TradAO: A visual analytics system for trading algorithm optimization

• Main Authors: TSANG, Ka Wing, LI, Haotian, LAM, Fuk Ming, MU, Yifan, WANG, Yong, QU, Huamin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Human-centered computing; Visualization; Visualization design and evaluation methods; Software Engineering; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5373; https://ink.library.smu.edu.sg/context/sis_research/article/6377/viewcontent/2008.11319.pdf
• Institution: Singapore Management University

With the wide applications of algorithmic trading, it has become critical for traders to build a winning trading algorithm to beat the market. However, due to the lack of efficient tools, traders mainly rely on their memory to manually compare the algorithm instances of a trading algorithm and further select the best trading algorithm instance for the real trading deployment. We work closely with industry practitioners to discover and consolidate user requirements and develop an interactive visual analytics system for trading algorithm optimization. Structured expert interviews are conducted to evaluateTradAOand a representative case study is documented for illustrating the system effectiveness. To the best of our knowledge, previous financial data visual analyses have mainly aimed to assist investment managers in investment portfolio analysis but have neglected the need of traders in developing trading algorithms for portfolio execution.TradAOis the first visual analytics system that assists users in comprehensively exploring the performances of a trading algorithm with different parameter settings.