Vertical Option Spreads: A Study of the 1.8 Standard Deviation Inflection Point
By Charles Conrick IV and Scott Hanson
Quick Summary
A quantitative approach to trading vertical option spreads (bull put spreads, bear call spreads, and iron condors) based on placing strikes at 1.8 standard deviations from the current price. Integrates fundamental analysis, technical indicators, Monte Carlo simulation using Oracle's Crystal Ball software, and behavioral finance concepts for systematic weekly option trading.
Executive Summary
Dr. Charles Conrick IV and Scott Hanson present a systematic methodology for trading vertical option spreads based on the statistical concept that approximately 96.4% of price movements fall within 1.8 standard deviations of the mean. The book covers the full workflow from fundamental and technical analysis to options theory, the Greeks, behavioral biases, normal distribution theory, Monte Carlo simulation, and practical trade execution using weekly options on the SPY ETF.
Core Thesis
By structuring vertical spreads with short strikes positioned at or beyond 1.8 standard deviations from the current price, traders can create positions with a statistically high probability of profit. The key innovation is combining this statistical framework with Monte Carlo simulation (using Oracle's Crystal Ball software) to model thousands of potential price outcomes and assess the probability of various spread structures being profitable.
Key Content
Options Fundamentals
Thorough coverage of vertical spreads (debit and credit), the Greeks (delta, gamma, theta, vega, rho), and the iron condor strategy as a market-neutral income approach.
Behavioral Finance
Reviews key biases (overconfidence, anchoring, mental accounting, confirmation bias, gambler's fallacy, herd behavior, loss aversion) and their impact on options trading decisions.
Statistical Framework
Explains normal distribution, skewness, kurtosis, Modern Portfolio Theory, CAPM, Black-Scholes, and the concept of the "sombrero" distribution of option returns.
Monte Carlo Simulation
Detailed walkthrough of setting up Crystal Ball simulations to model SPY price distributions, generate probability estimates for various strike placements, and optimize spread structures.
Weekly Trade Process
Step-by-step methodology for selecting and executing weekly option spreads, including timing, strike selection, position management, and exit rules.
Critical Assessment
Strengths
- Rigorous quantitative framework combining statistics, simulation, and options theory
- Practical weekly trading process with clear rules
- Integration of behavioral finance awareness with quantitative execution
- Companion website with additional tools
Limitations
- Heavy reliance on normal distribution assumptions; fat tails can devastate the strategy
- Crystal Ball software dependency adds complexity and cost
- Focused almost exclusively on SPY; limited discussion of other underlyings
- Tail risk management could be more thoroughly addressed
Conclusion
A solid quantitative framework for options income trading that combines statistical rigor with practical execution guidance. Best suited for traders comfortable with probability-based approaches and willing to accept the inherent tail risk of short premium strategies.
