Knowledge that Transforms

Installment credit grantors require a method of distinguishing delinquent borrowers from whom an extension will be likely to result in repayment of the loans from those for whom the probability of repayment is too low to warrant further expenditure and against whom additional collection efforts would be unprofitable. A method evolved from the techniques utilized in the Marginal Credit Risk Study in the attempt to distinguish personal bankrupts, who in filing bankruptcy could be presumed to express the intent to not repay, from petitioners filing under Chapter XIII of the Bankruptcy Act and debt counselees who, under both plans, voluntarily enter programs for the repayment of their debts.

This paper has considered the sequence of optimal credit expansion decisions of a bank operating under the legal structure imposed by the Federal Reserve System. Two alternative structures are considered, one relating to the pre-September 1968 period and the other to the currently enforced one. Using dynamic programming techniques, a closed-form equation for the optimal credit expansion decision has been derived in each case. The optimal level of credit expansion has been shown to be a nonlinear function of the prevailing interest rate, the parameters of the distribution of reserve losses, and several parameters set by Federal Reserve policy. The presence of uncertainty in the model has been shown to have an indefinite effect; however, several policy parameters may be chosen so as either to restrict or to encourage expansion to levels below or above the simple certainty prediction. These results are intuitively in accord with those of general inventory studies.

In many nonlinear programming applications the objective function has an inherent uncertainty that depends upon a set of random variables that have a known distribution. If one wishes to optimize the expectation of the objective, as suggested by the expected utility theorem, then as is shown here one can often solve such problems by modifying standard nonlinear programming algorithms. To illustrate what is involved, the details and justification for the application of the interior parametric sequential unconstrained maximization technique and the generalized programming method for the solution of such problems are given. Some related problems with stochastic constraints for which the solution method applies are mentioned and an example of a portfolio selection problem is given.

Robert J. Monroe, James S. Trieschmann, Portfolio Performance of Property-Liability Insurance Companies, The Journal of Financial and Quantitative Analysis, Vol. 7, No. 2, Supplement: Outlook for the Securities Industry (Mar., 1972), pp. 1595-1611

For almost a decade, Myron Gordon has argued repeatedly that an enterprise's dividend policy can affect its share price [2, 3, and 4]. The essence of his argument is that risk-averse investors are likely to perceive current dividends as less risky than future ones. Consequently, a corporate decision to reduce current, in favor of increased future, dividends will reduce share prices, even when the funds are invested to yield the firm's cost of capital.

By examining the annual data from 1937-1967, we found that odd-lot volume has become loss important in the market in recent years. Although the odd-lot trading volume has increased steadily in the absolute term since the end of World War II, the share of odd-lot trading in relation to total round-lot volume has been declining. By 1967, the percentage of odd-lot volume to round-lot total sales was down to 11.6 percent. The same data also indicate that odd-lot short sales have increased moderately since 1962; however, the volume is quite insignificant. The average of odd-lot short sales to total round-lot short sales for the 31-year period is only 1.9 percent. Odd-lotters were also found to be net purchasers during this period (1937-1967); however, odd-lotters have turned into net sellers in recent years. The total net sales from 1961 to 1967 amounted to 22.2 million shares, which is approximately 25 percent of the total net purchases of the entire period (1937-1967).

Unfortunately Professors Arditti and Levy (A-L) in their comment published in this issue of this journal did not realize that the determination of the investor optimum in my paper [1] was simultaneous with respect to the three parameters, the mean and the variance and the third moment of portfolio returns. When the nth moment was introduced, it was assumed that the investor chooses on the basis of all n parameters — the mean, second moment, third moment, etc. — through the nth moment.

In [2] Hakansson and Liu presented a multiperiod portfolio model in which there is an optimal myopic policy. In particular, at any decision point j and state m the optimal amount to invest in opportunity i, namely , may be found by maximizing(42a) subject to(42b) (42c) , where the expectation is taken with respect to the β's, and the p's and r are positive constants (r > 1). Assumptions are made in [2] which guarantee that (42) has a unique optimal solution and that the set of vijm which satisfies (42b and 42c) is a nonempty, compact, convex set for all j and m.

Using the mean-variance model, Sharpe [5] and Lintner [4] have derived an equilibrium model for price determination under uncertainty. Jean [2] has tried to generalize this model so that other moments of the distribution will be taken into account. The purpose of this note is to show that unlike the Sharpe-Lintner model, Jean's results make no economic sense.

This paper is a selective review of the received theory of financial institutions with some suggestions regarding future research on this topic. The major emphasis is placed on the positive economic theory of these firms. Financial institutions are considered to be firms that supply financial securities and contracts held as assets by other sectors of the economy and that use the proceeds of these sales to finance the purchase of financial securities and contracts which are the liabilities of other economic units. The theory discussed here is stripped of much of the regulatory and legal framework surrounding financial institutions. The primary reason for so limiting the scope of this paper is a conviction that a reasonably complete model of a simple financial institution is a necessary precursor to useful models of the positive economic behavior of financial institutions in any specific legal, regulatory, and operational framework. While recognizing that no tractable model of a financial institution is likely to be so general as to avoid the problem of model specificity, I take the view that many of the questions asked in the literature would be better answered in less specific models, i.e., in models capable of explaining additional important aspects of the behavior of the financial institution in question.