This folder is a comprehensive coursework that delves into various methodologies and models used in financial analysis and portfolio optimization. It covers:
- Regression Methods: This section includes topics like processing stock price data in Python, advantages of log returns, ARMA vs. ARIMA models, and Vector Autoregressive (VAR) models.
- Bond Pricing: It discusses examples of bond pricing, forward rates, and the duration of coupon-bearing bonds. It also explores the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT).
- Portfolio Optimization: This includes adaptive minimum-variance portfolio optimization and the determination of optimal weights.
- Robust Statistics and Non-Linear Methods: This section focuses on data import, exploratory data analysis, robust estimators, and robust trading strategies.
- Graphs in Finance: It covers stock selection, correlation and graphs, and dynamic time warping metric comparison.
The coursework is technical and detailed, aiming at providing an in-depth understanding of these financial concepts and their applications using statistical and machine learning methods.