Enhanced Intraday Trading Visualization Techniques

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Enhanced Intraday Trading Visualization Techniques

  • Day: 2024-11-16
  • Time: 22:30 to 23:25
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Data Visualization, Intraday Trading, Candlestick Chart, Heatmap

Description

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.

Evidence

  • source_file=2024-11-16.sessions.jsonl, line_number=0, event_count=0, session_id=c906ab0eb75d947dbaf2be52e75727e0203082950eb89b5bbe9bcbe9271ef62f
  • event_ids: []

Graph View

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