📅 2024-11-16 — Session: Enhanced Intraday Trading Visualization Techniques
🕒 22:30–23:25
🏷️ Labels: Python, Data Visualization, Intraday Trading, Candlestick Chart, Heatmap
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance the visualization techniques for intraday trading data using Python, focusing on creating and improving candlestick charts and heatmaps.
Key Activities
- Set up the local environment for data analysis by installing necessary Python libraries such as yfinance, pandas, seaborn, and matplotlib.
- Initiated the screening process for organizing and annotating knowledge related to data visualization.
- Implemented a guide to fetch and analyze 1-minute intraday stock data in Python, including visualization with sample code.
- Calculated pairwise close price ratios and visualized them using a heatmap.
- Created a Seaborn-styled candlestick chart for intraday trading data with customization options.
- Compared price visualization techniques, highlighting insights from a close price ratio heatmap and an intraday candlestick chart.
- Developed an upper-diagonal heatmap in Python using Seaborn, with improved time labeling and axis flipping for better intuitiveness.
- Enhanced the Python script for plotting heatmaps and candlestick charts, focusing on readability and aesthetic improvements.
Achievements
- Successfully set up the environment and implemented multiple visualization techniques for intraday trading data.
- Improved the intuitiveness and aesthetics of candlestick charts and heatmaps.
- Gained insights into market behavior and potential trading strategies from the visualizations.
Pending Tasks
- Automate analysis and pattern backtesting based on the insights derived from the visualizations.
- Explore further enhancements in visualization techniques for better trading decision support.