Department of Economics and Business Economics

Value Function Approximation or Stopping Time Approximation: A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression

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Value Function Approximation or Stopping Time Approximation : A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression. / Stentoft, Lars.

In: Journal of Computational Finance, 2014, p. 65-120.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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@article{d077fa2aa48945d2bd620eb2dd2d9444,
title = "Value Function Approximation or Stopping Time Approximation: A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression",
abstract = "In their 2001 paper, Longstaff and Schwartz suggested a method for American option pricing using simulation and regression, and since then this method has rapidly gained importance. However, the idea of using regression and simulation for American option pricing was used at least as early as 1996, by Carriere. In this paper, we provide a thorough comparison of these two methods and relate them to the work of Tsitsiklis and Van Roy. Although the methods are often considered to be similar, this analysis allows us to point out an important but often overlooked difference between them. We further show that, due to this difference, it is possible to provide arguments favoring the method of Longstaff and Schwartz. Finally, we compare the methods in a realistic numerical setting and show that practitioners would do well to choose the method of Longstaff and Schwartz instead of the methods of Carriere or Tsitsiklis and Van Roy for American option pricing.",
author = "Lars Stentoft",
year = "2014",
language = "English",
pages = "65--120",
journal = "Journal of Computational Finance",
issn = "1460-1559",
publisher = " Risk Publications",

}

RIS

TY - JOUR

T1 - Value Function Approximation or Stopping Time Approximation

T2 - A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression

AU - Stentoft, Lars

PY - 2014

Y1 - 2014

N2 - In their 2001 paper, Longstaff and Schwartz suggested a method for American option pricing using simulation and regression, and since then this method has rapidly gained importance. However, the idea of using regression and simulation for American option pricing was used at least as early as 1996, by Carriere. In this paper, we provide a thorough comparison of these two methods and relate them to the work of Tsitsiklis and Van Roy. Although the methods are often considered to be similar, this analysis allows us to point out an important but often overlooked difference between them. We further show that, due to this difference, it is possible to provide arguments favoring the method of Longstaff and Schwartz. Finally, we compare the methods in a realistic numerical setting and show that practitioners would do well to choose the method of Longstaff and Schwartz instead of the methods of Carriere or Tsitsiklis and Van Roy for American option pricing.

AB - In their 2001 paper, Longstaff and Schwartz suggested a method for American option pricing using simulation and regression, and since then this method has rapidly gained importance. However, the idea of using regression and simulation for American option pricing was used at least as early as 1996, by Carriere. In this paper, we provide a thorough comparison of these two methods and relate them to the work of Tsitsiklis and Van Roy. Although the methods are often considered to be similar, this analysis allows us to point out an important but often overlooked difference between them. We further show that, due to this difference, it is possible to provide arguments favoring the method of Longstaff and Schwartz. Finally, we compare the methods in a realistic numerical setting and show that practitioners would do well to choose the method of Longstaff and Schwartz instead of the methods of Carriere or Tsitsiklis and Van Roy for American option pricing.

M3 - Journal article

SP - 65

EP - 120

JO - Journal of Computational Finance

JF - Journal of Computational Finance

SN - 1460-1559

ER -