📅 2024-01-15 — Session: Developed Algorithmic Trading Functions for Stock Analysis
🕒 15:10–16:15
🏷️ Labels: Algorithmic Trading, Stock Analysis, Python, Data Manipulation, Investment Strategies
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine functions for algorithmic trading and stock price analysis, focusing on backtesting and data manipulation using Python and Pandas.
Key Activities
- Discussed investment strategies with a focus on algorithmic trading and backtesting historical stock data.
- Planned and outlined structured approaches for developing investment strategies using algorithmic trading.
- Developed functions for stock price analysis, including data extraction, logarithmic transformation, linear modeling, and residual calculation.
- Implemented
get_data_for_ticker
andcalculate_residuals
functions to extract stock data, perform transformations, and calculate residuals. - Addressed date mismatch errors in DataFrame and updated data retrieval functions.
- Added new columns to datasets to analyze long-term price trends and calculate 3-year returns.
Achievements
- Successfully developed and refined functions for stock price analysis and investment strategy development.
- Enhanced data retrieval and manipulation techniques using Python and Pandas.
- Implemented new data analysis features to support investment decision-making.
Pending Tasks
- Further testing and validation of developed functions to ensure accuracy and reliability.
- Explore additional financial metrics and strategies for comprehensive investment analysis.