Developed and Enhanced Stock Analysis Functions

• Day: 2024-01-15
• Time: 15:10 to 16:15
• Project: Business
• Workspace: WP 1: Strategic / Growth & Development
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Algorithmic Trading, Stock Analysis, Python, Data Manipulation, Financial Metrics

Description

Session Goal: The session aimed to develop and enhance functions for stock price analysis, focusing on algorithmic trading and backtesting techniques using Python.

Key Activities:

• Discussed investment strategies, particularly algorithmic trading and backtesting historical stock data.
• Outlined a structured approach to developing investment strategies using Python and Pandas.
• Developed functions for stock price analysis, including data extraction, logarithmic transformation, linear modeling, and residual calculation.
• Resolved date mismatch errors in DataFrame by ensuring proper date parsing.
• Updated the get_data_for_ticker function to improve data retrieval.
• Implemented the add_residual_column function to facilitate investment opportunity identification.
• Calculated 3-year returns and added relevant columns to datasets for deeper financial analysis.

Achievements:

• Successfully created and enhanced multiple functions for stock analysis, improving data manipulation and financial metrics computation.
• Enhanced understanding of investment strategies through algorithmic trading discussions.

Pending Tasks:

• Further backtesting of developed strategies to validate their effectiveness in real-world scenarios.
• Exploration of additional financial metrics for comprehensive investment analysis.

Evidence

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• event_ids: []