H1 Technical Sell Signal — Exit Early, Exit Clean
On the hourly timeframe, loss control is timing. Fintx surfaces sell setups when structure breaks, momentum flips and volatility health warn of deterioration—augmented by live news/social context to avoid staying in a fading story.
AI Scorecard for H1 Sells (0–10 per Factor)
- Structure Break: LL/LH shift, failed retests, MA stack inversion
- Momentum Reversal: bearish cross persistence, thrust stats, breadth deterioration
- Volatility & Liquidity: ATR regime, slippage filters, gap/event sensitivity
- Context: headline drag, social sentiment drop, macro/earnings proximity
- Timeframe Harmony: H1 sell not contradicted by H4/D1 regimes
Scores refresh continuously with live price/volume and narrative shifts.
Exit/Scale-Down Playbook
- Primary Exit: execute inside the AI exit window on a confirming candle
- Stop Tightening: trail above LH or via ATR bands when momentum accelerates
- Scale Down: cut size on liquidity deterioration or context downgrades
- Re-Entry: only on fresh rally failure or new structure break
Compare Symbols: Where Is Risk Highest?
View side-by-side rankings by factor breakdown (Structure vs. Momentum vs. Context). Prioritize exits where multiple risk pillars align, not just a single indicator flash.
Live Data & Social/News Drag
Narrative turns quickly. Fintx weighs headline velocity and social sentiment to catch distribution phases earlier—especially in low-liquidity names vulnerable to gaps.
Common Pitfalls (and Fixes)
- Exiting too late → act inside the AI exit window once structure breaks
- Ignoring event risk → trim ahead of policy/earnings when regime is fragile
- One-signal decisions → require confluence across factors
FAQ
Does a high score mean “sell everything”? No—use it to prioritize exits and reduce exposure.
How often is this updated? Continuously with live data and context changes.
Combine with fundamentals? Yes—weak context + deteriorating metrics warrants faster de-risking.
De-Risk with Discipline
Open the live list, check factor confluence, and execute exits where structure and context agree.
AI assisted data
Traditional data
