This thesis applies the methodology of finance to the study of insurance markets. The key ideas are: (1) representing the underlying fundamental source of uncertainty as a Marked Point Process and (2) allowing security trading to occur much more rapidly than spot trading in real commodities. The goal is the construction of a general equilibrium model with financial markets which is useful for applications, which I illustrate by treating the problem of providing earthquake insurance in California.; The general equilibrium model employed in this thesis is defined a discrete time, as is standard in dynamic macroeconomics. However, the driving stochastic process is defined over continuous time, taking the form of a Marked Point Process, a generalization of a Poisson process. The modeling framework that I propose takes these two different time scales--discrete time for spot trading in commodities, and continuous time for information revelation and security trading--and makes them mutually consistent.; This framework provides competitive dynamic prices for insurance contracts and insurance derivatives, such as catastrophe bonds, as the expected discounted value of their payoffs, and their risk premia are analyzed using standard finance tools. It also permits the analysis of trading behavior, which I use to show that risk-averse agents' optimal trading behavior is to share risk by buying insurance on themselves (thereby eliminating the idiosyncratic component in their endowments) and by trading aggregate securities such as catastrophe bonds and mutual funds to deal with aggregate uncertainty.; I use these theoretical results to study the problem of providing insurance for residential real estate in California, using data for the U.S. economy and for earthquakes to calibrate a simple general equilibrium model. The conclusion drawn from the simulation is that the competitive price of earthquake risk is well below current prices and that catastrophe bonds carry a large excess premium.
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