Abstract: It has been established that ambiguity aversion increases the optimal demand of (self-)insurance due to the resulting mean-preserving contraction in the distribution of expected utility. We extend the existing framework by further permitting the insurance indemnities to vary ex-ante based on the state of information concerning the loss probability that is realized expost. We show that ambiguity-averse agents will always strictly prefer state-of-information dependent insurances over ones with fixed indemnities. Our results also hold when the underlying state of information cannot be directly observed, but can be (partially) inferred from some observable indicators - based on which indemnities are further contingent.

Bio: Dr. Guan earned her PhD in Financial Mathematics from Florida State University in 2011. She earned her BS in Financial Mathematics from Peking University in 2006. Dr. Guan joined DePaul University in 2020.  She holds a joint appointment with the Department of Mathematical Sciences in the College of Science and Health and the Department of Finance in the Driehaus College of Business. As a member of those two departments, she serves as the Director of the Actuarial Science programs in each college. Dr. Guan is an Associate of the Society of Actuaries (ASA). Her research interests are in financial mathematics and actuarial science, focusing on heterogeneous agent models, risk management, and insurance economics.

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