The objective of this study is to determine the impact of money market conditions and a bank's regulatory environment on the interest rates banks charge on their loans. This is accomplished through the analysis of the effect of these impacts, in a multiperiod framework, on a bank's optimal investment and borrowing decisions and the minimum required rate of return on its asset portfolio.

The familiar two-parameter model for portfolio decisions, attributed to Markowitz [11], has individuals maximizing an objective function, ϕ [E(Y), V(Y)], of mean and variance of end-of-period wealth, subject to a constraint imposed by initial wealth. In the usual version there is an arbitrary number, n, of risky assets with stochastic end-of-period values (price plus dividend) represented by the vector X with exogenously given mean vector μ and nonsingular variance matrix σ. There is also one riskless asset, whose certain end-of-period value per dollar invested is p. Final wealth, as constrained by initial wealth, W, is given by Y = WP + a' (X – OP), where a and P are vectors of risky asset quantities and prices. Assuming ϕE > 0 (wealth preference), ϕV < 0 (risk aversion), and that the Hessian of $ is negative and semidefinite, portfolio optimum calls for ϕE(μ − OP) + 2ϕVσa = 0, or

This paper shows that the integer efficient frontier for capital budgeting problems can be computed using a modified Markowitz approach. It is shown that if the quadratic integer capital budgeting problem is reformulated as a parametric programming problem on the right-hand side of the return constraint, the problem indicated by Baum, Carlson, and Jucker [1] is eliminated. The traditional Markowitz approach is to formulate the problem as an objective function parametric programming problem. Baum, Carlson, and Jucker [1] show that the traditional approach cannot generally be applied to solve quadratic zero-one integer capital budgeting problems. They show that this approach may fail to identify some efficient points. The failure results from the objective function parametric programming approach. Even though the objective function and the right-hand side parametric programming approaches are equivalent in the continuous case, they may not be equivalent in the integer case.

Empirical tests of the Sharpe [36]–Lintner [23]–Black [3] Capital Asset Pricing Model (CAPM) have generally concluded that there is a positive, approximately linear, trade-off between average return and systematic risk (beta) for portfolio returns of common stocks. Most of the empirical studies, however, have reported data for short, usually monthly, time intervals. Exceptions to this rule include Blume and Friend [8] and Sharpe [38, pp. 289–292]. Their data provide evidence that long-term wealth ratios are concave, possibly nonmonotonic, functions of beta. These data are surprising since, if returns are intertemporally independent and the linear return model of CAPM is correct, expected multiperiod terminal wealth is a convex, monotone increasing function of beta. The results of this paper provide a theoretical framework for interpreting the long-term empirical data which does not violate the notion of a monotone increasing expected terminal wealth-beta relationship.

Since the landmark article of Thomas Navin and Marian Sears on the rise of the market for industrial securities in the Business History Review (XXIX, June 1955), there has been an active interest in the causal relationship between the remarkable upsurge in corporate mergers of industrial companies early in this century, and the greater activity of the securities markets. Professor Smiley adds to this literature with a study of interest rates and the growth of activity in what contemporaries called “financial banking” (lending money for transactions in securities) as opposed to commercial banking. There are limits to the inference of cause and effect relations from financial activity, however, and historians must continue to study these phenomena merger by merger in order to draw conclusions as to the reasons for them.