Financial Quantitative Big Data Platform Based on High Performance Computing

A big data platform to for financial quantitative data is designed and implemented on HPC system. Key technologies including data storage mechanism and distributed computing framework are resolved. Based on the platform, several important feature for financial quantitative strategy research is devel...

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Bibliographic Details
Published in2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC) pp. 303 - 307
Main Authors Sun, Yongze, Lu, Zhonghua
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2019
Subjects
Big Data
Big Data Platform
Distributed databases
Financial Quantitative Data
HPC
Parallel Computing
Quantitative Trading
Sparks
Supercomputers
Task analysis
Tuning
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Summary:A big data platform to for financial quantitative data is designed and implemented on HPC system. Key technologies including data storage mechanism and distributed computing framework are resolved. Based on the platform, several important feature for financial quantitative strategy research is developed, which are indicator computing, large scale backtest and distributed hyperparameter tuning. Tests shows that the platform can achieve much higher performance than single PC program, and can be used to design strategy base on large scale financial data.
DOI:10.1109/CSE/EUC.2019.00065