# Top Traders Report - July ‘24

📢 The "Top Traders Monthly Report - July '24'' 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! 💪 

# **1️⃣** Top 3 Traders by PnL ($) - Overview

July 2024 highlights its top three traders as follows:

[🏆 TRADERT22](https://www.binance.com/en/futures-activity/leaderboard/user/um?encryptedUid=13A05CEEA6B2B444C1AB8973255BAF9C) (Binance)

🥈 [andre\_is\_back](https://app.hyperliquid.xyz/explorer/address/0x9cbf099ff424979439dfba03f00b5961784c06ce) (Hype[rli](https://app.hyperliquid.xyz/explorer/address/0x21813dd67fecb6dffb3f74bb35c13336bc99a519)quid)

🥉 [Ape](https://app.hyperliquid.xyz/explorer/address/0x21813dd67fecb6dffb3f74bb35c13336bc99a519) ([Hyperliqu](https://www.binance.com/en/futures-activity/leaderboard/user/um?encryptedUid=13A05CEEA6B2B444C1AB8973255BAF9C)id)

July proved to be a challenging month for trading. Focusing on $BTC, the month began with an 11% loss in the first week, followed by a 23% rise over the next three weeks. The final week saw a further loss of approximately 15%. Despite these setbacks, Bitcoin managed to close the month with a modest gain of 2.9%, fluctuating between $54,000 and $70,000.

Among the top traders, **profits ranged from $904k to $1.5M**. At the first place was a newcomer to the Binance Leaderboard, **TRADERT22**, who secured the top spot with a total profit of $1.5M. After a turbulent first half of the month with a volatile PnL curve, TRADERT22 achieved substantial gains in the latter half of July. In second place, the familiar name **andre\_is\_back** continued to perform well, earning around $1M. Rounding out the top three was another new entry, **Ape** from Hyperliquid, who made $900k in profits, closely trailing andre\_is\_back.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724176928280/8ae4b261-f2d9-4abc-b52f-a1dd5bbb9069.png align="center")

# **2️⃣** Top 3 Traders - Performance Metrics

**TRADERT22** was the most active of the three traders, closing a total of 187 positions and executing 664 trades throughout July, achieving a win rate of approximately 61%. Although his Profit Factor was relatively low at 1.04, he leveraged the high volume of trades to accumulate substantial profits. His average holding period was about 4-5 hours, the shortest among the three.

In contrast, **andre\_is\_back** closed only 17 positions but managed them through 990 trades. He had the longest average holding period, often spanning multiple days, with winning positions held twice as long as losing ones.

Lastly, **Ape** closed 12 positions but engaged in nearly 5,000 trades, boasting the highest Profit-to-Drawdown ratio at 3.53. Interestingly, his average holding period for winning positions was half that of his losing positions, which is uncommon based on what we saw in the previous reports.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177015276/aca9d9cf-11a0-4187-b101-3203a71716cf.png align="center")

# **3️⃣** Trader Spotlight: TRADERT22

## 3.1. Notional exposure and PnL ($)

The notional exposure chart reveals that TRADERT22 frequently alternated between long and short positions, with exposure fluctuating between -$20 million and +$19 million. His PnL curve remained close to breakeven for the first half of July, with all significant profits ($1.4 million) being generated during the final two weeks of the month.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177084374/7f601b97-b09f-4f06-926b-7d8207ae1370.png align="center")

The figure below displays, for each closed position, the **PnL ($) by symbol traded and their holding period**. 

In July, TRADERT22 traded a diverse range of **29 symbols**, balancing between major cryptocurrencies like $BTC and $ETH and meme coins such as $BONK, $FLOKI, $PEPE, $RATS, and $SATS. Despite this variety, $BTC emerged as the primary symbol traded throughout the month, although most of the profits came from $ETH (see following image).

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177112322/308fa155-3972-43c6-9e93-9e70e2e14a8a.png align="center")

The figure below displays the **Total** **PnL ($) by symbol traded**.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177196712/20b476da-88b8-4543-8dd1-4c4ec740e0c4.png align="center")

The **cumulative distribution function (CdF)** of his PnL is slightly positively skewed (skewness: 1.76), with a positive edge since the 50th percentile:

* **25th percentile:** W/L ratio of 0.91 ($5.2k vs $-5.7k)
    
* **50th percentile:** W/L ratio of 1.13 ($17.7k vs $-15.7k)
    
* **75th percentile:** W/L ratio of 1.51 ($40.9k vs $-27k)
    

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177220318/95eb4bef-477e-4db6-8fd2-815f2cd09d8e.png align="center")

## 3.2. Position Case Studies

### ETHUSDT - Flip flopping 

Over the course of more than 20 trades on $ETH, TRADERT22 achieved total profits of $370k. Most of these positions were opened and closed quickly, with small gains or losses, as TRADERT22 frequently switched between long and short positions in response to price movements. 

