Title :
Designing a big data processing platform for algorithm trading strategy evaluation
Author :
Xiongpai Qin ; Xiaoyun Zhou
Author_Institution :
Sch. of Inf., Renmin Univ. of China, Beijing, China
Abstract :
Algorithm trading techniques are adopted by institutional and individual investors with the expectation of making profit. Not only the algorithms are getting more complex, but also the data on which algorithms are running is becoming bigger, and various data are exploited to make more accurate prediction. Next generation of algorithm trading will be big data driven. This paper presents the big data processing platform for algorithm trading strategy evaluation, which will facilitate the back testing process so that algorithms could be put into production use with a high degree of confidence. Various data processing techniques should be integrated in a unified system. Some data accessing optimization techniques are also discussed.
Keywords :
Big Data; electronic commerce; profitability; algorithm trading strategy evaluation; back testing process; big data processing platform; data accessing optimization; production use; profit; unified system; Containers; Data handling; Data models; Information management; Production; Real-time systems; Testing; Algorithm Trading; Back Testing; Big Data;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2013 10th International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/FSKD.2013.6816342