SAS for Monte Carlo Studies
A Guide for Quantitative Researchers
Authors: Xitao Fan, Akos Felsovalyi, Stephen A. Sivo, Sean C. Keenan
Publisher: SAS Publishing
For statisticians, a book covering the theory and practice of Monte Carlo (stochastic) simulation in the SAS environment. Covers generating random data, coding a simulation model (with many classic examples), and analyzing results.
Many of the examples and techniques use SAS/STAT. One chapter uses SAS/ETS.
Editions
Paperback (2002)
Paperback
Year: 2002
ISBN: 1-59047-141-5
Pages: 251
Publisher’s list price: 50.95
Contents
- 1. Introduction
- 2. Basic Procedures for Monte Carlo Simulation
- 3. Generating Univariate Random Numbers in SAS
- 4. Generating Data in Monte Carlo Studies
- 5. Automating Monte Carlo Simulations
- 6. Conducting Monte Carlo Studies That Involve Univariate Statistical Techniques
- 7. Conducting Monte Carlo Studies for Multivariate Techniques
- 8. Examples for Monte Carlo Simulation in Finance: Estimating Default Risk and Value-at-Risk
- 9. Modeling Time Series Processes with SAS/ETS Software
From the back cover
With the advance in computing technology, Monte Carlo simulation research has become increasingly popular among quantitative researchers in a variety of disciplines. More and more, statistical methods are being subjected to rigorous empirical scrutiny in the form of statistical simulation so that their limitations and strengths can be understood. With the combination of powerful built-in statistical procedures and versatile programming capabilities, the SAS System is ideal for conducting Monte Carlo simulation research!
