Parallel Option Pricing with BSDEs Method on MapReduce
MapKeduce is popular in cloud computing area. Its mainly used in Information Retrieval, Distributed Storage, DM, Machine Learning and so on. Its fit to parallel computing of great capacity for liquor data. Based on MapReduces property, we designed a computing model for option pricing with BSDEs on it. Option pricing is one of the most important parts in financial area. To promote precision of pricing, option pricing need complex calculating with big data set. This paper shows the implementation of option pricing with BSDEs on MapReduce. It gives the detail mapper and reducer method, and displays the architecture of the model of option pricing on MapReduce. In theory, the paper analyzes its feasibility and proves that MapReduce can get great performance and nicer speedup. It can be extended in financial area.
MapReduce OptionPricing BSDEs Monte Carlo
Yanxin Zhang Bin Gong YingPeng HuiLiu
Computer Science and Technology College, Shandong University,Jinan, Shandong, P.R. China
国际会议
上海
英文
289-293
2011-03-11(万方平台首次上网日期,不代表论文的发表时间)