The purpose of this paper is to examine the intertemporal relationship between variations in the prices of individual common stocks and variations in the rest of the stock market. Empirical data are analyzed to determine the frequency with which stock prices precede, occur simultaneously, and follow movements in the market average.

The structure and analytical representation of investors' utility-of-wealth functions has long been of interest in portfolio theory. In proposing convenient analytical utility functions most economists have used (i) constant elasticity (power) functions, (ii) the negative exponential function. Both (i) and (ii), of course, restrict the preference structure; Moreover, one may object to (i) because such functions are not uniformly bounded on [0, ∞). And, as has been shown by Arrow [1], this is undesirable in an axiomatic system. The negative exponential function has no such disadvantage, but objections may be raised on empirical grounds. Thus, no simple convenient specification of bounded utility functions on [a, ∞) is available. In fact, even polynomials in wealth of arbitrary order are restrictive since they immediately impose the requirement that moments of wealth are finite. (If the polynomial is of order n, then the nth moment must be finite.)

The comment by Linke and Kim correctly observes that the assumption regarding the maintenance of constant proportional use of capital sources is not appropriate for our argument and should be deleted. As our analysis did not make use of this assumption, the two conclusions hold.

1. The weighted average cost of capital calculated with the usual weights (original capital structure proportions) is not in general equal to the discount rate which equates the current value of the firm to the present value of future cash flows.

2. The above conclusion holds for any weights which can be constructed from the cash flows.

State-preference theory has developed as a choice-theoretic framework through which many problems of finance and economics dealing with time and uncertainty can be analyzed. Hirshleifer [3], [4], [5], [6] has used the approach to provide significant insights to areas such as production and exchange, investment decisions, and speculative behavior. However, the theory has not made progress in attempting to incorporate state-labeled utility functions into the body of the theory. This paper will develop a method of graphically and analytically allowing for differing utility functions across states. As a further step, the impact of belief-deviation upon the tangency optimum will be discussed. Finally, the significance of these findings upon the consideration of risk will be discussed.

The measurement and determination of risk have received considerable attention in recent years. One measure of risk is systematic risk, defined in terms of the covariance of a security's return with the return from the market portfolio. The relationship is often standardized by dividing the covariance by the variance of return from the market portfolio. Hereafter, this measure of standardized systematic risk shall be referred to as beta.

Statistical analyses of price series generated by auction markets has been oriented historically toward the detection of structure (or lack of structure). While the results of such studies have been mixed, insufficient empirical evidence has been obtained on the properties of the measures employed to capture the inherent behavior of the price series. The first differences of the closing price have been shown, theoretically, to be unbiased for a random walk process. The use of averages, particularly the first differences of the midrange, has been shown to introduce spurious serial dependence in mathematical time series. It is the purpose of this article to examine the properties of both the delta close and delta midrange as measures, and to perform a variety of statistical tests and analyses to establish empirically the relationship between them. The predominant effort in seeking this relationship consisted of the spectral analysis of 11 years of May potato futures prices. The results obtained support the contention that the delta midrange amplifies the delta close, and that the amount of amplification is stochastic distortion in the delta midrange.

Early studies on the effect of holding company affiliation on bank performance yield some curious results (see [9], [11], [12]). Specifically, these studies did not find that holding company affiliation results in changes in capital-asset ratios or bank profitability.

In his comment [1] Professor Frankle raises four potential problems that may have had an influence on the empirical results that I obtained when testing my model describing convertible bond prices [2]. Two of the points are interrelated and do much to explain the problems with the original empirical work. The other two points probably did not have an influence on the final outcome.

New stock financing is assuming increasing significance as a source of funds for private firms. The problem of management of external financing has grown as well. As a practical matter, financial managers must depend on the assistance of underwriters with respect to pricing and distribution of new corporate stock. But recent changes, some set in the context of the capital asset pricing model, imply systematic underpricing of new securities. If these charges are true, the financial manager is faced with the dilemma of paying monopsony profits, or accepting the cost and risk involved in taking the issue to market without the investment banker, or seeking an alternative source of funds. In any event, the process of marketing new equity depends on the relationship among the many characteristics unique to the firm and that firm's cost of equity capital. This paper discussed these interrelated issues.

Two prominent views pertaining to measures of risk aversion can be found in the literature. First, Arrow [2] and Pratt [3]developed risk aversion measures based on the curvature characteristics of the individual investor's utility for wealth function. If the investor's utility for wealth function is given by V(W), then

are the Arrow-Pratt measures of absolute and relative risk aversion, respectively. The investor is risk averse or a risk lover as r(W) and r* (W) are positive or negative. The investor exhibits increasing, constant, or decreasing absolute risk aversion as while he exhibits increasing, constant, or decreasing relative risk aversion as .