#广场发帖领$50 Whale Cloud Record: Some people turn their lives around overnight, while others die from obsession. Whales have become the focus of on-chain trading. Here, every day unfolds stories of wealth and zeroing out.

By digging deeper into on-chain data, these whales display a variety of styles. Some are "counter-indicators" holding heavy funds but repeatedly losing; some are "snipers" lurking for half a year just for that one strike; others are "cold-blooded machines" using algorithms to harvest retail traders every second.

Data strips away the mystery of these big players, revealing the five most representative addresses on-chain: including the famous "Maji Big Brother," a suspected insider with confidential information, a market maker with billions in capital, and recent "turnaround myths" and "iron-headed armies." Through their thousands of transaction records, we seem to find a piece that belongs to us within these portraits.

Maji Big Brother: Wins like "bird food," losses like "collapse"
When it comes to Maji Big Brother, he seems to have become a reverse indicator in the current market—massive losses leading to currently huge contract losses. His trading operations are almost textbook examples for industry practitioners or investors. But even negative examples are lessons. Maji Big Brother's losses have reached $46.5 million so far. He ranks high on the overall loss leaderboard. From his trading style, he exhibits high win rate and low profit-loss ratio. His overall win rate is 77%, but his profit-loss ratio is 1 : 8.6. Additionally, his average holding time for profitable orders is 31 hours, while the average holding for losing orders reaches 109 hours. This indicates he tends to exit when profitable but tends to hold through losses until huge losses or liquidation occur. Overall, his short-term market judgment is quite accurate, but his trading strategy always involves risking a loss of up to $8.6 to gain $1.

However, in actual trading, before the market crash on October 11, his overall position was still profitable at $15 million. After the crash, due to margin calls on orders like XPL and ETH, his total profit turned into a loss of over $11 million. Subsequently, with more operations, he is drifting further from breakeven.

The fundamental reasons behind Maji's losses have two fatal flaws:

First is being a "dead bull," with 94% of his trades being long positions and only 6% short. He lost $46.88 million on longs but made $380,000 on shorts. In a declining market, this one-sided style is deadly. Second is averaging down without stop-loss. In several large losing orders, when his positions were close to liquidation, he often chose to add margin rather than stop-loss, leading to even larger losses. Overall, Maji Big Brother's gains are like "bird food," but losses resemble "collapse." From a trading psychology perspective, he shows clear flaws in loss aversion, refusal to admit mistakes, and sunk cost fallacy—traits not worth emulating.

10.11 Insider Big Shot: Cold-blooded Sniper
If Maji Big Brother is a hot-blooded soldier sweeping with a machine gun, this big shot is a sniper who lurks three days just to pull the trigger once.

His trading frequency is extremely low, with only five trades in half a year, and an 80% win rate, earning $98.39 million. Unlike Maji, who keeps depositing, this whale continuously withdraws funds.

His most famous trade was depositing $80 million to short BTC on October 11, and five days later, withdrawing over $92 million profit. After that astonishing trade, he didn't indulge but remained disciplined. Then on October 20, he shorted again and earned $6.34 million. Although he lost $1.3 million on a long position on November 8, compared to previous profits, it's just a drop in the bucket. Currently, his account still holds $269 million worth of ETH longs with an unrealized profit of about $17.29 million. From his trading style, this insider-like whale resembles a lurking crocodile—rarely moving, but when he does, he bites off the biggest chunk of the market before leaving.

Market maker with $1 billion capital: Dominating with algorithms
This address is currently ranked number one in profitability. If the top two are "gamblers" and "hunters," this one is a super whale acting as a market maker. So far, this address has deposited $1.11 billion into H and withdrawn $1.16 billion, with an unrealized profit of about $143 million.

His strategy involves first opening several large baseline positions, such as short positions on ETH and other tokens. Then, he uses algorithms to frequently add and reduce positions, aiming to profit from two main methods: trend-based shorting and high-frequency arbitrage.

