In many circles the Mean Variance Capital Asset Pricing Model (MV CAPM) is synonymous with the theory of capital asset pricing. But in a single-period discrete-time model which explicitly recognizes the existence of limited liability the derivation of the MV CAPM, if it is to be consistent with the von Neumann-Morgenstern postulates of rational behavior, must be based on the assumption that all investors have quadratic utility functions. This assumption in turn implies that risky assets are inferior goods. However, if we turn to the broader class of linear risk tolerance (LRT) utility functions, for which the separation property holds, other simple two-mutual-fund CAPMs can be derived. The power utility LRT CAPMs are of particular interest as they are consistent with risky assets being normal goods.

The recent world-wide increase in consumer prices has created an intense interest in inflation on the part of both the academic and the financial communities. For example, in his American Financial Association presidential address, Professor Lintner [4, p. 259] states “few matters are of more serious concern to students of finance and to members of the financial community than the impacts of inflation on our financial institutions and markets and its implication for investment policy.”

These three papers deal with a common subject from three very different attitudes and perspectives. As a result, without challenging such restrictive conventions as the assumption that investor holding periods are fixed and knowable a priori or indeed disagreeing on anything of substance, the respective sets of authors sound three very different themes.

Since the seminal article by Black and Scholes on the pricing of corporate liabilities, the importance in finance of contingent claims has become widely recognized. The key to the valuation of such claims has been found to lie in the solution to certain partial differential equations. The best known of these was derived by Black and Scholes, in their original article, from the assumption that the value of the asset underlying the contingent claim follows a geometric Brownian motion.

The literature on leasing has generally concentrated on providing management with a selection criterion for the lease-versus-purchase decision; over the years, a variety of recommendations have been advanced ([1], [3], [6], [8], [16], and [18]). More recent papers, however, have shown that the terms of leasing contracts in a transaction-costless competitive capital market will inevitably be such as to render the stockholders of value-maximizing firms indifferent to that decision ([11] and [12]). Simply put, competition among potential lessors-together with the mandates of securities-price-equilibrating trading activities of investors in lessee and lessor firms—will necessarily drive the present values of the cash flows associated with lease arrangements to parity with direct asset purchase prices.

The finance literature has devoted considerable attention to the study of yields, yield spreads, and rating classification for fixed income securities. In the corporate market, authors such as Hickman [6], Johnson [7], Sloane [9], and Van Home [12] have investigated the behavior of yields and yield spreads over time. Johnson found that the yield differential, defined as the corporate yield minus the equal maturity Treasury rate, was unrelated to maturity. Van Home found that this differential widened during recessionary periods; he interpreted this to reflect either a higher default probability or greater investor risk aversion. In his important paper published in 1959, Lawrence Fisher [4] employed cross-sectional data at five points in time to relate corporate yield spreads to four key variables which serve as proxies for default and marketability risks. Pogue and Soldofsky [8] extended Fisher's approach to explain not corporate bond yield spreads but rather bond ratings. As explanatory variables, Pogue and Soldofsky chose several measures of the firm's income and debt capacity.

The following proof of Modigliani and Miller's (MM) [2] famous propositions concerning the valuation of the firm and the cost of capital does not require the usual risk-class or arbitrage assumptions; the proof depends only on the Fundamental Theorem of Parameter-preference, which states that the riskpremium for security A is a linear combination of its comoments with the market index, .

In this paper, we examine the effects of errors in measurement of the two independent variables, return on market (Rm) and return on risk-free assets (Rf), in the traditional one-factor capital asset pricing model (CAPM). After discussing Sharpe-Lintner's CAPM and both Jensen and Fama's specifications thereof, we review briefly the recent results of Friend and Blume [6], hereafter FB; Black, Jensen and Scholes [1], hereafter BJS; and Miller and Scholes (11], hereafter MS. In Section II, we first explore possible sources of measurement errors for both Rm and Rf; then we specify these errors mathematically and derive analytically their effects on estimates of systematic risk of a security or portfolio, , and the Jensen's measure of performance, . In Section III, we derive an analytical expression for the regression coefficient of estimated b's where we estimate the equation . The result is then examined to find the conditions under which errors in measurement of Rm and Rf can cause b to have a positive or negative value even if the true b is zero. The conditions are then used to examine FB's results and their interpretation. In Section IV, an alternative hypothesis testing procedure for the CAPM is examined. We show that the empirical results so derived are also affected by the measurement errors and the sample variation of the systematic risk. The relative advantage between the two different testing hypothesis procedures is then explored. Finally, we comment on the relevance of the result to the popular zero-beta model and indicate areas for further research.

The competitive bidding requirement in the underwriting of public utility securities has come under increasing scrutiny in recent years. The difficulties that utilities have encountered in raising funds at an historically reasonable cost have exacerbated this situation. “Utilities,” as used here, will refer to investor-owned gas and electric public utilities. The combination of reduced capital availability and rapidly expanding financial needs gives rise to a serious inquiry about whether competitive bidding in new utility underwritings can be justified on the basis of cost to the company.

