Investment decision making under conditions of uncertainty, and in particular portfolio selection, is carried out mainly in the Mean-Variance framework which has been developed by Markowitz [29], [30] and Tobin [42]. By assuming the lending and borrowing of money at a given riskless interest rate, Sharpe [39], [40], Lintner [27], [28], Mossin [34], and others derived and extended the Capital Asset Pricing Model, under which an equilibrium price of each risky asset is determined. However, though the mean variance rule is quite convenient to apply, its limitations are well known, i.e., one must assume either normal probability distributions with risk aversion or quadratic utility functions.

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.

Jensen [6] employed the instantaneous systematic risk concept to eliminate the problem associated with time horizon. Based upon the effective rate of return argument, Cheng and Deets [3] claimed that Jensen instantaneous risk is not independent of the time horizon used in the investment analysis. They have also proposed a so-called Cheng-Deets instantaneous risk to substitute for the Jensen instantaneous risk.

Following the log normal distribution assumption, this paper has shown that Cheng-Deets instantaneous risk is identical to Jensen instantaneous risk. The relationship between finite systematic risk and instantaneous risk is also identified. The roles played by the effective and the nominal rate-of-return concepts in the capital asset pricing process are also clarified. It is shown that both Jensen and CD instantaneous risks are biased unless the investment horizon is instantaneous. A testable generalized CAPM is derived to test the instantaneous investment horizon assumption. Finally, 30 securities of the Dow- Jones industrial average were used to test the generalized CAPM derived in this paper.

In 1952, Harry M. Markowitz [6] described a theory on the selection of assets in forming a portfolio. Assuming asset returns are stochastic, his theory postulated that rational investors should select a portfolio from the set of all portfolios which offered minimum risk (measured by variance) for varying levels of expected return. This set was named the efficient set by Markowitz.

Traditional models of portfolio selection assume that all assets are traded in competitive markets, so that rates of return to any individual investor are fixed. This paper represents an extension of portfolio theory to the case in which asset markets are not perfectly competitive and rates of return cannot be taken as given. Klein [10] has noted that, when asset markets are imperfect, the separation theorem no longer holds but does not solve explicitly for the relationship between risk and return. Here for simplicity we shall consider the case of the investor who has a monopoly in an asset he creates, so that its risk and return characteristics are determined by the decisions of the portfolio selector and hence are endogenous. It will be shown that even if the market for an asset in the portfolio is imperfectly competitive, as long as the demand curve for the asset is well behaved, the locus of efficient portfolios facing the investor, which is composed of combinations of the riskless asset and the optimal combination of risky assets, will be a concave function, as opposed to a linear function in the competitive case. In other words, the introduction of capital market imperfections does not affect the positive slope of the efficient set of portfolios. Moreover, the expected return on the imperfectly competitive asset will be shown to be easily decomposable into the standard risk premium and a monopoly premium.

This project was intended to test the usefulness of the Markowitz-based allocation model of which sampling fluctuations are clearly a possible weakness. Realistic conditions were formulated and a data set was simulated to insure a stable, independent, and normally distributed data set. The methodology was constructed such that the only difference in the portfolio performance results was the number of historical observations to estimate the inputs.

It was found that a minimum of 30 historical observations was required to yield efficient portfolio performance characteristics. It may be argued that this represents a large number of observations, although it is clearly not as large as those of other statistical procedures such as factor analysis or discriminant analysis.

This article addressed only the issue of the number of observations and not the appropriate length, i.e., monthly or quarterly. Dickinson demonstrated that the ratio of variances of two securities influenced the accuracy of the estimates of wi, the proportion of total capital invested in each of the two assets. Changing the length of the observation will change these variance ratios for many assets. A study is currently in progress to trace this effect on subsequent portfolio performance. It is hoped that these results, and those yet to come, will ease the burden of many of the arbitrary assumptions that we are presently forced to make in empirical investigations of efficient portfolio performance.

The findings, based on price movements alone, are that trading on the assumption that a large (small) proportion of increases in stocks' short ratios is bullish (bearish) produced significantly better than expected results at all Alphas tested above .02. This test-by-predictiveness strongly supports the validity of the assumptions.

A test of the components of the short ratio produced no evidence that the success of the ratio as a stock market predictor can be attributed to either of its components singly, i.e., to either changes in short interest or changes in trading volume.

