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The impact of biases on simulation-based risk aggregation : modeling cognitive influences on risk assessment
Publikationstyp
Journal Article
Date Issued
2011
Sprache
English
Author(s)
Journal
Volume
22
Issue
1
Start Page
79
End Page
105
Citation
Journal of Management Control 22 (1): 79-105 (2011)
Publisher DOI
Scopus ID
Publisher
Springer
This paper develops a systematic approach to quantifying the effect of judgmental biases on aggregate risk measures. Starting with the standard risk management process, we derive the areas that require expert judgment as input in order to aggregate risk into risk measures such as Earnings at Risk. We specify three possible gateways for biases and identify several psychological theories to quantify deviations of expert judgments from objective probabilities. The impact of these cognitive biases on the aggregate risk measure is investigated via Monte Carlo simulation experiments. Through experimental design, we can determine the size of both the average and the possible interaction effects of the different biases. The results show that aggregate risk is systematically underestimated if it is based on biased subjective judgment. Moreover, the existence of interaction effects indicates potential problems of simple debiasing strategies.
Subjects
Cognitive biases
Experimental design
Expert judgment
Risk management
Simulation
DDC Class
330: Economics