Home 2015 › Forums › Applications › Trading Strategies (Algo Quant) › Introduction to Algorithmic Trading Strategies 2011 @ NTU
This topic contains 0 replies, has 1 voice, and was last updated by Haksun Li 5 years, 6 months ago.

AuthorPosts

20111114 at 10:44 am #1892
Thank you very much for the comments and feedback from the NTU students in 2011!
Dengjie:
This course has been great! Iâ€™ve learned a lot of concepts I can almost immediately apply to my job. Originally I enrolled in MFE to understand better linear and timeseries statistical models. But after the 3 standard courses offered, although I had a great idea of how to play around with data and develop relationships between time series etc., there was a needing lack of application.
The QTS course opened me up to how I can use cointegration concepts to develop more pairs and basket trades. On top of that, the very interesting (but freaking difficult) research paper for our project has incorporated Markov Chains into cointegration which adds another filter to signals generated. It took me a long time to understand the paper and the material covered on Regime Switching and Cointegration helped a lot.
The topic on generating the optimal trading position strategy for a mean reverting process was a real eye opener to how math gets integrated into trading. Originally I thought that, being able to get the mean reverting relationship was enough, and position management would be done through trial and error. The added optimization was something I never thought of and is a real learning experience.
Omega definitely trumps Sharpe Ratio and Iâ€™m glad we had time to cover that portion. The fact that it reduces Excess return over a put price (SharpeOmega) makes everything easier to quantify, since I was wondering how we would find F(x) in real life. Overall, Omega is just a neat and comprehensive measure and I donâ€™t believe I would have learned about it in any other course or trader.
Frankly though, the course is a real hard slap to the face about how little I really know in terms of math sophistication and application. I think what you said in one of the early lectures really sums up a lot of the problems I currently have, which is to be able to put the math into logic and not just be able to go through the steps. That can only come with practice in real world situations I believe.
Overall, this course has been really really good to me, especially since Iâ€™m going back into HFT. From a student standpoint, the course is difficult as hell since it covers all aspects of math from high school to graduate level, plus the programming is there to amp things up. From a practitionerâ€™s viewpoint, I wished that we had more time to delve into more complicated concepts and not have to only cover the surface of a lot of the material due to time constraint.
Ashutosh:
Liked the way course is integrated to the real world scenarios. Hope to make money sometime in future using the knowledge attained from the course.
Prashant:
This course provided some concrete knowledge of algo trading. I had read some books on algo trading and some stuff on net, but all of them seem to give a very general idea rather than going into actual strategies. This way this course has really provided some real industry material.
Kenneth:
This course presents a terrific introduction to the basics of Quantitative Trading Strategies. Although the mathematics behind quantitative trading is difficult to absorb, this introduction has given me useful insights for further selfexploration on the topic. Also, the importance of programming was highlighted through the assignments and gave a good blend of both practical and theoretical approaches to the topic.
Lu:
Yes, I definitely benefit from this course a lot. This course provides a lot of insights into the quantitative trading area which represents a fresh perspective of trading. From homework1 and project, I have practice to transform the knowledge to the actual implementation of the strategy so that I have a feel how strategy works in real life and how the abstract trading ideas can generate real money 🙂 Thank you very much for your sharing.
Tji Hun:
I loved this course, prior to this course I always thought of trading as an endeavour of art, guts & luck. But after the course, I realised that for certain strategies there are sound scientific theories from which it can be analysed and soundly built on incrementally.
Considering that the course is an elective and was fully subscribed, speaks volumes about the interest in trading. I would recommend that this course be extended to 2 electives so that future classes can cover more material.
This is definitely one of the top 3 courses I have enjoyed while studying at MFE.
Chuan Xiang:
This course has provided me with an interesting perspective to trading; specifically from a very mathematical standpoint.
In my current work, I use a lot of technical indicators e.g., Fibonacci, DeMark and Moving Averages. Just simply from the first homework where we are to program Fibonacci as a trading strategy, I realized there is no fix rule as to how we use Fibonacci. It was always been seeing it in Bloomberg by simply identifying the lows and highs to give us the retracement levels.
In summary, I like this course. Thank you, Prof Haksun.

AuthorPosts
You must be logged in to reply to this topic.
Recent Comments