The implications for portfolio behavior and asset prices of transaction costs are central to the analysis of numerous issues in economics. For example, questions involving the demand for the financial contracts issued by financial intermediaries are intimately tied to the existence of transaction costs. Thus the analysis of questions involving the nature of the demand for mutual fund shares, insurance contracts, mortgage loans, etc., and the form those contracts take require the explicit inclusion of transaction costs.

The value of information to the investor is best described by Samuelson [15] in his prologue to the theory of speculation: “…Suppose my reactions are not better than those of other speculators, but rather one second quicker… in a world of uncertainty, I note the consequences of each changing event one second faster than anyone else. I make my fortune not once, but every day that important events happen…” Furthermore, the role of heterogeneous expectations was emphasized by Hirshleifer [7]: “…Speculation…emerges not from differences in individual risk aversion, but rather solely from differences in individual belief as to what the future will reveal.” Thus, information which is always partial and different to different investors, in imperfect markets, is perfectly consistent with the existence of heterogeneity in investors' expectations.

There has been a long-standing doctrine that high levels of employment tend to be accompanied by inflation. Closely related is the view that unemployment or slack economic conditions in general can be relieved by increases in the supply of money. These views have been held by economists of widely varying persuasions and particularly with widely varying views on appropriate economic policy. During the postwar period, the concept of a trade-off between inflation and unemployment was studied empirically and also used an extension of the basic Keynesian framework of analysis (a needed supplement since the General Theory had little to say about price movements in the absence of full employment).

There is a false, but widely-held belief about orthogonal (“zero-beta”) portfolios: for a given market index, all zero-beta portfolios have the same expected return and the minimal-variance, zero-beta portfolio is unique. This is true only when the index is mean/variance efficient. Every nonefficient index possesses zero-beta portfolios at all levels of expected return. For a given index, minimal-variance zero-beta portfolios corresponding to different expected returns lie along an “orthogonal frontier” in the mean/variance space. The frontier has some unusual properties which turn out to be relevant for empirical work on asset pricing. It is functionally related to deviations about the “securities market line.”

Figures I through III on the following pages were omitted from the article, “New Perspectives on Informational Asymmetry and Agency Relationships,” by Robert A. Haugen and Lemma W. Senbet which appeared in the November 1979 issue of this journal.

During the past decade considerable empirical evidence has been accumulated suggesting the stock market adjusts to the arrival of new information in an efficient manner. The studies providing this evidence consist of announcement tests of new publicly available information (such as earnings, stock splits, accounting changes, etc.) on the risk-adjusted return of securities. The specific methodology employed is crucial since it directly affects the results of a test for market efficiency. Following the pioneering work of Ball and Brown [1] and Fama, et al. [15], many researchers [6, 12, 21, 22, 27] have employed a similar methodology in order to test for market efficiency. This cumulative average residual (CAR) methodology consists of: (1) estimating the parameters of the market model based on data in a time period prior (and sometimes subsequent) to an announcement, and (2) analyzing the residuals derived from applying this model to a time period which includes the announcement date.

Virtually all commercial banks in the United States are supervised by one of the three Federal bank regulatory agencies. Although these agencies share the objective of identifying banks with financial difficulties that may lead to their failure under adverse conditions, they have never reached an agreement as to a uniform approach to capital adequacy. Under these circumstances and because of its critical value to bank regulation, the issue of capital adequacy has been extensively investigated by both practitioners and academicians. Those efforts have tended in recent years to concentrate on characterizing problem banks by using multivariate discriminant analysis. Typical examples are studies by Dince and Fortson [10], Sinkey [25, 26], and Sinkey and Walker [27], which use this method to identify the most indicative financial ratios for bank soundness and compare the ability of different formulas to predict bank failure.

The mean-variance capital asset pricing model (CAPM) of Sharpe and Lintner was extended by Brennan [3] to incorporate divergent borrowing and lending rates. He found that in equilibrium the security market line (SML) has the same structure as the SML under the single-rate CAPM of Sharpe and Lintner. That is, the expected return of a security or a portfolio remains linear in its systematic risk, with the intercept replaced by an equivalent risk-free return, which is an average of the divergent borrowing and lending rates weighted by the investors' taste parameters. The equivalent risk-free return is larger than the riskless lending rate and, hence, does not represent an inconsistency with the empirical findings by Friend and Blume [4] and by Black, Jensen and Scholes [1[ that the intercept of empirical SML estimated for the single-rate CAPM is larger than the riskless rate. Moreover, Brennan attempted to show that his construct can be extended to the extreme case where there are no riskless opportunities. The case of no riskless opportunities was of course investigated by Black [2], who generalized the CAPM and SML by inventing the concept of zero-beta port-folio to account for the same empirical problem encountered in the traditional SML tests of CAPM. Since the Sharpe-Lintner single-riskless-rate CAPM implies a perfect loan market, we may view the attempts by Black and Brennan as generalizing the CAPM by incorporating financial restrictions and loan market imperfections. Their primary motive, however, is empirical, i.e., to reconcile the results from the traditional SML tests with their generalized CAPM.

In the Arrow-Debreu approach to uncertainty it has been recognized that an inadequate number of markets in contingent claims would be a source of inefficiency. Several researchers have studied the allocative inefficiencies resulting from incomplete markets, i.e., when the number of independent securities is less than the number of states and therefore the state-space cannot be “spanned” by those securities. In a situation where the number of primitive assets is inadequate to span the state-space, the new spanning opportunities opened up by derived assets written on the primitives is an interesting question.

