This chapter focuses on strategies for managing and profiting from event-driven market risks, such as earnings announcements, elections, or macroeconomic policy decisions. These events often trigger sharp changes in market volatility, which traditional risk models, like the Black–Scholes model, struggle to capture due to their constant volatility assumption. The case introduces a technique for extracting forward implied volatility, which uses options with overlapping maturities to isolate expected volatility changes during event-specific periods, offering a precise tool for analyzing market reactions to these discrete events. A practical example involves Amazon’s stock (AMZN) leading up to an earnings announcement. The study examines two trading strategies: the first consists of buying a straddle (a combination of call and put options) that expires after the announcement. In contrast, the second combines this position with selling a straddle expiring before the announcement. These strategies aim to capitalize on anticipated volatility increases during the earnings period. By analyzing implied volatility before and after the event, the study demonstrates how forward implied volatility provides insights into market expectations, enabling traders to focus on event-specific risks. The case highlights challenges in trading around event risk, such as managing option sensitivities (“Greeks”) and market volatility mispricing.