Event-Driven and Arbitrage Strategies › Summary

Event-driven and arbitrage strategies exploit specific corporate events and relative value relationships with identifiable catalysts and timelines. Unlike purely statistical strategies, they require integrating quantitative analysis with fundamental judgment about event-specific risks.

Key concepts from this chapter include:

• Merger arbitrage captures deal spreads by going long targets and hedging acquirer risk in stock deals. The critical variable is deal completion probability, which determines whether the spread adequately compensates for break risk.

• Implied deal probability can be extracted from market prices using the formula $p = \frac{P_T - P_{\text{pre}}}{O - P_{\text{pre}}}$, providing a benchmark against which to compare fundamental probability assessments.

• Earnings strategies exploit predictable volatility around announcements and post-announcement drift. Options strategies target the high implied volatility before announcements, while directional trades profit from surprise-related price movements.

• Fixed income arbitrage trades relative mispricings in bond markets, including on/off-the-run spreads, yield curve positions, and basis trades between cash and futures. These strategies require careful attention to financing costs and leverage management.

• Event-driven risk features fat tails and negative skewness that standard risk measures underestimate. Scenario analysis and tail-aware position sizing are essential for managing these portfolios.

• Hedging with options can dramatically improve risk profiles at the cost of reduced expected returns. The appropriate hedge level depends on portfolio leverage and risk tolerance.

The next chapter on backtesting will explore how to rigorously test these strategies using historical data, accounting for survivorship bias and the unique challenges of simulating event-driven returns.