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Showing posts from November, 2017

Rank dependent expected utility

Prospect theory is most well known for its assumption that gains are treated differently to losses. Another crucial part of the theory, namely that probabilities are weighted, typically attracts much less attention. Recent evidence, however, is suggesting that probability weighting has a crucial role to play in many applied settings. So, what is probability weighting and why does it matter? The basic idea of probability weighting is that people tend to overestimate the likelihood of events that happen with small probability and underestimate the likelihood of events that happen with medium to large probability. In their famous paper on ' Advances in prospect theory ', Amos Tversky and Daniel Kahneman quantified this effect. They fitted experiment data to equation where  γ is a parameter to be estimated. In interpretation, p is the actual probability and  π (p)  the weighted probability. The figure below summarizes the kind of effect you get. Tversky and Kahneman found