Adaptive Moving Average Screening with AI Decisions and Risk Controls
Summary
The document describes an automated, single-instrument trading workflow that screens moving-average combinations and selects symbols using historical results. The supplied workflow material references liquid USDT perpetual markets, hourly candles, several fast/slow average pairs, and filters based on trade count, win rate, profit factor, and drawdown. It also describes market volatility checks, signal generation, portfolio rebalancing, and position monitoring. The listed strategy overview instead emphasizes an AI decision loop that combines technical indicators, news, current positions, and accumulated trade reviews to create and revise a bounded playbook.
Risk controls include position and leverage caps, hard stops, trailing profit exits, and limits on parameter changes. The material warns about AI errors, unreliable or delayed news, overfitting from small review samples, concentrated exposure, and sharp losses in extreme or illiquid conditions. The included workflow is truncated and does not provide interpretable backtest results, so the described screening criteria and control mechanisms should not be taken as evidence of profitability. The overview recommends observing decisions in notification mode before considering live trading.
Key ideas
- The strategy material combines moving-average screening with signal generation and rebalancing across selected USDT perpetual markets.
- The overview describes AI decisions that consider indicators, news, current positions, and prior trade reviews.
- Hard limits on position size, leverage, stop settings, and add-on trades constrain exposure.
- A playbook is revised from trade reviews, which can overfit when the sample is small.
- The workflow is incomplete and supplies no usable performance results.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.