Finance with Python

An In-Depth Online Training Course

NOW WITH VIDEOS



This is an in-depth online training course about Finance with Python that gives you the necessary background knowledge to proceed to more advanced topics in the field, like computational finance or algorithmic trading with Python. If you are primarily interested in algorithmic trading, our Python for Algorithmic Trading Course, which includes this one, might be the right choice.





Book the course today based on our special deal of 79 EUR (instead of 99 EUR) — or read on to learn more. Now includes 7+ hours of video instruction.




No refunds possible since you get full access to the complete electronic course material (HTML, Jupyter Notebooks, Python codes, etc.). Also note that the course material is copyrighted and not allowed to be shared or distributed. It comes with no warranties or representations, to the extent permitted by applicable law.

What Others Say
About Our Courses


Dear Yves,

Great stuff! I just purchased it. It is the Holy Grail of algo trading! All the things that someone would have spent hours and hours of research on the web and on books, they are now combined in one source. Thank you “Prometheus” for delivering “fire” to mankind!

Keep up the good work!

Best,

Konstantinos

Email from the Netherlands, January 2017


Award-Winning Analytics

We are proud to be named Top 10 Banking Analytics Solution Provider of 2017 by Banking CIO Outlook.

A Perfect Symbiosis

Both Quantitative and Computational Finance are fields in applied mathematics. For example, linear algebra, probability theory and analysis are fruitfully applied to phenomena and problems in financial markets. However, financial text books often use advanced mathematics and complex models from the beginning — diverting attention from the fundamental concepts and insights to the intricacies of the mathematical techniques. This course starts with the most simple models and progresses slowly to fully focus on the financial notions, results and applications first — thereby creating a solid understanding of important topics in Finance.

The Python programming language and its eco-system of powerful packages has become the technology platform of choice for Quantitative and Computational Finance. The syntax of the language is rather close to mathematical and financial notation such that translations from abstract mathematical models to executable Python codes are rather straightforward in general. In addition, packages like NumPy provide powerful vectorization approaches that make, for example, the coding of linear algebra operations highly efficient. It is therefore the ideal language for an introduction to computational aspects of Finance.

Topics of the course

This is an in-depth, intensive online course about Finance with Python (version 3.6). Such a course at the intersection of two vast and exciting fields can hardly cover all topics of relevance. However, it can cover a range of selected topics in-depth:


An incomplete list of the technical and financial topics comprises: static model economy, money & currency, agents, real assets, financial assets, cash flow, present value, net present value, uncertainty, return, interest, probability, expectation, expected return, volatility, contingent claim, replication, arbitrage, market completeness, market incompleteness, Arrow-Debreu securities, state prices, martingale measure, fundamental theorem of asset pricing, risk-neutral pricing, mean-variance portfolios, attainable contingent claims, span of financial assets, super-replication, approximative replication, capital market line, capital asset pricing model, optimality, equilibrium, utility function, preferences, time-additive utility, expected utility, arbitrage pricing, martingale pricing, pricing in incomplete markets, equilibrium pricing.

Table of Contents

Have a look at the (current) table of contents of the PDF version of the online course material.



Uniqueness and Benefits

The course offers a unique learning experience with the following features and benefits.

About the course author & instructor

Dr. Yves J. Hilpisch is founder and managing partner of The Python Quants, a group focusing on the use of open source technologies for financial data science, algorithmic trading and computational finance. He is the author of the books

Yves lectures on computational finance at the CQF Program, on data science at htw saar University of Applied Sciences and is the director for the online training program leading to the first Python for Finance University Certificate (awarded by htw saar).

Yves has written the financial analytics library DX Analytics and organizes meetups and conferences about Python for quantitative finance in Frankfurt, London and New York. He has also given keynote speeches at technology conferences in the United States, Europe and Asia.

Git Repository

All Python codes and Jupyter Notebooks are provided as a Git repository on the Quant Platform for easy updating and also local usage. Make sure to have a comprehensive scientific Python 3.6 installation ready.

Order the course

Currently, we offer you a special deal when signing up today — because we are still developing the course and the material. Just pay

79 EUR

instead of the regular price of 99 EUR. By signing up today you secure the attractive, reduced price while also securing access to all future updates. It has never been easier to learn Finance with Python.

Simply place your order through PayPal for which you can also use your credit card.




No refunds possible since you get full access to the complete electronic course material (HTML, Jupyter Notebooks, Python codes, etc.). Also note that the course material is copyrighted and not allowed to be shared or distributed. It comes with no warranties or representations, to the extent permitted by applicable law.

Get & Keep in Touch

Write us under training@tpq.io if you have further questions or comments. Sign up below to stay informed.