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- W2159162023 abstract "In this paper we identify important opportunities for parallelization in the least-squares Monte Carlo (LSM) algorithm, due to Longstaff and Schwartz, for the pricing of American options. The LSM method can be divided into three phases: path-simulation, calibration and valuation. We describe how each of these phases can be parallelized, with more focus on the calibration phase, which is inherently more difficult to parallelize. We implemented these parallelization techniques on Blue Gene using the Quantlib open source financial engineering package. We achieved up to factor of 9 speed-up for the calibration phase and 18 for the complete LSM method on a 32 processor BG/P system using monomial basis functions." @default.
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- W2159162023 date "2008-04-01" @default.
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- W2159162023 title "Optimizations in financial engineering: The Least-Squares Monte Carlo method of Longstaff and Schwartz" @default.
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- W2159162023 doi "https://doi.org/10.1109/ipdps.2008.4536290" @default.
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