Canonical valuation uses historical time series to predict the probability distribution of the discounted value of primary assets' discounted prices plus accumulated dividends at any future date. Then the axiomatically rationalized maximum entropy principle is used to estimate risk-neutral (equivalent martingale) probabilities that correctly price the primary assets, as well as any predesignated subset of derivative securities whose payoffs occur at this date. Valuation of other derivative securities proceeds by calculation of its discounted, risk-neutral expected value. Both simulation and empirical evidence suggest that canonical valuation has merit.

[Nonprofit, mutually owned insurance and banking organizations have significant market shares in the insurance and banking industries. A first step in a systematic study of these financial mutuals is to examine the reasons for their formation. Doing so provides empirical support for the view that these mutuals arose as an efficient means of addressing contracting challenges caused by aggregate uncertainties and moral hazard. A formal model with this property is presented. We argue that information asymmetries do more to explain the kinds of contracts offered by financial mutuals than do agency problems between owners, managers, and customers.]

Controversial econometric studies of mortgage data show that mortgage loan applications by some minorities are denied more frequently than are applications by whites with similar observable default risk factors. But recent evidence indicates that minority borrowers also default more frequently than whites with similar observable risk. This paper presents a simple equilibrium model of discriminatory credit rationing and finds parametric restrictions consistent with both these empirical findings. However, in this model, proposed antidiscrimination policies have surprising side effects. Thus, policy analysts accepting this empirical evidence should not expect to derive model-free conclusions about the effects of proposed policies. Journal of Economic Literature Classification Numbers: G21, G28, D63.

ABSTRACT Canonical valuation uses historical time series to predict the probability distribution of the discounted value of primary assets' discounted prices plus accumulated dividends at any future date. Then the axiomatically‐rationalized maximum entropy principle is used to estimate risk‐neutral (equivalent martingale) probabilities that correctly price the primary assets, as well as any predesignated subset of derivative securities whose payoffs occur at this date. Valuation of other derivative securities proceeds by calculation of its discounted, risk‐neutral expected value. Both simulation and empirical evidence suggest that canonical valuation has merit.

Canonical valuation uses historical time series to predict the probability distribution of the discounted value of primary assets' discounted prices plus accumulated dividends at any future date. Then the axiomatically-rationalized maximum entropy principle is used to estimate risk-neutral (equivalent martingale) probabilities that correctly price the primary assets, as well as any predesignated subset of derivative securities whose payoffs occur at this date. Valuation of other derivative securities proceeds by calculation of its discounted, risk-neutral expected value. Both simulation and empirical evidence suggest that canonical valuation has merit.

While optimally weighted generalized method of moments (GAM) estimation has desirable large sample properties, its small sample performance is poor in some applications. The authors propose a computationally simple alternative, for weakly dependent data generating mechanisms, based on minimization of the Kullback-Leibler information criterion. Conditions are derived under which the large sample properties of this estimator are similar to GAM, i.e., the estimator will be consistent and asymptotically normal, with the same asymptotic covariance matrix as GAM. In addition, the authors propose overidentifying and parametric restrictions tests as alternatives to analogous GAM procedures.

Recent theories of corporate organization hold that mutually owned firms arise to remedy agency problems associated with ownership by a separate class of stockholders. We propose an alternative theory of mutuality, in which mutuals arise endogenously as a self-selection mechanism to cope with adverse selection and systematic risk. This theory makes predictions about the nature of customer contracts and the pattern of dividend payments adopted by mutuals. We do not systematically test this theory against others. But the behavior of the Farm Credit System, a large financial mutual, is shown to be more in accord with our theory.

Nonprofit, mutually owned insurance and banking organizations have significant market shares in the insurance and banking industries. A first step in a systematic study of these financial mutuals is to examine the reasons for their formation. Doing so provides empirical support for the view that these mutuals arose as an efficient means of addressing contracting challenges caused by aggregate uncertainties and moral hazard. A formal model with this property is presented. We argue that information asymmetries do more to explain the kinds of contracts offered by financial mutuals than do agency problems between owners, managers, and customers.

1. Introduction. 2. Pricing of Bonds. 3. Measuring Yield. 4. Bond Price Volatility. 5. Factors Affecting Bond Yields and the Term Structure of Interest Rates. 6. Treasury and Agency Securities Markets. 7. Corporate Debt Instruments. 8. Municipal Securities. 9. Non-U.S. Bonds. 10. Residential Mortgage Loans. 11. Mortgage Pass-Through Securities. 12. Collateralized Mortgage Obligations and Stripped Mortgage-Backed Securities. 13. Commercial Mortgage-Backed Securities. 14. Asset-Backed Securities. 15. Collateralized Debt Obligations. 16. Analysis of Bonds with Embedded Options. 17. Analysis of Residential Mortgage-Backed Securities. 18. Analysis of Convertible Bonds. 19. Active Bond Portfolio Management Strategies. 20. Indexing. 21. Liability Funding Strategies. 22. Bond Performance Measurement and Evaluation. 23. Interest-Rate Futures Contracts. 24. Interest-Rate Options. 25. Interest-Rate Swaps and Agreements. 26. Credit Derivatives. Index.