OPTION PRICING AND THE ARBITRAGE PRICING THEORY

This paper applies the arbitrage pricing theory to option pricing. Under certain distribution assumptions or the assumption that there is only one common factor, the underlying asset of an option is the sole risky factor that explains its expected return. Based upon this relationship, a new and simple option-pricing formula is derived, and some important existing option-pricing formulae are reproduced. Empirical results show that the new formula performs as well as the Black-Scholes formula.     

On a family of data-based transformed models useful in forecasting technological substitutions

This paper examines, via real data, some well known models for technology substitution analysis. We propose a family of data-based transformed models that will include the models under examination as special cases. The basic thrust of the paper is the recognition that for technology substitution analysis, the observations are time series data and hence are not independent. Also, the functional form of the model should be determined by both theoretical considerations as well as the data on hand. This suggests that the traditional ordinary least squares procedure used in estimating the parameters and the resulting forecasting procedures are not adequate. The existing models examined here are Fisher–Pry, Gompertz, Weibull, and Normal. We stress the statistical aspects of the models and their relative merits in terms of predictive power. The criteria used for the purpose of comparison are the mean squared deviation and the mean absolute deviation of the predicted values compared with the actual observations.     

Gains,Losses, and the US-EPA <Emphasis Type="Italic">Economic Analyses Guidelines</Emphasis>: A Hazardous Product?

While offering many useful suggestions to improve economic analyses, the Guidelines take no account of widely reported behavioural economics research findings. Foregoing the opportunities to improve valuations and other analyses offered by this evidence is likely to lead to inappropriate assessments and consequent distortions of damage estimates, policy and regulatory design. JEL classifications: C91, D61, H43 This review is in part based on studies supported by the U.S. Forest Service and has benefited from comments and suggestionss of Bas Donkers, Robin Gregory, the editor, and referee.