Leave-one-out least squares Monte Carlo algorithm for pricing Bermudan options

Jeechul Woo, Chenru Liu and Jaehyuk Choi

Papers from arXiv.org

Abstract: The least squares Monte Carlo (LSM) algorithm proposed by Longstaff and Schwartz (2001) is widely used for pricing Bermudan options. The LSM estimator contains undesirable look-ahead bias, and the conventional technique of avoiding it requires additional simulation paths. We present the leave-one-out LSM (LOOLSM) algorithm to eliminate look-ahead bias without doubling simulations. We also show that look-ahead bias is asymptotically proportional to the regressors-to-paths ratio. Our findings are demonstrated with several option examples in which the LSM algorithm overvalues the options. The LOOLSM method can be extended to other regression-based algorithms that improve the LSM method.

Date: 2018-10, Revised 2024-05
New Economics Papers: this item is included in nep-big and nep-cmp
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Published in Journal of Futures Markets (2024)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1810.02071

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