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.

There is strong theoretical support for the notion that prices in a perfect capital market will vary randomly ([22], [16]). However, the existence of some nonrandomness in stock prices is well documented, see ([10], [11], [13], [14], [20]). Of special importance for this study is the research by Young [24] who finds predominantly negative autocorrelation for a sample of securities using a monthly differencing interval. Autocorrelation coefficients are often used as a measure of nonrandom price behavior; negative autocorrelation is an indication of price reversals.

The Journal of Financial and Quantitative Analysis © 1979 University of Washington School of Business Administration

Evaluating investments by discounting anticipated future benefits at an exogenously determined risk-adjusted discount rate (hereafter referred to as the RADR approach) is well accepted in the canon of finance. If benefits (D) are to be received for T periods and if k, the discount rate, is constant over each of the t periods, then the discrete time net present value (NPV) is de-fined as: T t (1) NPV = E D /(l + k). t=0 A positive NPV characterizes a desirable investment. A frequently offered criticism of the RADR approach centers on the fact that both risk and timing considerations are treated in the denominator of equation (1). The certainty equivalent (CE) method has been suggested as a way of distinguishing between the two effects. In computation of the CE-NPV, riskless benefits that are equal in utility to the risky projected benefits

This paper analyzed the issue of why large commodity futures traders hold a large percentage of their portfolios in straddle positions where, for the most part, such behavior implies that they are holding assets with negative expected returns. It showed that an earlier paper by Schrock [2], which suggested that such behavior provided a means by which investors could enhance their risk-return tradeoffs, provided only a partial explanation for this behavior which, in a world of positive interest rates, held only under fairly restrictive conditions. Thus, it went on to develop a more general result which strongly suggests that differentially low margin requirements on straddle positions provide a strong incentive in a world of positive interest rates for investors to hold commodity straddle positions. With some modification the model developed in this paper can be used to derive similar conclusions for certain classes of transactions in the stock options market.

The challenge of leadership is to look beyond the current expansion to consider the long–term outlook for the U. S. economy. My good friend Paul W. McCracken once described this process as looking across the valley to see what is on the other side. His message was: “What will be different on the other side of the valley is far more relevant to business planning than the valley itself.” Such advice is particularly meaningful at this time because of the basic need for more stability in our economic policies.

The opponents and proponents of competitive brokerage commission rates for the New York Stock Exchange have, for nearly a decade, been dueling in the hearing rooms of Congress and the Securities and Exchange Commission (SEC). The contest developed because financial institutions, in attempting to skirt the New York Stock Exchange (NYSE) and its fixed commission rates, had used a variety of trading practices that were sharply criticized by the government overseers of the securities markets. The securities industry, the government overseers, and scholars have debated what would be the most effective regulatory approach to improving the social performance of the securities marketplace. Would it be through initiating even more stringent federal regulation of exchange behavior? Or, would it be through selective deregulation to increase competition, particularly in the determination of commissions? Competitive forces might constrain and direct that behavior. The policy that has been developing would deregulate and restructure the marketplace to create a “central market system.” Competition would replace regulation to whatever extent may be possible, in determining both commission rates and the quality of marketplace services provided [6]. But, the contest has been long and often heated. From the thrusts and parries, there can be identified some fundamental issues concerning the economics of the stock exchange as a form of marketplace organization.

A market is commonly called thin if a large change in price is associated with a small change in supply or demand. The concept of thinness can refer to the markets for stocks, bonds, any category of financial instrument, or even any type of good. Most frequently, thinness has been casually discussed with regard to bond markets and stock markets.

Intuitively, a risk averter diversifies between two investments if there is some sort of negative interdependence. In [3], Samuelson gives the example of buying shares in a coal company and an ice company. It is of interest to characterize this concept of negative interdependence more sharply.

Marion L. Chiattello, Comment: "On the Use of Principal Components Analysis to Interpret Cross-Sectional Differences Among Commercial Banks", The Journal of Financial and Quantitative Analysis, Vol. 9, No. 6 (Dec., 1974), pp. 1047-1051