QuantCloud: A Software with Automated Parallel Python for Quantitative Finance Applications

doi:10.1109/QRS.2018.00052

Paper

QuantCloud: A Software with Automated Parallel Python for Quantitative Finance Applications

Published Jul 1, 2018 · P. Zhang, Yu-Xiang Gao, Xiang Shi

2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)

UNKNOWN SJR score

5

Citations

2

Influential Citations

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Abstract

Quantitative Finance is a field that replies on data analysis and big data enabling software to discover market signals. In this, a decisive factor is the speed that concerns execution speed and software development speed. So, an efficient software plays a key role in helping trading firms. Inspired by this, we present a novel software: QuantCloud to integrate a parallel Python system with a C++-coded Big Data system. C++ is used to implement this big data system and Python is used to code the user methods. The automated parallel execution of Python codes is built upon a coprocess-based parallel strategy. We test our software using two popular algorithms: moving-window and autoregressive moving-average (ARMA). We conduct an extensive comparative study between Intel Xeon E5 and Xeon Phi processors. The results show that our method achieved a nearly linear speedup for executing Python codes in parallel, prefect for today's multicore processors.

Study Snapshot

QuantCloud, a software with automated parallel Python for quantitative finance applications, achieves nearly linear speedup for executing Python codes in parallel on multicore processors.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

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Paper

QuantCloud: A Software with Automated Parallel Python for Quantitative Finance Applications

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References

Citations

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