Not within the traditional category of a financial book, Bueno de Mesquita's the Predictioneer's Game claimed, "that it is possible for us to anticipate actions, to predict the future, and, by looking for ways to change incentives, to engineer the future across a stunning range of considerations that involve human decision making" (p. xiv). Such knowledge should improve financial decision making. Based on game theory and using models, the author processes information on his subjects' self interest and determines what the subjects will do and why. Bueno de Mesquita acknowledged the limitations of this method. Some problems find better solutions with applied game theory or statistical forecasting.
The audit project that the author engaged in for Arthur Andersen in 2000 to assess the risk that some of their clients would engage in fraud pricked my interest. According to Bueno de Mesquita, his models with publicly available data on companies could "predict the likelihood of fraud two years in advance of its commission" (p. 116). Enron landed in the high risk category. The following flags signal fraud--decreases in dividends, management compensation packages below expectations, the size of institutional investor ownership, the number of directors, among others.
The author presented the steps for predictions with credibility. First, structure the question addressed into the choices or options available to the subject. Second, acknowledge the environmental context, the " 'what if' questions . . . background conditions . . . scenarios" (p. 49) that would influence the subject. Finally, gather the facts. The author lists four:
1. Identify every individual or group with a meaningful interest in trying to influence the outcome. Don't just pay attention to the final decision makers.
2. Estimate as accurately as possible with available information what policy each of the players identified in point 1 is advocating when they talk in private to each other--that is, what do they say they want.
3. Approximate how big an issue this is for each of the players--that is, how salient is it to them. Are they so concerned that they would drop whatever they're doing to address this problem when it comes up, or are they likely to want to postpone discussions while they deal with more pressing matters?
4. Relative to all of the other players, how influential can each player be in persuading others to change their position on the issue.
In a simple example of the process, the author suggested interviewing subjects via a survey on a simple question, such as which movie would be their preference movie A or movie B and rate the "salience" (p. 53) of the question on a scale to the subjects. Their responses demonstrate their position, the strength of their conviction to the position, and the power they bear. By making a decision, the subject exhibits the basic premise of game theory, that self interest motivates individuals. Another primary motivator, according to the author, is the desire for glory, "the ego satisfaction that comes from the recognition by others that they played an important part in putting a deal together" (p. 55). Another formula for predicting entails employing the weighted mean: "multiply the influence of each player (calling influence I) by his or her salience (S) and multiply that result by the numerical value of the position each player advocates (p), then add those totals up for all of the players and divide that total by the sum of the influence time salience for each of the players (sum of I x S x P)/(sum of I x S)" (p. 59). These manual methods, with a 75 percent accuracy rate do not replace the more exact computer models. Bruce Bueno de Mesquite applied his methods to various situations, described in the remainder of the book.
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