This study's purpose was to construct a performance criterion for New York Stock Exchange specialists which relates to their ability to affect price variability. It was emphasized that the price-setting behavior of the specialists, at times when trading imbalances prevail in the market, is the most important aspect of their performance. Their performance in this dimension may or may not be associated with their willingness to supply immediacy services to small orders. While the bid-ask spread is the correct variable to measure when the latter is considered, price variability or, more precisely, the functional relationship between price changes and trading imbalances is the variable to be measured when the price-setting behavior is of interest. While the experiment to evaluate the price-setting behavior of NYSE specialists using publicly available data may be considered a pioneer study, other studies have estimated the determinants of the bid-ask spread. The contributions of this study to the analysis of the spread can be summarized as follows: (a) observing an independent “specialist effect” on the size of the spread, (b) estimating the spread-volume relationships using a simultaneous system, and (c) estimating the association between the specialists' performance on both spread and price dimensions of their activity. The finding of this study is that there is a positive correlation between the quality measure of performance on both dimensions.

The Markowitz-Sharpe market model has been extensively applied to the study of price behavior of American common stocks. In this paper an international market model will be used assuming that the return on any security is a linear function of the return on the world market portfolio. A justification for this approach lies in the International Asset Pricing Model (IAPM) proposed by Solnik [14] and [15]. This market model is by no means the only stochastic process of security returns consistent with the IAPM, but it is the most simple and straightforward extension of the traditional approach to domestic markets.

The purpose of this paper is to indicate that the opportunity to obtain information regarding the probability distribution of the return on a risky asset, such as a portfolio or a mutual fund, may cause a risk-averse decision maker to accept a single-period actuarially unfair gamble. This behavior is the same as that implied by utility functions that have convex segments, as originally considered by Friedman and Savage [2] and by Markowitz [12], but the utility function derived is not convex on any interval, since it is the envelope of a finite set of strictly increasing, strictly concave functions. Similar utility functions have been obtained, by Fleming [1] because of transactions costs, by Hakansson [4] by imposing a borrowing restriction on an investment-consumption model, and by Masson [14] in the context of an imperfect capital market. In this paper acceptance of single-period actuarially unfair gambles by an individual risk averse with respect to future wealth levels results from the opportunity to acquire information. The acquisition of information creates a set of conditional decisions each of which the individual may treat in an optimal manner, and that set of conditional decisions may induce risk-taking behavior.

For many years, the stock option has been an investment device used primarily by speculators and some “sophisticated” investors. During the past few years, much more attention has been paid to options by mutual funds, insurance companies, and conservative investors who previously showed little concern for this investment alternative. The opening of the Chicago Board of Trade's exchange for the trading of options will lead to even wider interest in the area.

This paper examines the validity of two widely used methods for forming conditional predicted portfolio returns. The first method relies on a one-period, mean-variance theory of equilibrium expected return, sometimes referred to as the “capital asset pricing model” (CAPM). The second method is based upon a proposal by Markowitz [14] and is called the [market model] (MM).

The objective of this paper is to determine upper bounds of the potential savings that can be realized by the application of cash management optimization models. These upper bounds are found by simulation as the difference between the performance of a deterministic optimization model--which finds the optimal policy in hindsight--and the simulated performance of a hypothetical treasurer who uses simple heuristic cash management rules as informally practiced by many treasurers, based on prediction of random cash flows. The results of this analysis leave serious doubts as to profitability of cash management optimization models.

A link between the firm's operating decisions and the riskiness of its stocks was established. Differences in the production process affecting the relative shares of fixed and variable costs (i.e., the operating leverage) were found, both analytically and empirically, to be associated with risk differentials. Specifically, other things equal, the higher the operating leverage (i.e., the lower the unit variable costs) the larger the overall and systematic risk of the stocks.

Various practical implications are suggested by these findings. On the firm level, it can be expected that large capital expenditures associated with an operating leverage increase will increase stock riskiness. In these cases, the cut-off rate used for the capital budgeting decision (i.e., the cost of capital) should allow for the increased risk. The use of the current cost of capital as the cut-off rate would probably result in a decrease in stock prices, adversely affecting stockholders' wealth. On the investor level, these findings might assist in the estimation of common stocks' risk given expected changes in the firm's operating leverage. Specifically, they suggest that, if a firm will experience a significant operating leverage change, the estimation of risk measures based exclusively on historical returns would be inappropriate.

In considering trade credit, we need to ask three questions:

1. Why do nonfinancial firms commonly participate in the process of financial intermediation by extending credit to their customers?

2. What explains differences in credit periods between firms and industries as well as over time for specific firms and industries?

3. How do changing monetary conditions affect the credit that firms extend to their customers?

To answer these questions, we first identify two reasons for credit sales: the first we might call a financing motive, and the second a transactions motive. The transactions motive can readily be understood—it costs something to match the time pattern of payment for goods with the time pattern of receipt of goods. Buyers benefit if bills are allowed to accumulate for periodic payment. Furthermore, trade credit gives buyers time to plan for the payment of unexpected purchases, enables them to forecast future cash outlays with greater certainty, and simplifies their cash management. To the extent that buyers benefit, sellers have an opportunity to sell credit. It is likely that, to a large extent, the aggregate stock of trade credit is explained by the transactions motive.

Many of the typical problems encountered in forecasting a time series are alleviated when the series follows a seasonal pattern. The seasonal effect is independent of a long-term trend and cyclic effect. Furthermore, since the seasonal effect is recurrent and periodic, it is predictable. Thus, when the time series follows a seasonal pattern, the general shape of the series is known. Questions regarding the growth trend of the series, the expansion and contraction of the seasonal pattern, and random variation affecting the series are, however, left unanswered.

The shortcomings of a quadratic utility function are so serious and so widely known that by now one might assume that it would simply have been dropped from consideration. Arrow [1] and Pratt [6] have shown that such a function implies ever increasing absolute risk aversion, that is, reduced risk taking as wealth increases, which contradicts everyday experience. Moreover, the assumption of quadratic utility also implies ultimate satiation with respect to risk taking. This function has a well-defined maximum beyond which the marginal utility of money declines, and as a result the range of admissable returns must be restricted. Wippern [12] has focused attention on the second of the above two shortcomings. Using a rather ingenious device, based on the Sharpe-Lintner market model [8 and 5], Wippern has measured empirically the admissable range of returns implied by the quadratic utility function. Since his empirical findings imply that returns beyond as little as 1.3 standard deviations from the expected return provide negative marginal utility to investors, Wippern concludes that the Sharpe-Lintner market model, and/or the mean-variance portfolio theory upon which it is based, have “inconsistent and implausible properties.”