A study of business game stock price algorithms

A number of studies have examined the algorithms that business games use to simulate real-world company functions. This study extends that research tradition into the area of the firm's stock price algorithm while increasing the range of validates considered. An investigation of the stock price algorithms associated with six computer-based management games revealed diversity in the number and treatment of the variables used to create company stock prices. This diversity created radically different firm stock prices. These valuations also differed under simulation firm conditions of economic growth and decline. Most stock price results would meet a face validity test under conditions of improving firm performance, but most would be challenged under conditions of company decline.

[1]  Irrational Exuberance.  Irrational exuberance? , 2006, Nature Biotechnology.

[2]  Hugh M. Cannon,et al.  Constructs of Simulation Evaluation , 2002 .

[3]  Pablo Fernandez,et al.  Valuation Methods and Shareholder Value Creation , 2002 .

[4]  Precha Thavikulwat,et al.  Model for Currency Exchange Rates and Its Validation , 2002 .

[5]  S. Rubenfeld,et al.  Developments in Business Simulation & Experiential Exercises , 2002 .

[6]  Steven C. Gold,et al.  Historical Review of Algorithm Development for Computerized Business Simulations , 2001 .

[7]  James R. English.  Applied Equity Analysis: Stock Valuation Techniques for Wall Street Professionals , 2001 .

[8]  Patrick Cusatis,et al.  Streetsmart Guide to Valuing A Stock: The Savvy Investor's Key to Beating the Market , 1999 .

[9]  Ann L. Brown,et al.  How people learn: Brain, mind, experience, and school. , 1999 .

[10]  Steven C. Gold,et al.  Modeling Attributes in Demand Functions of Computerized Business Simulations: An Extension of Teach’s Gravity Flow Algorithm , 1997 .

[11]  A. Damodaran.  Investment Valuation: Tools and Techniques for Determining the Value of Any Asset , 1995 .

[12]  Hugh M. Cannon.  Dealing With the Complexity Paradox in Business Simulation Games , 1995 .

[13]  B. Bower.  A Child's Theory of Mind , 1993 .

[14]  Precha Thavikulwat.  Product Quality In Business Simulations , 1992 .

[15]  Steven Gold.  Modeling Cost Functions in Computerized Business Simulation: An Application of Duality Theory and Sheppard’s Lemma , 1990 .

[16]  C. Prahalad,et al.  To revitalize corporate performance, we need a whole new model of strategy. Strategic intent. , 1989, Harvard business review.

[17]  Precha Thavikulwat.  Modeling the Human Component of Computerized Business Simulations , 1989 .

[18]  Stephen M. Alessi,et al.  Fidelity in the design of instructional simulations , 1988 .

[19]  Steven C. Gold,et al.  Modeling Non-Price Factors in the Demand Functions of Computerized Business Simulations , 1984 .

[20]  Richard D. Teach.  Using Spatial Relationships to Estimate Demand in Business Simulations , 1984 .

[21]  Steven C. Gold,et al.  Inside the Black Box: An Analysis of Underlying Demand Functions in Contemporary Business Simulations , 1982 .

[22]  Kenneth R. Goosen.  A Generalized Algorithm for Designing and Developing Business Simulations , 1981 .

[23]  Elizabeth L Martin,et al.  Contributions of Platform Motion to Simulator Training Effectiveness: Study 1 - Basic Contact , 1978 .

[24]  R. C. Henshaw,et al.  The executive game , 1978 .

[25]  B. Malkiel.  A Random Walk Down Wall Street , 1973 .

[26]  J.J.S.B. Hall.  Model building for management , 1969 .

[27]  F. Modigliani,et al.  DIVIDEND POLICY, GROWTH, AND THE VALUATION OF SHARES , 1961 .

[28]  Franc M. Ricciardi,et al.  Top management decision simulation : the AMA approach , 1957 .

[29]  R. Gagn.  Training devices and simulators: some research issues. , 1954 .