In this paper, we present a new version of the capital asset pricing model CAPM) that provides a linear pricing equation substantially different from that implied by the traditional CAPM of Sharpe [18], Lintner [12], and Mossin [14, 15] (hereafter SLM model). It is assumed that each of the investors has an initial endowment of real resources (say, corn) which can be either consumed invested in investment opportunities available to the investor. A set of simultaneous equations is derived from the model. The set of equations determines the equilibrium values of these interdependent endogenous variables: the amount to be consumed by the investor; the proportion of each investment project be owned by the investor; the amount to be invested in each of the available investment projects; the market value of each project; the market price of risk; and the return imputed by the capital market for a risky project which has a zero-beta risk. If a riskless project exists, the zero-beta rate is just a risk-free rate.

In this paper we present a method for valuing American and European put and call options on debt securities. Although no exhange-traded options of this type currently exist in the United States, the Chicago Board Options Exchange plans to introduce option contracts on several government bonds, and the Chicago Board of Trade petitioned the Commodities Futures Trading Commission to allow the trading of options on the Ginny Mae futures contract. In addition to pricing put and call options, the model developed here can be applied to the valuation of other securities such as callable bonds and bank loan commitments.

The decomposition of a security risk into diversifiable (or unsystematic) and nondiversifiable (or systematic) risks has emerged from the portfolio approach of capital investment and has culminated in the well-known Capital Asset Pricing Model (CAPM), developed by Sharpe [4], Lintner [3] and others. In this framework, the diversifiable risk is the risk that can be “washed out” by diversification and the nondiversifiable risk is the risk which cannot be diversified away. It appears to us that the decomposition of risk into its components is in some cases vague and in most cases imprecise. We define the diversifiable and nondiversifiable risk measures as two complementary components of the standard deviation of a security's rate of return. Furthermore, we require thatthe nondiversifiable risk measure will completely determine its equilibrium market price. We shall see that the definition presented is appealing for all securities and particularly for those with negative Beta. To be more specific, recall that a security's β is given by the slope of the following time series regression:

Despite the proliferation of banking services, the basic commercial and industrial lending process remains the lifeblood of commercial banks and other banking institutions. The lending process is a relatively straightforward series of activities involving two principal parties whose association ranges from the initial loan request to the successful or unsuccessful repayment of the loan. Most students of banking would agree that the process is an interdependent one, but the exact dependencies are rarely articulated in a rigorous manner. One of the purposes of this paper is to investigate the association between at least two important aspects of the lending process, namely, the credit evaluation stage and the sequence of events that describes and quantifies the charge-off and subsequent recovery experience.

Wall Street abounds with folklore concerning aggregate stock price movements before and after Presidential elections. Some suggest that movements in the Dow Jones Industrial Average (DJIA) portend the outcome of elections. Others attribute movements in the market, prior to and after the election, to the anticipated outcome of the election. In this paper we examine some of the folklore with respect to the effect of Presidential elections on aggregate stock price movements and the implication of these movements on market efficiency.

The Capital Asset Pricing Model (CAPM) developed and popularized by Treynor [27], Sharpe [26], Lintner [16], Mossin [19], and Fama [6] is of the form

where

E is the expected return at time t for firm i (conditional on information available at time t); the subscript m denotes the analogous market variable; rf is the risk-free rate; and . Black [2] has developed a similar form with expected returns from a zero beta portfolio, , assuming the role of the risk-free rate.

The Capital Asset Pricing Model (CAPM), an equilibrium model for the price determination of risky assets, was developed by Sharpe [16], Lintner [9, 10] and Treynor [21], following the pioneering work of Markowitz [12, 13] and Tobin [20]. In spite of the tremendous impact of this model on the profession, the CAPM still raises many questions, and is inconsistent with a considerable body of empirical evidence.

In the theoretical literature of finance, it has been assumed for some time that capital markets are efficient, with security prices reflecting all available information [10]. One purpose of this paper is to consider market efficiency in the context of rights offerings. It has recently been suggested, for example, that rights offerings afford positive abnormal returns [17,18]. This view was immediately countered by the comment that the number of rights issued, and inversely the issue price, cannot affect the market value of the total exrights equity market [21, p. 44]. No empirical evidence was offered on either side, however.

This paper studies the relationship between real interest rates and housing using a microeconomic approach. The primary impact of interest rates is on the demand side. The partial equilibrium, comparative static model of demand behavior presented is based on intertemporal preference maximization subject to a multiperiod income constraint. The model is always in terms of real prices and interest rates and operates in discrete time. Consumer preferences are represente by a smooth utility function which depends on two kinds of goods, housing and other nondurables. This study is couched in a neoclassical framework with all markets assumed perfect unless otherwise specified. With this approach the theory of housing and interest rates becomes part of standard consumer theory, rather than being based on inappropriate present value considerations.

Sharpe's market model [29] is widely used both by academic researchers and practitioners in finance, but it cannot be accepted with complete confidence until some of its basic assumptions are tested more thoroughly. The applicability, usefulness, and reliability of the model are functions of its conformity to real data, which in turn depends partly on the unresolved question of heteroscedasticity.

Recently the standard market model has been used to examine holding period returns of corporate bonds. These studies have involved issues such as: the impact of accounting earnings data on bond price behavior [5]; the relationship of bond betas and ratings [19, 21]; the effect of ratings changes on bond prices [27]; the relationship of bond betas to duration and yield [3, 13, 15]; bond performance of bankrupt and nonbankrupt firms [26]; and tests of the Capital Asset Pricing Model based on bond returns [7]. While the empirical appropriateness of applying the market model to common stock returns has been demonstrated, similar tests have not been conducted with regard to long-term corporate bonds. Section II of this paper will examine the assumptions of the normal error regression model when used in the form of the market model and applied to a sample of long-term corporate bonds during the early years of their lives. The issue of systematic changes in the regression parameters will be addressed in Section III. Lastly, conclusions will be presented in Section IV.