Analyzing 43,000 Hyperliquid Accounts: Unveiling the Profit Systems of 12 Top Traders

Author: Minara AI

Compiled by: Luffy, Foresight News

In the past week, we conducted research on the Hyperliquid trading leaderboard to answer a key question: What is the most frequently used trading strategy among accounts that are actually profitable?

The answer is far from as simple as "buying quality coins early." Among the 12 top accounts we selected, the most mainstream pattern leans towards a complete trading system: 8 accounts belong to high turnover, bilateral execution traders; 3 are active day traders / ultra-short-term traders; and only 1 is a unilateral heavy trend trader.

The truly valuable signals come from the complete behavioral characteristics of addresses in the market: trading rhythm, balance of long and short positions, turnover rate, concentration of holdings, selection of trading targets, and the level of returns generated per unit of risk.

Screening Process: From 43,618 Addresses, 1,681 Eligible Candidate Addresses Were Identified

The entire screening process consists of 5 steps:

1. Export complete leaderboard CSV data. Import all 43,618 account records, including address, ranking, nickname, account net worth, as well as 1-day, 1-week, 1-month, full-cycle profit and loss, return rate, and total trading volume, using a complete snapshot sample rather than manually selected small samples.
2. Eliminate low-quality samples. Retain accounts that meet all the following conditions: account net worth of at least $10,000, positive full-cycle profit and loss and return rate, historical cumulative trading volume ≥ $1 million, monthly trading volume ≥ $100,000. Filter out accounts that rely on small funds for high returns, long-dormant wallets, and those that profit from a single stroke of luck.
3. Verify the sustainability of recent performance. Compare accounts' profit and loss and return rates across four time dimensions: 1-day, 1-week, 1-month, and full-cycle, focusing on weekly and monthly performance. Even if historical performance is impressive, if recent profitability has ceased, such accounts will not be retained.
4. Construct a comprehensive and robust scoring system. Score each address based on full-cycle profit and loss, full-cycle return rate, account net worth, cumulative trading volume, monthly trading volume, and the number of recent profitable cycles. Multi-index weighted evaluation can avoid data distortion caused by relying on a single ranking dimension.
5. Determine trading strategies based on transaction details. For high-scoring top accounts, retrieve Hyperliquid's public transaction records, tally their trading targets, trading frequency, whether they execute buy and sell operations simultaneously, nominal transaction scale, and trading concentration, analyzing not just "who made money," but digging deeper into "how they made profits."

Through this screening mechanism, we ultimately identified 1,681 profitable candidate accounts, from which we selected 12 high-scoring addresses for in-depth analysis of their transaction details.

This research method serves only as an approximate deduction. The CSV file provides snapshot data for different periods, not a complete daily net worth curve. We cannot prove that a particular account can achieve stable compound interest for an entire year. However, compared to solely relying on leaderboard rankings, the screening criteria this time are more stringent: positive profit and loss, positive returns, sufficient account funds, effective trading volume, sustainable profitability, along with observable real trading behavior.

The strategy distribution among the 12 accounts is 8-3-1. More importantly, the differences among the three types of strategies are not just about trading speed; their underlying logic for profitability is entirely different.

Type One: High Turnover, Bilateral Execution Traders (8 Addresses)

The 8 accounts generated a total of 16,000 transaction records, with a total nominal transaction amount of $51.37 million. The overall order flow is almost perfectly balanced: buy transactions account for 49.4%, and sell transactions account for 50.6%.

In this sampled transaction segment, 6 of the 8 accounts ultimately achieved positive net profits upon closing, collectively realizing a net profit of $156,464.

These data represent a strategy centered on trading throughput: the profit per transaction is negligible relative to the transaction scale, but the accounts repeatedly execute this trading logic thousands of times. This type of strategy does not rely on significant market fluctuations; it only needs to maintain a slight execution advantage across a large number of trades.

