Financial Modeling with Crystal Ball and Excel, 2nd Edition
Book PrefaceFinancial Modeling with Crystal Ball and Excel, 2nd Edition
I wrote this book to help statisticians, financial analysts, and other interested parties learn how to build and interpret the results of Crystal Ball R models for decision support. There are several books that exist to inform readers about Monte Carlo simulation in general. Many of these general books are listed in the References section of this book. This book focuses on using Crystal Ball in three main areas: corporate finance, investments, and derivatives. It also contains a chapter on using Crystal Ball in project management.
In 1982, University of Minnesota—Duluth Business School professor Henry Person introduced me to IFPS, computer software designed for financial planning, which we ran on VAX mainframe computers for an MBA class in quantitative methods. IFPS used a tabular layout for financial data similar to that used today by Excel. However, it was more abstract than Excel’s layout because one had to print the data to see the layout in IFPS instead of working with Excel’s tabular display of the data on the screen. Gray (1996) describes what is evidently the latest, and perhaps final, version of this financial planning software. It is significant to me because IFPS included a Monte Carlo command that gave me my first glimpse of using a computer as a financial risk analytic tool.
I was hooked. The next term, I took Henry’s class in discrete-event simulation based on Tom Schriber’s (1974) red GPSS textbook. I found the notion of discrete-event simulation fascinating. It made experimentation possible in a computer lab on models of real-world situations, just as the physical scale models of dams in the University of Minnesota—Twin Cities hydraulic laboratory made experimentation possible for the civil engineering researchers during my days as an undergraduate student there. I saw many places where systems simulation could have been applied to the construction industry when I worked as a field engineer, but was unaware at the time of what simulation could accomplish.
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