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In this course, you will 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
Syllabus :
- Financial Basics
- Time Series Analysis
- Portfolio Optimization and CAPM
- VIP: Algorithmic Trading
- VIP: The Basics of Reinforcement Learning
- VIP: Reinforcement Learning for Algorithmic Trading
- VIP: Statistical Factor Models and Unsupervised Machine Learning
- VIP: Regime Detection and Sequence Modeling with Hidden Markov Models
- Course Summary and Common Questions
- Extras
- Setting Up Your Environment FAQ
- Extra Help With Python Coding for Beginners FAQ
- Effective Learning Strategies for Machine Learning FAQ
