会议专题

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

2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

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)