Data Research: How Big Is the Liquidity Gap Between Hyperliquid and CME Crude Oil?

_Original Author / _Castle Labs

Translated by / Odaily Planet Daily Golem

Editor’s Note: This article systematically examines the differences in crude oil futures contract trading data between Hyperliquid and CME across weekday and weekend sessions, and draws several important conclusions. At present, Hyperliquid still cannot match CME on absolute metrics such as liquidity depth and slippage; overall liquidity is below 1%, which is consistent with the fact that the main users of RWA trading platforms remain crypto-native retail traders.

_What distinguishes Hyperliquid is that the trading volume of crude oil contracts on Hyperliquid increases noticeably during weekend sessions. __This suggests that, on weekends, besides retail traders with speculative demand, traders who want to obtain crude oil trading exposure before Monday and carry out hedging also trade on Hyperliquid. __Moreover, this trend is becoming more and more pronounced, meaning Hyperliquid already has price discovery capabilities for major 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-level orders in a timely manner, it will only be a temporary trading venue for traditional traders on weekends—ultimately becoming only a small supplement to the traditional financial landscape. _

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 contracts and the Chicago Mercantile Exchange (CME) contract CLJ6 (April 2026 NYMEX WTI crude oil futures).

The CME data comes from the Databento trading data source. This dataset captures trade-by-trade execution data rather than order book snapshots. Therefore, all CME depth and slippage estimates are based on actual executed volume rather than quoted depth. The Hyperliquid data comes from Hyperliquid’s publicly available S3 database, which contains complete on-chain execution records.

Therefore, the analysis of both trading venues is based on actual executed volume. All depth data represents visible liquidity, meaning the traded volume within a specific basis-point range inside a 5-minute window around the VWAP mid-price, rather than the full passive depth shown on the order book.

Research Period and Market Background

The research period runs from February 27, 2026 to March 16, 2026. During this timeframe, the geopolitical situation was unsettled after Iran launched attacks on February 28, 2026.

• Market close before the attack: the last CME trading day before the attack.
• Monday open: the reopening faced enormous pressure; the CME stock price gapped up sharply at the open, while the Hyperliquid xyz:CL market was constrained by the price discovery boundary.
• The following weekends: with oil prices staying high, market volatility kept the crude oil trading volume on the Hyperliquid platform elevated.

xyz:CL launched at the beginning of 2026, meaning that these three weekends’ observation windows encompass the early maturation stage of the Hyperliquid market. The trends observed—improving liquidity depth, increasing trading volume, and growing user numbers—partly reflect market maturation. But we believe that, at present, on absolute metrics such as liquidity depth or slippage, on-chain exchanges like Hyperliquid still cannot compare with traditional exchanges.

Our research goal is to track directional trends: whether the two parties’ price spreads are narrowing, how fast they narrow, and under what conditions they narrow.

Data Analysis

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

• Weekday sessions: covering the full three-week period, comparing the depth, slippage, and the premium/discount of trades executed on Hyperliquid versus CME during the overlapping active weekday sessions. For Hyperliquid, we also analyze its funding rates over the entire period.
• Weekend sessions: within a given timeframe, covering three weekends, we analyze price discovery and the deviation of the price gap between Hyperliquid and CME relative to CME’s opening price.

Weekday Session Data Analysis

This analysis covers the full three-week period and focuses on the time intervals when both exchanges are simultaneously active.

Liquidity depth is measured as the dollar trading volume within the VWAP mid-price ±2, ±3, and ±5 basis-point ranges for each 5-minute interval, then summarized as the median across all weekday intervals. As mentioned above, this reflects traded volume within the range, not the full passive order-book depth. This methodology may underestimate the liquidity depth on CME and Hyperliquid.

Execution slippage is estimated using a synthetic order book constructed by sorting executions by execution price. Within each 5-minute time interval, the observed taker execution records are sorted in ascending order by price (simulating sell-side market orders), and then sell-side orders are walked through sequentially until the target order size is reached. The arrived price is set as the lowest execution price in that time interval (representing the best sell price when the order arrives). Slippage is calculated as the difference between the execution volume-weighted average price (VWAP) and the arrived 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 across all weekday session 5-minute windows. This can capture any structural premium or discount of Hyperliquid relative to CME’s reference price during active periods. The Hyperliquid mid-price is derived from the volume-weighted average price (VWAP) of executions within each 5-minute trading interval, not from real-time order book quotes.

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

Weekend Session Data Analysis

This analysis focuses on CME’s three distinct weekend market-closure windows:

• W1：February 28 to March 1, 2026
• W2：March 7 to March 8, 2026
• W3：March 14 to March 15, 2026

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

For each weekend window, we report key metrics for Hyperliquid xyz:CL, including price, traded volume, and number of trades. To measure the deviation of the Monday opening spread, 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. Positive values mean Hyperliquid is above CME’s opening price, and negative values mean a discount.

