Many people ask me how to do quantitative trading in crypto prediction markets. Today I'm going to break down an insider-level "sweep the close" AI backtesting logic.

Sweeping the close pursues extreme win rate, but if you only know how to buy crudely at the 90-95 level in the final few minutes, you'll eventually get wiped out by slippage and reversals. The real top-tier approach is to use AI for data filtering—feed 1-2 years of K-line data into the system and let AI screen out those extreme factors where "buying never leads to reversal."

The entire process is actually closed-loop:

1. Data Feeding: Capture massive K-line data and require AI to design combination schemes that lock in absolute win rate zones before the 15-minute close.

2. Algorithm Backtesting: Let multiple AIs run open-source frameworks in parallel. They'll output a bunch of high-frequency factors, each pointing to extremely low reversal probability.

3. Strategy Consolidation: You don't need to understand complex code—just hardcode the trigger rules for these factors. Once the signal appears, go all-in and you're done.

Of course, there's still a gap between paper data and live trading involving fees, slippage, and order book depth that needs adjustment in live trading. But this logic is enough to give you a dimensional reduction attack in a market full of "just playing around" traders.

Anyone who really understands this playbook is already printing money.