AI-Supervised Crypto Futures Rotation with Trend Scores and Trailing Stops
Summary
This automated crypto futures system ranks liquid USDT perpetual contracts using a composite score built from four EMA relationships across multiple timeframes. It selects the strongest positive and negative signals, then combines those scores with recent news headlines and current position details for an AI adviser to recommend opening, holding, closing, or reversing positions. A separate monitor checks open trades frequently and closes them when profit retraces beyond a configured threshold. Orders are described as fixed-amount, leveraged market orders, with a position-clearance check before reversals.
The document explains fallback behavior when news is unavailable, ranking rules, and cases where signal strength and existing positions conflict. It also notes operational dependencies and limits: exchange-platform setup and an API key are required, news retrieval can be rate-limited, and stored peak-profit data resets after restart. The description supplies architecture and decision rules but no backtest or live-performance evidence. Its claims about risk controls and signal quality therefore remain unvalidated, and leverage, market execution, AI decisions, and turnover introduce material exposure to losses.
Key ideas
- The system ranks liquid USDT perpetual contracts with a composite score based on EMA alignment, spacing, and direction across timeframes.
- Recent news and position status supplement the technical rankings in AI-generated trade decisions.
- A separate frequent monitoring process uses peak unrealized profit and a drawdown threshold to trigger market exits.
- The workflow includes fixed-amount entries, leverage, and position verification before reversing trades.
- The document describes operational dependencies and failure modes but provides no backtest or live-performance evidence.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.