Top Traders Report - June '25
📢 The "Top Traders Monthly Report - June '25'' is out now! 🚀
Featuring curated, consistently profitable traders from the Binance and Hyperliquid Leaderboards.
We'll reveal key stats and insights that distinguish top traders in this competitive arena.
Let's explore the trading elites! 💪
Top 3 Traders of the Month - Overview
June 2025 highlights its top three traders of the month as follows:
🏆 0xtyle (Hyperliquid)
🥈 Trader 0x8bf (Hperliquid)
🥉 Trader 0xbca (Hyperliquid)
June was mostly flat for majors, marked by sharp volatility. $BTC hovered around the monthly open, closing up 2.6%. $ETH and $SOL ended nearly unchanged but saw deeper swings, with $ETH down as much as 15% and $SOL over 18% at their peaks.
Despite the choppy environment, the top three traders leveraged this volatility to post significant gains. Leading was 0xtyle with $7.9M in profits, followed by 0x8bf with $4.2M, and 0xbca with $3.6M. For context, their current perp balances stand at $18.2M, $4.8M, and $94.5M respectively.
In terms of key metrics:
0xtyle closed 83 positions with the highest win rate at 77.1% and a strong profit factor of 8.5. However, his average profit-to-drawdown was the lowest at 0.75, indicating that his realized profits were smaller than the maximum drawdowns on open positions. This is likely reflected in his holding periods, as his winners were held for half the time of his losers, suggesting he tends to keep losing positions open in search of a reversal.
0x8bf was the most active with 193 closed positions and a 55% win rate. His profit factor was solid at 2.8, with a strong average profit-to-drawdown of 2.08. His holding periods were the shortest, averaging 10 hours on winners and 7 hours on losers.
0xbca closed 22 positions with a 54.5% win rate and the best metrics among the three: a profit factor of 5.5 and an average profit-to-drawdown of 4.6. This indicates he gained, on average, 4.6 times the maximum drawdown of his positions. Notably, his holding periods for winners and losers were reversed compared to 0xtyle, suggesting a strategy focused on cutting losses quickly while letting winners run.
Trader Spotlight: 0xtyle
0xtyle was predominantly long throughout June, often holding a notional exposure above $60M. Aside from a brief dip into negative PnL during the first week, his equity curve trended steadily upward. The largest drawdown occurred in the second half of the month, with realized PnL dropping over 65% from +$6M to just below +$2M. However, he fully recovered by month-end, closing June with $7.8M in profits.
Of the 83 positions closed, beyond majors, 0xtyle actively traded a variety of meme coins, including both older and more recent ones, often holding multiple positions simultaneously.
In terms of PnL by symbol, he traded 26 symbols and lost money on only four, with total losses of $396k. His trades on the majors ($BTC, $ETH, and $SOL) alone generated $3.4M, accounting for around 43% of his total profits.
Looking at the PnL distribution across closed positions, the distribution is strongly positively skewed. Winners at the higher percentiles are significantly larger than the losses at the lower end. For example, while the 95th percentile reached +$531k, the 5th percentile was -$57k, nearly one-tenth of the size, highlighting the asymmetric payoff profile of his trading throughout the month.
Trader Spotlight: 0x8bf
0x8bf closed 183 positions with an average holding period of under 10 hours. As shown in the notional exposure chart, he was in and out of the market frequently, with a long bias during the first 10 days of June before shifting to a more short-biased approach thereafter. His notional exposure typically ranged between -$20M and +$20M, with occasional spikes exceeding +$60M and -$60M.
He started the month strong, reaching $1M in profits during the first week before giving it all back and more. It was only from the second week, coinciding with his shift to the short side, that his PnL began a steady recovery, increasing to over $4M by month-end with minimal drawdowns.
Despite his high trading frequency, 0x8bf focused on just nine symbols, concentrating most of his activity on $SOL, $BTC, $ETH, and $AVAX.
