Parallel option pricing with BSDEs method on MapReduce

MapReduce is popular in cloud computing area. It's mainly used in Information Retrieval, Distributed Storage, DM, Machine Learning and so on. It's fit to parallel computing of great capacity for liquor data. Based on MapReduce's 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.