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New York Institute of Finance

Using Machine Learning in Trading and Finance

This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. 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).

Status: Financial Trading
Status: Technical Analysis
IntermediateCourse8 hours

Featured reviews

GC

5.0Reviewed Apr 9, 2020

Very Good! Basic strategies explored in depth and applied in coding labs.

NA

5.0Reviewed Jan 1, 2022

Such a great course, the introduction(first part in specialization) was kinda useless for me, but this one is amazing.

DR

4.0Reviewed Apr 18, 2020

Useful for people who have previous knowledge of coding and trading basics. I get a lot of ideas from this course. I will recommend.

SP

5.0Reviewed Jan 2, 2025

Great introduction to time series analysis of stockprices and how to use statistics to determine market entrance and exit.

ML

5.0Reviewed Jul 13, 2021

Great course for the trading, clear structure and easy to understand.

AP

4.0Reviewed Jul 6, 2021

It's not deep enough to understand how to implement ML in algorithmic trading, but the course explains some helpful concepts like pairs trading and Kalmar filter.

EF

4.0Reviewed Feb 27, 2020

Very interesting insights and new tools learned to improve trading algos and make smarter quantitative strategies

PL

5.0Reviewed Feb 28, 2020

The course is inspiring. It gave me another perspective of learning trading not just for Machine Learning also for day to day trading algorithm.

SG

4.0Reviewed May 23, 2020

I wish better examples to cover everything was said during the lectures

RS

4.0Reviewed Jul 10, 2021

The concepts and algorithms are great. Unfortunately, the last 4 Jupyter Notebooks of the course did not work !!!!!

LT

5.0Reviewed Feb 8, 2020

Very interesting course with integrated notebooks to learn concepts of how to apply machine learning to trading and finance

GY

4.0Reviewed Jun 27, 2022

Although the often glitches in the Google Cloud platform prevented me to complete the exercises, the course material is very useful.

All reviews

Showing: 20 of 116

Saulo D. S. Reis
1.0
Reviewed Jan 14, 2020
Jiaheng Zhou
1.0
Reviewed Jan 17, 2020
Loo Ting Tan
2.0
Reviewed Mar 26, 2020
Dewald Olivier
2.0
Reviewed Feb 13, 2020
Peixi Zhao (Percy)
1.0
Reviewed Jan 18, 2020
Esteban Zuluaga
2.0
Reviewed May 25, 2020
John Nganda
2.0
Reviewed Feb 3, 2020
Samuel Thompson
5.0
Reviewed Jan 17, 2020
Marcos Fadul
4.0
Reviewed Jan 20, 2020
Rodney Fuller
5.0
Reviewed Feb 2, 2020
betty yuan
5.0
Reviewed Dec 17, 2020
Lina Ta
5.0
Reviewed Feb 9, 2020
dick lau
5.0
Reviewed Jan 19, 2020
ThemisZ
4.0
Reviewed Feb 4, 2020
Nissims s
4.0
Reviewed Jan 27, 2020
Colin Edwards
4.0
Reviewed Feb 11, 2020
Dennis Tabuena
4.0
Reviewed Jan 21, 2020
Kumar Saurav
4.0
Reviewed Feb 8, 2020
Manfred Rupp
4.0
Reviewed Mar 8, 2020
DeWitt Gibson
5.0
Reviewed May 18, 2020