Notes and exercises for Machine Learning for Trading Specialization Offered by Google Cloud and New York Institute of Finance on Coursera.
This Specialization is for finance professionals, including but not limited to: hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies.
The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create long-term trading strategies, short-term trading strategies, and hedging strategies.
I take this course during my internship as an data analyst at Asset Pro to:
- Equip myself with knowledge about quantitative trading strategies and application of ML to trading.
- Explore career interests and development opportunities in financial engineering.
To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. 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).
You may refer to the first course of another specialization offered by Rice University to get familiar with these financial terminologies. I have also uploaded my own notes and study materials for this course. You can find them here.
Specialization link: https://www.coursera.org/specializations/machine-learning-trading
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