Using Machine Learning in Trading and Finance (NYIF)

Colleagues, the Using Machine Learning in Trading and Finance developed by the New York Institute of Finance and Google introduces you to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. 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. 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). The four skill-based training modules cover: 1) Introduction to Quantitative Trading and TensorFlow - key components that are common to every trading strategy, no matter how complex. This foundation will help guide you as you develop more advanced strategies using machine learning techniques, 2) Introduction to TensorFlow - training neural networks with Tensorflow 2 and Keras, 3) Build a Momentum-based Trading System - momentum trading is a strategy in which traders buy or sell assets according to the strength of recent price trends, and 4) Build a Pair Trading Strategy Prediction Model - discuss what pairs trading is, and how you can make money doing it, and what you need to know about the members to form a suitable pair.

Enroll today (individuals & teams welcome): https://tinyurl.com/yfe4yncz 

Much career success, Lawrence E. Wilson - Financial Certification Academy