COM-GAME: A COMMODITY TRADING GAME FOR USE IN AN INTRODUCTORY BUSINESS STATISTICS COURSE New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 239 COM-GAME: A COMMODITY TRADING GAME FOR USE IN AN INTRODUCTORY BUSINESS STATISTICS COURSE William Roach School of Business University of Kansas There are two major objections to the use of any business game: 1) the absence of any clear identification of the objectives of the game with the objectives of the course using the game [1, p. 399], and 2) the high cost of game playing in terms of instructional resources (contact hours and preparation hours) which might be put to alternative and perhaps more productive use. This paper will demonstrate that adequate consideration has been given to both of these problems in the design of COM-GAME. Educational Objectives Rather than enumerating all of the objectives of an introductory course in business statistics that might be served by a commodity trading game, this paper will consider only a few such objectives and try to go into these objectives in sufficient depth to illustrate game-related class exercises to achieve these objectives. The topics considered include: 1) dispersion, 2) covariance/ correlation, and 3) the expected value decision criteria. 1. The application of dispersion or variance can be illustrated by comparing the margin requirements of various commodities to their trading range in the current contract year. The margin requirements are usually 1/8 to 1/5 of the value of the anticipated trading range. For example, current margin requirements for soybeans are $3,000. The value of the trading range is 5000 bushels x (7.80 - 4.80) = $15,000. Thus the margin is 1/5 of the trading range. A margin call is given when about 1/4 of the margin is used up; this corresponds to about 1/32 to 1/20 of the value of the annual trading range. Unusually volatile commodities, like soybeans or pork bellies, will provide a useful New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 240 illustration of data where the tail areas are larger than the normal tail areas, but smaller than Chebyshev areas. The life of contract trading range for these commodities will normally be more than 6 standard deviations. 2. Covariance/correlation is difficult for many students to master. Illustration of this concept via application in spreads/straddles might prove useful. For example, soybean contracts have an initial margin requirement of $3,000 while soybean spreads within the same contract year, have only a $250 margin requirement. If 3000 = k σ where σ is the standard deviation of the value of a single soybean contract then for a soybean spread 250 = k √2 σ (1 - ρ)1/2 Dividing one equation by the other and solving for p, gives an assumed p = .996. On the face of it, this value seems unrealistically high. A speculator with 12 soybean spreads is facing a much greater risk than the person with a single long or short position. This conclusion is confirmed by the advice given in broker advisory publications [3, pp. 12-13]. 3. The expected value decision criteria can be illustrated in the methodologies of some successful commodity traders. The conventional wisdom in commodity trading is that the market is efficient and that the well prepared trader should expect to make money on a trade only 50% of the time; therefore, a trader should enter a position only if the profit potential is twice the loss potential. If a is the amount of the potential loss and 2a is the amount of the potential gain, then the simple triangular distribution below is an appropriate model of the speculators evaluation of the situation. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 241 The expected profit on the transaction is 1/9a. Is this an adequate return? It depends on how much money was invested and for how long. If the speculator observes the conventional wisdom and never meets a margin call, then the maximum loss is that which would precipitate a margin call, the initial margin is usually about 4 times that amount or 4a. Thus the expected return is l/9a on an investment of 4a. If the speculator anticipates leaving the transaction open for a full calendar year, this represents a return of only The return is computed for values of n from 12 to 1/4 New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 242 This evaluation suggests that many trades which appear attractive from an initial technical analysis may not offer any real profit potential. The example that comes to mind is as crush or reverse crush spread between soybeans, soybean oil, and soybean meal where the future involved is relatively distant. While such a trade might meet the criteria for the ratio of possible gain to possible loss, the movement of the crush margin to a more normal level is likely to take place only as that future becomes a rear term future. That is the anticipated n is certainly more than 6. Hence, such a trade does not offer a really attractive investment. Another possible conclusion from this evaluation is that it is realistic for only the smallest commodity trader. A larger trader, who has several trades going at any given time, will normally have the profit from one trade to offset against another losing trade. Thus the larger trader can analyze trades losses using a larger figure for the acceptable loss level. As a result, his expected return will be larger. Assume the large trader will accept a loss twice as large as that which the small trader considers acceptable. a = maximum allowable loss 1/9 a = expected return Because of the higher acceptable loss the initial margin is only two times the acceptable loss (2a). Assuming the average investment is equal to the initial investment gives a return of The expected returns for the trader who can handle larger losses are twice those available to the small trader. Note the larger trader must find a trade with a correspondingly larger potential return. This coincides with the conventional wisdom and the promotional literature of commodity brokers. