Repository logo
Repository
Browse
SLIIT Journals
OPAC
Log In
  1. Home
  2. Browse by Author

Browsing by Author "Erandi, H"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Results Per Page
  • Sort Options
  • Thumbnail Image
    PublicationOpen Access
    Event Detection and Latency Analysis in High Frequency Trading Dashboards
    (Department of Mathematics and Statistics, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) de Silva, U; Perera, S; Liyanage, U.P; Erandi, H
    High frequency trading relies on millisecond-level decisions, where profitability is strongly influenced by both market responsiveness and system latency. Traditional dashboards offer real-time visualizations but fall short in detecting abrupt regime shifts or quantifying latency. This study presents an AI-aided Market Pulse and Latency Panel that integrates candlestick pattern recognition, change point detection and latency measurement into a unified dashboard. The system detects technical patterns, identifies structural market shifts, and quantifies infrastructural bottlenecks. Experimental results demonstrate that the panel enhances situational awareness by combining event detection with latency analytics, providing traders with actionable insights for strategy adjustment and infrastructural optimization.
  • Thumbnail Image
    ItemOpen Access
    Towards Real-Time Market Intelligence: Event Detection and Latency Analysis in High Frequency Trading Dashboards
    (Faculty of Humanities and Sciences, SLIIT, 2024-10-18) de Silva, U; Perera, S; Liyanage, U.P; Erandi, H
    High Frequency Trading (HFT) relies on millisecond level decisions, where market responsiveness and system latency directly determine profitability. Traditional dashboards offer real-time visualizations but often fail to detect abrupt market shifts or quantify the delays in system reactions. This paper presents an AI-aided Market Pulse and Latency Panel that integrates candlestick pattern recognition, statistical change point analysis, and latency measurement into a unified trader-facing dashboard. The system identifies technical patterns, detects structural regime shifts, and quantifies latency. Experimental evaluations demonstrate that the panel captures both microstructural signals and broader regime changes while exposing critical latency bottlenecks, such as API-induced delays. By combining event detection with latency analytics, the panel advances dashboards beyond descriptive visualization, providing traders with actionable insights for strategy adjustment and infrastructural optimization.

Copyright 2025 © SLIIT. All Rights Reserved.

  • Privacy policy
  • End User Agreement
  • Send Feedback