Option pricing method based on backward stochastic differential equation (BSDE)

A technology of stochastic differential equations and options, applied in the direction of machine execution devices, instruments, complex mathematical operations, etc., can solve problems such as performance bottlenecks, many execution times, and many simulation times, and achieve the effect of performance improvement

Inactive Publication Date: 2013-02-13
LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the large number of Monte Carlo simulations for each grid point, this step is not only executed many times, but also requires a large amount of data to be calculated; at the same time, the calculation of these data can only meet the characteristics of single instruction and single data, but is difficult to meet Features of Single Instruction Multiple Data (SIMD, Single Instruction Multiple Data)
Therefore, using BSDE's option pricing serial method to solve the option pricing problem has a certain performance bottleneck

Method used

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  • Option pricing method based on backward stochastic differential equation (BSDE)
  • Option pricing method based on backward stochastic differential equation (BSDE)
  • Option pricing method based on backward stochastic differential equation (BSDE)

Examples

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Embodiment 1

[0058] Specific implementation 1: In the entire spatial grid, the grid points on each event layer are executed sequentially, controlled by a for loop. In order to improve concurrency, the decrement of the loop is 2, and in each loop, execute twice Hotspot function, that is, the option pricing operation on two time layers, the starting index of each layer is controlled by the expression Ps*(N-j), and the values ​​of Y and Z are alternately stored by two groups of Y1, Z1 and Y2, Z2 for each time The Y and Z values ​​calculated by the layer, which in turn assist in executing the kernel function twice per loop. The implementation process is as follows:

[0059] / / Control the time layer, execute the kernel function twice in each cycle

[0060]for(j=N-1;j>=0;j=j-2)

[0061] {

[0062] ii=Ps*(N-j);

[0063] {

[0064] Call the option price kernel function

[0065]}

[0066] Determine whether the control variable of the time layer is greater than 0

[0067] if greater than ...

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Abstract

The invention provides an option pricing method based on a backward stochastic differential equation (BSDE). The method comprises the following steps that: a central processing unit (CPU) is used for dispersing the BSDE on time layers, constructing space-time discrete grids, and calculating a terminal condition which is used for pricing option according to the space-time discrete grids; and performing Monte Carlo simulation on each space point of each time layer between neighboring time layers at a many integrated core (MIC) end according to the terminal condition, and solving a final option pricing mathematical expectation value by performing backward calculation on each time layer one by one. By the method, the powerful parallel computing capabilities of the BSDE algorithm and the MIC are utilized, and option pricing calculation can be accelerated by dozens of times; and meanwhile, because of simple, short-period and good-performance code transplantation on an MIC architecture, the method is low in cost and has high parallelism degree and high-speed operational performance.

Description

technical field [0001] The present invention relates to a high-performance processing method for option pricing, in particular to an option pricing method based on backward stochastic differential equations, in particular to a method based on backward stochastic differential equations (BSDE, Backward Stochastic Differential Equation) on the MIC many-core architecture. ) option pricing method. Background technique [0002] MIC (Many Integrated Core) is a many-core processor launched by Intel Corporation. Compared with the general-purpose multi-core Xeon processor, the MIC many-core architecture has smaller cores and hardware threads, and the many-core processor has higher computing resource density. On-chip communication overhead is significantly reduced, and more transistors and energy are available for more complex parallel applications. Intel MIC products are based on the X86 architecture, based on heavy-core many-core processors, including more than 50 cores, and a vecto...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/04G06F17/13G06F9/38
Inventor 卢晓伟张清
Owner LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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