CaseMark Modeling Event Driven Trading Analysis
When To Use
- Evaluating M&A arbitrage spreads (merger arb, tender offers, spin-offs)
- Analyzing corporate actions as catalysts (earnings, restructurings, dividend changes, share buybacks)
- Assessing regulatory or legal event outcomes (FDA decisions, antitrust rulings, litigation verdicts)
- Pricing event-driven situations where a discrete catalyst will resolve pricing uncertainty within a known timeframe
- Screening for mispriced optionality around scheduled or anticipated corporate/macro events
Inputs To Gather
- Event specification: Type of event, expected date or date range, involved entities, and deal/event terms
- Security data: Current price, implied volatility, options chain (if applicable), historical price action around prior similar events, short interest, borrow cost
- Deal/event terms: Consideration offered (cash, stock, mixed), conditions precedent, regulatory approvals required, breakup/termination fees [VERIFY deal terms against latest proxy/filing]
- Comparable precedents: Historical completion rates for similar event types, typical timeline from announcement to close, historical spread behavior
- Market microstructure: Liquidity profile, bid-ask spreads, average daily volume, institutional ownership concentration
- Risk factors: Identified deal/event risks—antitrust, financing contingencies, shareholder vote thresholds, MAC clauses
Workflow
Classify the event type and define the scenario tree
- Identify the primary catalyst (e.g., merger close, FDA approval, earnings surprise)
- Map discrete outcomes: success/close, failure/break, modified terms, delayed timeline
- Assign initial probability estimates to each branch based on precedent data
Establish pricing under each scenario
- For M&A: calculate deal-close value (offer price adjusted for proration, collar, CVR), break price (standalone or re-rate target)
- For binary events (FDA, litigation): estimate upside and downside price targets using comps, DCF, or historical event-day moves
- For earnings/guidance: model beat/miss/inline scenarios with magnitude estimates anchored to consensus dispersion
Compute expected value and spread analysis
- Calculate probability-weighted expected return across scenarios
- Annualize the gross spread for time-value comparison:
Annualized Return = (Gross Spread / Current Price) × (365 / Days to Close) - Compare annualized return to cost of capital, financing costs, and borrow costs for short legs
Assess risk/reward asymmetry
- Calculate downside-to-upside ratio:
D/U = |Break Loss| / |Deal Gain| - Determine implied probability of completion priced into the current spread:
Implied Prob = Downside / (Downside + Upside) - Compare implied probability to your estimated probability—identify edge or lack thereof
- Calculate downside-to-upside ratio:
Model timing and carry dynamics
- Estimate timeline to resolution with confidence intervals
- Calculate carry cost: financing, borrow fees, dividend differentials, opportunity cost
- Stress-test returns under delayed-close scenarios (e.g., +30, +60, +90 days)
Run sensitivity analysis
- Vary completion probability (±10–20%) and observe impact on expected return
- Vary break price (±5–15% from base case) to capture valuation uncertainty
- Test portfolio-level impact if running multiple event positions simultaneously
Construct position sizing and hedging framework
- Size based on Kelly criterion or fractional-Kelly given confidence level
- Identify hedging instruments: put spreads for downside, index hedges for systematic risk, pairs for sector exposure
- Define stop-loss triggers tied to fundamental milestones (e.g., regulatory objection, financing withdrawal) rather than arbitrary price levels
Output
- Event summary table: Event type, key dates, involved parties, current spread, implied probability
- Scenario matrix: Each outcome branch with probability, target price, return, and annualized return
- Expected value calculation: Probability-weighted return, edge vs. implied market pricing
- Risk metrics: Downside/upside ratio, max loss, carry cost per month, breakeven hold period
- Sensitivity tables: Return sensitivity to probability changes, break-price changes, and timeline delays
- Position recommendation: Suggested sizing, entry levels, hedge structure, and catalyst-driven exit triggers
Quality Checks
- Implied probability derived from the spread must be internally consistent with the scenario prices used
- Annualized returns must account for actual expected days-to-close, not just announced target date
- Break price estimates should be supported by at least two independent methods (comps, pre-announcement price, DCF)
- Verify all deal terms against the most recent SEC filing or equivalent disclosure [VERIFY]
- Confirm borrow availability and cost for any short legs before finalizing the model [VERIFY]
- Cross-check event timeline against regulatory calendars (e.g., HSR waiting periods, FDA PDUFA dates) [VERIFY]
- Flag any position where gross spread is less than 2× estimated carry cost as marginal
- Ensure scenario probabilities sum to 100% and no outcome branch is omitted