Based solely on public transaction records, we cannot confirm that these addresses are market makers. The research cannot access order book records, identities of takers/makers, complete inventory positions, or hedging operations in other markets. However, observable trading behaviors align with the following various trading technique characteristics:

• Simultaneously quoting and trading in both directions in the market;
• Capturing small buy-sell spreads or brief price deviations;
• Timely reducing positions after short-term unilateral trends;
• Short-term mean-reversion trading;
• Cross-asset, cross-market hedging operations.

We selected 3 addresses to showcase different variants of this operational model:

• 0xe4c6ae25959d7fc66cf2dd5965fb78c5e09c4048 returned 2,000 transaction records, with a total nominal transaction amount of $24.92 million, and a net profit of $113,079 upon closing, yielding a return of 45.4 basis points. Bitcoin accounted for 69.2% of the observed transaction amount, with buy transactions making up 56.7%. This account tends to execute large order trading strategies in the most liquid markets.
• 0x523852be2db1a76a0e088ecbff32e849544054e5 (account name: perpfumbler) follows the same high turnover model across multiple targets including Bitcoin, S&P 500 index contracts, HYPE, and XYZ100 index contracts. The sampled nominal transaction scale is $12.27 million, with a net profit of $28,864 upon closing, yielding a return of 23.5 basis points, with buy transactions accounting for 43.4%. This account does not bet on the rise or fall of a single asset but reuses this high-frequency turnover trading model across multiple markets.
• 0x399965e15d4e61ec3529cc98b7f7ebb93b733336 is the fastest sample account. The time span for returning 2,000 transaction records is only about 20 minutes, with a median interval of 0.21 seconds between two transactions; the order flow has buy transactions at 49.85% and sell transactions at 50.15%. The sampled nominal amount is $1.44 million, with a net profit of $2,187 upon closing, yielding a return of 15.2 basis points.

The three accounts differ in trading varieties and single-order scales, but their underlying profit logic is highly consistent: seeking small trading advantages, strictly controlling exposure to achieve bilateral trading, and continuously executing.

Type Two: Active Day Trading and Ultra-Short-Term Trading (3 Addresses)

The 3 accounts also trade frequently, but do not exhibit the characteristics of bilateral balance. The order flow is significantly skewed towards one side, and profit and loss performance is more dependent on short-term price fluctuations.

The 3 accounts collectively returned 5,071 transaction records, with a total nominal transaction amount of $15.35 million, and a weighted buy proportion as high as 70.1%. Although these three accounts achieved a total profit of $61.43 million on the leaderboard over the full cycle, the sampled transaction segment showed negative net profits upon closing.

This data contrast is crucial: the accounts overall are profitable, but the recent sampled transactions have not consistently earned small execution profits like the bilateral trading group; profitability shows a characteristic of stage-wise explosions. Unilateral day traders may incur losses during a trend and then recover profits based on subsequent price movements; while profits from market-making strategies are evenly distributed across each turnover trade.

The three accounts exhibit different characteristics of day trading:

• 0x8c625ff57d8a4374784c7eff585dfdc42ccec974 is highly concentrated on DOGE, which accounts for 93.0% of the sampled transaction amount. The interface returned 1,071 transaction records over a time span of 23.35 days, with buy transactions accounting for 30.1% and sell transactions for 69.9%. This account's behavior does not lean towards neutral liquidity provision but resembles repeated unilateral trend trading within a single high-volatility target.
• 0x77375a8c9d13bf79afb2a87f1b0ac1dfd5f5bf66 includes trading targets such as ETH, SOL, PUMP, and BTC, but 94.7% of the sampled transaction records are buy orders. The nominal transaction scale is $14.09 million, with a segment closing loss of $142,648; however, the account's full-cycle profit reaches $47.06 million. This observed record may represent an aggressive accumulation of chips, external position hedging operations, or one of the loss branches within the entire profit strategy.
• 0xc926ddba8b7617dbc65712f20cf8e1b58b8598d3 has smaller single transaction amounts, averaging about $161 per transaction. Among the 2,000 returned transaction records, buy transactions account for 67.1%, and the trading model belongs to fast short-term or short-term unilateral trend systems; this sampled segment incurred a loss of $14,572.