Quantitative Analysis

This section first conducts an analysis comparing the liquidity of the Hyperliquid xyz:CL CL HIP-3 crude oil market and NYMEX CLJ6 during overlapping weekday trading intervals.

Liquidity Depth: Less Than 1% of CME

Without a doubt, the liquidity conditions of on-chain exchanges are fundamentally different from CME. Hyperliquid’s average liquidity depth for CL is less than 1% of CLJ6, and liquidity depth is consistent across price intervals (109x at ±5 bps). In the mid-price ±2 bps range, CME’s executable depth is $19 million, while Hyperliquid is only $152k—an approximately 125x difference.

Given Hyperliquid’s market novelty and the differences in its target user base, this outcome is not surprising. The main value of on-chain exchanges is to provide permissionless trading access to users who are traditionally excluded from institutions like CME.

However, as weekend trading volumes on DEXs like Hyperliquid grow, people’s perception of these platforms is starting to change. Institutional investors are increasingly interested in hedging positions during non-trading hours; therefore, for Hyperliquid, creating a market environment suitable for traditional investors and retail traders is becoming ever more important.

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

In fact, the inherent differences in the user base are reflected in the median trade sizes during these overlapping market intervals.

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

We expect that as these markets become increasingly legitimized in the eyes of more traditional investors and capital flows shift to on-chain platforms, the median trade size in Hyperliquid’s commodities market will reach an inflection point.

To further distinguish trades of different sizes, we ran order simulations with order size caps ranging from $10k to $1M.

For a $10k order, CLJ6 traders have no slippage, which aligns 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: at that level, Hyperliquid users’ slippage rises to 4.33 basis points, approaching the 5-bps threshold, while CME CLJ6 still has no slippage.

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

At a $1M trade size, 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-level orders. Considering Hyperliquid’s average trade size, the platform could provide users with equally high-quality service without generating slippage.

Significant slippage starts to appear for CLJ6 orders at around a $500k trade size, affecting execution.

When we extend the order-size analysis to weekend sessions, 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 declines were as follows:

• $10k: -16%
• $100k: -75%
• $1M: -86.9%

Funding Rates

CL’s funding rate fluctuates more during CME’s closing period, but less during the delivery period. This helps us reveal the internal pricing dynamics of the market during non-trading hours. Weekend openness means the CL market can use internal price discovery mechanisms (supported by DB and other risk-reduction mechanisms). Therefore, funding rates are expected to be more volatile, as highlighted below.

During active trading sessions, Hyperliquid’s xyz:CL closely follows CME’s CLJ6走势, but as oil prices rise, structural discounts form and widen. This is very likely due to funding-rate pressure caused by accumulated long positions. During weekends, CME is closed, and Hyperliquid’s price discovery is further constrained by the price range mechanism (DB). Without a real-time reference market, this mechanism limits the volatility range of the mark price.

Weekend-only analysis: Hyperliquid has already had price discovery capability

These three weekends show a rapid maturation process for the Hyperliquid market:

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

Prices on Hyperliquid rose from around $67.29 on CME to about $70.80, representing about 45% of the Monday’s final gap-up to $75 (+1146 bps).

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

This was not a “mistake” or “failure,” but risk protection implemented through market design. Therefore, from a data perspective, the correlation on the first weekend was the lowest. Nevertheless, it highlights that xyz:CL reacted to the initial shock from the Iranian airstrikes, and also recognized the importance of DB as a weekend price-discovery mechanism, especially for an emerging market.

W2：March 7 to March 8, 2026

The second weekend is the real test, because xyz:CL touched the boundary price of the range toward the market close. CLJ6’s opening price was $98 (up 737 bps from the $91.27 close), while xyz:CL peaked at about $95.83, capturing only 68% of the upside.

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

W3：March 14 to March 15, 2026

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

Convergence of xyz:CL and CLJ6 performance was at its best across this weekend: up 226 bps versus CME’s close, slightly higher than 62 bps above Monday’s open. CLJ6’s Friday close was $99.31, opening at $100.93 (up 163 bps), while xyz:CL’s opening price was $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 the DB price discovery mechanism (weekend 1 and weekend 2) to a phase where price discovery becomes increasingly freer, accompanied by overshoots and pullbacks (weekend 3).

Analyzing price deviation errors at different intervals before the CME open—3 hours, 1 hour, and 0 hours—shows that the W3 data is the most reliable. In the first two weekends, the xyz:CL market was affected by DB. In W3, xyz:CL’s errors at 3 hours and 1 hour before CME’s open were approximately +70 and -139 bps, indicating that its price discovery capability is better than 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 show sustained growth over several consecutive weekends.

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

In addition, the total number of trades increased from 26k in the first weekend to over 700k in the third weekend.

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

The first weekend’s average trade size was $1,199, growing to over $1,500 by the third weekend.

This could indicate that the user base using the platform on weekends has changed: retail users decline, while more traders need to obtain crude oil trading exposure before Monday, so weekend trading is more about hedging needs than speculation.