TradAO: A Visual Analytics System for Trading Algorithm Optimization
Ka Wing Tsang, Haotian Li, Fuk Ming Lam, Yifan Mu, Yong, Wang, Huamin Qu

TL;DR
TradAO is a novel visual analytics system designed to help traders optimize trading algorithms by enabling comprehensive exploration of performance across various parameter settings, addressing a gap in existing financial data visualization tools.
Contribution
It introduces the first interactive system specifically tailored for traders to analyze and compare trading algorithm performances with different parameters, based on industry collaboration.
Findings
Expert interviews validated system usefulness.
Case study demonstrated effective algorithm optimization.
System facilitates better decision-making for traders.
Abstract
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…
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Taxonomy
TopicsData Visualization and Analytics · Aesthetic Perception and Analysis
