📅 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 and calculate_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.