Event-Driven Trading
Overview
Event-driven trading capitalises on price dislocations caused by scheduled and unscheduled catalysts — earnings announcements, FOMC meetings, governance votes, protocol upgrades, token unlocks, mergers, and geopolitical shocks. The edge comes from correctly anticipating the event's impact or exploiting the volatility expansion around it.
Key Concepts
Implied vs realised volatility around events. Earnings surprises and guidance revisions. Token unlock schedules and supply shocks. Protocol upgrades and hard forks. Mergers, acquisitions, and spin-offs. Regulatory announcements and legal rulings.
Entry Signals
Pre-event: straddle/strangle if volatility is cheap relative to history. Directional: position before event if strong thesis. Post-event: trade the fade or continuation after initial reaction settles into clear structure.
Exit Signals
Volatility crush after event (close straddles). Initial reaction reversed significantly. Target hit or thesis invalidated by the actual event outcome.
Best Timeframes
15-minute to 4H for intraday events (FOMC, earnings). Daily for multi-day events (token unlocks). Weekly for structural events (hard forks, regulatory).
Pro Tips
Never risk your entire account on a single event. Use options or small position sizes to limit binary risk. The second move after an event (the 're-think') often provides better setups than the initial spike.
More Topics in This Category
Earnings & Valuation Analysis
Earnings and valuation analysis evaluates a company's financial performance and market pricing to determine whether its stock is undervalued, fairly valued, or overvalued. By examining revenue growth, profit margins, earnings per share, and valuation multiples such as price-to-earnings and price-to-sales ratios, traders and investors can assess whether the current market price is justified by fundamentals.
Qualitative Factor Analysis
Qualitative factor analysis evaluates the non-numerical attributes of an asset or company that influence long-term value — management quality, competitive moats, brand strength, regulatory positioning, and industry trends. While quantitative metrics measure what has happened, qualitative analysis assesses the strategic factors that will drive future performance, providing context that numbers alone cannot capture.
Intermarket Analysis
Intermarket analysis studies the correlations and divergences between asset classes — equities, bonds, commodities, currencies, and crypto — to gain a macro edge. When relationships that normally hold start breaking down, it often foreshadows major market regime shifts. Traders use these cross-market signals to confirm or contradict setups in their primary market.
Macro Trading
Macro trading uses macroeconomic data — GDP, inflation, interest rates, employment, and central bank policy — to establish directional biases across currencies, equities, bonds, and commodities. Traders position for large economic regime shifts rather than intraday noise, using fundamental catalysts as the primary edge.