Resources & Links

This folder collects cross-Part reference materials and external resource links.

⚠️ Important Note: Data provider pricing, latency metrics, and API specifications change frequently. This folder's content was last verified in 2025-01. Please check official documentation for the latest information before use.


File Index

FileContentApplicable Stage
Data-Provider-ComparisonComparison of major data providers (Binance, Yahoo, Bloomberg, etc.) - features, pricing, use casesPart 2+
Broker-Platforms-and-APIsIntroduction to trading APIs from major brokersPart 5
Top-Quant-Fund-Case-StudiesCase study snapshots of leading quant institutions in China and abroadExtended Reading
Tick-and-L2-Order-Book-Data-SourcesChannels and pricing for high-frequency data procurementPart 5 (Advanced)
HFT-Data-CentersHFT data center locations and co-location servicesBackground Knowledge
FIX-Protocol-IntroductionFIX 4.4 message structure, QuickFIX implementationPart 5
Market-Data-Licensing-BasicsPro vs Non-Pro, redistribution limits, SIP/OPRA vs direct feedsPart 2+
ArXiv-PapersRecommended academic papers related to quantitative tradingExtended Reading

External Resources

Data Sources

  • Yahoo Finance (Free daily data) - yfinance Python library
  • Alpha Vantage (Free/Paid API)
  • Binance API (Cryptocurrency data)

Backtesting Frameworks

  • VectorBT - Vectorized backtesting, fast execution
  • Backtrader - Event-driven, full-featured
  • zipline-reloaded - Community-maintained fork of original Quantopian framework (Quantopian shut down in 2020)
  • LEAN (QuantConnect) - Institutional-grade open-source backtesting engine
  • vnpy - Chinese quant framework, supports CTP interface

Multi-Agent Frameworks

  • Shannon OSS - Reference implementation for this course
  • AutoGen - Microsoft open source
  • CrewAI - Role-driven orchestration

See Part1/Background/Recommended-Reading

Cite this chapter
Zhang, Wayland (2026). Resources & Links. In AI Quantitative Trading: From Zero to One. https://waylandz.com/quant-book-en/resources-overview
@incollection{zhang2026quant_resources_overview,
  author = {Zhang, Wayland},
  title = {Resources & Links},
  booktitle = {AI Quantitative Trading: From Zero to One},
  year = {2026},
  url = {https://waylandz.com/quant-book-en/resources-overview}
}