February 5, 2026 — exactly one year after the DeepSeek crash that wiped $589 billion from NVIDIA's market cap. The stock sat at $172, forming a pivot bottom signal. What followed was a trade that returned +340% in just 4 days.
Important Notice
Market data in this article is real. Trade scenarios are hypothetical examples for educational purposes. Options trading involves significant risk of loss.
The Catalyst
On February 5, 2026 — exactly one year after the DeepSeek crash — NVDA formed a pivot bottom signal at $172. The stock had been under pressure in prior weeks, but three catalytic events converged:
Technical Analysis
- Pattern:Bullish engulfing pattern on 4H timeframe at $172 support. Pivot buy signal confirmed on February 5.
- Levels:Price broke above 50 EMA at $178, then resistance at $185.40 with significant volume spike (+180% vs. 20-day average).
- Signal:MACD crossover in positive territory confirmed momentum. RSI rose from 38 to 67 without becoming overbought.
Key Takeaway
Anniversaries of major market events create predictable narratives. The DeepSeek crash of January 2025 created a "recovery anniversary" effect — analysts and media drove sentiment. The smart trader positioned at the pivot bottom, not at the top.
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Disclaimer
The information on this page is for educational purposes only and does not constitute investment advice. Options trading involves significant risks and is not suitable for all investors.
*Names and amounts modified for privacy. Examples are hypothetical. Past performance is not indicative of future results.*

Author
Daniel Richter
Lead Quantitative Analyst
AI Options Strategist
Daniel Richter verbindet tiefgreifende Marktexpertise mit modernster KI-Technologie. Nach seinem Studium der Finanzmathematik an der TU München und mehreren Jahren bei führenden Investmentbanken in Frankfurt, spezialisierte er sich auf quantitative Handelsstrategien. Bei BeInOptions leitet Daniel das Analyseteam und entwickelt datengestützte Optionsstrategien. Seine Stärke liegt in der Kombination aus klassischer Finanzanalyse und maschinellem Lernen – er nutzt KI-Modelle zur Identifizierung von Marktmustern und Risikobewertung. "Mein Ziel ist es, komplexe Optionsstrategien für jeden verständlich zu machen und dabei die Kraft moderner Analysetools zu nutzen, um fundierte Entscheidungen zu treffen."
