Primal-Dual Simulation Algorithm for Pricing Multidimensional American Options

By Leif Andersen, Mark Broadie. Management Sciences, 2004

458 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2d3ae59227919e3d4521740a483366d908e29653

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Citations in the corpus

Monte Carlo valuation of American options (2002, unknown): “A benchmark example in this subject appears to be the Bermudan n-max-call, studied in Broadie and Glasserman (1997b), and used as a test example by Haugh and Kogan (2001), Fu et al. (2001) , and Andersen and Broadie (2001).”
The duality of optimal exercise and domineering claims: a Doob–Meyer decomposition approach to the Snell envelope (2007, background): “Minimax duality can be effectively combined through a convergent feedback loop with ingenuous optimal exercise time approximations that produce tight lower bounds, as in [15, 1, 25, 14].”
Extending quadrature methods to value multi-asset and complex path dependent options (2007, methodology): “Unfortunately, its calculation is often problematic, although there are practical approaches to circumvent this (see Andersen and Broadie, 2004, for more details). Of the various Monte Carlo techniques available, the most practical alternative to the dual approach could be those using regression to ”
Representations and regularities for solutions to BSDEs with reflections (2005, background): “[1,3,12,4]), the numerical analysis for BSDERs is yet fully explored.”
Pricing Asset Scheduling Flexibility using Optimal Switching (2008, methodology): “It is also possible to obtain upper bounds by using the duality theory developed for American options (Andersen and Broadie, 2004; Haugh and Kogan, 2004).”
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation (2018, background): “Problems of this nature arise naturally in many settings, most notably in the pricing of financial derivatives (Andersen and Broadie 2004, Haugh and Kogan 2004, Desai et al. 2012). We first give a brief formulation for a class of optimal stopping problems. A more detailed exposition can be found in ”
TRUE UPPER BOUNDS FOR BERMUDAN PRODUCTS VIA NON‐NESTED MONTE CARLO (2009, methodology): “We will now discuss, how the martingale M̂π can be used to reduce the variance in the primal-dual algorithm of Andersen and Broadie (2004).”
A PRIMAL–DUAL ALGORITHM FOR BSDES (2013, methodology): “This algorithm generalizes a variant of the primal–dual algorithms of Andersen and Broadie (2004) and Haugh and Kogan (2004) from classical Bermudan option pricing (i.e., the case f ≡ 0) to the case of convex generators.”
Error Criteria for Numerical Solutions of Backward SDEs (2010, background): “Moreover, by duality, upper biased numerical solutions can be obtained (see [1, 4, 20, 31]).”
Interpretable Optimal Stopping (2018, background): “Examples include Rogers (2002), Andersen and Broadie (2004), Haugh and Kogan (2004), Chen and Glasserman (2007), Brown et al. (2010) and Desai et al. (2012b).”
MONTE CARLO METHODS FOR THE VALUATION OF MULTIPLE‐EXERCISE OPTIONS (2004, unknown): “A recent development (Andersen and Broadie 2001; Haugh and Kogan 2001; Rogers 2002), has been to consider the dual problem and, using this, try to improve the Monte Carlo approach and produce a positive-biased estimate for the price.”
Simulation for American Options: Regression Now or Regression Later? (2004, methodology): “Broadie, Glasserman, and Ha [5] develop a method for pricing American options by simulation in which the conditional expectations in the dynamic programming recursion are approximated using weighted averages of simulated downstream option values.”