THE PYTHON QUANTS
OUR PRODUCTS & SERVICES
BROWSER-BASED FINANCIAL ANALYTICS
Experience a new level of productivity and a new approach to collaboration in financial analytics. The platform offers eg Jupyter Notebooks, full browser-based shell acess, GUI-based filemanagement, project/file sharing & publishing. Get a free trial.
Yves Hilpisch, CEO of The Python Quants and The AI Machine, has authored four books on the use of Python for Quantitative Finance. The first is Python for Finance (O’Reilly, 2018, 2nd ed.) which has become the standard reference on the topic. The second is Derivatives Analytics with Python (Wiley Finance, 2015). The third is Listed Volatility & Variance Derivatives (Wiley Finance, 2016), followed by Artifical Intelligence in Finance (O’Reilly, 2020). The lastest is Python for Algorithmic Trading (O’Reilly, 2020)
DERIVATIVES & RISK ANALYTICS
Completely modular and object-oriented open source library to model, manage, price and risk manage complex portfolios of (multi-risk) derivatives with potentially complex correlations structures. Optimize portfolios, value interest swaps and more. Visit http://dx-analytics.com.
SERVICES & TRAINING
LET'S DO IT TOGETHER
We help you in any way to start using Python for Quant Finance, to solve specific problems or to conduct ambitious, path-breaking projects. Be it with consulting, development or training. We help you transition from e.g. Matlab or R and also in streamlining your financial analytics processes with Python.
Experience new levels of productivity and collaboration in financial analytics.
Our approach to designing the Quant Platform is inspired by Bruce Lee's martial arts
philosophy: "Absorb what is useful, discard what is not, and add what is uniquely your own."
Benefit from powerful features of the platform.
ONLINE TRAINING CLASSES
Our unique set of training offerings. Tailored to your needs.
ROCKET SCIENCE WITH PYTHON
BEAT THE MARKETS WITH PYTHON
Data Analysis, Simulation,
Market-based valuation and management of equity options from theory and practical implementation. Wiley Finance, 2015.
Python for Algorithmic Trading
From Idea to Cloud Deployment
Learn all the Python skills to develop your algorithmic trading strategy from first idea to robust cloud deployment. O'Reilly, 2021.
Learn the relevant Python basics and profit from many real-world financial examples. Jupyter-based tutorial style. O'Reilly, 2018, 2nd ed.
ARTIFICIAL INTELLIGENCE IN FINANCE
A Python-based Guide
Learn all about data-driven and AI-first finance with Python. Apply neural networks to beat the markets. O'Reilly, 2020.
LISTED VOLATILITY &
Introduction to listed volatility and variance derivatives with directly executable Jupyter Notebooks. Wiley Finance, 2017.
Profit from our expertise: our team members are experts in Python, Quantitative Finance,
Artificial Intelligence, Machine Learning, Python for Excel, and more.
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The Experts in Data-Driven and AI-First Finance with Python. We focus on Python and Open Source Technologies for Financial Data Science, Artificial Intelligence, Algorithmic Trading and Computational Finance.