How does on-chain market making break through indicators and have no voice-controlled funds?

Author:0xLIZ

Taking the newly launched Binance alpha project $AGON as an example, let’s briefly talk about how on-chain market making silently controls chip distribution, and how to attack and defensively confront indicators (dev sell, bubble map, etc.) on data platforms such as gmgn.

Let's get closer to science together.

I paid attention to this project last month. Because I did not fluctuate with the market and walked out of the strong market trend, I used it to share some ideas for reading the data on the chain with my friends. At that time, I found that there were three interesting points on the data (the screenshot was cut in February):

1. Several Devs addresses are constantly selling, all sold for hundreds of dollars in the early stage, and they are all dumping them later.

2. The first 100 holders are very strange. They basically withdraw coins from CEX on the same day, and then they are all bought in small amounts of USDT around 200 coins, and occasionally sold a few times.

3. It seems like a group is constantly dividing small amounts of funds and taking them from the dev side.

Based on the above information, we have reason to suspect that this batch of addresses is actually bought by a person when selling them, so that he can avoid the collection function of the bubble map.

Then we can take a closer look at the traces on the chain and try to find clues associated with these addresses. Unfortunately, these addresses use exchange hot and cold wallets to avoid relevance, and they look like relatively mature players on the chain.

However, if you want to identify whether a batch of addresses is controlled by the same person, behavioural patterns are a good recognition pattern, especially for humans.

We don’t need many definitions. Just take a look at the behavior pattern composed of transaction records at each address and you can have a rough estimate of the similarity in your mind.

For example, these addresses only actively traded this token, and the number of transaction times is within the same range. I will post a set of examples .

After looking at a set of addresses, we found that these addresses are roughly divided into two categories, and we use two typical addresses to represent the two types of functions.

One type is the same address as the dev address, which plays a role in grabbing and distributing chips:

After buying in large quantities at the opening, the chips were distributed to small addresses in the cross-trading transaction, so that while buying and selling, the chips were distributed unconsciously.

The second category also plays the role of protecting the market. When the price falls below the target price, it will play a role of supporting the bottom.

There are considerable wear and tear on-chain transactions, and may be snatched by others (such as clip MEV). So how do these addresses deal with this problem when they change chips to small addresses?

There is an interesting BSC feature here, which is also a feature promoted by Binance teachers when everyone was discussing MEV a few days ago. It is called. Bundled Transaction.

Simply put, it is to pack a bundle of transactions and send them to the chain, either together or not together, so that no other transactions will be inserted in the middle.

Following this feature analysis, an obvious feature of using this service is that this string of transactions will be connected in the same block. You can look at the opening block. There is obviously a large number of addresses that almost all the chips are taken at the opening. It is reasonable to infer that this batch of addresses and the small addresses that change hands in the same block to receive chips are all from the dealer group.

This function will be used in two places. One is to make sure you make enough chips when opening the market, and the other is to make sure that there are no clips that get worn out when changing hands.

At this point, we are basically familiar with how to achieve almost lossless change from a dev address to a normal address through counter-desk transactions. This is also how the dealer breaks through some commonly used indicators (dev sell, bubble map, etc.) on platforms such as gmgn.

I also hope that when rushing to dogs, everyone will understand the risks of their decisions and do more risk control.

I have been dealing with data for a long time and have a relationship with Crypto, and I have come here to make data products. This version does have many challenges to data products and analysis logic. The fast pace has compressed everyone's decision-making time to the minute level. After reading several core indicators, I have to decide whether to get on the bus. I have also spent a lot of time adapting to this version.

However, offensive and defensive confrontation is continuous. Each indicator has and will only work in a window period. It is the same for individuals and institutions. If the indicators are thoroughly studied, they will fail. Only by dynamically adjusting the used indicators can we continue to move forward in this industry.