Variance Portfolio Research Articles

Patterns of Institutional Investment, Prudence, and the Managerial "Safety-Net" Hypothesis

Patterns of Institutional Investment, Prudence, and the Managerial Safety-Net Hypothesis Introduction The December 7, 1987 issue of Barron's reported that, as of September 30, 1987, the outstanding supply of equity in the U.S. capital markets was estimated to be $3.802 trillion. Of this amount, $1.427 trillion or 37.5 percent was in the hands of institutions. In the third quarter of 1987 alone, institutions purchased $142.393 billion worth of equity and sold $147.960 billion [Palmer (1987)]. Barron's also reported that, in the 13-month period of march 1986 to March 1987, on an average institutions accounted for 43.12 percent of the number of shares bought and 41.48 percent of the shares sold each month on the New York Stock Exchange [Norris (1987)]. (1) The law, recognizing the importance and the welfare implications of the monetary power of institutions, has laid down several crucial constraints, including severe penalties in case of imprudent management, on the investment behavior of institutional portfolio managers. similarly, researchers have long acknowledged the major role of institutional investors in U.S. capital markets [see Cummins, Percival, Westerfield, and Ramage (1980), Ledolter and Power (1984), Cummins and Westerfield (1981), and Demsetz and Lehn (1985)]. However, institutional portfolio managers' methods for selecting their investments in this environment hs received scant attention. Because their activities are governed by laws not applicable to an individual investor, it is conceivable that traditional portfolio selection criteria, such as minimizing portfolio variance for a given level of target return, may not adequately capture all the relevant aspects of institutional investment. Earlier research on institutional investment examined the effect of the passage of the Employee Retirement Security Act of 1974 (ERISA) on private pension plans. For example, Cummins et al (1980) present survey evidence regarding te impact of ERISA on the investment policies of private pension plans. They find that ERISA has caused these plans to adopt written statements of investment policy and guidelines, to purchase fiduciary liability insurance, to place greater emphasis on performance measurement, and to seek an oerall decrease in portfolio risk. Cummins and Westerfield (1981) investigate the impact of ERISA on the level of diversification in the portfolios of private pension plans, and suggest that the observed decline in their portfolio concentration ratios may be due to ERISA which evaluates prudence in the framework of modern portfolio theory. This differs from the traditional rule under common law in which each security in the portfolio had to indiidually qualify as a prudent investment. (2) These authors also documented evidene supporting the two-tier market hypothesis which implies that institutional investors concentrate their activity on the stocks of large firms. (3) This study of institutional investment behavior attempts to determine the impact of the prudent man rule in a broder sense. Particularly, the study investigates patterns of institutional ownership of common stock without discriminating between types of institutional investors. The interest is in determining factors which influence the investment choices of the institutional portfolio manager. The perspective taken is unique in that it incorporates the propensity of institutional portfolio managers to protect their income potential in determining investment choices. The decisions of institutional portfolio managers are distinguished owing to the fiduciary responsibility arising from the handling of client capital. Since managers' performance and investment choices are continually monitored and evaluated, they tend to insure that not only are their investment decisions intrinsically sound, but would be considered by others to be decisions which are reasonable, well-informed, and prudent. This external evaluation of investment choices becomes substantially more significant during times of lack-luster performance. …

Regional Cyclical Instability: An Empirical Examination of Wage, Hours and Employment Adjustments, and an Application of the Portfolio Variance Technique

KURRE J. A. and WELLER B. R. (1989) Regional cyclical instability: an empirical examination of wage, hours and employment adjustments, and an application of the portfolio variance technique, Reg. Studies 23, 315–329. We investigate issues related to regional cyclical instability through an examination of twenty-five years of monthly data for the Erie, Pennsylvania, regional economy. The first portion of the analysis examines the relationship among wages, hours worked per week, and employment in the manufacturing industries. Over the study period, Erie manufacturers tended to adjust to cyclical fluctuations primarily by hiring and firing, and to a lesser extent, by adjusting hours worked per week. The study finds no evidence of cyclical adjustments in nominal wages. The paper then demonstrates the use of the portfolio variance technique in measuring and analysing regional cyclical instability in employment. The portfolio variance measure focuses on interindustry relationships with respect to both the degre...

Hedging Interest Rate Risk with Futures Portfolios Under Full-Rank Assumptions

A spot portfolio of rate-sensitive assets can be hedged by a portfolio of interest-sensitive futures contracts. The hedge ratios of minimum-variance portfolios are unique when the fixed cash flows of underlying instruments are linearly independent and when the covari? ance matrix of unexpected changes in spot rates over the term of the cash flows is of full rank. Hilliard's (1984) full-rank model has produced smaller portfolio variances than a duration model in a short-term hedging context. However, the methodology typically re? quires extensive econometric analysis. This paper develops a structured covariance matrix of full rank that requires only one parameter estimate. Hedging examples are provided.

