Financial decision-making under ambiguity

Which job opportunity is more likely to yield the best result for career growth? One may consider an array of criteria in making such a choice and be influenced by subjective biases. But the real question is: how can alternatives be ranked by the criterion of ambiguity?* Shadow probability theory captures the multidimensional nature of uncertainty by assuming that probabilities of events are themselves, random. This model, introduced by Dr Izhakian, allows us to make a distinction between subjective aversion to ambiguity and objective degree of ambiguity. The objective degree of ambiguity can be tested empirically with data, while preferences toward ambiguity can be easily monitored in laboratory experiments. By challenging the conventional wisdom of financial theory, Dr Izhakian shows that once ambiguous probabilities are incorporated into asset-pricing models, full diversification may not necessarily be optimal.
My research focuses on the implication of ambiguity on financial decision making. During the recent decade it has become commonly agreeable that existing financial models cannot explain many observable phenomena in the financial world. One flaw of the existing models is that they do not capture the entire picture of uncertainty. My research generalizes models of asset pricing to accommodate additional tier of uncertainty, called ambiguity. Namely, it models financial decision making in a more realistic manner by dropping the standard and restrictive assumption that economic agents know the precise odds of possible events.