Financial Engineering and Artificial Intelligence in Python

Financial Analysis, Time Series Analysis, Portfolio Optimization, CAPM, Algorithmic Trading, Q-Learning, and MORE!







What you'll learn:







Forecasting stock prices and stock returns







Time series analysis







Holt-Winters exponential smoothing model







ARIMA







Efficient Market Hypothesis







Random Walk Hypothesis







Exploratory data analysis







Alpha and Beta







Distributions and correlations of stock returns







Modern portfolio theory







Mean-Variance Optimization







Efficient frontier, Sharpe ratio, Tangency portfolio







CAPM (Capital Asset Pricing Model)







Q-Learning for Algorithmic Trading















Requirements







Decent Python coding skills







Numpy, Matplotlib, Pandas, and Scipy (I teach this for free! My gift to the community)







Matrix arithmetic







Probability















Description







Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering?















Today, you can stop imagining, and start doing.















This course will teach you the core fundamentals of financial engineering, with a machine learning twist.















We will cover must-know topics in financial engineering, such as:















Exploratory data analysis, significance testing, correlations, alpha and beta















Time series analysis, simple moving average, exponentially-weighted moving average















Holt-Winters exponential smoothing model















ARIMA and SARIMA















Efficient Market Hypothesis















Random Walk Hypothesis















Time series forecasting ("stock price prediction")















Modern portfolio theory















Efficient frontier / Markowitz bullet















Mean-variance optimization















Maximizing the Sharpe ratio















Convex optimization with Linear Programming and Quadratic Programming















Capital Asset Pricing Model (CAPM)















Algorithmic trading (VIP only)















Statistical Factor Models (VIP only)















Regime Detection with Hidden Markov Models (VIP only)















In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as:















Regression models















Classification models















Unsupervised learning















Reinforcement learning and Q-learning















***VIP-only sections (get it while it lasts!) ***















Algorithmic trading (trend-following, machine learning, and Q-learning-based strategies)















Statistical factor models















Regime detection and modeling volatility clustering with HMMs















We will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense. It is a lesson in how not to apply AI in finance.















As the author of ~30 courses in machine learning, deep learning, data science, and artificial intelligence, I couldn't help but wander into the vast and complex world of financial engineering.















This course is for anyone who loves finance or artificial intelligence, and especially if you love both!















Whether you are a student, a professional, or someone who wants to advance their career - this course is for you.















Thanks for reading, I will see you in class!















Suggested Prerequisites:















Matrix arithmetic















Probability















Decent Python coding skills















Numpy, Matplotlib, Scipy, and Pandas (I teach this for free, no excuses!)















Who this course is for







Anyone who loves or wants to learn about financial engineering







Students and professionals who want to advance their career in finance or artificial intelligence and machine learning