Seeing a large order, the most immediate thought is: With such a large amount of capital in play, should I follow? I will hesitate for a moment, looking to see who is behind this order and what actions they take afterward. Today, I will walk through this process using the major on-chain orders from Hyperliquid. On-chain, we can see the order execution situation and the corresponding address, which serves as a clue to trace the account. Decentralized exchanges use internal matching mechanisms, making it difficult for us to track the accounts behind orders through public order books. This level of transparency gives me the opportunity to continue tracking capital behavior, and whether the trades can be executed correctly still depends on specific judgment.
In the past two weeks, BTC has dipped close to 81,000 twice, and the overall direction remains unclear. The 81,000 mark was originally the upper boundary of the previous upward range, and after the price retraced, it has experienced multiple rebounds here. If this round of adjustment continues to expand, 79,000 and 75,000 will be key positions for us to observe next. However, these two points cannot guarantee that they will hold up the market, nor can they serve to assess specific position risks.
Let's look back at the five-minute K-line of BTC on October 12. It was a corrective market after a significant drop, with prices still in the upward rebound phase. At 13:21, a large sell order was placed at 84,250 USD, and the order began to execute at 14:56, lasting for 1 hour and 35 minutes. The chart shows a transaction amount of 16.4623 million USD, with the initial order amount being 16.2155 million USD, resulting in a transaction ratio of 101.52%. This order came from the Hyperliquid blockchain. The transaction amount exceeding the original order amount may correspond to subsequent additional orders; one should not judge solely based on a single transaction amount but should continuously track subsequent changes.
After this short selling order completed its execution, the price fluctuated briefly and then began to show a downtrend. Following this large order, I traced its corresponding address and used the smart money tracking feature to display the historical buying and selling records of this address on the K-line, while also setting alerts to continue monitoring this account’s subsequent operations. This address closed part of its short position at a lower price level. In this case, the price range from opening a short position to partial liquidation was approximately 3.5%. This only reflects price fluctuations in a non-leveraged state and does not equate to the actual profits one can achieve by following the order, nor can it guarantee that others can execute trades at the same price point. By connecting entry and position reduction together, the trade has a cause and effect.
Enabling this feature is simple: open the major order settings panel and check Hyperliquid; you can also observe alongside Binance spot large orders. If you are solely studying on-chain related cases, you can temporarily filter out data from other platforms. If you can't find the corresponding option on the interface, check the client version and data loading status. I encountered a situation where an outdated client did not display properly, and I only saw the corresponding large orders after an update.
The current demonstration version requires us to first confirm the address behind the large orders before adding smart money tracking. You cannot simply click on any large order to directly obtain the address; the one-click connectivity feature for addresses was still in subsequent planning at that time and had not officially launched. Do not treat the inferred addresses as confirmed addresses.
Once you have the address, select BTC or similar target currencies in the alert settings, and choose the actions you want to monitor: going long, going short, closing long positions, closing short positions, or transferring. Then set the minimum position amount and minimum change amount, with notification channels available via the APP, PC, or email. After saving all parameter settings, remember to save. In the sample screenshot, the minimum position amount is set at 1 million USD, and the minimum change amount is 500,000 USD; I have also demonstrated another set of parameters with a position threshold of 500,000 USD and a change threshold of 300,000 USD, which can be adjusted based on the trading habits of the account—do not just copy the demonstration parameters as the only answer.
If you do not receive alerts after setting them, it does not mean the function is ineffective. Some accounts have a large overall position size but trade in batches, transacting only hundreds of thousands of dollars at a time. For example, if the target position is 10 million USD, it could be split into 20 transactions of 500,000 USD each. If the change threshold is set too high, such batch trades may not trigger alerts. The threshold needs to be flexibly adjusted according to the trading habits of the target address; for small accounts or funds built in batches, higher sensitivity should be set. If saving the settings still does not yield alerts, check notification permissions and technical issues; we cannot guarantee that every transaction will be captured.
