Skip to Main content Skip to Navigation
Conference papers

Method of Domain Specific Code Generation Based on Knowledge Graph for Quantitative Trading

Abstract : Quantitative methods have been adopted by more and more individual investors for investment activities. Many third party platforms have been developed to help users complete the process of backtesting, which fills the gap between the trading strategy code and the trading strategy model. However, using a quantitative platform for backtesting has a high threshold for users who do not have programming experience. There is still a huge gap between the description and the code of trading strategy. Code generation allows developers to focus more on business related design and implementation, thereby increasing the efficiency of software development. The import of domain knowledge can improve the accuracy of requirement parsing to improve the quality of constructed code model. The general knowledge base is often incomplete in terms of domain specific terms and relationships, and the construction of domain knowledge graphs requires more domain related data. In this paper, encyclopedia data and the financial report data are used to extract domain terms and relations. And then a domain knowledge graph for quantitative trading is constructed to realize the automatic generation of quantitative trading strategy code.
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download

https://hal.inria.fr/hal-01888627
Contributor : Hal Ifip <>
Submitted on : Friday, October 5, 2018 - 11:21:16 AM
Last modification on : Saturday, October 6, 2018 - 1:14:36 AM
Long-term archiving on: : Sunday, January 6, 2019 - 2:09:43 PM

File

470174_1_En_3_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Jianshui Bi, Hongming Cai, Bo Zhou, Lihong Jiang. Method of Domain Specific Code Generation Based on Knowledge Graph for Quantitative Trading. 11th International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS), Oct 2017, Shanghai, China. pp.21-33, ⟨10.1007/978-3-319-94845-4_3⟩. ⟨hal-01888627⟩

Share

Metrics

Record views

129

Files downloads

12