Jack Farmer
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: – Design basic quantitative trading strategies – Use Keras and Tensorflow to build machine learning models – Build a pair trading strategy prediction model and back test it – Build a momentum–based trading model and back test it 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). The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders …
Instructor Details
Courses : 3
Specification: Using Machine Learning in Trading and Finance
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37 reviews for Using Machine Learning in Trading and Finance
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 13 hours |
| Year | 2020 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Saulo D S e R –
You will learn concepts of trading and machine learning. But you will not implement strategies to learn how to transpose concepts between trading and ML. You’ll be given ready codes, that barely uses what is thought in courses. In fact, the grading exercise for week three doesn’t use in a clear way the concepts presented, and to be solved you’ll need a new concept presented at the notebook. Do not waste you money in it.
Saulo D S e R –
You will learn concepts of trading and machine learning. But you will not implement strategies to learn how to transpose concepts between trading and ML. You’ll be given ready codes, that barely uses what is thought in courses. In fact, the grading exercise for week three doesn’t use in a clear way the concepts presented, and to be solved you’ll need a new concept presented at the notebook. Do not waste you money in it.
Jiaheng Z –
Hardly learned anything from this course, many lectures are not informative, fulfilled with wordy guidance and coding labs are not actually telling about any insights, just show me the codes… Worst and most time wasting courses after taking 13 courses here.
Esteban Z –
One could basically get a very high grade just copying, pasting and clicking SHIFT + ENTER
Jiaheng Z –
Hardly learned anything from this course, many lectures are not informative, fulfilled with wordy guidance and coding labs are not actually telling about any insights, just show me the codes… Worst and most time wasting courses after taking 13 courses here.
Esteban Z –
One could basically get a very high grade just copying, pasting and clicking SHIFT + ENTER
Samuel T –
Great crouse, with very focused material.
Samuel T –
Great crouse, with very focused material.
Chien–Fu L –
really good course to capture most ideas in machine trading
Peixi Z –
The contents are not organized at all the lab work has occasional bugs that are clearly due to oversight. Most importantly, the labs are not very closely related to the lectures. I would not recommend doing this series.
Chien Fu L –
really good course to capture most ideas in machine trading
Chien Fu L –
really good course to capture most ideas in machine trading
Peixi Z –
The contents are not organized at all the lab work has occasional bugs that are clearly due to oversight. Most importantly, the labs are not very closely related to the lectures. I would not recommend doing this series.
Marcos F –
Very informative. I does not go too much in details but you get a lot of insight about trading and using ML in trading strategies
Marcos F –
Very informative. I does not go too much in details but you get a lot of insight about trading and using ML in trading strategies
Dennis T –
Lots of material in a very short time, especially on momentum trading.
Dennis T –
Lots of material in a very short time, especially on momentum trading.
Nissim –
I enjoyed the course. Well organized, Good topics. I miss more projects, higher challenge in the projects. (more TODO) There was no practice of Kalman filters. links on the slides are not accessible : (
Nissim –
I enjoyed the course. Well organized, Good topics. I miss more projects, higher challenge in the projects. (more TODO) There was no practice of Kalman filters. links on the slides are not accessible : (
Manfred R –
very informative!!!!
John N –
Good introduction to trading concepts, but the quality of the labs is poor. Week 3 was the worst where the labs feel disconnected from the lessons.
Rodney F –
A lot of great examples. Thanks for the introduction and access to all of the Auquan tutorials. This class’s major feature is that it introduces to the wealth of information available and points the way to study more.
John N –
Good introduction to trading concepts, but the quality of the labs is poor. Week 3 was the worst where the labs feel disconnected from the lessons.
Rodney F –
A lot of great examples. Thanks for the introduction and access to all of the Auquan tutorials. This class’s major feature is that it introduces to the wealth of information available and points the way to study more.
ThemisZ –
The lectures and labs were very good, thanks to all the Google and NYI of Finance folks who worked on them 1 star for not making ppt/pdf notes available (or did I miss the links???) , I think most of us want to learn AND then come back for refreshers/reference in future. Wouldnt want to go through all the video lectures all the time, its time wasting
ThemisZ –
The lectures and labs were very good, thanks to all the Google and NYI of Finance folks who worked on them 1 star for not making ppt/pdf notes available (or did I miss the links???) , I think most of us want to learn AND then come back for refreshers/reference in future. Wouldnt want to go through all the video lectures all the time, its time wasting
KUMAR S –
Video lectures were good. Expected better material for lab
KUMAR S –
Video lectures were good. Expected better material for lab
Alexey L –
A lot of useful information but theory practice are quite disjoint. Code examples in the last video in section 2 along with non clickable links are disappointing. In general the course is OK but could be done much better.
Lina T –
Very interesting course with integrated notebooks to learn concepts of how to apply machine learning to trading and finance
Alexey L –
A lot of useful information but theory practice are quite disjoint. Code examples in the last video in section 2 along with non clickable links are disappointing. In general the course is OK but could be done much better.
Lina T –
Very interesting course with integrated notebooks to learn concepts of how to apply machine learning to trading and finance
Colin E –
The material is immediately useful and highly practical for people already in financial services.
Dewald O –
The course content for financial terms and explanation behind them and strategies are fine. When it comes to the grading tools these are FAR below par. Zero explanation on what the code means and zero implementation of the actual strategies discussed during the course content. The videos explaining the grading tools are also about 5 years old and have been recycled.
Naren T –
The audio for every lecture is horrible. Especially the coding solution lectures. The lab assignments are not engaging and poorly executed. A very disappointing course
Loo T T –
The content is fine, but the lab does not demonstrate any of the concepts in the lectures. E.g. in pairs trading they talked about hierarchical clustering and PCA but both of these were not discussed at all in the lab. First module talked about Tensorflow Estimator API, but does not show how they are applied in subsequent modules. They just don’t flow together as a course at all. At some point, it seems to be videos taken from different places to form a course. This collaboration was not well planned at all. The course should also be accompanied with more detailed readings. 2 labs in pairs trading and momentum trading are taken directly from Auquan. They would be better off just reading directly from Auquan instead of paying for this course.
Henry M –
Feels very rushed.