When banks engage in financial market transactions they get exposed to two different types of risk: event risk and behavioural risk. When it comes to analyzing risk situations, two different types can be identified: stochastic risk management and strategic risk management. Event risk can best be analyzed by using the stochastic approach. In contrast, behavioural risk can best be analyzed by using the strategic approach. The mathematical instrument to analyze strategic interactions of the players involved is game theory. However, now behavioural risk is being analyzed using the stochastic approach. In addition, based on historical data analysis the stochastic concepts are applied to determine all kinds of financial decisions. As a result, many banks and financial intermediaries get into trouble due to neglect of the proper risk management concepts. The paper shows that game theory may become fruitful in handling behavioural risks.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

In this paper we claim that modeling financial markets based on probability theory is a severe systematic mistake that led to the global financial crisis. We argue that the crisis was not just the result of risk managers using outdated financial data; we think that the employed efficiency model-also referred to as stochastic model-is basically flawed. In an exemplary way, we will prove to the reader that this model is unable to account for interactions between market participants, neglects strategic interdependences and hence leads to erroneous solutions. Our central message is that the existing efficiency model should be replaced by an approach using agent-based scenario analysis.

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