Closer analysis shows that not only the top profit-ranked address employs this strategy, but the second and third-ranked addresses are also whale arbitrageurs using similar methods.

Take the second-ranked address as an example: 51% of his trades involve placing limit orders on both sides of the order book, exploiting tiny price fluctuations. Although each fluctuation trade is small—about $733—the address completes 1,394 trades in a day, accumulating tens of thousands of dollars in profit daily.

However, for retail traders, the operations of such whales are almost impossible to replicate. Whales benefit from fee advantages, high-speed quantitative algorithms, and hardware support.

Most profitable over the past week: Scrambling carefully
This address isn't quite a whale by size, but its recent high yield has brought it into the spotlight on PANews.

In terms of funds, this address initially invested about $46,000, appearing as an ordinary retail trader. Looking at past trading results, until the end of November, its funds kept decreasing, with an 85% loss rate. During that period, it was a typical loser—chaotic operations and stubbornly holding small altcoins.

However, after December 2, it seems to have changed entirely, perhaps discovering a trading holy grail. By December 9, it had won all 21 trades, increasing its capital from $129 to $29,000, showing exponential growth.

On December 3, it tentatively opened a position with 1 ETH, earning $37. On December 5, feeling confident, it increased to 5-8 ETH, earning about $200 per trade. On December 7, it increased to 20 ETH, with profits reaching $1,000. On the 8th, the position grew to 50–80 ETH, with $4,000 profit per trade. On December 9, it reached 95 ETH, with a single-trade profit of $5,200.

This overview shows some key changes: first, switching from trading a dozen tokens to focusing solely on ETH; second, abandoning stubborn holding in favor of quick trades—its average holding time shrank from about 33.76 hours to 4.98 hours in the past week, moving away from losses and toward profit-taking; third, changing from disorderly opening to a "rolling" position mode, a common technique for rapid small-cap growth.

Though profits have accelerated, leverage has also increased. Previously, his average leverage was 3.89x; recently, it has risen to around 6.02x. This amplifies risk. As of this writing, his ETH position has already incurred a loss of over $9,000 due to rapid market movement, nearly halving his gains. The profit curve shifted from exponential growth to a cliff dive. Overall, this strategic shift has made him more powerful but also more fragile. Whether he can recover from losses depends on how he manages losing orders and maintains high win rates.

Iron-headed Multi-arm: The tragedy of a dead bull
Compared to the traders above, this whale's style is more like a steadfast bullish believer and also a "victim" of SOL.

This whale's total investment reaches $236 million, with 86.32% long positions. Out of over 700 trades, about 650 are longs. He has lost over $5.87 million on longs but made $189,000 on shorts. Despite a total loss of over $5 million, relative to his total flow of over $200 million, this drawdown (~2.4%) is still within manageable limits. But his biggest problem lies in his position structure—the losses are heavily concentrated on SOL. Among the tokens he traded, FARTCOIN and SUI earned over $1 million each, ETH and BTC nearly $1 million. But a single loss on SOL hit $9.48 million. Excluding SOL losses, he is actually a very skilled trader—other tokens accumulated around $4 million in profit. But he seems obsessed with SOL, holding long positions stubbornly, only to be repeatedly hit by SOL's bearish trend.

From his trading, we learn that even with over a billion in funds, if you develop "emotional attachment" or "obsession" toward a certain coin, it can easily destroy you—especially avoid fighting the trend.

In summary, in this deep sea of whales, algorithms, and insider info, there is no such thing as a "sure-win holy grail." For ordinary investors, most of these whale operations are not replicable. The only lessons to learn from them are perhaps not how to earn a billion dollars, but how to avoid becoming a "Maji Big Brother" type loser who "holds through" losses, and not to challenge tireless algorithm machines with limited funds and speed.

Respect the market, honor the trend—that may be the most valuable insight the market leaves us.