Resources

[!tldr]+ TL;DR

Introduction¶

Popular back-trading libraries and frameworks¶

The most popular Python libraries and frameworks specifically focused on backtesting trading strategies as of 2025 include:

Backtrader
A widely-used, feature-rich backtesting framework that supports custom indicators, multiple data feeds, portfolio management, and broker integration. Suitable for both beginners and advanced users with a large community and example strategies.linkedin+2
Zipline
Developed by Quantopian and later maintained as Zipline Reloaded, it remains popular for backtesting algorithmic strategies with an event-driven system. Integrates well with historical equity data and is used in both research and live trading environments.analyticsinsight+2
VectorBT
Known for ultra-fast execution using vectorized computations, VectorBT allows backtesting thousands of trading strategies quickly. It’s excellent for quants working with large datasets and portfolios and integrates deeply with Pandas and NumPy.quantinsti+1
PyAlgoTrade
Focuses on simplicity and ease of use for backtesting and live trading, supporting event-driven strategies and some technical indicators. It’s suitable for those starting algorithmic trading.ibridgepy
QSTrader
An open-source, institutional-grade backtesting library with realistic simulations including slippage and fees. It’s designed for professionals and supports equity and other asset classes.quantstart+1
BT
A flexible backtesting framework focused on portfolio-based strategies. Often used for tactical asset allocation strategies and supports integration with other Python libraries.quantstart

Summary Table¶

Library	Key Feature	Target User	Open Source
Backtrader	Feature-rich, broker support	All levels	Yes
Zipline	Event-driven, Quantopian legacy	Researchers, quants	Yes
VectorBT	Ultra-fast vectorized execution	Quantitative quants	Yes
PyAlgoTrade	Simple, event-driven	Beginners	Yes
QSTrader	Institutional-grade realism	Professional quants	Yes
BT	Portfolio-focused	Portfolio managers	Yes

These libraries remain dominant choices for Python-based backtesting due to their balance of usability, speed, and realistic simulation features.linkedin+3

Resources to learn¶

https://www.threads.net/@ctt31200

Hnay rảnh ngồi tổng hợp vài resources về quant cho mn xem nha:

Math: Mathematics for Finance: An Introduction to Financial Engineering (Springer) https://shorturl.at/js0Qm Time Series Analysis and Its Applications by RH Shumway https://shorturl.at/y2HfD A Primer For The Mathematics Of Financial Engineering by Dan Stefanica https://shorturl.at/lpnBq
Code: Trading system: https://blog.quantinsti.com/automated-trading-system/
Finance: Options, Futures, and Other Derivatives, 8^th Edition by John Hull: https://shorturl.at/LIaTV Option Volatility and Pricing: Advanced Trading Strategies and Techniques by Sheldon Natenberg https://shorturl.at/D2cDT Beat the Market by Eward Thorp https://shorturl.at/M2zlt
Interview Questions: A Practical Guide To Quantitative Finance Interviews by Xinfeng Zhou https://shorturl.at/3aaDZ Frequently Asked Questions in Quantitative Finance by Paul Wilmott https://shorturl.at/5RHas
Data Database Design and Implementation by Edward Sciore

https://simpledb-java.netlify.app/database-design-and-implementation.pdf Machine learning cơ bản: https://shorturl.at/Cn0ab Deep learning: https://shorturl.at/Z4cJd Statistic + ML + DL: https://www.youtube.com/@statquest

Blogs + Utube: https://www.quantinsti.com https://www.quantstart.com/articles https://quantgirl.blog/quant-project https://epchan.blogspot.com https://www.youtube.com/@DimitriBianco https://youtube.com/@dirtyquant

Quantitative Trading Books¶

Algorithmic Trading: Winning Strategies and Their Rationale by Ernest P. Chan
This book provides practical insights into mean reversion and momentum strategies with code examples and risk management tips. It's suitable for traders wanting to build systematic strategies with retail platforms.quantmatter
Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernest P. Chan
A great introduction that covers designing, testing, and managing trading systems with a focus on real-world applications and pitfalls such as slippage and overfitting.nurp+1
Inside the Black Box by Rishi K. Narang
Explains how quantitative hedge funds operate their models and trading systems in an accessible way, suitable for intermediate learners interested in the mechanics behind quant trading.quantmatter
Advances in Financial Machine Learning by Marcos López de Prado
For quants who want to integrate machine learning into trading, this book offers professional techniques used by hedge funds and funds with big data approaches.reddit+1
Finding Alphas: A Quantitative Approach to Building Trading Strategies
Focuses on turning trading ideas into validated signals, addressing overfitting, and practical testing frameworks.newsletter.quantreo

General Trading Books¶

Market Wizards by Jack D. Schwager
A classic collection of interviews with top traders presenting diverse successful trading styles and their mindset approaches.tradingview+1
Trading in the Zone by Mark Douglas
Focuses on the psychological aspects of trading, discipline, and thinking probabilistically to improve trading decisions.acy+1
A Random Walk Down Wall Street by Burton Malkiel
Popular for understanding market efficiency and investing basics; good for foundational knowledge.reddit

Recommended Path for Beginners and Quants¶

Start with Quantitative Trading by Ernest Chan for a hands-on intro to strategy construction.
Complement with Algorithmic Trading by the same author for deeper, practical strategies and coding.
Include Market Wizards and Trading in the Zone for mindset and general trading skills.
Explore machine learning in trading via Advances in Financial Machine Learning as an advanced resource.

These books cover theory, application, psychology, and advanced methods, forming a comprehensive learning path for aspiring quantitative or systematic traders.newsletter.quantreo+3

Additional Notes¶

https://www.investopedia.com/articles/active-trading/112614/steps-becoming-quant-trader.asp
https://www.quantstart.com/articles/Self-Study-Plan-for-Becoming-a-Quantitative-Trader-Part-I/
https://www.cqf.com/blog/guide-becoming-quantitative-developer
https://www.quantstart.com/articles/Self-Study-Plan-for-Becoming-a-Quantitative-Developer/