A general approach for lookback option pricing under Markov models
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AbstractWe propose a computationally efficient method for pricing various types of lookback options under Markov models. We utilize the model-free representations of lookback option prices as integrals of first passage probabilities. We combine efficient numerical quadrature with continuous-time Markov chain approximation for the first passage problem to price lookbacks. Our method is applicable to a variety of models, including one-dimensional time-homogeneous and time-inhomogeneous Markov processes, regime-switching models and stochastic local volatility models. We demonstrate the efficiency of our method through various numerical examples.
All Author(s) ListGongqiu Zhang, Lingfei Li
Journal nameQuantitative Finance
Volume Number23
Issue Number9
PublisherTaylor & Francis
Pages1305 - 1324
LanguagesEnglish-United States
KeywordsLookback options, Drawdown, Markov chain approximation, Gauss quadrature

Last updated on 2023-22-12 at 14:11