The Obstacle Version of the Geometric Dynamic Programming Principle: Application to the Pricing of American Options Under Constraints

We provide an obstacle version of the Geometric Dynamic Programming Principle of Soner and Touzi (J. Eur. Math. Soc. 4:201–236, 2002) for stochastic target problems. This opens the doors to a wide range of applications, particularly in risk control in finance and insurance, in which a controlled stochastic process has to be maintained in a given set on a time interval [0,T]. As an example of application, we show how it can be used to provide a viscosity characterization of the super-hedging cost of American options under portfolio constraints, without appealing to the standard dual formulation from mathematical finance. In particular, we allow for a degenerate volatility, a case which does not seem to have been studied so far in this context.

[1]  Bruno Bouchard,et al.  Stochastic Target Problems with Controlled Loss , 2009, SIAM J. Control. Optim..

[2]  W. Ames Mathematics in Science and Engineering , 1999 .

[3]  H. Soner,et al.  A stochastic representation for mean curvature type geometric flows , 2003 .

[4]  Bruno Bouchard,et al.  Barrier Option Hedging under Constraints: A Viscosity Approach , 2006, SIAM J. Control. Optim..

[5]  H. Soner,et al.  Optimal Replication of Contingent Claims Under Portfolio Constraints , 1996 .

[6]  N. Karoui Les Aspects Probabilistes Du Controle Stochastique , 1981 .

[7]  Nizar Touzi,et al.  Stochastic Target Problems, Dynamic Programming, and Viscosity Solutions , 2002, SIAM J. Control. Optim..

[8]  H. Soner,et al.  Dynamic programming for stochastic target problems and geometric flows , 2002 .

[9]  Jakša Cvitanić,et al.  Super-replication in stochastic volatility models under portfolio constraints , 1999, Journal of Applied Probability.

[10]  I. Karatzas,et al.  On the pricing of contingent claims under constraints , 1996 .

[11]  丸山 徹 Convex Analysisの二,三の進展について , 1977 .

[12]  Nizar Touzi,et al.  Superreplication Under Gamma Constraints , 2000, SIAM J. Control. Optim..

[13]  B. Bouchard Stochastic Target with Mixed diffusion processes , 2002 .

[14]  S. Shreve,et al.  Methods of Mathematical Finance , 2010 .

[15]  N. Karoui,et al.  Dynamic Programming and Pricing of Contingent Claims in an Incomplete Market , 1995 .

[16]  Steven Kou,et al.  Hedging American contingent claims with constrained portfolios , 1998, Finance Stochastics.

[17]  Steven E. Shreve,et al.  Valuation of exotic options under shortselling constraints , 2002, Finance Stochastics.

[18]  Jakša Cvitanić,et al.  Hedging Contingent Claims with Constrained Portfolios , 1993 .

[19]  G. Barles Solutions de viscosité des équations de Hamilton-Jacobi , 1994 .

[20]  H. Föllmer,et al.  Optional decompositions under constraints , 1997 .

[21]  Bruno Bouchard,et al.  Weak Dynamic Programming Principle for Viscosity Solutions , 2011, SIAM J. Control. Optim..

[22]  Hui Wang,et al.  A Barrier Option of American Type , 2000 .

[23]  Bruno Bouchard,et al.  Optimal Control under Stochastic Target Constraints , 2009, SIAM J. Control. Optim..

[24]  Nizar Touzi,et al.  The Problem of Super-replication under Constraints , 2003 .

[25]  Bruno Bouchard Stochastic targets with mixed diffusion processes and viscosity solutions , 2002 .

[26]  P. Lions,et al.  User’s guide to viscosity solutions of second order partial differential equations , 1992, math/9207212.

[27]  Nizar Touzi,et al.  Penalty approximation and analytical characterization of the problem of super-replication under portfolio constraints , 2005 .

[28]  Dimitri P. Bertsekas,et al.  Stochastic optimal control : the discrete time case , 2007 .