A second test of the assumptions incorporated in the SR Expectations Model consisted of a comparison of model results against buy-and-hold results. In all cases except at Alpha .01 model results exceeded buy-and-hold results–and greatly so at Alphas above .02, thus strongly supporting the validity of the assumptions.

The test against the buy-and-hold “control” standard was then extended to incorporate dividend and commission considerations. These considerations sharply reduced the model's performance. Therefore, an alternate strategy was tested which markedly reduced commissions, offset the opportunity cost of dividends missed when the portfolio was not long stocks, and avoided the explicit dividend drains caused by short positions. This strategy consisted of substituting Treasury Bill holdings for short positions in the basic model. This policy, consisting of switches between Treasury Bills and SSP “stocks” in accordance with Alpha .05 signals produced a terminal portfolio value greater than the buy-and-hold policy even after the introduction of a 30 percent income-tax consideration. Moreover, this higher return was generated with less risk than that inherent in the buy-and-hold policy.

With respect to the optimum filter, it was found that Alpha .11 was best for price predictive purposes, with Alpha .05 a close second, but that once commission considerations are allowed for, Alpha .05 was the optimum filter.

In conclusion, the hypothesis of this study is that when speculative expectations become extremely one-sided, a high probability exists that stock prices will reverse towards the unanticipated direction. This view is consistent with the theory that the stock market is generally efficient, but not perfectly so. A test of a model using changes in short ratios as a measure of shifts in investor expectations is consistent with the hypothesis: returns generated by the model significantly outperform random expectations. The test indicates a systematic tendency for investors to over-discount events when an overwhelming majority share the same optimism (pessimism) about future stock prices.

Several studies have investigated the reaction of the stock market to a firm's changing its method of accounting for external reporting purposes. By contrast, this study investigates the reaction of proper subsets of the stock market to changes in accounting methods–specifically, the reaction of the set of investors in the common stock of the firm which has changed its accounting measurement rules.

This brief paper will show that (a) a theoretical equilibrium state of the world exists in the absence of capital controls and trade barriers when prices for the same goods in different markets are equal, after translation at the spot exchange rate; (b) differences in rates of aggregate price change in different markets eventually cause offsetting exchange rate changes which restore condition (a); (c) returns on equivalent securities denominated in different currencies but covered in the forward market are almost instantaneously equalized; (d) the market's expected rate of change of the exchange rate equals, to a close approximation, the control-free interest rate differential between the two currencies; (e) in the absence of predictable exchange market intervention by central banks, the interest rate differential is the best possible forecaster of the future spot rate; and (f) the forward rate also provides the best forecast of the future spot rate. A final corollary identifies a relationship between inflation rates and international interest rate differentials.

The rising cost of funds internationally is forcing multinational corporations to pay more attention to effective cash management on a global basis. However, the available literature is preoccupied with cash management in only one currency. This is a serious oversight given the heavy involvement of U.S. firms overseas. In 1970, for example, the ratio of foreign source earnings plus income from abroad (royalties, fees, service charges) to total U.S. corporate after-tax profits was over 25 percent [14]. If export and import activities were included, this statistic would be more impressive yet.

In a recent article in this Journal, Amir Barnea [1] proposes a criterion for assessing the market-making efficiency of New York Stock Exchange specialists. The appealing aspects of Barnea's method are that it uses publicly available data (common stock prices) and operates on a variable of primary concern to investors, the variance of returns on common stock. The difficulty we see in applying his approach, however, is that Barnea's performance criterion can be sensitive to a number of factors in addition to any impact the specialist might have, and that effective specialist intervention might have either a positive or negative impact on the performance measure. Thus, his specialist ranking seems to be quite misleading, and his empirical findings appear to be amenable to a substantially different interpretation than that which he provides.

In my paper utilized time-variance relationships to detect the impact of NYSE specialists on stock price changes. Schwartz and Whitcomb (SW) seem to agree that return variability and not average bid ask spreads is the appropriate measure on which performance of NYSE specialists should be evaluated. They raise, however, several objections regarding the use of time-variance relationships to evaluate specialists' performance. In particular they show that the proposed performance measure which is the average (per specialist unit) ratio of short term relative to long term return variance depends on the degree of autocorrelation in the return series. For first order serial correlation of returns they obtain,

where r is the performance measure (in terms of a single security),

T is the length of the differencing interval,

are returns variances for one day and T day intervals respectively,

ρ1,2 is first order serial correlation.