# LongOnly/Quantitative-Notebooks

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

Repository: https://github.com/LongOnly/Quantitative-Notebooks
Canonical: https://ross.abutalabs.com/products/quantitative-notebooks
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: quantitative-finance, quantitative-trading, asset-management, asset-allocation, algotrading, trading-algorithms, trading-strategies, financial-analysis, pairs-trading, algorithmic-trading, asset-pricing, stock-trading, python, machine-learning, data-analysis, data-science, jupyter, notebook
Archived: true
Last push: 2020-07-02T00:17:39+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2894, "days_push": 2254, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1393, forks 215 (observed 2026-08-28T04:04:36.260414+00:00)

## What it is
A collection of educational Jupyter notebooks on quantitative finance, covering algorithmic trading strategies, pairs trading, and dynamic asset allocation. It is intended for idea generation and learning rather than production trading use.

## Use cases
- learn quantitative finance with python notebooks
- understand pairs trading strategies
- example of machine learning for trading
- learn dynamic asset allocation and diversification
- educational algorithmic trading examples
- financial modelling tutorials in jupyter

## When to choose
- you want educational, well-explained quant finance notebooks
- you are learning pairs trading or asset allocation concepts
- you want starter code combining pandas, scikit-learn, and market data

## When to avoid
- you need production-ready trading strategies
- you need current market data (last updated July 2020)
- you want a maintained trading framework or backtesting engine

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, trading
- domain: fintech, data-science, education
- platform: python
- tags: quantitative-finance, algorithmic-trading, jupyter-notebooks, pairs-trading, asset-allocation, educational, jupyter

## Member repositories
- LongOnly/Quantitative-Notebooks (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:36.260414+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 2026-08-30T04:39:27.866905+00:00, confidence not recorded.
  - readme: https://github.com/LongOnly/Quantitative-Notebooks (fetched 2026-08-28T04:04:36.260414+00:00, sha 8d76f425b792)
- Data as of 2026-08-30T08:39:29.467469+00:00.