Knowledge that Transforms

The past two decades have seen a proliferation of mathematically sophisticated portfolio selection models. Of these, the mean variance (MV), expected utility, and growth optimal (GO) models have received the bulk of attention.

Over the past years the beta coefficient has been widely used as a measure of systematic risk in investment and portfolio analysis. The validity of using the beta coefficient as the proper measure of systematic risk is dependent upon the assumption that the beta coefficient is stationary over time. Unfortunately, this assumption has been challenged by a number of empirical studies which have found the beta coefficient to be unstable over time. Examples of such empirical investigations are those documented by Blume [4], Levy [12], Levitz [11], Baesel [2], Altman, Jacquillat, and Levasseur [1], and Roenfelt, Griepentrong, and Pflaum [16]. Most recently, Fabozzi and Francis [9] reported that some security beta coefficients tend to be random over time. Their findings also support the regression tendency of the beta coefficients towards the mean over time, as found by Blume [4]. Thus, because the beta coefficient is changing over time, the use of the ordinary least-squares (OLS) method in investment and portfolio analysis will yield an inefficient estimate of systematic risk. Furthermore, the OLS estimates of security and portfolio residual risks will be influenced by the variability of beta coefficient. Therefore, the purpose of this paper is to investigate the relationship between the variability of the beta coefficient and portfolio residual risk, and hence to provide a real picture of the process of portfolio diversification under the condition of beta nonstationarity. It is shown that the use of the OLS method to estimate security and portfolio residual risks will produce an incorrect conclusion that larger residual risks tend to be associated with higher variability in the beta coefficient.

Cash concentration is the task of moving funds from depository banks into the central cash pool. It is useful to structure cash concentration by dividing it into two major problems––management and design. Management is the day-to-day operation of the cash concentration system once it is designed. Design is specifying the structure of the cash concentration system.

Peter J. Ryan, Jean Lefoll, A Comment on Mean-Variance Portfolio Selection with Either a Singular or a Non-Singular Variance-Covariance Matrix, The Journal of Financial and Quantitative Analysis, Vol. 16, No. 3 (Sep., 1981), pp. 389-395

Cheng-Few Lee, J. Kenton Zumwalt, Associations Between Alternative Accounting Profitability Measures and Security Returns, The Journal of Financial and Quantitative Analysis, Vol. 16, No. 1 (Mar., 1981), pp. 71-93

The stationarity of beta factors has received considerable attention in the financial economics literature. One particular area of study has been to investigate how the measured stationarity of beta factors changes over data sets of varying lengths. By increasing the length of the estimation period, sampling fluctuations may be reduced; however, the probability of beta factors having changed will increase. The optimal data set length, then, involves a trade-off between these two opposing phenomena. Baesel [2] reported the empirical finding that the stationarity of beta was, indeed, dependent upon the estimation period length over which beta factors were estimated. He found, using transition matrices that beta stationarity was an increasing function of the calendar period used for beta estimation. In this paper, analytic expressions will be derived to explain how and when this empirical phenomenon arises. Conditions will be presented for beta stationarity to increase with calendar period length, and it will be demonstrated that beta stationarity will not increase indefinitely with estimation period length. An identical condition is required for beta stationarity to be an increasing function of the subsequent calendar period length. This phenomenon was empirically investigated by Roenfeldt, Griepentrog, and Pflaum [6], and the analysis presented here explains, in part, their findings.

In this paper Ho and Saunders apply a model that has been used to analyze dealer spreads to banking.A potential contribution to a field can arise whenever a well-developed framework of analysis in one problem area is applied to another field. The risk of a mechanical application, however, is that the institutional structure of the two problem areas is so different that no real insights are gained. What are the facts here?

Edward I. Altman, Menachem Brenner, Information Effects and Stock Market Response to Signs of Firm Deterioration, The Journal of Financial and Quantitative Analysis, Vol. 16, No. 1 (Mar., 1981), pp. 35-51

Analysis of the growth record of many economies indicates that foreign capital is an important factor in the process of economic development. For many developing countries, a continuing flow of foreign funds is necessary if desired growth targets are to be achieved. These funds are most likely to be in the form of loans rather than grants. This link between economicdevelopment and debt accumulation manifested itself in the enormous growth of less developed countries’ (LDCs) external indebtedness in recent years, especially after the oil crisis of 1973.

In an efficient capital market, prices fully reflect available information and adjust to new information in a rapid and unbiased fashion. As a result, prices provide unbiased estimates of the underlying values. No known trading rule or security selection strategy which uses only publicly available information would provide an investor with the ability to earn, on average, positive “abnormal” returns in a market that is efficient in the semi-strong sense. Thus, a finding that common stocks selected, using a readily available, widely disseminated set of rules which requires only publicly available information for decision-making purposes, earn, on average, positive abnormal returns represents strong contradictory evidence regarding the semi-strong form of the efficient markets hypothesis.