• 09/03/2020
  • Public Content

Finance: Monte Carlo

Monte Carlo algorithms solve deterministic problems by using a probabilistic analogue. The algorithm requires repeated simulations of chance that lend themselves well to parallel processing and vectorization. The simulations in this example are run serially, with Intel® Cilk™ Plus Array Notation (AN) for vectorization, with Intel Cilk Plus
cilk_for
for parallelization, and with both vectorization and
cilk_for
. In this example, the Monte Carlo algorithm is utilized to estimate the valuation of a European swaption, which is fundamentally calculated by the difference between the strike price and the future estimated value, or forward swap rate. The Monte Carlo algorithm estimates the valuation by applying the initial conditions to a normal distribution over many simulations to calculate a normal valuation.
Click here for a more in-depth discussion about the sample as well as more information about the design choices of this sample.
Based on an original code by Paul Glasserman and Xiaoliang Zhao (Columbia University, 1999-2000) with subsequent modifications by Mike Giles (Oxford University, 2005-8)
 
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Product and Performance Information

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Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserverd for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804