📅 2024-11-16 — Session: Intraday Trading Analysis and Visualization

🕒 22:30–23:25
🏷️ Labels: Data Analysis, Intraday Trading, Visualization, Python, Trading Strategies
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to set up a local environment for data analysis and conduct a comprehensive analysis of intraday trading data using Python.

Key Activities

  • Installed necessary libraries for data analysis, including yfinance, pandas, seaborn, and matplotlib.
  • Initiated a screening process for message organization and knowledge management.
  • Fetched and analyzed 1-minute intraday stock data using Python, with a focus on visualization techniques.
  • Calculated pairwise close price ratios and visualized them using a heatmap.
  • Created a Seaborn-styled candlestick chart for intraday trading data.
  • Compared different price visualization techniques, including a close price ratio heatmap and an intraday candlestick chart.
  • Developed an upper-diagonal heatmap and enhanced visualization scripts for better readability.
  • Improved the intuitiveness of heatmaps by flipping the y-axis.
  • Analyzed intraday price movements using heatmaps and candlestick charts, deriving insights for potential trading strategies.

Achievements

  • Successfully set up the local environment and installed required libraries.
  • Developed various visualization techniques to analyze intraday trading data.
  • Gained insights into market behavior and potential trading strategies through detailed analysis.

Pending Tasks

  • Further automate analysis and pattern backtesting for trading strategies.

Outcome

The session was successful in achieving its goal of setting up the environment and conducting a detailed analysis of intraday trading data, providing valuable insights for future trading strategies.