A Stochastic Generalized Network Model and Large-Scale Mean-Variance Algorithm for Portfolio Selection

Abstract This paper describes a generalized network framework and an efficient, practical algorithm for large scale mean-variance portfolio selection, based on the nonparametric description of stochastic processes in the frequency domain. A constraint on the variance of uncertain incoming flows to a node in a network model results in a quadratic expression, involving the variance aαd covariance of the distributions of these flows. We show that, when the portfolio variance is decomposed into its frequency components using the Fourier transform, this kind of nonlinear side constraint can be relaxed to produce a set of linear side constraints. Our approach based on this relationship is particularly convenient for large scale problems since no covariance matrix input is required.

Note—Naive Diversification and Portfolio Risk—A Note

A number of authors have used the portfolio standard deviation to model the risk reduction advantages of naive diversification. Other authors have pointed out that when risk is modelled by the portfolio's variance the modelling process becomes much simpler and is computationally more efficient. In this note we derive an exact parametric relationship between portfolio standard deviation and size and thus highlight the dangers of using the standard deviation in conjunction with O.L.S. regression techniques to model the risk reduction advantages of naive diversification. It is then shown that past empirical studies which have used this methodology are deficient.

The Application of Errors-In-Variables Methodology to Capital Market Research: Evidence on the Small-Firm Effect

Errors in variables due to nonsynchronous trading and benchmark error are significant problems for capital market research. This paper develops the use of direct and reverse regression to bound true coefficient estimates when the data exhibit error structures arising from these two sources both separately and jointly. The approach appears to have broad applicability for capital markets research. As an example, the paper reexamines the small-firm effect to show that it cannot be attributed to nonsynchronous trading or benchmark error in the estimated variance of the market portfolio. This result is shown to hold even when the tax-selling effect is controlled for by excluding January returns.

MEASURES OF DIVERSIFICATION: PREDICTORS OF REGIONAL ECONOMIC INSTABILITY*

ABSTRACTThis work focuses on determining which measure of regional economic diversification best explains differences in economic instability across regions. One recent article found that a portfolio variance measure had the highest explanatory power. Another researcher found that an entropy measure was best after the model was corrected for heteroscedasticity. Results presented here indicate that, after correction for heteroscedasticity, portfolio variance once again displays the greatest power to explain cross‐sectional variation in observed regional instability.

Implications of the Discreteness of Observed Stock Prices

ABSTRACTStock prices on the organized exchanges are restricted to be divisible by ⅛. Therefore, the “true” price usually differs from the observed price. This paper examines the biases resulting from the discreteness of observed stock prices. It is shown that the natural estimators of the variance and all of the higher order moments of the rate of returns are biased. An approximate set of correction factors is derived and a procedure is outlined to show how the correction can be made. The natural estimators of the “beta” and of the variance of the market portfolio, on the other hand, are “nearly” unbiased.

AN EMPIRICAL STUDY OF THE DIFFUSION PROCESS OF SECURITIES AND PORTFOLIOS

AbstractThe nature of the stochastic process generating the path of security prices through time plays an important role in dynamic theories of financial economics. An important consideration is the possible dependency of return variances on price levels. Using 55 years of data separated into five‐year intervals, this study demonstrates that, in general, security and portfolio variances are dependent on stock price levels and the relationship is a function of portfolio size. The relationship is unstable over time. The results suggest possible detrimental effects of diversification and financial models based on log‐normality are questionable.

Portfolio Analysis with Factors and Scenarios

ABSTRACTRecently there has been a growing interest in the scenario model of covariance as an alternative to the one‐factor or many‐factor models. We show how the covariance matrix resulting from the scenario model can easily be made diagonal by adding new variables linearly related to the amounts invested; note the meanings of these new variables; note how portfolio variance divides itself into “within scenario” and “between scenario” variances; and extend the results to models in which scenarios and factors both appear where factor distributions and effects may or may not be scenario sensitive.

Real and Nominal Efficient Sets

incorporate the influence of inflation in constructing mean-variance efficient portfolios. He used two different sets of data in deriving the portfolio composition. One was the history of nominal returns of securities; the other was the history of real returns. The efficient portfolios derived from the real data differed in composition from their nominal counterparts and were found to dominate them. Solnik [7] has explored the impact of inflation on the composition of the efficient set. He shows that the real efficient set can be expressed as a combination of the real minimum variance portfolio and a second portfolio common to all investors. Although the second portfolio has no net investment (sum of portfolio investment proportions is zero), the amount of it that is held will vary depending on individual tastes. This paper extends the work of Solnik in that it investigates the difference between the real and nominal efficient sets by showing that every nominal efficient portfolio can be transformed into a real efficient portfolio by the additional purchase of a hedge portfolio. The hedge portfolio requires no net investment, has zero expected return, and its composition does not depend on the composition of the nominal efficient portfolio. The derivations and analysis of this hedge portfolio reveals several interesting facts: (1) If there exists one portfolio that is nominal efficient but not real efficient, then no portfolio can be efficient both in real and nominal terms. Similarly, if there exists one portfolio that is efficient both in nominal and real terms, then all efficient portfolios are both nominal efficient and real efficient; the nominal efficient set and the real efficient set are either identical or disjoint. (2) If the real and nominal efficient sets are identical and the market portfolio is efficient, the risk and expected return of any asset is determined by its covariance with the inflation rate. (3) If the real and nominal efficient sets are disjoint, the real variance of any nominal efficient portfolio can be reduced, with no additional net investment, by acquiring the hedge portfolio. The acquisition of the hedge portfolio will reduce the real variance by an amount equal to the covariance between the hedge portfolio and the inflation rate.

