Momentum Trading Strategies Course
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One of the biggest barriers to creating a quantitative strategy is knowing how to code. The other barrier is having sufficient theoretical and empirical knowledge. Getting a degree in finance can help with the latter, and a computer science degree can help with the former but if you want to be able to do both you often have to start from scratch which can be very intimidating. I recently took the Momentum Trading Strategies Course by Quantra which is unique because it teaches you both the background theory and empirical research as well as how to code examples in Python– currently the most popular language for algorithmic traders. Given that my coding skills are limited to using Microsoft Excel, this course was especially useful and I even learned a few new things on the research side. Readers interested in enrolling in the course can follow this link and receive an additional 5% off by using the coupon code: CSSA5
Note: This course is currently priced at $179 but will return to its normal price of $499 on November 2.
Before getting to my review of the course below it is important for readers to know a little bit more about the service and the players behind the scences:
Quantra is a learning platform for algorithmic trading courses, where through advanced interactive & hands-on learning technology offers content curated by some of the top thought leaders in the domain of algorithmic trading including;
1) Dr Ernest P. Chan
2) Laurent Bernut
3) Dr Terry Benzschawel
4) National Stock Exchange (World’s Biggest Derivatives Exchange)
5) Multi Commodity Exchange (India’s Leading Commodity Exchange)
6) Interactive Brokers
7) Forex Capital Markets (FXCM)
The parent company of Quantra is QuantInsti, which was founded by one of India’s biggest HFT firms; iRage, is today one of the world’s most prominent algorithmic & quantitative trading & research institutes with a user base in 180+ countries.
Review On Momentum Trading Strategies Course
First I have to say that this is a really comprehensive course with very slick technology for the e-learning community. The course took me a couple days to complete which was longer than I expected but it also went into far greater depth than I expected as well. To get the most out of the course you should also read the recommended research articles and also work on coding the examples.
It starts off very basic- almost too basic for those familiar with momentum- but gradually builds and gets more advanced with each segment. The topics covered early on include answering what momentum is and why it exists as an anomaly. By the time you get to the fifth section you are being introduced to Python and how to work with commands and loading in data for analysis. You then cover more advanced topics like how to use the Hurst Exponent to cross-sectional arbitrage strategies in futures that exploit roll returns.
In this comprehensive curriculum it seems like every major popular paper on momentum is neatly summarized and the course also covers important topics like Momentum Crashes and risk management. Each segment has examples linked to using Python. There are also multiple choice questions that are there to test your memory and comprehension of the material. As you reach the end of the course you are introduced to even more practical topics like how to automate trading strategies and link to broker APIs.
Overall I was very impressed and I think this is exactly the kind of e-learning alternative that both students and traders/investors need to make their dreams of having their own automated strategy a reality. In subsequent posts I plan to continue to share my learning journey by trying new courses and will provide readers again with a review. Hats off to the team at QuantInsti for being an innovator in this space.
CSSA 
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