The common feature of this group of accounts is not merely high-frequency trading, but high-frequency trading combined with unilateral position imbalance. This strategy requires both trading execution advantages and relies on price fluctuations to generate market movements.

Type Three: Heavy Unilateral Trend Trading (1 Address)

Among the 12 accounts, only 1 address belongs to the heavy unilateral trading type.

0x862dd8e68f30693e3d3c9daa42a440bc6d2a1f0c returned only 14 transaction records over a period of 12.05 days, all of which were buy orders, and all transactions were for the same target. The observed nominal transaction amount is $18,504, and this segment did not achieve any closing profit or loss.

This account's full-cycle profit reaches $6.45 million, but the public transaction data cannot prove that this long-term profit comes from these 14 pending orders. Observable behavior can only indicate that during the sampling period, this account has been accumulating heavy positions rather than rolling trades around short-term inventory.

From the transaction data, unilateral trend strategies exhibit these characteristics: low trading frequency, one-way opening, high concentration on targets, and profits depend on subsequent price increases to be realized rather than relying on frequent turnover for immediate gains.

Although this type of strategy can generate enormous profits, it is a minority among this batch of top accounts that balance profitability stability, capital size, and trading activity.

Target Selection Serves Trading Strategies

These profitable accounts do not have a unified preference for any specific coin; market selection entirely depends on the type of trading advantage the trader wants to capture.

BTC, ETH, and SOL account for the bulk of the observed nominal transaction amounts: these markets can accommodate large orders, have ample liquidity, and facilitate quick opening and closing. HYPE, PUMP, xyz:SKHY, and xyz:CRCL have a relatively higher number of transactions compared to their transaction amounts, indicating smaller individual orders and faster capital turnover.

The difference between the two is significant; the average transaction scale for BTC is about 8 times that of HYPE; the average transaction amount for S&P 500 contracts is the highest, while xyz:CRCL has a low average transaction scale.

For the high turnover bilateral trading group, the transaction amount for Bitcoin is $21.66 million, followed by ETH, S&P 500 contracts, HYPE, xyz:SKHY, and xyz:CRCL. These accounts will accept large orders in deep market coins while seeking more concentrated short-term trading opportunities in smaller coins.

The day trading group's holdings are more concentrated in ETH, SOL, PUMP, BTC, and DOGE, with an asset mix that meets the needs of capturing short-term trends and volatility rather than merely pursuing market depth.

The truly valuable conclusion of this research is not that profitable accounts all prefer Bitcoin, but that the choice of coins itself is part of strategy design: throughput trading strategies require sufficient liquidity; short-term strategies need enough price volatility; unilateral heavy trading strategies only require traders to have strong confidence in market judgments for a single market.

The True Commonality Among Profitable Accounts

The long and short judgments of the 12 top accounts vary, the trading targets differ, and the trading time periods are entirely different.

What truly distinguishes the profit gap is the way profits are generated. Bilateral trading accounts earn about 30.5 basis points of thin profits through a turnover scale of $51.37 million, with their trading advantages being slight, repeatable, and reliant on systematic execution. Day traders accept higher unilateral exposure, with short-term profit fluctuations being larger and profit and loss results being chaotic. The last type of account concentrates all risks in a single market, patiently waiting for market movements to realize profits.

Thus, the most mainstream strategy among these profitable accounts is not simply high-frequency trading. Instead, it is a high turnover, bilateral execution trading system that, under the premise of controlling position sizes, earns tiny trading advantages thousands of times.

This also means that merely copying trades without understanding does not hold much significance; position sizes are just one outcome of the trading system's output, and the truly complete strategy lies in trading rhythm, buy-sell balance, order sizes, market selection, capital turnover rates, and the entire risk cycle management.

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