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README.md

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# template
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A Template Repository for OpenSpringFest (OSF)
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# QuantResearchStarter
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A modular, open-source quantitative research and backtesting framework designed for clarity and extensibility. Perfect for researchers, students, and developers interested in quantitative finance.
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![Python Version](https://img.shields.io/badge/python-3.10%2B-blue)
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![License](https://img.shields.io/badge/license-MIT-green)
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[![CI](https://github.com/username/QuantResearchStarter/actions/workflows/ci.yml/badge.svg)](https://github.com/username/QuantResearchStarter/actions)
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## Features
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- **Data Management**: Download real data or generate synthetic data for testing
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- **Factor Library**: Implement momentum, value, size, and volatility factors
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- **Backtesting Engine**: Vectorized backtester with transaction costs and constraints
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- **Risk Metrics**: Comprehensive performance and risk analytics
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- **Modular Design**: Easy to extend with new factors and strategies
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- **Production Ready**: Type hints, tests, CI/CD, and documentation
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## Quick Start
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### Installation
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```bash
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# Clone the repository
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git clone https://github.com/username/QuantResearchStarter.git
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cd QuantResearchStarter
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# Install package in development mode
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pip install -e .
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# Install development dependencies
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pip install -e ".[dev]"
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# Optional UI
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pip install streamlit plotly
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```
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### Quick Demo
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```bash
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make demo
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```
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Or step-by-step:
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```bash
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qrs generate-data -o data_sample/sample_prices.csv -s 5 -d 365
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qrs compute-factors -d data_sample/sample_prices.csv -f momentum -f value -o output/factors.csv
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qrs backtest -d data_sample/sample_prices.csv -s output/factors.csv -o output/backtest_results.json
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# Streamlit dashboard (optional)
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streamlit run src/quant_research_starter/dashboard/streamlit_app.py
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```

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