/finance_playground

Juypter notebooks playground to explore and analyse economy and finance ideas

Primary LanguageJupyter NotebookMIT LicenseMIT

Binder

Finance Playground

In God we trust, all others bring data - William Edwards Deming

In this project our aim is to explore and analyse financial instruments (stocks and options in particular) and to develop profitable trading strategies. To that end, we focused on the relation between price time series and factors such as market volatility, interest rates, and various economic indicators.
We started this as a learning tool. As developers, we advocate a hands on approach, we like trying out ideas and tinkering with models. If that sounds at all interesting, you can follow our progress which will be documented in Jupyter notebooks here.

Collaboration is welcome: by all means, if you spot a mistake or just want to add an interesting notebook you've been playing with, please submit a pull request.

Notebooks

Requirements

  • Python >= 3.5
  • pipenv

Usage

If you want to view the notebooks locally, simply install the dependencies with:

$ pipenv --three && pipenv install

Then start Jupyter Lab

$ cd notebooks && jupyter lab

Recommended reading

For complete novices in finance and economics, this post gives a comprehensive introduction.

Books

Papers

Introductory

  • Option Volatility and Pricing 2nd Ed. - Natemberg (2014)
  • Options, Futures, and Other Derivatives 10th Ed. - Hull (2017)
  • Trading Options Greeks: How Time, Volatility, and Other Pricing Factors Drive Profits 2nd Ed. - Passarelli (2012)

Intermediate

  • Trading Volatility - Bennet (2014)
  • Volatility Trading 2nd Ed. - Sinclair (2013)

Advanced

  • Dynamic Hedging - Taleb (1997)
  • The Volatility Surface: A Practitioner's Guide - Gatheral (2006)
  • The Volatility Smile - Derman & Miller (2016)

Data sources

Exchanges

Historical Data