Beating the Omega Clock: An Optimal Stopping Problem with Random Time-horizon under Spectrally Negative Lévy Models

Abstract

We study the optimal stopping of an American call option in a random time-horizon under exponential spectrally negative Lévy models. The random time-horizon is modeled as the so-called Omega default clock in insurance, which is the first time when the occupation time of the underlying Lévy process below a level $y$, exceeds an independent exponential random variable with mean $1/q>0$. We show that the shape of the value function varies qualitatively with different values of $q$ and $y$. In particular, we show that for certain values of $q$ and $y$, some quantitatively different but traditional up-crossing strategies are still optimal, while for other values we may have two disconnected continuation regions, resulting in the optimality of two-sided exit strategies. By deriving the joint distribution of the discounting factor and the underlying process under a random discount rate, we give a complete characterization of all optimal exercising thresholds. Finally, we present an example with a compound Poisson process plus a drifted Brownian motion.

35 pages, 1 figure. The Annals of Applied Probability, forthcoming

References in corpus (3)

• On magnitude, asymptotics and duration of drawdowns for Lévy models
• Optimal Multiple Stopping with Negative Discount Rate and Random Refraction Times under Levy Models
• On obtaining simple identities for overshoots of spectrally negative Lévy processes

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