An Intelligent Web-Based Platform for Swing Trading Analysis | IJCT Volume 13 – Issue 5 | IJCT-V13I5P46
International Journal of Computer Techniques
ISSN 2394-2231
Author
Rohit Kulkarni, Dr. Shazia Mannan
Abstract
Swing trading occupies a unique niche within financial markets, leveraging medium-term price momentum over holding periods typically spanning two to fourteen days. Despite its growing adoption among retail investors, a comprehensive, open-architecture web platform unifying real-time data ingestion, technical analysis computation, portfolio tracking, and risk assessment under a single interface remains largely absent in the open-source domain. This paper presents SwingTrader, a full-stack web application constructed on the MERN (MongoDB, Express.js, React.js, Node.js) technology stack. The system integrates live market data feeds, computes widely adopted technical indicators—including the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands, and Average True Range (ATR)—and presents actionable buy/sell signals through an intuitive, responsive dashboard. A Socket.IO-powered WebSocket layer delivers sub-second quote updates, while a JWT-based authentication module ensures secure, stateless user session management. Empirical evaluation across 10,000 concurrent simulated sessions demonstrates a mean API response latency of 87 milliseconds and 99.7% uptime over a 90-day observation window. User experience assessments with 42 participants yield a mean System Usability Scale (SUS) score of 81.4, categorising the application as ‘excellent’. The proposed architecture serves as a replicable blueprint for practitioners and researchers designing scalable, real-time financial analytics platforms.
Keywords
swing trading; MERN stack; React.js; Node.js; MongoDB; technical analysis; WebSocket; real-time finance; portfolio management; REST API
Conclusion
This paper presented SwingTrader, a full-stack swing trading web application engineered on the MERN technology stack. The system architecture integrates a React.js SPA with Redux-managed state, an Express.js REST and Socket.IO backend, a Node.js Worker Thread indicator computation pipeline, JWT-based stateless authentication, and a MongoDB Time Series database. Empirical evaluation demonstrated a mean API response latency of 87 ms and 99.7% uptime over a 90-day production observation window, with WebSocket market data delivery sustaining latencies below 35 ms at 10,000 concurrent connections. A usability study with 42 participants yielded a mean SUS score of 81.4, affirming the application’s accessibility to traders across experience tiers. The presented architecture establishes a validated, replicable blueprint for financial analytics web applications demanding real-time data responsiveness and scalable backend throughput.
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How to Cite This Paper
Rohit Kulkarni, Dr. Shazia Mannan (2026). An Intelligent Web-Based Platform for Swing Trading Analysis. International Journal of Computer Techniques, 13(5). ISSN: 2394-2231.
