ODSC London 2022 Half-Day Training
Dr. Yves J. Hilpisch
CEO The Python Quants | The AI Machine
Adjunct Professor of Computational Finance
London, 15. June 2022
This half-day trading session covers the most important Python topics and skills to apply AI and Machine Learning (ML) to Algorithmic Trading. The session shows how to make use of the Oanda trading API (via a demo account) to retrieve data, stream data, place orders, etc. Building on this, a ML-based trading strategy is formulated and backtested. Finally, the trading strategy is transformed into an online trading algorithm and is deployed for real-time trading on the Oanda trading platform.
- Module: Setting up the Python and Oanda (paper) trading infrastructure
- Module: Financial data logistics and backtesting of an ML-based algorithmic trading strategy
- Module: Deployment of the ML-based algorithmic trading strategy in real-time
Basic knowledge of Python and data science packages, such as NumPy, pandas, and matplotlib.
To come.
Platinum Package Program (Self-Paced): https://platinum.tpq.io
Algorithmic Trading Online Bootcamp: https://platinum.tpq.io
Our newest book about Financial Theory with Python (https://home.tpq.io/books/ftwp/).
Sign up under https://finpy.pqp.io to access all the Jupyter Notebooks and execute them on our Quant Platform.
Our recent book about Python for Algorithmic Trading (https://py4at.tpq.io).
Sign up under https://py4at.pqp.io to access all the Jupyter Notebooks and execute them on our Quant Platform.
Our recent book about Artificial Intelligence in Finance (https://aiif.tpq.io).
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Our standard reference book about Python for Finance (http://py4fi.tpq.io).
Sign up under https://py4fi.pqp.io to access all the Jupyter Notebooks and execute them on our Quant Platform.
If you have either Miniconda or Anaconda already installed, there is no need to install anything new.
Otherwise, you might want to install Miniconda for your operating system: https://conda.io/en/master/miniconda.html
Read more about the management of environments under: https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
Use this link to get a 10 USD bonus on DigitalOcean when signing up for a new account.