Estimation and control of security risk are subjects of major theoretical and practical importance. Much of the literature in this area has focused on the risk associated with returns over a single holding period. Within this context, a great deal of attention has been devoted to estimation of security betas, which relate to coveriance with “the market,” since the well-known Capital Asset Pricing Model implies that expected returns will, in equilibrium, be related to such values. However, a number of papers [3, 7, 14] have considered “extra-market covariances,” i.e., covariances among security returns not due to common correlations with the market as a whole. Accurate estimates of such covariances are necessary for tailoring portfolios to account for differences in investors' circumstances (e.g., tax brackets) and, a fortiori, for active portfolio management designed to exploit any security mispricing.

Empirical research has played an important role in recent theoretical developments in the theory of finance, particularly in the formulation and testing of various theories of capital asset pricing. A common procedure in much of that empirical research is to use historical price and dividend data to estimate the parameters of a characteristic line which relates the return on an asset or portfolio to the return on the market. While several possible limitations of such procedures have been explored, one recurring question is the appropriate length of each interval used in the estimation. The purpose of this study is to investigate intervaling in greater detail so as to better understand its impact on the results of empirical research and hence of further developments in the field of finance. This is accomplished by examining the effect of different intervals on the return distributions and estimated characteristic lines of 200 common stocks over the two decades 1950–1969. Section II reviews the relevant literature and attempts to place the intervaling effect in perspective. Research design for the investigation is described in Section III, and findings are presented in Section IV. A brief conclusion appears as Section V.

Krouse and Lee [5] have formulated an optimal financing problem of a firm in the dynamic setting of optimal control theory. Specifically, the problem is to find a financing mix of retained earnings and external equity over time in a way that maximizes the present value of the entire future dividends stream accruing to the firm's initial stockholders subject to a given maximum allowable growth rate for the firm.

Lanstein and Sharpe (LS) attempt to explain residual covariances between stocks on the basis of duration considerations. The results, by admission are mixed. Rather than to focus on these per se, I would like to further the work by making some suggestions with respect to the formal model development and the empirical tests-on the basis that both could be made crisper and thereby increase the value of what already is a contribution.

Two methods for deriving efficient sets involve either the Markowitz [3] approach, where every security can be viewed as being related to an index unique to itself, or the Sharpe [4] single-index model, where every security is related to the same index. Given the extreme differences between these models, Cohen and Pogue [1] developed two intermediate models. They found that the efficient set derived from the Sharpe single-index model came closer to approximating the Markowitz model's efficient set than their models when empirically tested on a sample of common stocks. Subsequently a similar test was performed by Wallingford [6] which yielded contradictory conclusions.

Capital market equilibrium has been extensively studied in the recent past, mostly in a mean-variance framework. In a perfect capital market with riskless assets and homogenous expectations among risk-averse investors, Sharpe and Lintner have shown that the efficient set of all investors could be described by only two portfolios (or mutual funds):

(1) the market portfolio

(2) the riskless asset.

Capital budgeting can be described as the problem of allocating scarce capital among a number of investment opportunities in such a manner that the outcome most preferred by a decision maker will result. When a single, mathematically explicit criterion is assumed, mathematical programming techniques can be applied. However, a single criterion, such as maximizing the return on investment or minimizing the risk of losing a sizable fraction of the original investment, is not appropriate for a significant number of real-world decision makers for whom two or more criteria, e.g., a judicious combination of return on investment and risk, are important. It has been argued [1] that it is usually not possible to obtain an explicit utility function for the decision maker and, consequently, that it is usually not possible to apply conventional (optimizing) mathematical programming techniques to find the most preferred outcome.

According to a now classic study of stock market price behavior by Fama [6], the empirical distributions of daily log price relatives are usually stable Paretian, non-Gaussian. However, there appears to have been substantial reluctance to accept Fama's [6] research results as indicative of a fundamental return generating process which is stable Paretian, non-Gaussian. Blattberg and Gonedes [1], Clarke [4], Officer [18], Praetz [19], and Press [20] have each in their own way questioned the Fama [6] results. Most recently Hsu, Miller, and Wichern (HMW) [13] have suggested that in periods of homogeneous activity for a firm the empirical distribution of rates of return on a common share may be Gaussian, in other words, that the fundamental return generating process may be normal.

In recent years, academicians and practitioners have been using the concept of duration more frequently in the analysis of debt securities. Although the use of duration has greatly expanded our insights into the behavior of bond prices and bond risk, it has given rise to a considerable degree of confusion and misunderstanding. The purpose of this review paper is twofold: (1) to clarify the record on what duration is and is not and what it can do and cannot do, and (2) to discuss the appropriate uses of duration in the analysis of security portfolios.

One of the innovative and successful new markets developed in recent years has been the registered exchange for the trading of option contracts. Key innovations provided by the option exchanges include the standardization of some contractual terms and the creation of a central clearing corporation to serve as issuer and obligor of each option contract, thus severing the contractual link between a specific option writer and buyer. These changes have facilitated the trading of existing call options in the secondary market and have provided increased liquidity, continuous public reporting of prices, better information on trading volume and open positions, and reduced transaction costs.

Of the behavioral recommendations garnered from modern capital market theory, few, if any, generalizations have been documented as convincingly as the simple advice to hold several assets in one's portfolio. Sharpe made such a conclusion perfectly clear when he stated [27, p. 184]:

If the market is efficient and if an investor is privy to no special information or predictive power, what should he do? First, and most important: diversify.