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Journal of Scientific Computing

, Volume 58, Issue 2, pp 409–430 | Cite as

A Comparison of Iterated Optimal Stopping and Local Policy Iteration for American Options Under Regime Switching

  • J. Babbin
  • P. A. Forsyth
  • G. Labahn
Article

Abstract

A theoretical analysis tool, iterated optimal stopping, has been used as the basis of a numerical algorithm for American options under regime switching (Le and Wang in SIAM J Control Optim 48(8):5193–5213, 2010). Similar methods have also been proposed for American options under jump diffusion (Bayraktar and Xing in Math Methods Oper Res 70:505–525, 2009) and Asian options under jump diffusion (Bayraktar and Xing in Math Fin 21(1):117–143, 2011). An alternative method, local policy iteration, has been suggested in Huang et al. (SIAM J Sci Comput 33(5):2144–2168, 2011), and Salmi and Toivanen (Appl Numer Math 61:821–831, 2011). Worst case upper bounds on the convergence rates of these two methods suggest that local policy iteration should be preferred over iterated optimal stopping (Huang et al. in SIAM J Sci Comput 33(5):2144–2168, 2011). In this article, numerical tests are presented which indicate that the observed performance of these two methods is consistent with the worst case upper bounds. In addition, while these two methods seem quite different, we show that either one can be converted into the other by a simple rearrangement of two loops.

Keywords

Iterated optimal stopping Local policy iteration Regime switching 

Mathematics Subject Classification

60G40 65N06 65K15 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Computational MathematicsUniversity of WaterlooWaterlooCanada
  2. 2.Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada

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