Using Machine Learning in Trading and Finance
About this course
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).
83/100
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- What the provider tells you
- 32/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
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What you'll learn
- design basic quantitative trading strategies
- build machine learning models with Keras and TensorFlow
- develop a pairs trading strategy and backtest it
- create and backtest a momentum-based trading model
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