A Sneak Peek into AI Based HFT Trading Strategies [WEBINAR]

Share on Facebook0Tweet about this on Twitter0Share on LinkedIn5Share on Google+0

Webinar Recording:

High Frequency trading uses complex algorithms to analyze markets and cutting-edge technological tools achieve fastest speed in implementation.

About Webinar

In this webinar, we learnt how machine learning techniques can help us design better trading strategies. We learnt about alpha in trading and how we can extract it by applying the knowledge about the market structure and order flow. We also understood how to use machine learning for predicting asset paths. The webinar was open to everyone who has interest in understanding the high frequency trading and using Artificial Intelligence for trading.

Instructor – Sameer Kumar

Sameer Kumar

Sameer is a director and faculty at QuantInsti. In Executive Programme in Algorithmic Trading, he teaches students to build the low latency systems as well as strategies involving artificial intelligence. Sameer has been leading the infrastructure development team along with the low latency programming division at iRageCapital Advisory Private Ltd for more than 5 years now.

Date – 27th February 2015      Time – 6:00PM IST

To learn more about implementation of Artificial Intelligence in Trading, join us for our upcoming webinar on Machine Learning.

A Must Watch:
Leveraging Artificial Intelligence to Build Algorithmic Trading Strategies [WEBINAR]

Next Step

If you’re a retail trader or a tech professional looking to start your own automated trading desk, start learning high-frequency trading today! Begin with basic concepts like automated trading architecture, market microstructure, strategy backtesting system and order management system. You can also enrol in our algorithmic trading course EPAT which is one of the most extensive certification programmes available in the industry.

Share on Facebook0Tweet about this on Twitter0Share on LinkedIn5Share on Google+0

Leave a Reply

Your email address will not be published. Required fields are marked *