Numerische Mathematik

, Volume 122, Issue 1, pp 133–167 | Cite as

Iterative methods for the solution of a singular control formulation of a GMWB pricing problem

  • Y. Huang
  • P. A. Forsyth
  • G. Labahn


Discretized singular control problems in finance result in highly nonlinear algebraic equations which must be solved at each timestep. We consider a singular stochastic control problem arising in pricing a guaranteed minimum withdrawal benefit (GMWB), where the underlying asset is assumed to follow a jump diffusion process. We use a scaled direct control formulation of the singular control problem and examine the conditions required to ensure that a fast fixed point policy iteration scheme converges. Our methods take advantage of the special structure of the GMWB problem in order to obtain a rapidly convergent iteration. The direct control method has a scaling parameter which must be set by the user. We give estimates for bounds on the scaling parameter so that convergence can be expected in the presence of round-off error. Example computations verify that these estimates are of the correct order. Finally, we compare the scaled direct control formulation to a formulation based on a block version of the penalty method (Huang and Forsyth in IMA J Numer Anal 32:320–351, 2012). We show that the scaled direct control method has some advantages over the penalty method.

Mathematics Subject Classification (2000)

65N06 93C20 


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of WaterlooWaterlooCanada
  2. 2.Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada

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