$COIN Options Trade Blunder | AI vs. Flow — Who Wins?

– When LSTM Confidence Misfires at the Top
This week I entered puts on off a 95% confidence signal from my LSTM model, anticipating a bearish reversal near the premium zone.
It looked clean:

🔺 Price had tapped a weak high

📈 Extended rally from discount to premium

🧠 LSTM model flagged a local exhaustion top

But I ignored the bullish options flow.
Institutions were loading calls.
Volatility structure showed strength.
I chose the model. The market chose pain.

📉 Trade Setup:
Short thesis: Rejection from premium + weak high

Entry: $370 zone

Target: $325 (mid EQ)

Invalidation: Break above $380

Actual Result:
Price consolidated, then held bullish structure.
Implied volatility stayed elevated. No follow-through on the short.
Loss: ~50% on puts.

💡 Lesson:
Chart logic aligned

AI signal was compelling

But real-time flow > model output

LSTM is 70% of my AI trading system, and I’m now integrating options flow override filters to prevent this kind of mismatch in future signals.

📌 I’m currently risk-off, rotating capital into 5Y Treasury futures ($Z) to cool down, refine logic, and reassess volatility pricing models.

🧠 This phase is experimental. If you’re watching my trades – don’t follow. Observe. Learn from the debug phase.

—
Prabhawa Koirala (Pravo)
Founder – WaverVanir International LLC
#COIN #TradingView #SmartMoneyConcepts #LSTM #AITrading #OptionsFlow #WaverVanir #PremiumZone #QuantTrading #VolanX

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