📅 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.