Even if I see a huge order, I won't directly place a trade based on it. I will first look at where the order is placed, how prices behave at that time, and how much has been executed. Large orders are worth paying more attention to, but it is also important to discern whether this account has continuously acted in a two-way market-making manner. Even if the transactions occurred on-chain are real, that does not mean that every order placed by this account is a one-sided bet on market direction. Finding the address and then checking what it does afterward is more useful than fixating on a big number.
Reading the major order charts follows some simple rules: the length of horizontal lines represents the duration of the order; the thickness of the lines represents the order amount; the darkness of the color indicates the transaction status; as soon as part of the order is executed, the color deepens. Dark color does not equal 100% of the order being fully executed. To see the precise execution ratio, you need to open the details page. Large orders that are placed for several days require separate judgment based on their position and trend, compared to fast transactions near market price. A large sell order hanging at a critical resistance point may suppress the market, but it is also necessary to continuously observe whether the order is withdrawn or consumed by buy orders, and we cannot directly equate pending orders with executed trades. The length and thickness of the horizontal lines in the chart can be referenced together in the same chart.
When encountering execution ratios exceeding 100%, further verification can be done to check whether additional orders were placed after the initial order. In analysis, it is important to simultaneously compare the initial order amount, the executed amount, and the timeline; one cannot simply decide on the entire position or capital intent based solely on a percentage.
Next, let's discuss the MA120 combined with the rebound thoughts from major orders. The period is fixed on the five-minute K-line, and here MA120 refers to the moving average formed by 120 five-minute K-lines, not a 120-day moving average. It is used to filter market trends. This approach specifically targets rebound movements after declines and is not applicable to all market conditions. My observation order is: the K-line operates below the MA120 moving average; continuous major buy orders appear below the moving average, supporting it; wait for the price to actively break above the MA120 and for the K-line to close稳above the moving average before considering entering a long position. A brief intrusion above the moving average within the market does not count as effective confirmation, and one should not enter just because of observable major buy orders supporting the market.
Take-profit can consider sell orders that hold reference value above, prioritizing those that have been pending for a long time, involve large funds, and have clear price levels. Some may choose to hold positions to capitalize on a larger movement, while I prefer adhering to trading discipline, reducing or exiting positions upon reaching target levels. In past cases, there were take-profits in short ranges of 0.4%, 0.5%, as well as situations where the subsequent market continued to expand around 2%. These are merely historical cases, not unified take-profit parameters, and they certainly cannot serve as promises for daily stable profits. The potential space that the market manages to achieve afterward cannot be retroactively deemed as guaranteed profit from the moment of entry.
We also need to distinguish between two different types of moving average "crossing." One is where the price actively moves up, breaking through the moving average with real buying momentum; the other is where the price oscillates at a low level while the moving average gradually converges toward the price, resulting in a passive crossover. I place more emphasis on the first type of active breakthrough. If the moving average merely descends and comes close to the price, with weak active buying momentum, then even if a major buy order can be seen, this opportunity can be abandoned. Conditions such as excessive declines, significant bottoming major buy orders, prices actively breaking above, and closing confirmations should be analyzed together to provide clarity on whether this crossover is accompanied by buying support.
The logic of combining on-chain large orders with smart money indicators is: relying on large orders at key price levels to find clues about capital, verifying the corresponding account address, checking the historical buying and selling records of this address, judging whether it provides liquidity in both directions, and then setting alerts to continuously track its opening and closing actions. Large orders can provide clues to real capital activities, but trades may still be judged incorrectly. The MA120 rebound method is used to filter out suitable entry environments, and address tracking helps understand complete capital behavior. By connecting these two parts, it becomes less likely to rush to conclusions based simply on a large order.
If one only focuses on that 16.462 million USD sell order, they will overlook the subsequent liquidation actions of that address; linking the trading behaviors of the address together brings us closer to understanding the complete process of this trade.
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