of trades. To measure Monday opening spread deviation, for each weekend we measure the price gap between Hyperliquid and CME at three reference points:

3 hours before CME reopens / 1 hour before CME reopens / at CME open (T=0)

All spreads are expressed in basis points. A positive value means Hyperliquid is above the CME opening price, and a negative value indicates a discount.

Quantitative Analysis

This section first analyzes and compares the liquidity of the Hyperliquid xyz:CL WTI crude oil market versus the NYMEX CLJ6 during overlapping weekday trading hours.

Liquidity Depth: Less Than 1% of CME

There is no doubt that the liquidity conditions on on-chain trading venues are fundamentally different from CME. Hyperliquid’s average liquidity depth for CL is less than 1% of CLJ6’s, and the liquidity depth is consistent across price levels (109x at ±5 bps). In the mid price ±2 bps range, CME’s executable depth is $19.0 million, while Hyperliquid is only $152k—an 125x difference.

Given Hyperliquid’s novelty as a CL market and the different target user base, this outcome is not surprising. The main value of an on-chain trading venue is to provide a permissionless trading channel for users who are traditionally excluded from CME and other institutions.

However, as weekend trading volumes on DEXs such as Hyperliquid grow, perceptions of these platforms are starting to shift. Institutional investors’ interest in hedging positions during non-trading hours is increasing. Therefore, for Hyperliquid, it becomes increasingly important to cultivate a market environment that suits traditional investors and retail traders.

For retail traders with trading notional of $10k, this cost difference is negligible. But for institutional investors with trading notional exceeding $1M, the on-chain trading costs of CL (and most other markets) remain difficult to bear.

In fact, the inherent differences in the user base are reflected in the median trade size during the overlapping time windows.

The clearest proof of the fundamental differences in the user groups served by these trading venues is the 166x disparity in median trade size (90,450 USD vs 543 USD). CLJ6’s median trade size is comparable to a standard crude oil futures contract (based on the current price, nominal value is about $94k), while Hyperliquid’s median trade size is $543, reflecting leveraged directional bets by crypto-native retail traders.

We expect that as these markets become increasingly legitimate in the eyes of more traditional investors and capital shifts onto the chain, Hyperliquid’s commodity market median trade size will reach an inflection point.

To further distinguish between different trading sizes, we ran order simulations with upper limits on order size ranging from $10k to $1M.

For a $10k order, CLJ6 traders experience no slippage, which is consistent with expectations, while Hyperliquid users’ median execution slippage is below 1 basis point, at 0.77 basis points. The gap appears at the $100k order size, where Hyperliquid users’ slippage rises to 4.33 basis points, approaching the 5-basis-point threshold, while CME CLJ6 still has no slippage.

Notably, this is higher than the median trade size in the CLJ6 market ($90,450).

At a trade size of $1M, Hyperliquid’s 15.4 basis points is about 20x CME’s 0.79 basis points, confirming that this venue currently lacks the capability to handle institutional-grade orders. Considering Hyperliquid’s average trade size, the platform should be able to provide users with equally high-quality service without incurring slippage.

CME CLJ6 orders only begin to show meaningful slippage around a $500k trade size, affecting execution.

When we expand the order-size analysis to weekends, slippage declines across all order sizes, especially for $100k and $1M orders, indicating that the market has matured. Over the three weeks analyzed, the simulated slippage decreased as follows:

· $10k: -16%

· $100k: -75%

· $1M: -86.9%

Funding Rates

CL’s funding rate fluctuates more during CME close sessions but less during delivery sessions. This helps us reveal the market’s internal pricing dynamics during non-trading periods. Weekend opening means the CL market can leverage internal price discovery mechanisms (supported by DB and other risk-reduction mechanisms). Therefore, funding rates are expected to fluctuate more, as highlighted below.

During active trading sessions, Hyperliquid’s xyz:CL is closely correlated with CME’s CLJ6 trajectory, but as oil prices rise, structural discounts emerge and widen. This is very likely caused by funding-rate pressure accumulated from long positions. During weekends, CME is closed; Hyperliquid’s price discovery is further constrained by the price range mechanism (DB). In the absence of a real-time reference market, this mechanism limits the magnitude of price volatility in the mark price.

Weekend-Only Analysis: Hyperliquid Already Has Price Discovery Capability

These three weekends show Hyperliquid’s market quickly maturing:

W1: February 28, 2026 to March 1, 2026 (Iran attack event)

The price on Hyperliquid rose from a level near $67.29 on CME to about $70.80—roughly 45% of the jump Monday’s final gap-up to $75 (+1146 basis points).

It is particularly important to note that, due to the ±5% price range limit mechanism (DB) for trade.xyz mentioned above, price discovery during this weekend was constrained. This explains why the curve in the chart is relatively smooth and why there is a gap-up on Monday. Even so, in the first second after the paired data was published, the difference between Hyperliquid xyz:CL ($73.89) and CME CLJ6 ($75) remained within 1.5%.

This is not a “mistake” or “failure,” but rather risk protection achieved through market design. Therefore, from a data perspective, the first weekend has the lowest correlation, but it highlights that xyz:CL reacted to the initial shock of the Iranian airstrike, while also acknowledging the importance of DB as a weekend price discovery mechanism—especially for emerging markets.

W2: March 7, 2026 to March 8, 2026

The second weekend is the real test, because xyz:CL touched the range boundary price at the market’s end. The CLJ6 opening price is $98 (up 737 basis points from the $91.27 close), while xyz:CL reached a high of only about $95.83, capturing just 68% of the upside.

In the second weekend, xyz:CL captured the market trajectory better and was closer to CME’s opening price than the previous weekend.

W3: March 14, 2026 to March 15, 2026

The data for the third weekend indicates that in a relatively calm market environment, Hyperliquid can predict CME’s final opening direction more reliably.

The convergence between xyz:CL and CLJ6 trajectories on this weekend is the best: up 226 basis points versus CME’s closing price, slightly higher than Monday’s opening price by 62 basis points. CLJ6’s Friday close is $99.31, and its opening price is $100.93 (+163 basis points), while xyz:CL’s opening price is $101.56.

Overall, these three snapshots show structural changes in the xyz:CL market on the Hyperliquid platform: the market transitions from an emerging market constrained by DB price discovery (weekend 1 and weekend 2) to a market with increasingly freer price discovery, accompanied by overshooting and pullbacks (weekend 3).

When we analyze the price deviation error at different times before the CME open (3 hours, 1 hour, and 0 hours) across different weekends, we find that W3 data is the most reliable. In the first two weekends, the xyz:CL market was affected by DB. In W3, the errors for xyz:CL at 3 hours and 1 hour before CME open are approximately +70 and -139 basis points, indicating that its price discovery capability is better than in the previously analyzed weekends.

Other Metrics

We also provide additional metrics from the weekend summary analysis, including trading volume, total number of trades, and average trade size. These metrics vary across weekends and have continued to grow for several consecutive weekends.

Over the three weeks, total trading volume in the xyz:CL market increased from $31 million to more than $1 billion, reflecting growth in the number of users and the market’s final maturation.

In addition, the total number of trades increased from 26k on the first weekend to more than 700k on the third weekend.

Notably, the weekend average trade size actually increased from the median mentioned earlier to $534. The same growth trend is observed across all three weekends, which may indicate more institutional capital flowing into the market.

The average trade size on the first weekend was $1,199, and by the third weekend it grew to more than $1,500.

This may indicate that the user base using the platform on weekends changes: retail users decrease, while more traders need to obtain crude oil trading exposure before Monday. Therefore, weekend trading is more aligned with hedging needs rather than speculation.

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