Research Repository
A curated collection of research papers, documentation, wikis, and technical resources related to machine learning, algorithmic trading, and quantitative finance
Project Documentation
Internal documentation and wikis explaining how this platform works
Machine Learning & Algorithms
Model Architecture
GRU neural network architecture, two-tier training approach, and multi-interval forecasting
backend/docs/MODEL_ARCHITECTURE.mdSentiment Analysis Integration
News sentiment (Finnhub) and social sentiment (Reddit) analysis using DistilBERT
backend/docs/SENTIMENT_INTEGRATION.mdFinancial Analysis
SEC EDGAR integration, financial ratio calculations, and risk scoring algorithms
backend/docs/FINANCIAL_ANALYSIS.mdReinforcement Learning Trading Bots
Deep Q-Network (DQN) implementation for autonomous paper trading
docs/RL_TRADING_FEATURE.mdEarly Stopping Implementation
Training optimization techniques to prevent overfitting
backend/docs/EARLY_STOPPING_IMPLEMENTATION.mdUser Guides & Wikis
Understanding Our AI Technology
User-friendly explanation of our machine learning systems
/wiki/ai_technologySentiment Analysis Explained
How we analyze market sentiment from news and social media
/wiki/sentiment_analysisFinancial Indicators Guide
Understanding financial ratios and company health metrics
/wiki/financial_indicatorsTechnical Indicators
MACD, RSI, candlestick patterns, and other technical analysis tools
/wiki/technical_indicatorsDevelopment & Setup Guides
Main README
Project overview, quick start, and architecture
README.mdProject Context
Comprehensive guide for developers and AI assistants
docs/PROJECT_CONTEXT.mdQuick Start Guide
Fast reference for common tasks and setup
docs/QUICK_START.mdAPI Credentials Setup
Configure Finnhub, Reddit, and other API credentials
backend/docs/CREDENTIALS_SETUP.mdTesting Guide
How to run tests for backend and frontend components
docs/TESTING_GUIDE.mdResearch & Analysis Reports
Academic Research Papers
Foundational papers and research that inform our algorithms and approaches
Deep Learning & Neural Networks
Learning Phrase Representations using RNN Encoder-Decoder
Cho et al., 2014 - The original GRU paper introducing Gated Recurrent Units
arXiv:1412.3555Generating Sequences With Recurrent Neural Networks
Graves, 2013 - Comprehensive treatment of RNNs for sequence generation
arXiv:1308.0850Empirical Evaluation of Gated Recurrent Neural Networks
Chung et al., 2014 - Comparison of LSTM vs GRU architectures
arXiv:1409.2329Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Mnih et al., 2013 - The foundational DQN paper from DeepMind
arXiv:1312.5602Deep Reinforcement Learning with Double Q-learning
van Hasselt et al., 2015 - Improvements to DQN algorithm
arXiv:1509.06461Prioritized Experience Replay
Schaul et al., 2015 - Enhanced experience replay for RL agents
arXiv:1511.05952Natural Language Processing
DistilBERT, a distilled version of BERT
Sanh et al., 2019 - Efficient BERT variant used for sentiment analysis
arXiv:1910.01108BERT: Pre-training of Deep Bidirectional Transformers
Devlin et al., 2018 - The original BERT paper
arXiv:1810.04805Time Series & Forecasting
External Resources & Tools
Libraries, APIs, tutorials, and learning resources used in or relevant to this project
Machine Learning Frameworks
PyTorch
Deep learning framework used for GRU models and RL agents
pytorch.orgHugging Face Transformers
NLP library providing DistilBERT for sentiment analysis
huggingface.coscikit-learn
Machine learning library for data preprocessing and scaling
scikit-learn.orgData Sources & APIs
Finnhub API
Financial news and market data API for sentiment analysis
finnhub.ioReddit API
Social media API for retail investor sentiment tracking
reddit.com/dev/apiSEC EDGAR
Official SEC database for company financial statements
sec.gov/edgarYahoo Finance
Historical price data for stocks, ETFs, and mutual funds
finance.yahoo.comLearning Resources & Tutorials
Deep Learning Specialization
Andrew Ng's comprehensive deep learning course on Coursera
coursera.orgSpinning Up in Deep RL
OpenAI's educational resource for reinforcement learning
spinningup.openai.comPyTorch Tutorials
Official PyTorch tutorials and documentation
pytorch.org/tutorialsInvestopedia
Financial education and trading strategy resources
investopedia.comRecommended Reading
Deep Learning
Ian Goodfellow, Yoshua Bengio, Aaron Courville
Comprehensive textbook on deep learning fundamentals
Available free online: deeplearningbook.orgReinforcement Learning: An Introduction
Richard S. Sutton, Andrew G. Barto
Definitive introduction to reinforcement learning
Available free online: incompleteideas.netAdvances in Financial Machine Learning
Marcos López de Prado
Machine learning techniques specifically for quantitative finance
Wiley PublishingContribute to this Repository
This research repository is a living document. If you have suggestions for additional papers, resources, or documentation that would benefit the community, please contribute!
Ways to Contribute:
- Suggest relevant research papers or academic resources
- Add links to useful tutorials or learning materials
- Create internal documentation for new features
- Write guides or wikis to help users understand the platform
- Share interesting articles or blog posts about ML in finance