Python is very well suited for automated financial trading — especially for low- and mid-frequency strategies. This Webinar illustrates how easy it is to implement typical steps of an automated trading approach:
- Historical data scraping
- Backtesting of trading strategies
- Working with streaming data
- Automated trading in real-time
All examples shown are based on the platform and API of http://oanda.com. Background information about Python and the libraries used can be found in the O’Reilly book Hilpisch, Yves (2014): “Python for Finance – Analyze Big Financial Data”.
Tentative Date and Time
10 February, Wednesday
13:30 Central European Time
18:00 Indian Standard Time
20:30 Singapore Time
Dr. Yves J. Hilpisch
Yves J. Hilpisch is founder and managing partner of The Python Quants GmbH, Germany, as well as co-founder of The Python Quants LLC., New York City. The group provides Python-based financial and derivatives analytics software as well as consulting, development and training services related to Python, Open Source and Finance. Yves is also author of the book “Derivatives Analytics with Python” (Wiley Finance, 2015). As a graduate in Business Administration with a Dr.rer.pol. in Mathematical Finance, he lectures on Computational Finance at the CQF Program.
If you are a coder or a tech professional looking to start your own automated trading desk. Learn automated trading from live Interactive lectures by daily-practitioners. Executive Programme in Algorithmic Trading covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading. Enroll now!
You can also check out our interactive course, ‘Python for Trading‘, you’ll get hands-on experience on Python coding. You’ll get to code your own strategy and backtest it as well plus a joint certification from QuantInsti and MCX.