Data-Driven Portfolio Optimization

HKUST ELEC3180 - Homework and Midterm Exam Solutions

Disclaimer: The solutions presented here are not guaranteed to be 100% accurate. They have been refined based on student submissions and used the TAs' solutions as a reference. To preserve the educational purpose of the assignments, full solutions are not disclosed.

Content Overview

1. Homework 1

   • Portfolio Optimization and Risk-Return Tradeoff Analysis using Modern Portfolio Theory

2. Homework 2

   • Factor Model Analysis and Optimization for Stock Returns
   • Portfolio Optimization and Sharpe Ratio Analysis Using Shrinkage Estimators

3. Midterm Exam

   • Risk Parity Portfolio: Asset Allocation and Convex Optimization Analysis
   • Hierarchical Risk Parity: Portfolio Optimization through Clustering, Quasi-Diagonalization, and Recursive Bisection
   • Multi-Factor Models in Walk-Forward Process: Comparative Analysis of Risk Parity, Hierarchical Risk Parity, and Global Minimum Variance Portfolios

4. Homework 3

   • Comparative Analysis of Gradient Descent, Newton’s Method, and Conjugate Gradient Algorithms for Quadratic Minimization
   • Comparative Analysis of Jacobi and Majorization Minimization Algorithms for Convex Optimization

Note on Complexity and Difficulty

The materials are presented in the chronological order of their occurrence: Homework 1, Homework 2, Midterm Exam, and Homework 3, signifying an ascending trend in complexity and difficulty.