QUANTITATIVE MODELS IN PORTFOLIO MANAGEMENT

Abstract

This project consists of six chapters. Chapter 1 is a brief introduction to the investment process. Discussions are given to the main steps in this process and quantitative tools’ role in improving portfolio performance. Chapter 2 and Chapter 3 cover two main financial optimization models in detail. In chapter 2, we commence with an introduction of standard mean variance model and CAPM (Capital Asset Pricing Model), which are the foundation of modern portfolio theory. Then some extensions of standard mean variance models are discussed, which cover the mean absolute-deviation model, downside risk model and mean-variance model in a surplus framework. The expected utility model with mean variance model as a special case is derived in Chapter 3. In the next three chapters, we concentrate on the application of financial optimization models in asset allocation, equity portfolio management and fixed-income portfolio management. We explore asset allocation in Chapter 1. By using US economy data, we observe how main asset classes performed in the last several decade and construct a mean-variance efficient portfolio. In chapter 5, we propose a disciplined stock selection process. Emphasis is put on how to use statistical tools to generate good predictions about input of mean-variance model i.e. expected returns, standard deviation and correlation matrix. Finally, in Chapter 6, we discuss the traditional strategies in fixed-income portfolio management immunization and cash-matching in the beginning. In order to overcome the weak points of these two methods, stochastic programming methods are applied to generate better results.