Knowledge that Transforms

Robert H. Litzenberger, O. Maurice Joy, Charles P. Jones, Ordinal Predictions and the Selection of Common Stocks, The Journal of Financial and Quantitative Analysis, Vol. 6, No. 4 (Sep., 1971), pp. 1059-1068

The pivotal role of earnings expectations in equity valuation and therefore in certain areas of business finance is widely recognized, yet there is little theoretical or empirical evidence as to the manner in which investors and other groups actually formulate their estimates of future earnings. The resulting necessity to utilize proxy or indirect measures of expected earnings specified largely according to the predispositions of the investigator has led to numerous difficulties in the testing of cost of capital propositions and models of equity valuation.1 This study is intended to supply a preliminary response to the question of how earnings expectations are determined by appraising the extrapolative component of a limited sample of short-term estimates of earnings per common share. More specifically, the issues are the extent to which the earnings estimates (1) are extrapolative in nature and (2) may be approximated by familiar, naive, extrapolative techniques. In this context, “extrapolative” simply means determined by application of a specified weighting scheme to prior observations in the time series.

This paper presents a discrete stochastic programming model for commercial bank bond portfolio management. It differs from previous bond portfolio models in that it provides an optimization technique that explicitly takes into consideration the dynamic nature of the problem and that incorporates risk by treating future cash flows and interest rates as discrete random variables. The model's data requirements and its computational demands are sufficiently limited so that it can be implemented as a normative aid to bond portfolio management. In addition, it can be extended by the addition of other asset and liability categories to serve as a more general model for commercial bank asset and liability management.

A substantial amount of scholarly effort in recent years has been devoted to the determination of the relationship between banking structure and performance. In general, the results of these studies indicate that banking structure affects both the price and quantity of banking services, but, for practical policy purposes, the impact of banking structure is quite small. Yet, the results of these studies have been inconclusive and contradictory to a substantial degree.

The Sharpe or diagonal portfolio model has been accepted by a large segment of both academic and practical researchers in portfolio theory. The model is tractable, requires a relatively small set of inputs, and is viewed by many to present “reasonable” assumptions regarding the workings of the security market.

A portfolio frontier superior to the Markowitz one-period buy-and hold efficient frontier does exist. Such a superior frontier can be generated by pursuing a rebalancing policy, even under the conditions of random walk. By rebalancing we mean that an investor maintains a fixed but optimal set of weights among the securities in a portfolio throughout an investment period by buying and selling securities at the end of some predetermined intervals.

The relationship between capital market equilibrium and firm financial policy has received extensive attention in recent years. Until recently, accepted theory was generally consistent in its view that the diversification effect of new investment on firm earnings is a necessary consideration in project selection. In arguing this position, no distinction was made between the perfect market situation exemplified by the models of Modigliani and Miller (M-M) [9, 10, 11] and those of Sharpe [19], Lintner [6, 7] and Mossin [12] (LSM model) and the traditional case in which firm value is not independent of debt policy, e.g., as might be the case if individual investors cannot lever on terms comparable to those available to firms. In a recent article, Mossin [13] examines the implications of the former case of perfect markets. Using a single period model with riskless rate borrowing and lending by individuals and firms, homogeneous expectations, mean-variance portfolio selection, and no taxes, Mossin shows that the effect on the investing firm's value of a new project is independent of the stochastic properties of the other income earned by the firm. This conclusion and the M-M [10] Proposition I follow from the statistical property of Mossin's model that any income stream has the same value regardless of how that stream is divided into the equity or debt streams of one or more firms; or, equivalently, firm value and financial structure are independent. Schall [18] presents a general proof that firm value and financial structure are independent and that firm investment diversification effects are irrelevant in perfect capital markets.

To assure that the commercial banking industry's performance serves the “convenience and needs” of the public, bank supervisory authorities have been vested with broad powers to alter the competitive environment in bank markets. While several criteria have been used to evaluate the effects of entry, merger, branching, and other changes in the allocation of bank resources, the results have been largely inconclusive. Since the regulatory authorities have pursued somewhat conflicting objectives in seeking a “failure-proof” system that is also “efficient, ” there may be no single criterion for evaluation of bank behavior that is wholly consistent with the behavior predicted by the neoclassical theory of the firm.

Articles by Sharpe [1], Lintner [2], and Hastie [3] introduce concepts of systematic and unsystematic risk associated with portfolio rate of return. Defining risk as variation in portfolio return, such risk comprises two elements:1. Systematic risk or variation, which is the covariation of portfolio rate of return with market rate of return.2. Unsystematic risk or variation, which is the difference between total portfolio variation and systematic variation. Unsystematic variation is therefore variation due to attributes of individual securities.

Robert H. Litzenberger, A. P. Budd, A Note on Geometric Mean Portfolio Selection and the Market Prices of Equities, The Journal of Financial and Quantitative Analysis, Vol. 6, No. 5 (Dec., 1971), pp. 1277-1282