Answer In Data: Quant Investing & AI & Coding
ποΈ Answer in Data Podcast β EP.01 "How My Quant System Saw the Crash Coming β 2026 Market Outlook" Welcome to the first episode of Answer in Data! I'm Dee, a data scientist and quant investor from Korea. In this episode, I share how my 44-indicator automated trading system responded to the recent market chaos β including the US-Iran airstrikes on February 28th. What happened: - Feb 9: My rotation system hit Level 3 β sold all growth stocks (NVDA, TSLA, etc.) - Bought defensive ETFs (XLP, TLT, DBC) + held 45% cash - Feb 28: Iran crisis hit β my tech exposure was 0%. DBC jumped +9.6%. - Result: Zero losses from the tech crash. System worked exactly as designed. 2026 Full Year Outlook: - Cycle Composite: Why May is the inflection point - RRP Liquidity Tank: It's empty β what that means for spring - Midterm Election Year: 18% average drawdown, but 14% rally after November - My playbook: Cautious through April β Defensive May-Oct β Buy in October Key Insight: I didn't predict the war. My system tracks where money flows β not why. Whether it's war, tariffs, or rates, capital moving to safety looks the same on the charts. That's why this works. π°π· νκ΅μ΄ μ±λ: λ°μ΄ν°κ° λ΅μ΄λ€ (YouTube) π± Instagram: @answer_in_data π Coming Soon: κ°λ―Έλ λ€ β ML/Quant based trading signal service (Beta) #QuantInvesting #2026StockMarket #SectorRotation #DataDriven #USStocks #MarketOutlook #TradingSystem #RiskManagement #MidtermElection #AnswerInData
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