Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics

Chapter Three

Stochastic Modeling in Finance and Economics

This chapter is included for the sake of readers who are not familiar with econometrics and the modeling techniques that are commonly used in finance and financial economics. Needless to say, the following treatment is not meant as a substitute of one of the several excellent books on the subject. Our limited aims are:

1. To offer a concise introduction for readers with a background, e.g., in mathematics or engineering.

2. To provide readers with a short refresher, and possibly an introduction to some specific topics with which they might be not quite familiar.

3. At the very least, we use the subject of this chapter as an excuse to introduce some useful R functions to deal with probability distributions and some multivariate analysis methods.

Here we only deal with modeling; issues related to estimation are deferred to Chapter 4, which has similar objectives and limitations. In modeling, one typically works with parameters, expected values, variances, etc. In estimation, one typically works with their sample counterparts, like sample mean and sample variance. However, since it is often useful to illustrate ideas by simple but concrete examples, we will occasionally use sample counterparts of probabilistic concepts. In doing so, we will rely on readers’ intuition and, possibly, some background in elementary inferential statistics, as well as the availability of easy to use R functions; more advanced concepts and issues ...