MEME Coin Investment Practical Guide: Methodology, Techniques and Tools – glodchain

Since the cryptocurrency market entered the MEME season, countless stories of getting rich overnight or losing everything have been unfolding. People marvel at the hundred-fold or thousand-fold increases in tokens like $PEPE, $Turbo, $AIDOGE, and $MILADY, but when they buy MEME tokens, they lose money right away. Many people scorn MEME tokens as having no value, but others say that trading MEME tokens is all about trading emotions and attention. Both of these views are somewhat mechanistic. Today, I will analyze MEME tokens from the perspective of chip allocation and how to check chain address associations, to help you make better decisions when trading MEME tokens. I may not be able to help you pick the best ones to invest in, but I might be able to help you identify the worse ones.

If we view the issuance of tokens as a business, then we need to recognize the following points:

1. The project team is creating a product, and although the entire product has no specific purpose, the project team must find ways to get more people to buy it.

2. Any business needs to consider the input/output ratio. The project team can choose to take more tokens in the initial distribution (level one) and then sell them when the time is right, or they can distribute the tokens at a low price to the public initially and then buy them back from them (level two), or they can even rug the trading pool and run away with themoney.

3. Some MEME tokens may even involve changing owners. The project team has already sold all the tokens they held in the early stages, but the hype around the token remains, and some investors continue to invest, so the story can continue.

So how do we start this business? I think we need to address the following issues:

Locking in seed users. There are many cases at this stage, such as vampire attacks where tokens are airdropped based on whether users are eligible to receive them on platforms like Arbitrum. Or, through various IDO platforms or Alpha communities, presales or LGE/TGE (Liquidity Generate Event/Token Generate Event) can be set up. Or, fake mass distribution can be carried out (as will be explained below).

Creating initial liquidity. For digital assets to circulate and be traded, there needs to be capital to provide initial liquidity. The project team will create a liquidity pool by using the Uniswap factory function to pair the token with ETH (usually) so that everyone can buy and sell the token through this liquidity pool.

Media matrix coverage. If everyone in our CT information flow is talking about a certain MEME token, curiosity will drive us to take a look. There are KOLs who can naturally attract traffic, those who are paid to promote, and those who try to cater to deconstructive ideological trends and sell other products.

Price and volume rising together. In order to facilitate shipping, the project teamholds a large number of tokens in the early stages to achieve the effect of controlling the market and pushing up the price. With the increase in trading volume and price, major quote websites such as Dextool and Dexscreen will recommend the token on their Gains list, bringing it into the view of retail investors.

Next, I will give two specific examples to show how these two projects locked in seed users and distributed tokens in a cold start, and what kind of trend the tokens developed under these circumstances. It should be noted that the tokens mentioned below are not investment recommendations, and I hope everyone will be responsible for their own investments.

Case 1: Simpson

Contract address:


Main trading pool:


Contract deployment address:


Total token supply:


Let’s try using Arkham to interpret the initial distribution of the Simpson token:

From the above chart, we can see that:

The creator of the Simpson token deployed approximately 1/3 of the initial tokens to the Uniswap liquidity pool.

The token creator distributed 8,800T Simpson tokens to 20 addresses, with each address holding about 2% of the total, totaling 40%.

With this operation, 70% of the tokens have already been distributed, and it’s now time for the token creator’s shady operations.

Through on-chain behavior, we can see that the token creator used the Multisender function of CoinTool, a tool familiar to those who are knowledgeable about on-chain data. CoinTool has previously ranked high on the ETH Gas consumption leaderboard for a long time. The token creator used CoinTool to distribute Simpson tokens to a large number of addresses. By using browser tools, we can see that the token creator used CoinTool four times, distributing a total of 1000 Simpson tokens to 800 addresses.

Furthermore, we can observe that the addresses to which the token creator sent tokens all start with “0x059a”. Those familiar with hash algorithms would understand that these are batch-generated addresses or some addresses whose private keys are unknown even to the project team and were randomly distributed, as 1000 Simpson tokens out of a total supply of 420Q are not significant. However, such operations allowed the project to have 800 on-chain holding addresses during the cold-start phase.

