A note on the Robust Trend and ARARMA methodologies used in the M3 Competition

This brief note describes two of the forecasting methods used in the M3 Competition, Robust Trend and ARARMA. The origins of these methods are very different. Robust Trend was introduced to model the special features of some telecommunications time series. It was subsequently found to be competitive with Holt’s linear model for the more varied set of time series used in the M1 Competition. The ARARMA methodology was proposed by Parzen as a general time series modelling procedure, and can be thought of as an alternative to the ARIMA methodology of Box and Jenkins. This method was used in the M1 Competition and achieved the lowest mean absolute percentage error for longer forecasting horizons. These methods will be described in more detail and some comments on their use in the M3 Competition conclude this note.     

Ratio Analysis Using Rank Transformation

This paper presents an alternate method for transforming financial ratios. Ratios are ranked and scaled into a uniform distribution with boundaries between 0 and 1. Conceptually, we suggest that this method solves a number of methodological problems associated with ratios, including constrained choice of regression models, ratio outliers, negative ratios, and non-normal distributions. Scaled ranks of financial ratios are also conceptually appealing because they appear to capture comparative ordinal data about cross-sectional relationships between firms.The study empirically tests scaled rank transformations by examining the association of the transformations with stock returns. Results show that models using relative ranked accounting ratios have more explanatory and predictive power than untransformed, log-transformed and square-root transformed ratios.     

Contingent Valuation: Controversies and Evidence

Contingent valuation (CV) has become one of the most widely usednon-market valuation techniques. CV's prominence is due to itsflexibility and ability to estimate total value, includingpassive use value. Its use and the inclusion of passive use valuein benefit-cost analyses and environmental litigation are thesubject of a contentious debate. This paper discusses key areasof the debate over CV and the validity of passive use value. Weconclude that many of the alleged problems with CV can beresolved by careful study design and implementation. We furtherconclude that claims that empirical CV findings are theoreticallyinconsistent are not generally supported by the literature. Thedebate over CV, however, has clarified several key issues relatedto nonmarket valuation and can provide useful guidance both to CVpractitioners and the users of CV results.     

FORECASTING VOLATILITY FOR PORTFOLIO SELECTION

The volatility of an asset is a primary input to the portfolio selection problem. Information about volatility is available from two sources, namely the share market and the option market. This paper examines the forecasting performance, over a three month investment horizon, of time series forecasts (from the share market) and option based implied volatilities. Three time series models, including GARCH, are used and twenty four implied volatility estimation models are employed. Using a data set of twelve UK companies, it is demonstrated that implied volatilities produce better individual forecasts than time series. However, more remarkably, forecasts combining implied volatilies and time series estimates significantly outperform both component forecasts.     

The diffusion of successive generations of a technology: A more general model

In many cases of technological development, successive generations of a technology evolve, each more efficient than its predecessor. It has been assumed when modeling and forecasting the adoption of these technologies that the market reaction to each generation was similar. Using the terminology of the Bass model, this similarity is encapsulated in the assumption that the coefficients of innovation and imitation are constant. New data for two and three generations of mobile telephone technology from eleven countries are modeled. The modeling framework used—simultaneous estimation for successive generations using a full information maximum likelihood procedure—demonstrates that, in most cases, the hypothesis of constant coefficients can be rejected. Use of a model with changing coefficients is shown to considerably improve forecasting performance. These results were reinforced by analysis of data for four generations of IBM mainframes.     

An Antitakeover Amendment for Stakeholders?

The non-financial effects (NFE) antitakeover amendment addresses the duties of company directors and management when faced with a possible takeover bid. The NFE amendment either permits or requires managers to consider the interests of the company's stakeholders during takeover bids. Other types of antitakeover devices have been viewed as protecting either stockholder or management interests. The NFE amendment would appear to protect a broad spectrum of interests including those of company employees, creditors, and the community in which the company operates. Positive market returns to the adoption of NFE amendments provide some evidence that investors approve. The percent of both management and institutional ownership are positively related to the market reaction to the NFE amendment adoption. To the extent that institutional ownership proxies for the broad spectrum of stakeholder interest, NFE devices, unlike some other amendments that have been studied, appear to be in the interests of more than a single interest group.     

The Impact of the Electric Car on the US Economy: 1998–2005

This paper presents an exercise in using the INFORUM LIFT macro-economic interindustry model of the US to analyze the industry and macro-economic impacts of structural change in the motor vehicles industry. This structural change is the result of the assumption that 3.6% of US automobiles sold will be electric vehicles by 2003, as a result of California legislation expected to be adopted by 13 states, which will take effect from 1998. In this study, alternative input–output coefficients for the motor vehicles and the automotive repair industries are derived for this mix of electric car production, and assumptions about fuel consumption and maintenance expenditures are also developed. The results of the study show that, although macro-economic effects are minimal, impacts on particular industries are significant, given the small level of market penetration assumed.