Practice Real-Time Stock Data Analysis with Python and kdb+: Step-by-Step Tutorial

Unlock the power of real-time stock data analysis with this comprehensive tutorial! In this step-by-step guide, we will walk you through the entire process of integrating Python with kdb+ to build a high-performance, real-time stock data processing system. Here’s what you’ll learn: WebSocket Setup: Learn how to subscribe to live stock prices for AAPL and MSFT using the Finazon service in Python. Data Ingestion with qPython: Discover how to use qPython to connect to a kdb+ table and insert live stock prices seamlessly. Feature Engineering: Enhance your live data with essential metrics like Moving Averages, EMA20, and EMA50, and publish the results to another kdb+ table on a different port. Practical Implementation: Follow the “Building real-time tick subscribers using kdb+” white paper to ensure a robust and efficient setup. This tutorial includes a detailed video demonstration to guide you through each step. Whether you’re a data scientist, fintech enthusiast, or algorithmic trading developer, this tutorial will equip you with the skills to handle real-time financial data efficiently. Github: https://github.com/DeepakSingh260/HFT/tree/main/data/real-time paper used for this project : https://code.kx.com/q/wp/rt-tick/