Knowledge that Transforms

Industry analysis has long been a cornerstone in both the academic and professional segments of the investment community. Concepts such as “an industry providing downside protection” or “another is certain to outperform the market” have been prevalent throughout the profession. The importance of industry analysis in terms of stock price changes has been suggested by King, while the influence of the industry factor on corporate earnings changes has been documented by Brown and Ball. These studies and others have indicated that industry analysis has been an important part of security valuation.

Since the Second World War the corporate pension trust has become a prominent method of provision for employees' retirement income. The continuing liberalization of pension provisions and pressures to match pension trust liabilities with assets has established pension contributions as a significant component of corporate cash outlays. Asset accumulation in pension trusts has rendered such institutions a major source of capital funds.

Burton Zwick, Comment: The Effect of Interest-Rate Risk on Liquidity Premiums: An Empirical Investigation, The Journal of Financial and Quantitative Analysis, Vol. 9, No. 5, 1974 Proceedings (Nov., 1974), pp. 911-913

Among the topics that have been subjected to intensive research by businessschool scholars over the past two decades, few have received more attention than those which collectively comprise the field of investments. What is more important, even fewer have witnessed the plethora of important research findings that has been forthcoming in the investments field. Indeed, it seems reasonable to argue that in recent years no other business field's research accomplishments have been either as impressive or as generally reinforcing.

Mark Nelson, Comment: Evaluative Techniques in Consumer Finance--Experimental Results and Policy Implications for Financial Institutions, The Journal of Financial and Quantitative Analysis, Vol. 9, No. 2 (Mar., 1974), pp. 285-286

Econometric research in the past two decades has vitnessed a considerable use of dummy variables in regression analysis. The analysis of covariance has long been a standard statistical technique to test the equality of coefficients in linear regressions. While students and researchers are generally aware of the close relationship between the two methods, they are often frustrated at choosing one method instead of the other in practice and wonder whether the two methods lead to the same test results. This note shows that the two methods are equivalent from the point of view of hypothesis testing.

It has been suggested that information has the three following uses:1. Information can be employed to earn trading profits.2. Information can improve the operating decisions of a firm or group of firms and thereby increase the stock price.3. Information can reduce the risk of a firm or group of firms and thereby increase the stock price.

This paper seeks to document some simple and not-so-simple facts. My thesis is that, to an unprecedented degree, Federal Reserve (F.R.) Board Chairman Arthur Burns has engaged himself and the System in political action. Burns' leadership has contributed to politicizing the monetary control process, the dialogue concerning the nature and effects of that process, and perhaps even F.R. decisions themselves. These tactics have reduced the Federal Reserve's power to resist external political influence, a power that Chairman McCabe “bled” for in 1951 and that over the next two decades Chairman Martin labored assiduously to consolidate. On the other hand, this behavior at least maintained and probably increased Burns' standing with President Nixon.

Professor Melicher has conducted an interesting study of the effects of financial factors on beta coefficients and their variations. He reduced the perennial multicollinearity problem by using a factor analysis to screen the financial variables used in the statistical analysis. This study is another in the growing body of literature concerned with beta coefficients as measures of risk. My comments on this paper will consider separately (1) the research design (i.e., what the study directly covered), and (2) the inferences drawn by the author versus what the beta coefficients and their variation really do measure.

It has been said [2, 4, 5, 6, 7, and 8], and it seems to be widely accepted, that the geometric mean of the price relatives of a group of securities can be interpreted as the return which would have been earned on a portfolio of those securities, managed continuously over time to maintain an equal money investment in each security. This is a theoretical concept which could not be implemented literally by a portfolio manager, but it can still be treated rigorously in a mathematical sense. In a recent paper in this journal Rothstein [8] defined continuous reallocation as the limiting case of a policy which does have an operational definition. He showed that the index corresponding to a policy of the equalization of dollar investments approaches the geometrically averaged index as its limiting value. We shall argue that this interpretation of the geometric mean is a misleading one, since it depends upon assumptions which imply serious market inefficiencies.