Knowledge that Transforms

William W. Alberts, Gailen L. Hite, The Modigliani-Miller Leverage Equation Considered in a Product Market Context, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 4 (Dec., 1983), pp. 425-437

The Sharpe-Lintner Capital Asset Pricing Model (CAPM) has always contained an implicit question: what if all investors are single-period wealth maximizers but the length of the single period varies across investors? Gressis, Philappatos, and Hayya (GPH) [7] have pointed out that as the assumption of investment horizon length is changed, the Capital Market Line (CML) intersects the Efficient Frontier (EF) at different points causing different investors to hold different efficient portfolios. GPH assert that these different portfolio holdings will result in an inefficient market portfolio—and dire consequences for the capital market model.

Recent developments in the literature on bond portfolio management have identified conditions under which uncertainty of the investment return attributable to interest rate changes is eliminated. Such a strategy, called immunization, is achieved when the duration of the bond or portfolio of bonds is equal to the investor's holding period. Duration is defined as a weighted average time to maturity and was originally developed by Macaulay [13]. The condition under which immunization is obtained by setting duration equal to holding period was derived by Redington [14] and Fisher and Weil [10] and further developed by Bierwag and Kaufman [4], Bierwag [2], and Khang [12]. Bierwag [3] has provided a concise summary of the theory of immunization, and Bierwag and Khang [7] show that immunization is equivalent to selecting a strategy in which the worst possible return is maximized, i.e., a minimax strategy. Bierwag [1] examines immunization under multiple shocks to the term structure and Bierwag, Kaufman, and Toevs [6] extend the concept to a general equilibrium, two-state Arrow-Debreu world.

The search for an economically sound procedure for estimating an appropriate rate of return on equity consistent with the Supreme Court's ruling in the Hope case [13] has led many economists, financial experts, and public service commissions to estimate the rate of return on equity with the capital asset pricing model (CAPM) (see [30], [19], and [21]). The popularity of the CAPM in regulatory proceedings was reported by Harrington [15] who, in a survey of public service commissions, found that 38 states were considering or had seen the CAPM used, two jurisdictions preferred the CAPM, Oregon required the CAPM, and South Carolina would require the CAPM in all future cases. Hence, given the popularity of the CAPM and the tremendous economic impact that outcomes of regulatory proceedings have on the financial well-being of both the regulated firm and the consumer, it is critical that if the CAPM is used in regulatory proceedings that it be applied in the best manner possible and that any limitations associated with the CAPM be recognized fully.

In the analysis of problems of choice under uncertainty, many results depend on the investigator's ability to determine the signs of certain integrals. A recently derived method of doing this—christened the “covariance method” by Batra [2]—demonstrates that, in certain cases, recognition of the fact that the integrals involved are composed of covariance terms can provide a simple and elegant solution to the problem. This paper uses a simple portfolio model to demonstrate that these covariance terms can be exploited to obtain other useful results as well.

David S. Kidwell, Charles A. Trzcinka, The Impact of the New York City Fiscal Crisis on the Interest Cost of New Issue Municipal Bonds, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 3 (Sep., 1983), pp. 381-399

Varouj A. Aivazian, Jeffrey L. Callen, Itzhak Krinsky, Clarence C. Y. Kwan, Mean-Variance Utility Functions and the Demand for Risky Assets: An Empirical Analysis Using Flexible Functional Forms, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 4 (Dec., 1983), pp. 411-424

Empirical studies in finance generally use data defined over the shortest return period available. Originally, data bases such as CRSP, tended to have data collected over monthly periods and most analyses tended to use monthly data rather than data compounded over periods greater than a month with the implicit argument that the more data the “better”. Since the development of data bases with data collected over shorter differencing intervals, there has been a growing tendency in finance to use returns data defined over increasingly shorter differencing intervals. This development is desirable, but is not without problems. The problem with using data defined over shorter differencing intervals is that, although greater estimating efficiency will be achieved, nontrading effects could be introduced into the analysis. These will lead to biased beta estimators and biases in tests of capital market efficiency. The purpose of this paper is to investigate, analytically, the interrelation of the intervaling and nontrading effects both in estimating beta factors and in testing capital market efficiency.

Chulsoon Khang, A Dynamic Global Portfolio Immunization Strategy in the World of Multiple Interest Rate Changes: A Dynamic Immunization and Minimax Theorem, The Journal of Financial and Quantitative Analysis, Vol. 18, No. 3 (Sep., 1983), pp. 355-363

Periods of high mortgage interest rates that characterized the early 1980s have escalated the use of assumption financing in home buying. In these periods, there is an increased demand for alternative sources of financing and a movement away from conventional sources. The purpose of this study is to provide a theoretical and empirical analysis of the effect of the increased use of assumption financing on selling prices of single-family residential housing. Aside from physical characteristics, the financing arranged by the homebuyer is considered a major influence in determining house prices. This is especially true in real estate appraisal practice where differences in types of financing are one of the major categories of adjustment (see [1], [4], and [10]).