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A General Approach for Lookback Option Pricing under Markov Models

Gongqiu Zhang and Lingfei Li

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Abstract: We propose a very 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.

Date: 2021-12
New Economics Papers: this item is included in nep-cwa and nep-rmg
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Handle: RePEc:arx:papers:2112.00439