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This short paper briefly describes the implementation of the least squares Monte Carlo method in the rlsm package.
J. Carriere, Valuation of the early-exercise price for options using simulations and nonparametric regression , Insurance: Mathematics and Economics 19
1996
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J. Demmel, Applied numerical linear algebra , Society for Industrial and Applied Mathematics, 1997
1997
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J. Tsitsiklis and B. Van Roy, Optimal stopping of Markov processes: Hilbert space, theory, approximation algorithms, and an application to pricing high-dimensional financial derivatives , IEEE Transactions on Automatic Control 44
1999
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F. Longstaff and E. Schwartz, Valuing American options by simulation: a simple least-squares approach , Review of Financial Studies 14
2001
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E. Clement, D. Lamberton, and P. Protter, An analysis of the Longstaff-Schwartz algorithm for American option pricing , Finance and Stochastics 6
2002
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L. Andersen and M. Broadie, Primal-dual simulation algorithm for pricing multidimensional american options , Management Science 50
2004
Cited alongside, same era.
M. Haugh and L. Kogan, Pricing American options: A duality approach , Operations Research 52
2004
Cited alongside, same era.
L. Rogers, Pathwise stochastic optimal control , SIAM J. Control Optimisation 46
2007
Cited alongside, same era.
D. Belomestny, A. Kolodko, and J. Schoenmakers, Regression methods for stochastic control problems and their convergence analysis , SIAM Journal on Control and Optimization 48
2010
Cited alongside, same era.
D. Brown, J. Smith, and P. Sun, Information relaxations and duality in stochastic dynamic programs , Operations Research 58
2010
Cited alongside, same era.
D. Eddelbuettel and R. Francois, Rcpp: Seamless R and C++ integration , Journal of Statistical Software 40
2011
Later among the works it cites.
R Core Team, R: A language and environment for statistical computing , R Foundation for Statistical Computing, 2013, ISBN 3-900051-07-0
2013
Later among the works it cites.
S. Tompaidis and C. Yang, Pricing american-style options by monte carlo simulation: alternatives to ordinary least squares , Journal of computational finance 18
2014
Later among the works it cites.
J. Yee, rlsm: Least squres monte carlo , 2017, Available at https://github.com/YeeJeremy/rlsm, R package version 1.0
2017
Later among the works it cites.
by same author, StochasticProcess , 2017, Available at https://github.com/YeeJeremy/StochasticProcess, R package version 1.0
2017
Later among the works it cites.
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