The System
A Fully Quantitative, Rules-Based Approach to Volatility Premium Selling
System Overview
The Volatility Anomaly System is a fully quantitative, rules-based platform that identifies persistent mispricings in implied volatility across 2,000+ equities, earnings events, and derivatives markets. Every signal is data-driven and grounded in the volatility risk premium — no discretionary calls, no gut feel, no opinions. If the numbers do not support the trade, the system does not flag it.
Step 1: Automated Screening
Every morning before the market open, our algorithm scans over 2,000 stocks across four major indexes, ranking each by Implied Volatility Rank (IVR), IV percentile, skew, and earnings proximity. Only stocks that meet all criteria are surfaced — everything else is filtered out:
Screening Criteria
Step 2: Volatility Regime Classification
Regime-Aware Screening
The screener classifies each opportunity by volatility regime. High-IV environments favor premium sellers; low-IV regimes favor buyers. Knowing the regime is the first step to selecting the right strategy.
- •IVR ≥ 50 — options expensive vs. history
- •IV Percentile ≥ 60th — elevated vs. peers
- •Volatility risk premium present (IV > HV)
- •IVR < 25 — options cheap vs. history
- •IV Percentile < 30th — depressed vs. peers
- •VRP negative — realized vol exceeds implied
Step 3: Strategy Selection & Setup Construction
For each qualified stock, the system recommends the optimal strategy based on regime, skew, and earnings proximity. Iron condors, short strangles, and vertical spreads are the primary vehicles:
Example: AXP Trading at $200
Setup Construction Rules
Step 4: Trade Management & Exit Rules
Disciplined exit rules are critical to the system's success. We use a two-tier exit strategy:
Profit Target (50% of Max Gain)
Close when the position reaches 50% of maximum profit. Research shows this dramatically improves risk-adjusted returns vs. holding to expiration.
Time-Based Exit (2 Days Before Expiration)
If profit target not hit, close position 2 days before expiration to avoid assignment risk.
Stop Loss (2× Premium Received)
If the position reaches a loss equal to 2× the premium collected, close to preserve capital. Prevents catastrophic drawdowns.
Risk Management Protocol
Position Sizing
- •Maximum 5% of portfolio per trade
- •No more than 3 concurrent positions
- •Total exposure capped at 15% of portfolio
Diversification
- •No more than 2 positions in same sector
- •Spread trades across different expiration dates
- •Avoid correlated stocks (e.g., JPM + WFC)
Backtesting Methodology
Every aspect of the system has been backtested against 1,847 trades across 2,000+ stocks spanning five years of market data. Our backtesting framework follows institutional-grade standards:
Walk-Forward Analysis
Parameters optimized on 12-month rolling windows, then tested on the next 3 months. No look-ahead bias—every decision uses only data available at the time.
Realistic Execution
All backtests include slippage (0.5% per leg), commissions ($0.65/contract), and bid-ask spread costs. No mid-price fills assumed.
Out-of-Sample Validation
30% of data held out for validation. System parameters were NOT adjusted based on out-of-sample results to prevent overfitting.
Monte Carlo Simulation
10,000 randomized trade sequences tested to verify the system's edge persists across different ordering of trades and market conditions.
Key finding: The system's edge is statistically significant (p < 0.01) across all test periods. The 94.2% win rate in high-IVR environments is not a product of curve-fitting — it reflects the persistent volatility risk premium that has been documented in academic literature for decades.
Strategy Comparison: Why Volatility Selling Works
We tested multiple options strategies across different volatility regimes. Here's how they compare in high-IVR environments:
| Strategy | Win Rate | Avg Return | Max Loss | Verdict |
|---|---|---|---|---|
| Iron Condor ✓ | 95.7% | +12-18% | Defined | Selected |
| Straddle | 45% | +8% | Unlimited | Rejected |
| Calendar Spread | 62% | +6% | Variable | Marginal |
| Covered Call | 70% | +4% | Stock risk | Marginal |
| Directional Puts/Calls | 35% | -22% | 100% | Rejected |
Technology Stack
The system is powered by a custom-built technology stack designed for speed, reliability, and transparency:
Python Screener
Custom-built screening engine that scans S&P 500, NASDAQ-100, and Russell 2000 stocks daily using Polygon.io API, pandas, and numpy for statistical analysis.
Real-Time Data
Live options chain data via Polygon.io API with sub-second refresh rates. Dividend calendar integration with Alpha Vantage.
Auto-Profit Taker
Automated monitoring of all open positions. When a position reaches 85% of max profit, the system flags it for immediate closure.
Tools & Automation
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Why Fixed $2K Position Sizing Outperforms
We extensively backtested dynamic position sizing ($2K-$5K based on portfolio utilization) against fixed $2K per trade. The results were clear: fixed sizing wins.
| Metric | Fixed $2K | Dynamic $2K-$5K | Verdict |
|---|---|---|---|
| Win Rate | 95.7% | 95.7% | Tie |
| Net P/L | $208K | $4,081 | Fixed wins |
| Profit Factor | 2.41 | 1.42 | Fixed wins |
| Avg Per Trade | $90.24 | $52.32 | Fixed wins |
| Max Drawdown | Lower | Higher | Fixed wins |
The $5K Position Size Problem
When dynamic sizing scales positions to $5,000, the losses become disproportionately large. Our backtest data shows:
Why Larger Positions Underperform
Recommendation: Use fixed $2,000 per position. This is the optimal size that maximizes risk-adjusted returns while keeping drawdowns manageable. If you have a larger account, take more positions rather than bigger positions.
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