📅 2024-01-15 — Session: Developed and Refined Investment and Trading Strategies
🕒 03:50–07:45
🏷️ Labels: Investment, Trading, Data Analysis, Visualization, Python
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal:
The session aimed to explore and refine various investment and trading strategies, focusing on leveraging data analysis and visualization techniques to enhance decision-making.
Key Activities:
- Investment Strategies: Discussed key strategies like trend following, momentum investing, and dollar-cost averaging, emphasizing the importance of backtesting.
- Data Processing and Backtesting: Outlined steps for processing monthly price data, developing trading strategies, and conducting backtests.
- Data Analysis: Calculated period returns using DataFrames to analyze stock performance and identify trends.
- [[Data Visualization]]: Utilized Python’s Matplotlib and Pandas for visualizing stock data, including scatter plots and color gradients.
- Troubleshooting: Addressed issues with Pandas styling in VS Code, providing solutions for rendering problems.
Achievements:
- Developed a comprehensive framework for testing trading strategies using historical data.
- Implemented Python code for calculating and visualizing stock returns.
- Enhanced data visualization techniques with color gradients and scatter plots.
Pending Tasks:
- Further refine backtesting methods to improve strategy effectiveness.
- Explore additional visualization techniques for better data interpretation.