AI Disclosure: This daily report was generated by our AI trading system. All financial
data comes from live sources: Alpaca (broker), FRED (Treasury yields), and our RAG system
(lessons learned). Every number is verifiable. Human oversight: Igor Ganapolsky.
Learning Day: Sunday, February 22, 2026
Day 117/90 of our AI Trading R&D Phase
TL;DR: Daily P/L $-132.83 (-0.13%), portfolio $101,222.49, trades: 0.
Executive Summary
| Metric | Value |
|---|---|
| Daily P/L | $-132.83 (-0.13%) |
| Total P/L | $+1,222.49 (1.22%) |
| Portfolio Value | $101,222.49 |
| Cash | $101,815.49 |
| Buying Power | $197,630.98 |
Today's Trades
No trades executed today (market closed or no signals).
Portfolio Allocation
Our current strategy focuses on:
- US Equities: SPY, sector ETFs
- Options: Cash-secured puts, covered calls
- Fixed Income: Treasury ETFs (SHY, IEF, TLT)
Treasury & Fixed Income
Live Treasury Yields (FRED API):
| Maturity | Yield |
|---|---|
| 2-Year | 3.47% |
| 5-Year | 3.65% |
| 10-Year | 4.08% |
| 30-Year | 4.70% |
Yield Curve Spread (10Y-2Y): +0.60%
Curve Status: Normal (positive slope)
Data source: Federal Reserve Economic Data (FRED) API
Risk Metrics
- Max Position Size: 2% of portfolio (Kelly Criterion)
- Stop Loss: Volatility-adjusted per position
- Circuit Breakers: Active (no triggers today)
Backtesting & Risk-Adjusted Returns
Sharpe Ratio Analysis
The Sharpe Ratio measures risk-adjusted return: how much excess return we get per unit of risk.
| Metric | Value | Interpretation |
|---|---|---|
| Sharpe Ratio | 0.00 | Negative (strategy losing money) |
| Sortino Ratio | 0.00 | Downside risk-adjusted |
| Profit Factor | 0.00 | Gross profit / Gross loss |
| Max Drawdown | 0.0% | Worst peak-to-trough decline |
Backtest Performance
| Metric | Value |
|---|---|
| Total Trades | 6 |
| Win Rate | 100.0% |
| Strategy | Iron Condors on SPY |
Our Backtesting Methodology
- Historical Data: We use Alpaca's historical options data with realistic IV estimation
- Black-Scholes Pricing: Options priced using Black-Scholes with rolling historical volatility
- Slippage & Costs: 0-5% slippage built into simulation
- Exit Rules: 50% profit target, 200% stop loss, or 7 DTE exit (per LL-268)
Strategy: Iron Condors on SPY
Our strategy sells both put spreads and call spreads on SPY:
Bull Put Spread (downside protection)
└── Sell 15-delta put
└── Buy 20-delta put ($5 wide)
Bear Call Spread (upside protection)
└── Sell 15-delta call
└── Buy 20-delta call ($5 wide)
Why Iron Condors?
- Collect premium from BOTH sides
- 15-delta = ~85% probability of profit
- Defined risk on both directions
- Profit when SPY stays within range
Risk Management:
- Max 5% of capital per trade ($248 on $5K account)
- Stop loss at 200% of credit received
- Close at 7 DTE to avoid gamma risk (LL-268: improves win rate to 80%+)
Sharpe ratio calculated using annualized returns with 4.5% risk-free rate (current 3-month T-bill).
Tech Stack in Action
Today's trading decisions were powered by our AI stack:
flowchart LR
subgraph Today["Today's Pipeline"]
DATA["Market Data
(Alpaca)"] --> GATES["Gate Pipeline"]
GATES --> CLAUDE["Claude Opus 4.5
(Risk Decision)"]
GATES --> RAG["LanceDB RAG
(Past Lessons)"]
CLAUDE --> EXEC["Trade Execution"]
RAG --> CLAUDE
end
Technologies Used Today
| Component | Technology | Role |
|---|---|---|
| Decision Engine | Claude Opus 4.5 | Final trade approval, risk assessment |
| Cost-Optimized LLM | OpenRouter (DeepSeek/Kimi) | Sentiment analysis, market research |
| Knowledge Base | LanceDB RAG | Query lessons learned |
| Retrieval | LanceDB | Semantic search over trade history |
| Broker | Alpaca API | Paper trading execution |
| Data | FRED API | Treasury yields, macro indicators |
How It Works
- Market Data Ingestion: Alpaca streams real-time quotes and positions
- Gate Pipeline: Sequential checks (Momentum → Sentiment → Risk)
- RAG Query: System retrieves similar past trades and lessons
- Claude Decision: Final approval with full context (86% accuracy)
- Execution: Order submitted to Alpaca if all gates pass
Alpaca Snapshot + PaperBanana Technical Narrative
Paper Account
| Alpaca Snapshot | PaperBanana Financial Diagram |
|---|---|
 |
 |
Captured: 2026-02-20T21:24:10Z
Technical interpretation: Paper Account: net liquidation value $101,224.20; daily P/L -141.20 (-13.9 bps) indicating a negative drift session; cumulative P/L +1,224.20 (+1.22%); low capital deployment at 0.0% utilization with cash $101,817.20; open position proxy 6; win-rate estimate 100.0% (n=1); North Star gate LOW.
Brokerage Account
| Alpaca Snapshot | PaperBanana Financial Diagram |
|---|---|
 |
 |
Captured: 2026-02-20T21:24:10Z
Technical interpretation: Brokerage Account: net liquidation value $209.42; daily P/L +0.00 (+0.0 bps) indicating a flat premium-decay session; cumulative P/L +189.42 (+947.10%); high capital deployment at 90.4% utilization with cash $40.00; open position proxy 0; win-rate estimate 0.0% (n=0); North Star gate LOW.
Market Context
US equity markets trade Monday-Friday, 9:30 AM - 4:00 PM ET.
What's Next
Day 118 focus:
- Continue systematic strategy execution
- Monitor open positions
- Refine ML signals based on today's data
FAQ
What was today's P/L?
$-132.83 (-0.13%).
What is the current portfolio value?
$101,222.49.
Where is the canonical version of this report?
This post's canonical URL is https://igorganapolsky.github.io/trading/reports/2026-02-22-daily-report/
About This Post
How this post was created:
- 🤖 AI Generated: Content structured by Claude Opus 4.5
- 📊 Data Sources: Alpaca API (trades), FRED API (yields), RAG (lessons)
- ✅ Data Verification: All numbers pulled from live APIs, no fabrication
- 👤 Human Oversight: Igor Ganapolsky reviews publication workflow
- 📅 Generated: 2026-02-22 17:23 ET
Per WordPress AI Guidelines: We clearly disclose
AI involvement, verify all data, and maintain human oversight.
Not financial advice. Paper trading only.
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