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 243 Other instructional objectives which the game might serve might be: a) extensions of 3) involving other statistical distributions, b) Markov chain/random walk analysis of the movement of commodity prices, c) using ruin theory to select the size of the largest acceptable loss, and d) the sampling methodologies used by the Department of Agriculture to make crop estimates. Because of space limitations, no further instructional objectives will be discussed here. Instead the paper will move on to discuss the resource requirements of CON- GAME. Instructional Resources Required For Game Use COM-GAME has been designed to minimize the instructional resources required for use of the game in a class. The facets of the game which effect the resource requirements are: 1. The role of the administrator in COM-GAME is rather modest. A student manual has been written to assist the administrator in briefing students prior to playing the game. The student manual describes the terminology and mechanics of commodity trading and it provides sufficient background to allow students to follow the commodity column in the WSJ and the various broker advisory letters. During the play of the game, the administrator is not responsible for scoring the game. Scoring is the responsibility of the individual student; it involves the daily evaluation of the student’s trading account. The students’ manual includes a simplified explanation of brokerage accounting and several numerical examples of scoring (see Appendix) so that the administrator does not have to play an active role in this aspect of the game. The administrator, however, is required to maintain a daily log of commodity price quotes, from the WSJ, and a daily log of commodity trades New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 244 submitted by students. At the end of the game the administrator must verify the scoring of only the apparent winners. 2. Homework and classroom exercises, related to the game and the learning objectives of the initial business statistics course, have been partially outlined above. A more complete compilation of such exercises will be included in the game administrators manual. Clearly this aspect of the game is in need of further development. However, enough has been done to verify that COM-GAME can be meaningfully tied to the educational objectives of the business statistics course. Summary and Conclusions Much of the current research on business games [2, pp. 124-129] suggest that an effusive endorsement of COM-GAME and the joy of business gaming is not an appropriate conclusion to this paper. However, the conclusion of this paper leaves the author believing that he has designed a game which is educationally relevant and inexpensive to administer. New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 245 New Horizons in Simulation Games and Experiential Learning, Volume 4, 1977 246 REFERENCES 1. Boseman, F. Glenn and Robert E. Schellenberger, “Business Gaming: An Empirical Appraisal,” Simulation & Games, Vol. 5, No. 4 (December 1974), pp. 383-402. 2. Neuhauser, John J., “Business Games Have Failed,” Academy of Management Review, Vol. 1, No. 4 (October 1976). 3. Schwager, Jack, A Guide To Trading Commodity Spreads (New York: Hornblower & Weeks-Hemphill, Noyes, 1975). Table of Contents Volume 4, 1977 Double Play for Gaming Effectiveness Adaptive Rule Changes in Computer Simulation Gaming Œ A Means of Pedagogical Reactive Interchange Monte Carlo Simulation in Personnel Management Training Teaching About the Implementation of Job Redesign Using Simulation and Group Discussions An Interactive Simulation of Private Sector Collective Bargaining Leadership Evaluation and training through Behavioral Simulations: Method, Results and Future An assessment of the Effect of Experiential, Simulation and Discussion Pedagologies Used in Laboratory Sections of an Introductory Management Course An Experiential Understanding of the Trust Dimension Using Consulting Cases to teach Business Policy An Experimental Testing of Teaching Methodologies in Marketing Interpersonal Skill Development: The Experiential Training Unit (ETU) and Transfer of Training An Analysis of the Relationship between Personality characteristics and Preferred Styles of Learning Analysis of Effective Communication Skill Development in Graduate Business and Engineering Experiential Education Changing Perceptions of Learning in a Simulated Environment Student Perceptions: Simulation and the Corporate Policy Course Degree of Uniformity in Achievement Motivation Levels of Team Member: Its Effect on Team Performance in a Simulation Game Channel Conflict, Cooperation and Control: an Experiential Learning Exercise Differences in Experiential and Non-Experiential Learners' Reactions to Conflict between Individual and Organizations Behavior The Evolution and Evaluation of a Required, Senior-Level Course in Experiential Business Applications Building Management Skills through Problem Solving A Live-Case Approach to the Business and Society Course Experiential Learning: Toward the Development of a Theoretical Base and the Identification of Variables and the Hypotheses to Guide Research The Role of the Administrator in Experiential Learning and Simulations Some Thoughts on a Theory of the Use of Games and Experiential Exercises Three Applications of the Management of Learning Grid An Analysis of ABSEL: Its Past Achievements and Future Prospects New Horizons in Simulation Research Prediction of Academic Achievement in a Simulation Mode via Personality Constructs Sex Differences in a Bargaining Simulation COM-GAME: A Commodity Trading Game for Use in an Introductory Business Statistics Course A Financial Institution Management Game with Direct Participant Interactions A Non-Computerized Marketing Planning and Strategy Game Delphi in the Classroom: A Demonstration of Forecasting Economic Activity The Potential of Programmable Calculators for Processing Small Business Simulations Can a Small Predominantly Clack University Incorporate the Computer Simulation Gaming Teaching Methodology into it Curriculum Measuring the Effect of an Experiential Exercise Experiential Learning - Analysis of a Partial Success Predicting Participants' Performance and Reactions in an Experiential Learning Setting: An Empirical Investigation A Simplified, Non-Computerized Marketing Channels Game Manufacturers and Retailers: A Negotiation Game for Beginning Management Students Petroleum Management Game A Securities Dealer Simulator SIM ECO SOC with Business Curriculum Modules: A Simulation for Business Ethics and Morals The Picnic: A Perceptual Errors Exercise Salt III; an Experiential Exercise to Highlight the Interpersonal Dynamics Involved in the Negotiation Process Experiential Exercise on Values, Attitudes and Conflict Resolution in Organizational Behavior Kick'N Go: A Product Management and Social Responsibility Dilemma The Use of Self-Assessment Work-shops in a school of Business Administration The Dilemma of Self-Perception