A portfolio model for foreign exchange exposure management

This paper summarizes the results of our research into applications of decision analysis and portfolio theory to the management of foreign exchange exposure. In contrast with much current practice in foreign exchange management, the portfolio approach takes into explicit consideration the inherent relationships among the currencies in the company's foreign currency portfolio. The hedging model developed in this article traces out an ‘efficient frontier’ or trade-off curve between expected value and variance of the foreign currency portfolio at the end of the planning period. In doing so, the model chooses the optimal amount and method of hedging for each currency in the portfolio.

A Portfolio Approach to Capital Budgeting: An Application to the Expansion to Additional Product Lines

The importance of the covariance of returns between capital assets is one of the basic principles of modern portfolio theory. An investor should seek capital assets which have negative covariance of returns, or if such capital assets are not available, capital assets with low covariance should be sought for a portfolio. From the variance-covariance structure of returns of the capital assets and the expected returns for each capital asset, a risk-reward trade-off or efficient frontier can be generated. The trade-off represents the minimum risk, as measured by portfolio variance, that could be incurred to realize a desired rate of return for the portfolio. This concept applies to a portfolio of capital budgeting projects as well as to a portfolio of securities. This paper demonstrates how this concept of portfolio diversification can be applied to a capital budgeting problem. The problem involves an actual problem faced by a U.S. distributor who must decide whether to expand sales into one of two industries. Quadratic programming is used to generate the risk-reward relationships and it is shown that the entry into one industry clearly provides a superior risk-reward relationship than entry into the other industry and compared to the company's present sales policy.

ON THE EFFECTS OF STATUTORY INTEREST RATE CEILINGS: COMMENT

A RECENT ARTICLE by Avio [1] presented a theoretical model of the loan market which suggests that an increase in legal loan rate ceilings will not necessarily expand the availability of consumer credit. If true, his result could have important policy implications. However, his model contains deficiencies that make any policy conclusions drawn from it highly suspect and potentially misleading. The problem with the Avio paper is that it is a micro-economic analysis that applies to a single firm with an unrealistic capital constraint. That restraint lets a firm obtain all the capital it wishes at a fixed rate, z, so long as it maintains a minimal cash dictated by its financier. If it does not maintain the minimum required cash reserve, its borrowing rate becomes infinite.' The firm's cash reserve requirement depends on expected portfolio losses, portfolio variance, and a constant. The requirement is curious in that it does not explicitly depend on the financier's expected return, which presumably equals z times the amount of capital extended by the financier. Consequently, Avio does not allow his financiers to lower reserve requirements in order to increase their mean expected returns-in spite of the fact that he does note that some (non-risk-averse) equity-holding financiers might lower reserve requirements in the event that greater portfolio variance existed in order to take a chance on realizing a greater return. The lack of a feedback between the financier's expected rate of return, the cash reserve requirement which the financier imposes on the firm (to reduce his risk), and the amount of capital that the firm is able to obtain from its financier is unrealistic and severely weakens the applicability of Avio's model. In the real world many financiers might be willing to accept slightly more risk in order to increase their expected rate of return or, if not, a firm might be able to change financiers (if it desired) in order to find one that would accept more risk in return for an increased rate of return. In Avio's model, where the amount that can be borrowed at capital cost z is determined by the financier, the firm is basically operating under a potential fixed capital constraint. If the firm is loaned-up, i.e., borrowing as much as it can from a (non-equity holding) financier at rate z while still meeting its cash reserve requirement, it can expand its high-risk loans only by decreasing its holdings of lower yielding, but lower-risk, loans. Elsewise, cash reserve requirements would

Homogeneous Risk Measures and the Construction of Composite Assets

The use of the expected utility hypothesis and the “portfolio approach†has recently become quite popular by both writers in monetary theory and in financial management. Most discussions are given within what might be called the Tobin-Markowitz framework. One very important result recently discussed at some length is the Tobin “separation theorem.†This theorem essentially says that a quadratic preference function, or a normal distribution of returns on risky assets is a sufficient condition for the proportions of the various risky assets in a portfolio to be independent of the proportion of the portfolio held in a safe asset. The proofs of this theorem are given within a framework of the decision maker who minimizes portfolio variance for a given portfolio return, using variance as a measure of risk of the portfolio.

SECURITY PRICES, RISK, AND MAXIMAL GAINS FROM DIVERSIFICATION*

SECURITY PRICES, RISK, AND MAXIMAL GAINS FROM DIVERSIFICATION*