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Price Regulation in Property-Liability Insurance: A Contingent-Claims Approach
A discrete-time option-pricing model is used to derive the “fair” rate of return for the property-liability insurance firm. The rationale for the use of this model is that the financial claims of shareholders, policyholders, and tax authorities can be modeled as European options written on the income generated by the insurer's asset portfolio. This portfolio consists mostly of traded financial assets and is therefore relatively easy to value. By setting the value of the shareholders' option equal to the initial surplus, an implicit solution for the fair insurance price may be derived. Unlike previous insurance regulatory models, this approach addresses the ruin probability of the insurer, as well as nonlinear tax effects.
Informational Efficiency and Information Subsets
This paper proposes a new definition of the Efficient Markets Hypothesis with respect to information, which is more formal and precise than those of Rubinstein [13] , Fama [4] , Jensen [6] , and Beaver [1] , and which fits well as a framework for interpreting the many tests of the Efficient Markets Hypothesis in the literature. Security markets are here considered “efficient with respect to information set ϕ ” if and only if revealing ϕ to all agents would change neither equilibrium prices nor portfolios. In addition to other desirable features, this definition has the “subset property”: efficiency with respect to ϕ implies efficiency with respect to any subset of ϕ .
Asset Price Volatility, Bubbles, and Process Switching
Asset Price
Asset Pricing and Expected Inflation
Valuation of American Futures Options: Theory and Empirical Tests
Loan Commitment Contracts, Terms of Lending, and Credit Allocation
This paper analyzes the structure of loan commitment contracts and the interrelationships among their component parameters. Lenders offer borrowers a set of loan “packages,” from which the latter may choose that “package” found to be most appealing. Borrowers may “trade off” changes in any loan parameter in exchange for other adjustments. The borrower, at this time, may “purchase” a larger credit ration for a price. Supporting empirical evidence is presented.
Returns and Risks of U.S. Bank Foreign Currency Activities
In this paper the risks and returns on U.S. banks' foreign currency positions are analyzed in a portfolio setting when both exchange rate and foreign interest rate risks are present. It is shown that U.S. banks could achieve considerable reductions in risk by optimally selecting their foreign currency positions. Actual foreign currency portfolio returns generated from expected exchange rate changes and exchange rate surprises were positive on average but those generated from interest rate surprises were negative. Although the total portfolio returns were positive, on a risk‐adjusted basis bank return performance was relatively poor. Nevertheless, despite this relatively poor performance, the risk of ruin or failure for a “representative bank” from foreign currency activities was found to be approximately zero when judged in comparison to the capital funds available to large money center banks to cushion such losses.
On Timing and Selectivity
Benchmark Portfolio Inefficiency and Deviations from the Security Market Line
This paper theoretically evaluates the robustness of the Security Market Line relationship when the market proxy employed is not mean‐variance efficient. The analysis focuses on the behavior of the “benchmark errors,” the deviations of assets and portfolios from the Security Market Line. First, we characterize how the location of an asset in mean‐variance space determines its benchmark error. Then the continuity properties of the benchmark errors are studied. The results indicate that the magnitudes of the errors exhibit continuous but not uniformly continuous behaviors. The relative rankings based on deviations from the Security Market Line, however, exhibit some severe discontinuities. In fact, these can be exactly reversed for two proxies arbitrarily close in mean‐variance space.