\( \newcommand{\bm}[1]{\boldsymbol{#1}} \newcommand{\textm}[1]{\textsf{#1}} \newcommand{\textnormal}[1]{\textsf{#1}} \def\T{{\mkern-2mu\raise-1mu\mathsf{T}}} \newcommand{\R}{\mathbb{R}} % real numbers \newcommand{\E}{{\rm I\kern-.2em E}} \newcommand{\w}{\bm{w}} % bold w \newcommand{\bmu}{\bm{\mu}} % bold mu \newcommand{\bSigma}{\bm{\Sigma}} % bold mu \newcommand{\bigO}{O} %\mathcal{O} \renewcommand{\d}[1]{\operatorname{d}\!{#1}} \)

Chapter 6 Portfolio Basics

“It is not the man who has too little, but the man who craves more, that is poor.”

— Seneca

In this chapter, we introduce fundamental concepts related to portfolios, including the definition of portfolio weights and the notion of rebalancing. We also discuss common portfolio constraints and performance metrics, as well as a selection of prevalent heuristic and risk-based portfolios employed by practitioners. Examples of these portfolios include the equal-weighted \(1/N\) portfolio, the quintile portfolio, and the global minimum variance portfolio.

This material will be published by Cambridge University Press as Portfolio Optimization: Theory and Application by Daniel P. Palomar. This pre-publication version is free to view and download for personal use only; not for re-distribution, re-sale, or use in derivative works. © Daniel P. Palomar 2025.