Quant Finance Resources: Data, Code and Learning Paths

Resources for building a quantitative finance research workflow.

This collection brings together resources for studying quantitative finance and developing a research workflow, from market structure and mathematical foundations to Python and financial data. The public starting points below explain where to begin. The fuller resource workspace is available to paid subscribers.

Who this is for

Start here if you are learning quantitative finance or organising your research tools. The data and book examples can be explored without coding. The Python path assumes basic programming; more mathematical material is best approached with probability, calculus and linear algebra in place.

Public starting points

These examples are freely accessible starting points for data, code and learning. They are separate from the fuller subscriber workspace.

Data: FRED and ALFRED

FRED economic data is useful for exploring macroeconomic time series. ALFRED historical vintages lets you check which release was available on a particular date. For a historical study, compare the available vintage with today’s revised series rather than assuming the latest value was known at the time.

Code: pandas introductory tutorials

The official pandas tutorials cover reading tables, selecting observations, combining datasets and handling time series. With basic Python in place, practise loading a CSV, checking dates and missing values, and summarising the data before fitting a model.

Learning: the quant-finance library

Use my annotated quant-finance library to choose a book sequence for derivatives and market intuition, mathematical foundations or machine-learning research. Pick the path that matches your prerequisites and the question you are trying to answer.

Subscriber workspace

• Market Theory & Microstructure
  Market structure, execution mechanics and liquidity

• Python for Finance
  Python libraries and resources for financial data and research

• Mathematics for Finance
  Core concepts and applied techniques grounded in real-world quant practice

• Interview & Career Prep
  Hedge fund guides, technical exercises, and case studies

• Quant Learning Roadmap
  A study sequence across quantitative-finance topics

• Media Worth Your Time
  Podcasts and talks on markets and quantitative finance

• Financial Data Tools
  APIs, datasets, and visualization libraries

• Crypto Quant Toolkit
  Strategies and data resources for high-volatility markets

The public examples above are free to explore. The fuller collection is available to paid subscribers; its access link and instructions are below the subscriber boundary.

For research articles and further learning routes, see Start Here.