Preface (GARCH Toolbox)

GARCH Toolbox

Using This Guide

Organization of the Document

Tutorial provides a brief overview of GARCH, then demonstrates the use of the GARCH Toolbox by estimating GARCH model parameters, and performing pre- and post-estimation analysis. Chapter 1 continues with discussions of simulation, forecasting, and regression, as well as model selection and analysis.

Function Reference describes the individual functions that comprise the GARCH Toolbox. The description of each function includes a synopsis of the function syntax, as well as a complete explanation of its arguments and operation. It may also include examples and references to additional reading material.

Glossary defines terms associated with modeling the volatility of economic time series.

Bibliography lists published materials that support concepts implemented in the GARCH Toolbox.

Expected Background

This guide is a practical introduction to the GARCH Toolbox. In general, it assumes you are familiar with the basic concepts of General Autoregressive Conditional Heteroskedasticity (GARCH) modeling.

In designing the GARCH Toolbox and this manual, we assume your title is similar to one of these:

Analyst, quantitative analyst
Risk manager
Portfolio manager
Fund manager, asset manager
Economist
Financial engineer
Trader
Student, professor, or other academic

We also assume your background, education, training, and responsibilities match some aspects of this profile:

Finance, economics, perhaps accounting
Engineering, mathematics, physics, other quantitative sciences
Bachelor's degree minimum; MS or MBA likely; Ph.D. perhaps; CFA
Comfortable with probability, statistics, and algebra
May understand linear or matrix algebra, calculus, and differential equations
Previously doing traditional programming (C, Fortran, etc.)
May be responsible for instruments or analyses involving large sums of money
Perhaps new to MATLAB