Chevron Left
Zurück zu Reinforcement Learning for Trading Strategies

Kursteilnehmer-Bewertung und -Feedback für Reinforcement Learning for Trading Strategies von New York Institute of Finance

3.7
Sterne
104 Bewertungen
25 Bewertungen

Über den Kurs

This course is for finance professionals, investment management professionals, and traders. Alternatively, this Specialization can be for machine learning professionals who seek to apply their craft to trading strategies. At the end of the course you will be able to do the following: - Understand what reinforcement learning is and how trading is an RL problem - Build Trading Strategies Using Reinforcement Learning (RL) - Understand the benefits of using RL vs. other learning methods - Differentiate between actor-based policies and value-based policies - Incorporate RL into a momentum trading strategy To be successful in this course, you should have a basic competency in Python programming and familiarity with the Scikit Learn, Statsmodels and Pandas library.You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

Top-Bewertungen

MS

Mar 06, 2020

It was easy to follow but not easy. I learned a lot and I now have the confidence to implement Reinforcement learning to my own FX trading strategies. Thank you so much.

GS

Mar 07, 2020

Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn

Filtern nach:

1 - 24 von 24 Bewertungen für Reinforcement Learning for Trading Strategies

von Yutong X

Apr 27, 2020

I think this course is in the middle of a simple introduction and a practical course. You should not enroll if you expect to be able to be able to build a RL system. You should not enroll if you are expecting some simple intuitive introduction of RL. This is more difficult than an introduction but tells you nothing more than some introduction, so it is an introduction done in a difficult way. I think it is better to avoid it.

von Nissim

Feb 20, 2020

Disapponting.

Last project week 3 does not have any connection to the topic.

Most of week 3 lessons are hand waving general recommendations, not real teaching or discussions

I feel deceived.

von Mike S

Mar 06, 2020

It was easy to follow but not easy. I learned a lot and I now have the confidence to implement Reinforcement learning to my own FX trading strategies. Thank you so much.

von Manfred R

Mar 08, 2020

I learned new perspectives of trading - great

von Jiaheng Z

May 03, 2020

Only learned small pieces of concepts about quant trading, reinforcement learning parts are not connected well at all, it's all about advertising Google Cloud services.

von Brian M Y

Mar 23, 2020

Really general level concepts and does not go deep into the code of reinforcement models. The labs are scarce and not helpful at all.

von Masa

Feb 22, 2020

I do not recommend this course to my friends.

Exercises are not prepared to help learners to understand ML for Trading.

von Yun Z L

Apr 12, 2020

Very knowledgable theories from Jack Farmer and the AutoML lab was quite straight forward. However, it would've been good to have the week 3 Portfolio Risk Management code added included as an actual lab exercise instead of talking through it.

von Grigoriy S

Mar 07, 2020

Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn

von Steve H C F

Mar 15, 2020

Good course introducing concepts in RL. Wish course provided more examples of using RL in stock prediction.

von Mohammad A S

Apr 07, 2020

It has good practical stuff, BUT not any practical RL related to trading.

von Colin E

Mar 01, 2020

It was ... OK. The lectures by the NYIF guy were immediately relevant to me, worth taking the course for. They should just have removed the Google stuff entirely and just started with an assumption of a basic knowledge of ML - just focus on the financial applications. So, bottom line: the good content is good, but mixed with a bunch of generic, time-wasting junk... that at least can be skipped over.

von Abhinandan T N

Apr 17, 2020

This course seemed like movie trailer where there many jargons are introduced which are definitely worth but the information on the same is very limited which does not make students comfortable.

This course was more towards introducing the facility in Google Cloud than on the Title of the course.

von DeWitt G

May 24, 2020

Really good stuff, thank you! The Deep Q networks were a bit over my head, I will need to keep studying. It was good theory, but I would have like to see these models trade in the markets to really understand how they act in live trading environments.

von Jair E R L

Jun 07, 2020

This content really is ahead of the Business As Usual.

Congrats!

von 李艳丹

Mar 25, 2020

perfect!

von Niels S

Apr 16, 2020

Nice with the RL classes, it is a bit random.

von WAI F C

May 10, 2020

The course could be improved if the lab included stock trading related works for both RL and LSTM. I had already learned stock trading with RL and LSTM before I took this class.

von Aadam

Apr 02, 2020

It is geared more towards people who already have an understanding of the stock market and its lingo. Not much information about stock market lingo for a beginner.

von Jonathan G

Jul 06, 2020

Very unusual course. Some useful theory on RL but very little practical coded examples of RL for trading. Heavy on pushing Google cloud services.

von Dmitrievskiy A

Apr 19, 2020

Reinforcement learning tasks are not related to financial domain. Financial topics are superficial. Course for absolute newbies in RL and FinTech

von Chaojun L

May 18, 2020

No practical, and useless for people who only wants more details about implementation of RL algo in trading rather than details about GCP.

von David G

Jun 18, 2020

Few financial applications. RL is a complex notions. Exerices are too difficult.

von Biagio B

May 30, 2020

Most of the course is a generic lecture about RL and LSTM taken from other courses. The rest is mostly advertisement for GoogleCloud, which it is not useful since you could do all exercises on a local laptop. Only a fraction of the course talks about finance and it is so generic that cannot be applied to any real world case.