# awesome-algorithmic-trading

**Repository Path**: triobox/awesome-algorithmic-trading

## Basic Information

- **Project Name**: awesome-algorithmic-trading
- **Description**: A curated list of awesome algorithmic trading frameworks, libraries, software and resources
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 0
- **Created**: 2021-06-05
- **Last Updated**: 2025-01-01

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## awesome-algorithmic-trading

A curated list of awesome algorithmic trading tutorials, projects and communities.

## Table of Contents

1. Stock Prices
2. Market Mechanics
3. Data Processing
4. Stock Returns
5. Momentum Trading
6. Quant Workflow
7. Outliers & Filtering
8. Regression
9. Time Series Modeling
10. Volatility
11. Pairs Trading & Mean Reversion
12. Breakout Strategy
13. Stock, Indices & Funds
14. ETFs
15. Portfolio Risk & Returns
16. Portfolio Optimization
17. Smart Beta & Portfolio Optimization
18. Factors
19. Factor Models & Factor Types
20. Risk Factor Models - Time Series & Cross Sectional
21. Risk Factor Models with PCA
22. Alpha Factors
23. Alpha Factor Research Methods
24. Advanced Portfolio Optimization
25. Multi-factor Model

## Tutorials
- [Algorithmic Trading Strategies](https://www.experfy.com/training/courses/algorithmic-trading-strategies)

- [Artificial Intelligence for Trading](https://www.udacity.com/course/ai-for-trading--nd880)

- [Computational Investing, Part I](https://www.coursera.org/learn/computational-investing)

- [Financial Engineering and Risk Management Part I](https://www.coursera.org/learn/financial-engineering-1/)

- [Financial Engineering and Risk Management Part II](https://www.coursera.org/learn/financial-engineering-2/)

- [MIT Open Courseware - Analytics of Finance](https://ocw.mit.edu/courses/sloan-school-of-management/15-450-analytics-of-finance-fall-2010/)

- [MIT Open Courseware - Investments](https://ocw.mit.edu/courses/sloan-school-of-management/15-433-investments-spring-2003/)

- [MIT Open Courseware - Topics in Mathematics with Applications in Finance](https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/)

- [Machine Learning and Reinforcement Learning in Finance Specialization](https://www.coursera.org/specializations/machine-learning-reinforcement-finance)

- [Machin Learning for Trading](https://www.udacity.com/course/machine-learning-for-trading--ud501)

- [Model a Quantitative Trading Strategy in R](https://www.datacamp.com/courses/model-a-quantitative-trading-strategy-in-r/)

- [Trading Strategies in Emerging Markets Specialization](https://www.coursera.org/specializations/trading-strategy)

- [Time Series with R](https://www.datacamp.com/tracks/time-series-with-r)

- [Quantitative  Analyst with R](https://www.datacamp.com/tracks/quantitative-analyst-with-r)


## Projects

## Articles

- [10 Things to Know About Every Cash Flow Statement](https://investinganswers.com/education/financial-statement-analysis/10-things-know-about-every-cash-flow-statement-1023)

- [The 15 Stock Diversification Myth](http://www.efficientfrontier.com/ef/900/15st.htm)

- [The Limitations of Ratio Analysis](https://www.accountingtools.com/articles/what-are-the-limitations-of-ratio-analysis.html)

- [The Right Way and the Wrong Way to Benchmark a Diversified Portfolio](https://blog.wealthfront.com/benchmark-diversified-portfolio/)

- [Performance Measurement: The What, Why, and How of the Investment Management Process](https://blogs.cfainstitute.org/investor/2012/06/01/performance-measurement-and-attribution-the-what-why-and-how-of-the-investment-management-process/)

- [Utility Theory and Attitude toward Risk (Explained With Diagram)](http://www.economicsdiscussion.net/articles/utility-theory-and-attitude-toward-risk-explained-with-diagram/1384)

- [The Guide to Diversification](https://www.fidelity.com/viewpoints/investing-ideas/guide-to-diversification)

- [Diversification: How much is too much?](https://www.livemint.com/Money/dvv39OemfWlZ2zPB9RGobL/Diversification-How-much-is-too-much.html)

