Developed Data-Driven Investment Strategies

• Day: 2024-08-28
• Time: 19:55 to 20:05
• Project: Business
• Workspace: WP 1: Strategic / Growth & Development
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Value Investing, Data Processing, Investment Strategies, Algorithmic Trading, Data Scraping

Description

Session Goal

The session aimed to explore and develop value investing opportunities through advanced data processing pipelines, focusing on leveraging algorithmic trading and real-time data integration to identify undervalued assets.

Key Activities

• Discussed the potential of value investing as a business feature or career path.
• Outlined strategies for data-driven investment, including algorithmic screening and real-time data integration.
• Explored optimization of retail investment strategies through personal finance management and portfolio optimization.
• Initiated the setup of a data scraping system for price tracking, focusing on time-series data management.
• Reviewed best practices for managing time-series price data, including data storage, retrieval, and analysis.

Achievements

• Developed a conceptual framework for leveraging data processing pipelines in investment strategies.
• Established a phased approach for optimizing retail investment strategies.
• Initiated the development of a data scraping system to enhance price tracking capabilities.

Pending Tasks

• Further development and implementation of the data scraping system for comprehensive price tracking.
• Detailed exploration of algorithmic trading strategies and their integration into the investment framework.

Evidence

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