The unprecedented proliferation of data in derivatives markets has led to the rise in popularity of Python, a multi-purpose programming language known for its ease of use, versatility and flexibility. Undoubtedly, the increased adoption of Python has helped enable greater collaboration and customizations for valuation and risk modelling and reporting.
To delve more deeply into the application of Python within financial markets, Risk.net will be holding a webinar on Wednesday, October, 17, titled: How to Apply Python to Complex Markets. Speakers, Joel Clark of Risk.net, Gary Collier of Man Group Alpha and I will be discussing the benefits that Python can bring to businesses and the challenges associated with adopting the language and extending its use.
Overcoming Challenges with Python
Python may now be more accessible and easier to learn, but it is not without its challenges. For instance, it is not as fast as other languages, making it unsuited to areas like high-frequency trading. Programmers must know how to implement the language properly, to put it to best use and upgrades or changes must be well managed to avoid disruptions.
During the webinar, there will be an extensive discussion around the challenges, risks and limitations associated with implementing and using Python for data-intensive processes. Attendees can expect to learn valuable best practices that will help them to mitigate these inherent risks. Additionally, the advantages of using Python to analyze and value derivatives will also be explored.
If you are interested in the upcoming Python webinar, you can learn more and register here. For more insight around Python, check out the blog I posted a couple weeks ago: Is Python the New Excel?
