A nonparametric method for pricing and hedging American options

In this paper, we study the problem of estimating the price of an American option and its price sensitivities via Monte Carlo simulation. Compared to estimating the option price which satisfies a backward recursion, estimating the price sensitivities is more challenging. With the readily-computable...

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Main Authors: FENG, Guiyun, LIU, Guangwu, SUN, Lihua
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Language:English
Published: Institutional Knowledge at Singapore Management University 2013
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6509
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7508/viewcontent/059.pdf
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spelling sg-smu-ink.lkcsb_research-75082020-02-13T08:59:04Z A nonparametric method for pricing and hedging American options FENG, Guiyun LIU, Guangwu SUN, Lihua In this paper, we study the problem of estimating the price of an American option and its price sensitivities via Monte Carlo simulation. Compared to estimating the option price which satisfies a backward recursion, estimating the price sensitivities is more challenging. With the readily-computable pathwise derivatives in a simulation run, we derive a backward recursion for the price sensitivities. We then propose nonparametric estimators, the k-nearest neighbor estimators, to estimate conditional expectations involved in the backward recursion, leading to estimates of the option price and its sensitivities in the same simulation run. Numerical experiments indicate that the proposed method works well and is promising for practical problems. 2013-12-08T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6509 info:doi/10.5555/2675983.2676073 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7508/viewcontent/059.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Operations and Supply Chain Management
spellingShingle Operations and Supply Chain Management
FENG, Guiyun
LIU, Guangwu
SUN, Lihua
A nonparametric method for pricing and hedging American options
description In this paper, we study the problem of estimating the price of an American option and its price sensitivities via Monte Carlo simulation. Compared to estimating the option price which satisfies a backward recursion, estimating the price sensitivities is more challenging. With the readily-computable pathwise derivatives in a simulation run, we derive a backward recursion for the price sensitivities. We then propose nonparametric estimators, the k-nearest neighbor estimators, to estimate conditional expectations involved in the backward recursion, leading to estimates of the option price and its sensitivities in the same simulation run. Numerical experiments indicate that the proposed method works well and is promising for practical problems.
format text
author FENG, Guiyun
LIU, Guangwu
SUN, Lihua
author_facet FENG, Guiyun
LIU, Guangwu
SUN, Lihua
author_sort FENG, Guiyun
title A nonparametric method for pricing and hedging American options
title_short A nonparametric method for pricing and hedging American options
title_full A nonparametric method for pricing and hedging American options
title_fullStr A nonparametric method for pricing and hedging American options
title_full_unstemmed A nonparametric method for pricing and hedging American options
title_sort nonparametric method for pricing and hedging american options
publisher Institutional Knowledge at Singapore Management University
publishDate 2013
url https://ink.library.smu.edu.sg/lkcsb_research/6509
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7508/viewcontent/059.pdf
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