Date of Award

Summer 5-21-2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Risk Management and Insurance

First Advisor

Daniel Bauer

Second Advisor

George Zanjani

Third Advisor

Ajay Subramanian

Fourth Advisor

Stephen Mildenhall

Abstract

Pricing risks in the insurance business is an essential task for actuaries. Implementing the appropriate pricing techniques to improve risk management and optimize its financial gain requires a thorough understanding of underlying risks and their interactions. In this dissertation, I address risk pricing in the context of insurance company by reviewing methods applied in practice, proposing new models, and also exploring different aspects of insurance risks.

This dissertation consists of three chapters. The first chapter provides a survey of existing capital allocation methods, including common approaches based on the gradients of risk measures and “economic” allocation arising from counterparty risk aversion. All methods are implemented in two example settings: binomial losses and using loss realizations from a catastrophe reinsurer. The stability of allocations is assessed based on sensitivity analysis with regards to losses. The results show that capital allocations appear to be intrinsically (geometrically) related, although the stability varies considerably. Stark differences exist between common and “economic” capital allocations.

The second chapter develops a dynamic profit maximization model for a financial institution with liabilities of varying maturity, and uses it for determining the term structure of capital costs.

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As a key contribution, the theoretical, numerical, and empirical results show that liabilities with different terms are assessed differently, depending on the company’s financial situation. In particular, for a financially constrained firm, value-adjustments due to financial frictions for liabilities in the far future are less pronounced than for short-term obligations, resulting in a strongly downward sloping term structure. The findings provide guidance for performance measurement in financial institutions.

The third chapter estimates a flexible affine stochastic mortality model based on a set of US term life insurance prices using a generalized method of moments approach to infer forward-looking, market-based mortality trends. The results show that neither mortality shocks nor stochasticity in the aggregate trend seem to affect the prices. In contrast, allowing for heterogeneity in the mortality rates across carriers is crucial. The major conclusion is that for life insurance, rather than aggregate mortality risk, the key risks emanate from the composition of the portfolio of policyholders. These findings have consequences for mortality risk management and emphasize important directions of mortality-related actuarial research.

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