Crypto Rotation Using Moving-Average Scores, News, and AI Oversight
Summary
This document describes a cryptocurrency rotation system that ranks liquid coins using a composite of moving-average arrangement, spread changes, and the direction of several averages. It selects high and low scoring assets for potential long and short positions, while retaining held assets in the candidate lists so the system can reassess them. Recent headlines provide context, and an AI layer considers signal strength, news, position direction, and unrealized profit or loss before recommending whether to open, hold, close, or reverse.
Execution uses a fixed USDT amount per trade, with trailing stops and monitoring features also described. The article explains the workflow and gives illustrative decision cases and a contract sizing example, but it does not present systematic performance results. News coverage can be incomplete or delayed, and AI decisions and technical signals can fail. The text also suggests possible extensions such as sizing by account equity, model voting, on-chain data, adaptive stops, and trade-history analysis; these are proposals rather than demonstrated improvements.
Key ideas
- A composite score combines moving-average arrangement, spread behavior, and the direction of the averages to rank cryptocurrencies.
- The system uses the highest and lowest ranked assets to identify possible long and short candidates.
- News and position status supplement technical signals when AI recommends opening, holding, closing, or reversing a trade.
- Fixed-amount sizing and trailing stops are intended to manage exposure, but the document provides no performance validation.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.