Advanced Options Guide III: Macro Event and Earnings Trading
Pricing Volatility Around Scheduled Events
Advanced Options Guide · Intermediate
Earnings, CPI and FOMC: comparing the move the market prices with the move that actually arrives.
ABOUT THE BOOK
Many traders know the earnings-season experience well. They call the direction correctly and the options they bought still lose money, because implied volatility collapses the moment the announcement is out. Or, having heard that IV crush is payday for sellers, they sell a straddle and are run over by a gap larger than anyone priced. CPI and FOMC days are no different: plenty of rules of thumb circulate, and few of them have been checked against data.
Across seven chapters, the book returns to one central question: compared with the move an event actually produces, is the price the market set for it rich or cheap? It shows how to read the implied move from at-the-money straddles and the IV term structure, reviews earnings moves in NVDA, TSLA, AAPL and others, and tests the results of selling volatility across 51 earnings releases from six large technology companies between 2022 and 2024. It builds an event-trading framework from straddles, iron condors, calendars, ratio spreads, Gamma scalping and Vega-neutral positions. The macro chapters test how rates, CPI and FOMC affected volatility in 2022 to 2024, and the final two chapters cover portfolio risk management and the decision biases described by behavioral finance.
After reading it, you will be able to calculate the move the market is pricing before each event, judge whether it is rich or cheap, and then choose a structure, size the position and control tail risk. The conclusions rest on historical data and the calculations can be reproduced, so you can retest them against your own trading costs and capital. The book also gives calculable answers to two practical questions: how long a losing streak is normal, and how many trades a thin edge needs before it shows.
HIGHLIGHTS
Reading the implied move. The at-the-money straddle price roughly equals the market's expected absolute move, about 0.8 standard deviations. The book shows how to extract event information from near-dated IV and the term structure.
Testing beliefs on earnings. Across 51 earnings releases from six large tech companies in 2022 to 2024, actual moves exceeded and fell short of the priced move about equally often, which challenges the idea that IV is always too expensive.
Macro claims, checked. Popular claims about rates and the VIX, jobs data and short-dated IV, and whether sellers win after data releases are tested on 2022 to 2024 data, showing which hold and which hold only in some periods.
Reproducible backtests. Backtests use public data with sources, parameters and samples stated, so readers can rerun them and see the cost index option sellers pay in a handful of crisis weeks.
Discipline in numbers. The illusion of control, the disposition effect and the gambler's fallacy are explained, and the normal range of losing streaks is calculated, helping readers follow written rules and control the size of every bet.
WHO IT IS FOR
Option traders who call the direction right yet lose after earnings, and want to understand how IV crush works.
Sellers who routinely write straddles or iron condors before earnings and want to quantify their tail risk.
Investors who follow CPI, FOMC and other macro data and want to express event views through option structures.
Individual investors and practitioners building a process for screening, backtesting and reviewing event trades.
IN BRIEF
Earnings season is when volatility pricing is most concentrated; the book shows how to read the opportunity. Cases cover popular stocks such as AAPL, NVDA and TSLA, close to real trading. Handle CPI and FOMC with confidence and judge whether high IV is overpriced.
CONTENTS
Chapter 1 The Underlying Logic of Earnings and Volatility
1.1 The Volatility Mechanism of Earnings Season: Information Asymmetry and the Game of Expectations
1.2 The Rise-Before, Crush-After Effect in Implied Volatility: How Institutions Position and Harvest along the Curve
1.3 The Pricing Structure of Market Expectations: Mapping from EPS to Changes in IV
1.4 Case Review: Pre- and Post-Earnings Volatility Models for NVDA, TSLA and AAPL
Chapter 2 Event-Driven Strategic Thinking
2.1 Earnings as Event Risk: How Institutions Define It
2.2 Expectation Gaps and Volatility Gaps: How Institutions Position Ahead of Time
2.3 The Pre-Event Volatility Premium: Why Buying Volatility Often Loses Money
2.4 Post-Earnings Volatility Collapse: How to Capture IV Crush Opportunities
Chapter 3 A Practical Framework for Volatility Arbitrage
3.1 Straddles and Strangles: Pure Volatility Trades When Direction Is Unknown
3.2 Iron Condors and Butterflies: Range Trades with Controlled Risk
3.3 Ratio Spreads and Backspreads: Asymmetric Event Bets
3.4 Gamma Scalping: Dynamically Capturing Volatility in Violent Markets
3.5 Vega Neutral: Balancing Risk in Volatility Trading
Chapter 4 Macro Events and Cross-Cycle Linkages
4.1 The Coupling of Earnings Season and the Macro Cycle
4.2 How Fed Policy and Interest Rates Transmit to Volatility
4.3 How Macro Data (CPI, PPI, Employment) Affect Short-Term Volatility
4.4 Case Study: The Evolution of Earnings-Season Volatility Patterns, 2020 to 2023
Chapter 5 Deconstructing and Backtesting Strategies
5.1 Building an Event Trading Model from Historical Data
5.2 Backtesting Earnings-Season Volatility in SPY and QQQ
5.3 Single-Stock Event Trades: Structured Strategies on AMZN, META and NFLX
5.4 Statistical Validation: P&L Distributions Under Different Volatility Structures
Chapter 6 From Speculation to Systems: How Institutions Think About Event Trading
6.1 How Institutions Measure the Expectation Gap and Volatility Mispricing
6.2 How to Build a Quantitative Screening System for Earnings Events
6.3 From Single Events to Portfolio Management: Reducing Systematic Volatility Risk
6.4 The Professional Trader’s Review Logic and Capital Allocation Framework
Chapter 7 Mindset and Execution: The Trader’s Psychological Discipline
7.1 From Emotion to Probability: Avoiding the Earnings-Gamble Mindset
7.2 Discipline in Event Trading: Planning, Execution, and Adjustment
7.3 Coping with Losing Streaks and Drawdowns
7.4 Steady Long-Term Growth and the Professional Mindset
