Curve Labs
Philosophy
- To understand the truth with data-driven analysis.
- To explore the data world with creative thinking and right value.
-
To share the results in understandable language.
- Ultimately to make world better place through these works.
Reference Timeline
Steps
- 2017.05 : First encounter - Concept of Data Science
-
2017.08 : Construction of a personal database (Microsoft SQL Server)
- 2018.06 : Extension of range of collecting data (Korean - Indices, Stock, ETFs / Forex / Global Commodities / Global Stock Market Indices)
- 2018.09 : Construction of Curvelib Package ver 1.0 (Personal tools for data analysis, with Python language)
- 2018.11 : Initiation of semi-automated system trading program in Korean stock market
-
2018.12 : Performance improvements of Curvelib Package by Asynchronous Programming & Multiprocessing (5 times faster than initial version 1.0)
- 2019.05 : Launching open-source python package ‘wecolib’ (researching and executing tools for quantitative trading)
- [Link] : https://github.com/Onewquant/wecolib
- 2019.07 : Develoment of ‘Mosell’ (A local program for helping individual e-commerce business to keep ledger)
- 2019.07 : Develoment of ‘Mosell BOK Distributor (A local program for scraping whole keyword data and alarming searching keywords in low competition, BOK means Blue Ocean Keyword)’
- 2019.08 : Launching open-source python package ‘Hexpot’ (An infrastructure library for ‘Hexpo’ - researching and executing tools for quantitative trading with realtime streaming data)
- [Link] : https://github.com/Onewquant/Hexpot
- 2019.08 : Developing python package ‘Hexpo’ (meaning Hyper Exponential)
Technical Skill Sets
- Programming Language : Python, Go, SQL Query
- Database : MongoDB, Microsoft SQL-Server
Forward
- Introduction of Machine Learning techniques into the trading system
- Improvement in speed of analyzing realtime streaming data and trading execution
- Study for statistical decision making
- Study for Complex system, Network Science (Esp. Log-Periodic Power Law Model)