Multi-Confluence Trend Strategy with Sentiment and Risk Filters

Summary

This one-hour strategy combines trend, breakout, sentiment, volume, and market-structure signals into a weighted confluence score. Its components include fast and slow EMAs, a Donchian Channel breakout, a higher-timeframe EMA filter, a nonparametric kernel ribbon, an online ELM-style learning filter, order-flow proxies, and smart-money structure signals. A VIX reading and an SPX proxy add broad-market context; sentiment can affect position size or block long entries during extreme fear.

Trade management uses ATR-based stops and partial profit targets, with optional trailing exits and channel-based stops. Session limits, volatility-regime checks, and an equity guard can pause entries after a loss streak or drawdown. The script exposes many tunable weights and thresholds, but the supplied excerpt contains no complete strategy logic or performance report. Its broad set of filters and asset-specific settings therefore describe a configurable framework, not evidence that the strategy is profitable or robust across markets.

Key ideas

• The strategy scores several trend, breakout, sentiment, volume, and structure signals before entering.
• A VIX measure and an SPX trend proxy add market context and can influence entry eligibility or position size.
• ATR-based stops, partial exits, and optional trailing rules define trade management.
• Session limits, volatility checks, and an equity guard are intended to constrain trading during adverse conditions.
• The excerpt provides no performance evidence, so effectiveness remains unestablished.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.