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SAS for Monte Carlo Studies: A Guide for Quantitative Researchers

About the Book

book cover SAS for Monte Carlo Studies: A Guide for Quantitative Researchers
By: Xitao Fan, Akos Felsovalyi, Stephen A. Sivo, and Sean C. Keenan
ISBN: 978-1-59047-141-8
Pages: 264


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With the advance of 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!

SAS for Monte Carlo Studies: A Guide for Quantitative Researchers provides a detailed and practical guide for conducting Monte Carlo studies using the SAS System. Quantitative researchers will find this book attractive for its practicality and for its many hands-on application examples of Monte Carlo research.

Topics addressed in this book include:

  • basic procedures for Monte Carlo simulation
  • generating univariate random numbers in SAS
  • generating data in Monte Carlo studies
  • automating Monte Carlo simulations
  • conducting Monte Carlo studies that involve univariate statistical techniques
  • conducting Monte Carlo studies for multivariate techniques
  • examples for Monte Carlo simulation in finance: estimating default risk and Value-at-Risk (VaR)
  • modeling time series processes with SAS/ETS software.

About the Authors

author photo Xitao Fan is an Associate Professor at the Curry School of Education, University of Virginia. He specializes in educational/psychological measurement and quantitative research methods in social and behavioral sciences. He has been a SAS user for more than ten years and has used SAS in his Monte Carlo simulation studies on many occasions. author picture Ákos Felsovályi, M.S., is a vice president of Risk Architecture at Citigroup. He has been an avid SAS user since 1982, using the SAS System in direct marketing research and currently in Risk Management, where he applies Monte Carlo simulation to various projects.

author photo Stephen A. Sivo, Ph.D., is a Research Psychologist and an Assistant Professor of Educational Research at the University of Central Florida. He received his Ph.D. in Research, Measurement, and Statistics from the Educational Psychology department at Texas A & M University. The primary focus of his research has centered on the use of structural equation modeling to fit time series models to longitudinal data. He has used SAS software since 1991. author picture Sean C. Keenan, Ph.D., is currently a Vice President in Citigroup's Risk Architecture Group, where he is involved in the development of quantitative tools and methodologies for assessing credit risk for obligors and pools of obligors, as well as for a variety of credit and structured credit portfolios. His research involves a wide range of Monte Carlo applications, often with large data sets, and SAS is his preferred tool for handling these tasks. Sean holds a Ph.D. in Economics from New York University.