Date of Award

8-11-2015

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Risk Management and Insurance

First Advisor

George Zanjani

Second Advisor

Ajay Subramanian

Third Advisor

Daniel Bauer

Fourth Advisor

Stephen Shore

Fifth Advisor

Michael Powers

Abstract

The dissertation includes two essays on insurer's risk management. The first essay is about how insurers use contract structure to manage their underwriting risks. Existing research on insurance contract theory emphasizes information problems and demand side issues when explaining contract structure. Supply-side factors, especially risk considerations at the insurer, have received much less attention. In this paper, we extend the optimal contracting framework of Raviv, 1979 to explore how background risk at the insurer affects optimal contract structure. We confirm earlier findings that insurer background risk may reduce risk sharing in the optimal contract. We go further to show that positive correlation between the insurer's background risk and the insured's loss can yield contract forms ruled out by the standard model, such as upper limits on coverage, and explain patterns of risk sharing not addressed in the literature, such as large deductibles in catastrophe contracts.

The second essay studies the capital allocation rule in a general portfolio optimization problem with irreversible investments. I find that marginal cost pricing can still be connected to capital allocation in this setup, although the basis for allocation is different from that found in static problems. The investment decision for an opportunity presented today is made on the basis of an expected future marginal cost of risk associated with that opportunity. The capital allocated for today's opportunity is a probability-weighted average of the product of the marginal value of capital in future states of the world and the amount of capital consumed by today's opportunity in those future states. In addition, our numerical examples show that failure to explicitly model uncertainties regarding future opportunities can lead to understatement of the marginal cost of risk, and, as a result, over-investment in current opportunities.

DOI

https://doi.org/10.57709/7366031

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