The **largest loss** occurred on July 15th, when a short position with a maximum notional exposure of $6.3 million resulted in a **$286k loss**, equating to a -4.5% ROI and contributing 4.6% to the overall PnL. After a series of minor gains and losses, TRADERT22 successfully captured another short on July 24th as $ETH experienced a nearly 7% drop within a day. With a maximum exposure of $8.6 million, this trade yielded a **$517k (6% ROI) in just 12 hours**.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177247542/c1a74a49-9ca7-43ca-a71f-cc9944efb9ba.png align="center")

# **4️⃣** Trader Spotlight: andre\_is\_back

## 4.1. Notional exposure and PnL ($)

As for andre\_is\_back, most of his trading activity occurred during the first half of the month. He initially held a **significant short exposure of over $5 million but shifted to a predominantly net long exposure until July 15th**. Of the 17 positions he closed, approximately 53% were longs. Despite a rough start, with his PnL dipping to a nearly $500k loss, andre\_is\_back managed to recover and end the month with over $1 million in profits.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177369008/b70183f6-0a1b-4bfc-8610-f836ceed34bb.png align="center")

The figure below displays, for each closed position in July ‘24, the **PnL ($) by symbol traded and their holding period**. 

andre\_is\_back mainly focused on trading high cap tokens such as $ETH, $SOL, and $TON.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177387338/e281cfc7-5d74-402d-ab5c-a0810e860d0d.png align="center")

The figure below displays the **Total** **PnL ($) by symbol traded**. 

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177427929/764891df-9b7c-4190-ba92-4d975829cad0.png align="center")

# **5️⃣** Trader Spotlight: Ape

## 5.1. Notional exposure and PnL ($)

In July, Ape's exposure typically fluctuated between -$5M and just under +$5M. He maintained a net short position during the first half of the month, reaching a peak PnL of $800k. However, between July 15th and July 25th, he gave back half of these gains, only to recover them by the end of the month, ultimately closing with a profit of approximately $900k.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177488268/0072fedc-7b5e-40ba-be57-b4797d47306d.png align="center")

The figure below displays, for each closed position in July ‘24, the **PnL ($) by symbol traded and their holding period**.

Ape only closed positions on 4 majors during the month: $BTC, $ETH, $SOL, and $BNB.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177500583/246a9979-fd22-496a-a065-5ec03f1d33db.png align="center")

The figure below displays the **Total** **PnL ($) by symbol traded**.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177675777/f5d3f1b8-072d-4f36-b6b7-3afa665c5605.png align="center")

## 5.2. Position Case Studies

SOLUSDT - Catching the breakout

* **Side:** Long
    
* **Trades executed:** 477
    
* **Max DD ($):** \-$33k
    
* **Final Pnl ($):** +$531k
    
* **ROI (%):** 20%
    
* **Holding Period:** ~10 days
    

The $SOL long trade was Ape's second-best trade of the month, earning him a profit of $531k against a maximum drawdown of $33k, resulting in a remarkable **16x profit-to-drawdown ratio**. Ape initiated this long position on July 14th, likely aiming to capitalize on a breakout from the 4-hour resistance area around $140.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177712785/f178ec43-ef96-4ec6-b049-08492ed24a4f.png align="center")

After the breakout was confirmed his **maximum notional exposure reached $2.6M** and he just had to ride till the $180 area where Ape started to load off and finally close it on July 24th. The final ROI was ~20% and this long **contributed for more than 30% to his total PnL**.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1724177730883/7dd660f3-d645-4cbd-9322-0f663175f834.png align="center")

# **6️⃣** Conclusion

The top three traders of July **did not exhibit a strong preference for either long or short positions**. Instead, they frequently adjusted their strategies throughout the month, responding to the challenging and choppy market conditions. Despite $BTC ending the month with only a slight gain, these traders managed to generate impressive profits ranging from $900k to $1.4M. The key takeaways from their performance are:

1. **Compounding on Small Positive Edge:** Like casinos, you do not need a large edge to make money in the markets—a small edge, when managed effectively, can be highly profitable. An example of this is TRADERT22 who leveraged large position sizes and short-term trades to effectively manage and compound his relatively modest, but positive, edge, ultimately accumulating $1.4 million in profit.
    
2. **Prioritizing Profits Over Being Right: The top traders this month showed a clear focus on making money rather than holding onto a specific market bias (long vs. short). This flexible approach allowed them to respond to market movements dynamically, rather than trying to predict them, leading to their successful performance.**
    

  

Stay connected for more insights in the upcoming month's edition.

**Follow our highlight traders on Twitter:**

TRADERT22: *please if you know, let us know his twitter handle*

andre\_is\_back: *please if you know, let us know his twitter handle*

Ape: *please if you know, let us know his twitter handle*

**Data analysis provided by** [@0xfab\_eth](https://twitter.com/0xfab_eth). Drop him a follow! 

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