Reinforcement Learning for Trading Strategies

Colleagues, in the Reinforcement Learning for Trading Strategies program you will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy. 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). Acquire high-demand skills in Reinforcement Learning Model Development, Trading Algorithm Optimization, Trading Strategy Development and Trading Algorithm Development. Skill-based training modules address: 1) Introduction to Course and Reinforcement Learning - history and evolution of reinforcement learning is presented, including key concepts like value and policy iteration. Also, the benefits and examples of using reinforcement learning in trading strategies are described. We also introduce LSTM and AutoML as additional tools in your toolkit to use in implementing trading strategies, 2) Neural Network Based Reinforcement Learning - look at how reinforcement learning has been integrated with neural networks. We also look at LSTMs and how they can be applied to time series data, and 3) Portfolio Optimization - practical steps required to create a reinforcement learning trading system. Also, we introduce AutoML, a powerful service on Google Cloud Platform for training machine learning models with minimal coding.

Enroll today (individuals & teams welcome): https://tinyurl.com/44cf8rm2 

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