Artificial Intelligence in Finance
Artificial Intelligence in Finance


Artificial Intelligence (AI) is about to reshape finance and the financial industry. Many decisions in the industry are already made by algorithms, such as in stock trading, credit scoring, etc. However, most of these applications do not harness the capabilities of recent advances in the field of AI.

Today's programmatic availability of basically all historical and real-time financial data, in combination with ever more powerful compute infrastructures, facilitates the application of even the most advanced and compute intensive algorithms from AI to financial problems. In that sense, finance already is data-driven to a large extent these days. And it will become an AI-first discipline in the near future.

The workshop provides some introductory background to AI in Finance. It then proceeds with the introduction to and application of different machine and deep learning algorithms to financial problems. The focus here lies on classification algorithms applied to the algorithmic trading of financial instruments. More specifically, the AI algorithms are used to create directional predictions about the future movements of financial prices.

The workshop uses Python and standard packages such as NumPy, pandas, scikit-learn, Keras/TensorFlow and matplotlib. Most of the coding will be presented based on Jupyter Notebooks.


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, artificial intelligence, algorithmic trading, and computational finance. He is also founder and CEO of The AI Machine, a company focused on harnessing the power of artificial intelligence for algorithmic trading via a proprietary strategy execution platform. He is the author of Python for Finance (2nd ed., O'Reilly) and of two other books: Derivatives Analytics with Python (Wiley, 2015) as well as Listed Volatility and Variance Derivatives (Wiley, 2017). Yves lectures on computational finance at the CQF Program and on algorithmic trading at the EPAT Program. He is also the director of the first online training program leading to a University Certificate in Python for Algorithmic Trading. Yves wrote the financial analytics library DX Analytics and organizes meetups, conferences, and bootcamps about Python for quantitative finance and algorithmic trading in London, Frankfurt, Berlin, Paris, and New York. He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

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