Resources for Building Your Value Investing AI Agent
This page provides a comprehensive collection of resources to help you continue learning and improving your value investing AI agent. Whether you're looking to deepen your understanding of value investing principles, enhance your programming skills, or explore advanced AI techniques, you'll find valuable resources here.
Value Investing Resources
Books
- The Intelligent Investor by Benjamin Graham - The definitive book on value investing
- Security Analysis by Benjamin Graham and David Dodd - The foundational text on fundamental analysis
- Value Investing: From Graham to Buffett and Beyond by Bruce Greenwald - Modern perspectives on value investing
- The Little Book That Still Beats the Market by Joel Greenblatt - A simple approach to value investing
- Margin of Safety by Seth Klarman - Risk-averse value investing strategies
Online Courses
- Value Investing (Coursera) - University of Pennsylvania's course on value investing principles
- Value Investing Bootcamp (Udemy) - Practical approach to value investing
- Financial Analysis for Decision Making (edX) - Understanding financial statements
Websites and Blogs
- ValueWalk - News and analysis for value investors
- GuruFocus - Stock screeners and analysis tools based on value principles
- Old School Value Blog - Value investing strategies and stock analysis
- Value Investing World - Curated links and commentary on value investing
Financial Data Resources
Free Data APIs
- Yahoo Finance - Comprehensive financial data with Python API (yfinance)
- Alpha Vantage - Free API for real-time and historical financial data
- Financial Modeling Prep - Financial statements, ratios, and more
- Quandl - Financial and economic datasets (free tier available)
Paid Data Services
- Bloomberg Terminal - Professional-grade financial data (expensive)
- EOD Historical Data - Affordable financial data API
- Intrinio - Financial data API with various pricing tiers
- Refinitiv Eikon - Comprehensive financial data platform
SEC Data
- SEC EDGAR - Official source for company filings
- SEC-API - API for accessing SEC filings
- sec-edgar Python package - Python tool for downloading SEC filings
Python Programming Resources
Python for Finance
- Python for Finance by Yves Hilpisch - Comprehensive guide to financial analysis with Python
- Finance Fundamentals in Python (DataCamp) - Interactive course series
- Python for Finance Code Repository - Code examples from the book
Data Analysis Libraries
- pandas - Data manipulation and analysis
- NumPy - Numerical computing
- scikit-learn - Machine learning
- statsmodels - Statistical models and tests
Visualization Libraries
- Matplotlib - Basic plotting library
- Seaborn - Statistical data visualization
- Plotly - Interactive visualizations
- Bokeh - Interactive web visualizations
Web Development Resources
Python Web Frameworks
Frontend Development
- React - JavaScript library for building user interfaces
- Tailwind CSS - Utility-first CSS framework
- Bootstrap - CSS framework for responsive design
- Chart.js - JavaScript charting library
Deployment Platforms
- Heroku - Platform as a service for easy deployment
- AWS - Comprehensive cloud platform
- Google Cloud - Google's cloud platform
- Vercel - Platform for frontend frameworks and static sites
AI and Machine Learning Resources
Machine Learning for Finance
- Advances in Financial Machine Learning by Marcos López de Prado - Advanced ML techniques for finance
- Machine Learning for Algorithmic Trading by Stefan Jansen - Practical ML for trading
- Machine Learning for Trading (Coursera) - Specialization by Google Cloud and New York Institute of Finance
Deep Learning
- TensorFlow - Deep learning framework
- PyTorch - Deep learning framework
- Keras - High-level neural networks API
- Deep Learning Book - Comprehensive resource by Goodfellow, Bengio, and Courville
Natural Language Processing
- Hugging Face Transformers - State-of-the-art NLP models
- spaCy - Industrial-strength NLP
- NLTK - Natural Language Toolkit
- Financial NLP Research - Research papers on NLP for finance
Sample Projects and Code
GitHub Repositories
- PyPortfolioOpt - Portfolio optimization in Python
- Microsoft Qlib - AI-oriented quantitative investment platform
- MLFinLab - Implementations from "Advances in Financial Machine Learning"
- stockstats - Technical analysis indicators in Python
Kaggle Notebooks
Complete Projects
- FinanceDataReader - Open source library for financial data
- yfinance - Yahoo Finance market data downloader
- ffn - Financial Functions for Python
- Technical Analysis Library - Technical analysis indicators
Communities and Forums
Reddit Communities
- r/ValueInvesting - Discussion of value investing principles
- r/algotrading - Algorithmic trading strategies
- r/FinancialCareers - Career advice in finance
- r/learnpython - Python learning community
Forums and Q&A Sites
- Quantitative Finance Stack Exchange - Q&A for quant finance professionals
- Stack Overflow (Python) - Programming help
- RStudio Community - For R users in finance
- Streamlit Forum - Help with Streamlit apps
Professional Networks
- CFA Institute - Professional organization for investment professionals
- Global Association of Risk Professionals - Risk management professionals
- Python Finance Meetups - Local groups focused on Python in finance
- Quantitative Finance Group on LinkedIn - Professional networking
Newsletters and Podcasts
Newsletters
- Morningstar Newsletter - Investment research and analysis
- Value Investing Insight - Professional value investing ideas
- Python Weekly - Python news and tutorials
- Data Elixir - Data science news and resources
Podcasts
- The Intelligent Investing Podcast - Value investing discussions
- Motley Fool Money - Stock market analysis
- Talk Python To Me - Python topics and interviews
- Data Skeptic - Data science and machine learning
YouTube Channels
- Aswath Damodaran - Valuation expert's lectures
- sentdex - Python programming tutorials including finance
- The Swedish Investor - Value investing book summaries
- PyData - Python for data analysis conference videos
Next Steps in Your Learning Journey
Suggested Learning Paths
Based on your interests, here are some recommended learning paths to continue developing your skills:
Path 1: Deepen Your Value Investing Knowledge
- Read "The Intelligent Investor" by Benjamin Graham
- Take the Coursera "Value Investing" course
- Study Warren Buffett's annual letters to shareholders
- Practice analyzing financial statements of real companies
- Join value investing communities to discuss ideas
Path 2: Enhance Your Technical Skills
- Improve your Python skills with "Python for Finance"
- Learn more about data visualization with Plotly and Matplotlib
- Study SQL for more efficient data handling
- Explore web development with Flask or Streamlit
- Practice building small projects that solve specific problems
Path 3: Explore Advanced AI Techniques
- Study machine learning fundamentals with scikit-learn
- Learn about time series analysis for financial data
- Explore natural language processing for sentiment analysis
- Experiment with deep learning for price prediction
- Implement reinforcement learning for portfolio optimization
Path 4: Build a Production-Ready System
- Learn about software architecture and design patterns
- Study database design for financial applications
- Explore cloud deployment options (AWS, GCP, Azure)
- Implement proper testing and monitoring
- Consider scaling issues and performance optimization
Feedback and Contributions
We're always looking to improve this guide and add more resources. If you have suggestions, corrections, or want to contribute additional resources, please reach out to us.