- [Successful Backtesting of Algorithmic Trading Strategies - Part I](https://www.quantstart.com/articles/Successful-Backtesting-of-Algorithmic-Trading-Strategies-Part-I)

- [Successful Backtesting of Algorithmic Trading Strategies - Part II](https://www.quantstart.com/articles/Successful-Backtesting-of-Algorithmic-Trading-Strategies-Part-II)

## Research Papers

- [Are Markets Efficient?](http://review.chicagobooth.edu/economics/2016/video/are-markets-efficient)

- [Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers](https://www.chicagobooth.edu/~/media/FE874EE65F624AAEBD0166B1974FD74D.pdf)

- [Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings?](http://econ.au.dk/fileadmin/Economics_Business/Education/Summer_University_2012/6308_Advanced_Financial_Accounting/Advanced_Financial_Accounting/2/Sloan_1996_TAR.pdf)

- [Betting Against Beta](http://pages.stern.nyu.edu/~lpederse/papers/BettingAgainstBeta.pdf)

- [Momentum](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=299107)

- [Separating Winners from Losers Among Low Book-to-Market Stocks Using Financial Statement Analysis](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=403180)

- [The 101 Ways to Measure Portfolio Performance](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1326076)

- [Does the Composition of the Market Portfolio Really Matter?](https://faculty.mccombs.utexas.edu/keith.brown/Research/JPM-12.87.pdf)

- [Pairs Trading: Performance of a Relative Value Arbitrage Rule](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=141615)

## Books
- [Algorithmic Trading and DMA: An introduction to direct access trading strategies](https://www.amazon.com/gp/product/0956399207/ref=as_li_tf_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0956399207&linkCode=as2&tag=quant0f-20)

- [Building Winning Algorithmic Trading Systems, + Website: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading (Wiley Trading)](https://www.amazon.com/Building-Winning-Algorithmic-Trading-Systems/dp/1118778987/ref=sr_1_1?s=books&ie=UTF8&qid=1538798383&sr=1-1&keywords=Building+Winning+Algorithmic+Trading+Systems%2C+%2B+Website%3A+A+Trader%27s+Journey+From+Data+Mining+to+Monte+Carlo+Simulation+to+Live+Trading+%28Wiley+Trading)

- [Finding Alphas: A Quantitative Approach to Building Trading Strategies](https://www.amazon.com/Finding-Alphas-Quantitative-Approach-Strategies/dp/1119057868/ref=sr_1_1?ie=UTF8&qid=1538798212&sr=8-1&keywords=finding+alpha)

- [Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1491962291/ref=sr_1_1?ie=UTF8&qid=1538798436&sr=8-1&keywords=hands+on+machine+learning+with+scikit-learn+and+tensorflow)

- [Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading](https://www.amazon.com/Inside-Black-Box-Quantitative-Frequency-ebook/dp/B00BZ9WAVW)

- [Python for Finance: Analyze Big Financial Data](https://www.amazon.com/Python-Finance-Mastering-Data-Driven/dp/1492024333/ref=sr_1_4?ie=UTF8&qid=1538798406&sr=8-4&keywords=python+for+finance)


- [Technical Analysis Explained, Fifth Edition: The Successful Investor's Guide to Spotting Investment Trends and Turning Points](https://www.amazon.com/Technical-Analysis-Explained-Fifth-Successful-ebook/dp/B00H878Q2W)

- [Quantitative Investing: Strategies to exploit stock market anomalies for all investors](https://www.amazon.com/Quantitative-Investing-Strategies-anomalies-investors/dp/0857193007/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=&sr=)

## Communities
- [Advanced Risk and Portfolio Management](https://www.arpm.co/)

- [Certificate in Quantitative Finance](https://www.cqf.com/)

- [The Python Quants Group](http://tpq.io/)

- [Quantor](https://quantor.co/)

- [Quantopian](https://www.quantopian.com/home)

- [QuantConnect](https://www.quantconnect.com/)

- [QuantNet](https://quantnet.com/courses/)

- [QuantStart](https://www.quantstart.com/)


## License

[![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)](https://creativecommons.org/licenses/by/4.0/)

This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).