# cybergeekgyan/Quant-Developers-Resources

Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds

Repository: https://github.com/cybergeekgyan/Quant-Developers-Resources
Canonical: https://ross.abutalabs.com/products/quant-developers-resources
Homepage: https://cybergeekgyan.github.io/Quant-Developers-Resources/
Language: Python
License Family: other
Topics: algorithmic-trading, quant-finance, quantitative-finance, quantitative-trader, quantitative-trading, trading-strategies, quantitative-projects, hedgefund
Last push: 2026-08-15T22:02:08+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 97, release rhythm 35, longevity 75
- inputs: {"age_days": 1052, "days_push": 18, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3718, forks 447 (observed 2026-08-28T04:08:15.417217+00:00)

## What it is
A curated collection of resources for preparing for quantitative developer, researcher, trader, and analyst interviews at quant trading firms, HFTs, and hedge funds. It covers interview processes, key topics like probability, stochastic calculus, option pricing, and portfolio theory, plus programming and data science material.

## Use cases
- prepare for quant developer interview
- study for quantitative researcher role at a hedge fund
- find resources for quant trader interview questions
- learn option pricing and greeks for interviews
- review probability and stochastic calculus for quant roles
- prepare for HFT firm hiring process
- find algorithmic trading learning materials

## When to choose
- you are interviewing for quant developer, researcher, trader, or analyst roles
- you want a curated topic checklist for quant finance interviews
- you need a starting point covering math, finance, and programming for quant careers

## When to avoid
- you need executable trading software or backtesting code rather than study material
- you want a formal course or textbook with structured lessons
- you need production-grade quantitative finance libraries

## Facets
- artifact type: learning-resource
- maturity: active
- function: trading, developer-tools
- domain: fintech, tutorials, education
- platform: cross-platform
- tags: quant-finance, interview-preparation, awesome-list, hedge-funds, hft, algorithmic-trading, study-guide

## Member repositories
- cybergeekgyan/Quant-Developers-Resources (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:15.417217+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:29:21.429089+00:00, confidence not recorded.
  - readme: https://github.com/cybergeekgyan/Quant-Developers-Resources (fetched 2026-08-28T04:08:15.417217+00:00, sha a7aab83ccac0)
  - homepage: https://cybergeekgyan.github.io/Quant-Developers-Resources/ (fetched 2026-08-29T09:24:05.863203+00:00, sha db799a24b2c0)
- Data as of 2026-08-30T08:39:29.467469+00:00.