His most profitable trades came from $BTC (+$1.5M), followed by $HYPE (+$1.2M) and $ETH (+$990k). The only loss came from $LAUNCHCOIN, with a negligible -$11k.
0x8bf’s PnL distribution was less positively skewed compared to 0xtyle, with 98% of his closed positions falling between -$94k and +$630k, accounting for $3.8M, or around 90% of his total profits for the month.
Trader Spotlight: 0xbca
Contrary to the other two traders, 0xbca frequently maintained a hedged stance throughout June, often shifting his net notional exposure from positive to negative within a range of nearly -$20M to +$30M. After a strong start to the month, his PnL remained largely flat, hovering just below $3M for most of June, before pushing higher to $3.6M in the final week while being long exposed.
He traded 12 symbols across 22 closed positions, with no particular preference aside from $BTC, which he traded consistently throughout the month. Beyond that, he focused primarily on mid- to large-cap coins, mostly L1s.
Nearly all of his profits came from $BTC and $SOL, generating a combined $3.9M. Outside of these two, his positions were mostly flat, with the largest loss coming from $SUI at -$210k.
Like the others, 0xbca displayed a positively skewed PnL distribution. However, a notable difference is that two trades out of 22 (those in the 99th and 1st percentiles) accounted for a significant 40% of his total profits. Specifically, a short on $SOL brought in nearly $1.8M, while his worst loss was a $SUI long, costing him $329k.
Case Study - High Conviction Under Pressure
The standout trader this month was without doubt 0xtyle. With a perp balance of $18.2M at the time of writing, he realized $7.8M in profits during June, maintaining a 77% win rate over 83 positions and achieving a profit factor of 8.5. His performance on $BTC alone, which brought in $1.2M, was particularly impressive, closing every position in profit.
Reaching these metrics, however, likely required strong conviction and nerves of steel. An average profit-to-drawdown of 0.75 implies that, on average, his positions were underwater at their worst by more than the profits eventually realized, requiring him to withstand significant drawdowns before closing in profit.
For example, one of his most profitable trades was a long on $FARTCOIN, which netted $809k on a maximum notional of $8.5M. He began entering at $1.1, gradually increasing size as the price dropped to $0.9, about 18% below his initial entry. At the bottom, the position showed a loss of over $1.1M (1.36 times the final realized profit) before the price reversed, allowing him to close in profit as the price recovered.
A similar but more challenging case was his long on $HYPE, which ended as his largest loss of the month at -$317k, though it could have been much worse. Initially entering around $42 with a $5M notional, he increased exposure to $16.5M as the price fell, lowering his average entry to $38 while the price dropped to $32, 24% below his first entry. As the price rebounded, he closed a third of the position at a loss and exited the rest between $38 and $41, reducing what could have been a -$2.7M drawdown to a contained -$317k loss.
While this style of execution, which involves averaging down, is considered highly risky, it is important to note that we only have partial visibility into 0xtyle’s full risk management and strategy. What is clear is that his results in a month where the broader market was largely flat were exceptional.
We will continue monitoring whether he can maintain this consistency in the coming months. For users considering copy trading 0xtyle, it’s worth being aware of his trading style to understand what to expect when aiming to replicate his results.
Conclusion
June’s market environment tested traders with flat yet volatile conditions, and the top performers demonstrated that it is still possible to generate strong results. 0xtyle’s high-conviction style, 0x8bf’s active intraday trading, and 0xbca’s flexible hedging approach each captured opportunities differently, reflecting the diverse paths to profitability even in a challenging month.
As markets continue to shift, we will track how these and other top traders adapt and evolve their strategies. For sure, their performance this month sets a clear benchmark for what is possible.
Stay connected for more insights in the upcoming month's edition.
Follow our highlight traders on Twitter:
Trader 0xtyle: likely corresponds to https://x.com/0xtyle, though we are not fully certain.
Trader 0x8bf: please if you know, let us know his twitter handle
Trader 0xbca: please if you know, let us know his twitter handle
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