🤖 A relatively complete sharing of MEME quantitative trading ideas and strategies Referring to the "art" of buying and selling written a few days ago, coupled with data acquisition, Swap trading, and price monitoring, a relatively complete quantitative trading process for meme tokens can be achieved. For example, a process like this: 1. Initial screening of meme tokens 2. Determine the target worth buying 3. Call Jupiter API interface to buy tokens 4. Real time monitoring of token quantity and price information for holdings 5. According to preset conditions, take profit and stop loss Next, we can elaborate on it. one ️⃣ Initial screening of tokens In terms of manual operation, you can open any K-line chart website and use the filtering function to customize a filtering system, such as based on: *Flow pool size (greater than $300000, etc.) *Market value size (1M~5M, or 5M~10M, etc.) *Token duration (0-6 hours, 24-72 hours, etc.) *1-hour transaction volume (greater than 1M, etc.) Similarly, filtering through programs follows the same approach, except for switching from web UI to API interface. There are many APIs in the industry that provide Solana token filtering, some of which are publicly available for free, some are paid, and some are used by websites themselves, but can be temporarily borrowed by you. For example, I plan to "borrow" the seemingly gibberish like data returned by this WSS interface, and after a simple regularization process, I can extract the core key information: Pool Address & Token Address two ️⃣ Buy judgment After the initial screening, the number of tokens is greatly reduced, but not everyone who passes the initial screening can blindly buy (you can do this, but you need to lower the purchase amount) The second step is to perform secondary filtering on the initial screening results to identify the truly worthwhile targets for purchase. Here, you first need an API interface for token K-line data (many free ones are sufficient), preferably including complete OHLCV data (Open, High, Low, Close, and Volume) With data, simple or complex quantitative rules can be added to determine the buying criteria. A slightly simpler approach is to quantitatively score each indicator and ultimately buy based on the rating.