We also know the subsequent story: with Binance launching $PEPE on May 5th, the MEME token once again ignited the enthusiasm of many speculators, who began frantically searching for the next $PEPE. What are the general standards people use to look for such tokens? New coins, a certain number of holding addresses, a certain trading volume, simple and easily spreadable imagery, and good social media performance.

However, while buyers dream of getting rich, the chips laid out in the early stages have already been dumped for cold hard cash.

In addition to token distribution, we also have another angle of observation, which is the interaction of the trading pool.

We can see that in addition to some common retail trades and trading aggregators, there are also participants who have helped to promote the MEME craze, such as MEV Bots.

Various types of MEME tokens have easily reached daily trading volumes of millions and even tens of millions of dollars, mainly thanks to MEV Bots. It can be said that almost 90% of the trading volume of most MEME tokens comes from MEV Bots, as some tokens have a mechanism for trading taxes, which forces traders to increase the slippage of their trades, making them easy targets for MEV.

Here, I recommend a tool called Eigenphi. Users can input the trading pool address of the token they want to trade, and Eigenphi will show the MEV trading volume statistics for them, thereby estimating the actual trading volume and making cross-comparisons between different MEME tokens.


In the case of Simpson, we can summarize the following two points:

In order to play a good game with the project team, we need to calculate the project team’s costs. In this project, the project team spent 6 ETH as the initial liquidity pool, 2 ETH as Gas to use CoinTool to create 800 holding addresses for themselves, and additional costs for promotion and hype. These costs can give us a rough estimate of the project team’s expenses.

Concentrated selling. It can be seen that the 20 addresses that were early distributed cashed out on May 13th. If you continue to participate in this game at this time, it may not be a good choice.

Case Two:GenerationalWealth (GEN)

Contract address:


Main trading pool:


Contract deployment address:


Total token supply:


Let’s try to use the same method to interpret the initial distribution of GEN token:

The initial distribution of GEN token had a presale process, and we first need to find the contract address for the presale (contract address link).

According to the project’s description, 15% of the GEN tokens will be initially sold through a presale process. From on-chain data, we can see that a total of 672 people participated in the presale, each contributing 0.05 ETH and receiving 105B GEN tokens.

Here, we can see that among the addresses that participated in the presale, there are many with ENS domain names, and many have been marked by Arkham as OpenSea users. These addresses have diverse characteristics and some on-chain activity, making them healthy and diverse seed users, which contributed to the success of the token’s initial sale.

On the other hand, in large holding addresses, we can see that:

The GEN token creator deployed 302T, accounting for 72% of the circulating supply of GEN tokens, to the Uniswap liquidity pool.

The three associated addresses with larger holdings, 0x83Fae943b5381eCE611bda1fA44f744966Bc9552, 0xa0F06e6Ab3A999294E4b6B1EF8f4689c5D785482, and 0x7E0DaBBC101402880D281f86E51E439f897A752a, respectively hold approximately 6.9%, 3.68%, and 2% of the circulating supply, totaling about 12.5%. By observing, we can seethat two of these addresses currently do not have ETH, and therefore cannot transfer the tokens.

So what did we find while speculating on this token? And what do we need to pay attention to?

Firstly, we found that the seed user group of this token may come from the NFT/Alpha community or a certain NFT circle KOL’s promotion. Users participated in the presale at a price of 0.05 ETH and have currently gained more than 20 times profit.

Next, we found that the project team publicly reserved 12.5% of the tokens, but since they currently do not have ETH in their accounts, we can monitor the actions of these large holding addresses.

Is there a possibility of rug pull? The action of the token creator was to deposit the LP tokens into the GEN token contract, and there have been no further actions. This can be continuously monitored.

Through Eigenphi, we found that GEN did indeed have strong buying demand during certain time periods.

In terms of the interaction level of the trading pool, it appears to be more active as well.


In the case of GEN, we can summarize the following two points:

1.The diversity of seed users can bring many surprises to the project in the early stages, especially when accompanied by the wealth effect.

2.By excluding MEV trading volume and finding the actual demand trading volume, it is easier to make cross-comparisons between MEME projects.

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