HFTViz: Visualization for the exploration of high frequency trading data

Abstract

High Frequency Trading (HFT), mainly based on high speed infrastructure, is a significant element of the trading industry. However, trading machines generate enormous quantities of trading messages that are difficult to explore for financial researchers and traders. Visualization tools of financial data usually focus on portfolio management and the analysis of the relationships between risk and return. Beside risk-return relationship, there are other aspects that attract financial researchers like liquidity and moments of flash crashes in the market. HFT researchers can extract these aspects from HFT data since it shows every detail of the market movement. In this paper, we present HFTViz, a visualization tool designed to help financial researchers explore the HFT dataset provided by NASDAQ exchange. HFTViz provides a comprehensive dashboard aimed at facilitate HFT data exploration. HFTViz contains two sections. It first proposes an overview of the market on a specific date. After selecting desired stocks from overview visualization to investigate in detail, HFTViz also provides a detailed view of the trading messages, the trading volumes and the liquidity measures. In a case study gathering five domain experts, we illustrate the usefulness of HFTViz.

Intelligent big data visual analytics based on deep learning

“…Song, J. et al used classification analysis and cluster analysis to analyze construction engineering data, and established a digital analysis technology for construction sites, which brought a digital revolution to construction sites [12]. Hurtut, T. et al studied a visual analysis technique for analyzing high-frequency trading, using this technology to analyze the relationship between portfolio options and returns and risks, and promote the development of highfrequency trading and risk control [13]. Machado, J.…”