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Voltar para Reinforcement Learning for Trading Strategies

Comentários e feedback de alunos de Reinforcement Learning for Trading Strategies da instituição New York Institute of Finance

3.7
estrelas
192 classificações
51 avaliações

Sobre o curso

In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. 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)....

Melhores avaliações

MS

5 de mar de 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.

RA

2 de fev de 2021

After the first two courses, this one grabs you into the reinforcement learning spectrum. This topic has been revealing to me and its applications to trading

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26 — 50 de 51 Avaliações para o Reinforcement Learning for Trading Strategies

por Sarvari P

20 de mai de 2021

Succinct and great explanation of deep reinforcement learning methods with amazing demo lab scripts

por Jair R

7 de jun de 2020

This content really is ahead of the Business As Usual.

Congrats!

por Sridhar S

9 de mar de 2021

Need more time to finish the ML model

por Edgar C

23 de fev de 2021

Muy buen curso.!

por 李艳丹

25 de mar de 2020

perfect!

por Martin L

14 de jul de 2021

Provide the idea and method of RL for trading, but seems like less practice knowledge for the trading. hope can add more detail for for the trading build up. overall the course are good.

por Макс К

4 de out de 2020

Great course, exactly what I was looking for! But there were some technical difficulties on practical tasks ...

por Gustav K F Y

1 de jul de 2022

I look forward to examples of integration of decision based on reinforcement learning and algo-trading logic

por RENATO V M S

13 de jul de 2021

A touhg and very advanced course, with an amazing Google Cloud Platform !!!!

por Deleted A

16 de abr de 2020

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

por Andrew C

10 de out de 2020

There are some lectures on RL and some on Trading. But there aren't enough materials on the application of RL to Trading. It just talks about some high level concepts on how it could be used. We could get this from any basic article on RL and Trading. Even the last exercise is not RL on Trading. It's just a machine learning exercise to predict S&P500's direction. Basically there is zero example and exercise on RL for Trading Strategies, which is the main topic.

por Jakub K

28 de ago de 2020

I learned a few cool things. The main problem with this specialization is that the Machine Learning Stuff and Finance stuff are really separated (Google, NY univ). What I was looking for is the place where two concepts meets. Also i felt like ML stuff went too deeply too fast. Still... Cool Introduction.

por WAI F C

10 de mai de 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.

por Aadam

2 de abr de 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.

por Dmitrievskiy A

19 de abr de 2020

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

por Sushil V

24 de mar de 2021

no actual model on stock prediction using RL

por Oliver P

4 de ago de 2020

While there were a lot of interesting concepts in this course, I didn't feel that I learned a lot from it and certainly was nowhere near implementing what I wanted to. It pushes Google's cloud services so you're on your own if you want to program on your own computer. I've since completed a course by deeplearning.ai (not trading focussed) which I felt was a lot better, I learned a lot of theory to develop an understanding of what they're teaching as well as practical coding assignments that I felt I could actually take the code and apply to my own projects.

Google pushes its ability to learn from BigData but I really don't consider stock data to be BigData, at least if you're processing a single instrument/currency/stock at a time. If you're trying to go down to tick level data then you're going to have more problems with lag and execution making processing that amount of data a bit pointless... unless that's really really what you want/need to be doing.

To be fair to this course, it is good to know what is out there should it be suitable for your challenges and yeah, they can process a massive, huge, gigantic amount of data very quickly.

por Simone B

4 de mai de 2022

There is no real application of RL in trading in this course. They just first skim quickly to the basics of RL, quite superficially, then they explain the basics of portfolio management. These two rails go parallel and never touch each other. Moreover, the part covering RL, MDP, TD and Q Learning is illustrated too fast to understand any subtle points, with too many details (equations quickly explained, code fragments gone through in a minute or too) put together roughly to be a qualitative introduction.

por David G

28 de jun de 2022

A few interesting nuggets buried in a mess of cobbled together material, dodgy slide decks with poorly formatted code snippets, all combined with the annoying "QwikLabs" that takes about 3 minutes to start for every single assessment. This could be so much better.

por David G

18 de jun de 2020

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

por Novi K

13 de jul de 2020

not really make me statisfied

por Hyder A A

1 de jan de 2022

Way below expectations!

por Amos E

27 de jun de 2021

I​ went through the first two classes in this specialization to get to the reinforcement learning material. Total waste of time. The RL material consists of an introduction to RL in general, and some pre-done notebooks that execute RL on ai gym. None of it has anything to do with trading strategies. The finance lectures, of course, do relate to trading strategies, but they're just advice - it's all "do x, don't do y," with no explanation of *how* to do x or avoid doing y.

por Lloyd P

11 de mai de 2021

Too general to pursue any meaningful work with RL for trading. The class is trying to cover too much material from too many different angles to be useful.

por Nitin K

10 de nov de 2020

Highly limited information with extremely steep learning curve.