Has International Financial Integration Increased?

This paper compares the behavior of real interest rate differentials across the major countries under the Bretton Woods regime and the regime of floating exchanges that replaced it. The primary object is to investigate both the extent of market integration and its changes over time. For all fifteen possible country pairs real interest differentials are mean reverting, and in two-thirds of these cases indistinguishable from zero statistically. For all country pairs on average and for most such pairs individually, moreover, the estimated differentials are not appreciably different in absolute value than the differentials that we estimate for various money-market rates within the United States. Additional evidence points to a narrowing of differentials under floating rates over time and an increase in speeds of convergence.     

The Causal Relationship Between Real Estate and Stock Markets

This paper examines the dynamic relationship that exists between the US real estate and S&P 500 stock markets between the years of 1972 to 1998. This is achieved by conducting both linear and nonlinear causality tests. The results from these tests provide a number of interesting observations which primarily show linear relationships to be spuriously affected by structural shifts which are inherent within the data. Linear test results generally show a uni-directional relationship to exist from the real estate market to the stock market. However, these results are not consistent with financial theory and for all sub-samples of the data. In contrast, the nonlinear causality test shows a strong unidirectional relationship running from the stock market to the real estate market, and is consistent in the presence of any structural breaks.     

Speed of adjustment of the current account: an international comparison

A model of the current account using a mean-reverting Ornstein–Uhlenbeck process is developed and tested for three different measures of the current account. The results show very different adjustment patterns for the current accounts of seven large develpoed countries. This information can be very useful for further detailed analysis of behavior within these individual countries. We find that with the exception of Canada and Japan all countries have a constant long-term mean which, in most cases, was not significantly different from zero. The speed of adjustment to the mean was always between 0 and 1. France and Italy exhibited much more rapid adjustment patterns than did the other five countries.     

Accounting for Intangibles: A Theoretical Perspective

This paper uses a transactions theory approach to analyse some of the measurement and disclosure issues involved in accounting for goodwill and other intangibles. The recent professional and academic literature is reviewed and the traditional economic theory approach to interpreting accounting issues in these areas is criticised. A form of transactions theory called ‘Statistical Transactions Theory’ is then used to investigate several conceptual problem areas, notably: the definition of goodwill and fair values; the distinction between goodwill and other intangibles; and capitalisation, amortisation and valuation issues. The authors conclude that the most fruitful course of action in dealing with these issues would be a substantial research effort designed to investigate the distributional properties of accounting numbers relating to the subject of intangibles measurement, including goodwill as defined in this paper. They call for more analytic and empirical work in this field.     

Modelling mean reversion of asset prices towards their fundamental value

In this paper we extend the study of mean reversion behavior by modelling the fundamental value as a stochastic process. The market value of the asset is then modelled as a mean reverting Ornstein Uhlenbeck process towards the fundamental value. Solving backwards, we determine the functional form of the regression equation of changes in asset prices and returns to changes to the fundamental value. Using earnings and dividends as proxies for the fundamental value we test our model empirically. In general, other than the shortest horizon of 1-year, our model shows good explanatory power. Since our model is compatible with Campbell and Shiller (1988) framework in the earnings case and Fama and French (1988) model in the dividend case, the performance of our model has been compared with those two models. In comparison, the performance of our model is comparable to that of Campbell and Shiller and compares favorably with Fama and French.     

MEAN GINI CAPITAL ASSET PRICING MODEL: SOME EMPIRICAL EVIDENCE

The capital asset pricing model of Sharpe (1964) and Lintner (1965) provides a valid approach to portfolio selection if either the distribution of asset returns is jointly normal or the investor's preference function is quadratic. Various authors have questioned the validity of these assumptions, and Roll (1977) raises the question whether the traditional CAPM can be tested. An alternative Capital Asset Pricing Model has been proposed by Shalit and Yitzhaki (1984). In this model the extended mean Gini coefficient is used to measure risk. As little research has been conducted on this model, this paper estimates systematic risk as derived from the extended mean Gini model for a sample of Australian companies and compares the empirical security market line with the predicted extended mean Gini security market line.     

A Comparative Study of Gini's Mean Difference and Mean Variance in Portfolio Analysis

The methods traditionally used for comparing uncertain prospects are the mean variance and the stochastic dominance approaches. Yitzhaki has recently presented an alternative model based upon Gini's mean difference to compare uncertain prospects. The mean Gini model is similar in nature to the mean variance model in that it uses a two-parameter statistic to describe the probability distribution of risky returns. Theoretically, the mean Gini model is consistent with the behaviour of investors under conditions of uncertainty for a wider class of probability distributions. Thus Gini's mean difference appears to be more adequate than variance as a measure of risk. This study firstly generated the mean Gini efficient frontier and secondly compared the mean variance efficient frontier with it. For the sample data employed, the mean variance model gave a very good approximation to the mean Gini model. Since the computational costs of the mean variance approach were a small fraction of those of the mean Gini approach, the theoretical advantage would not appear in this case to translate into a practical one.