Financial Engineering and Artificial Intelligence in Python

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 betaTime series analysis, simple moving average, exponentially-weighted moving averageHolt-Winters exponential smoothing modelARIMA and SARIMAEfficient Market HypothesisRandom Walk HypothesisTime series forecasting ("stock price prediction")Modern portfolio theoryEfficient frontier / Markowitz bulletMean-variance optimizationMaximizing the Sharpe ratioConvex optimization with Linear Programming and Quadratic ProgrammingCapital 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 modelsClassification modelsUnsupervised learningReinforcement 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 modelsRegime detection and mode