Negotiation support using the Graph Model for Conflict Resolution

The Graph Model for Conflict Resolution is a flexible methodology for systematically studying strategic conflicts in the real world, and is therefore a natural tool for negotiation support. The basic definitions underlying the graph model are reviewed, and the techniques for analysis and interpretation are discussed. The modeling and analysis of a case study, an international trade negotiation concerning the export of Canadian softwood lumber to the United States, are used to demonstrate the practical application of the Graph Model for Conflict Resolution as a negotiation support tool. The modeling and analysis is carried out using the GMCR software system. The ability of the Graph Model for Conflict Resolution to provide insights and advice to negotiators is emphasized.     

International trade in a differentiated good: Trade elasticities in the world rice market

In many previous rice trade models, the commodity has been regarded as a homogeneous product. However, homogeneity is not an appropriate assumption, given the various types of rice that are traded and consumed. Parameters estimated from these models, therefore, do not reflect the real world market for rice and, hence, may mislead decision makers who use the results for policy evaluation purposes. This study uses an Armington approach to model the world rice trade as a differential good market and to derive trade elasticity parameters.     

Simulating the Evolution of the Implied Distribution

Motivated by the implied stochastic volatility literature (Britten–Jones and Neuberger, forthcoming; Derman and Kani, 1997; Ledoit and Santa–Clara, 1998) this paper proposes a new and general method for constructing smile–consistent stochastic volatility models. The method is developed by recognising that option pricing and hedging can be accomplished via the simulation of the implied risk neutral distribution. We devise an algorithm for the simulation of the implied distribution, when the first two moments change over time. The algorithm can be implemented easily, and it is based on an economic interpretation of the concept of mixture of distributions. It can also be generalised to cases where more complicated forms for the mixture are assumed.     

Stability, Asymmetry and Seasonality of Fund Performance: An Analysis of Australian Multi‐sector Managed Funds

Using a sample of Australian Multi-sector trusts we examine selectivity and market timing performance and extend the analysis to include the relatively new measure of volatility timing. This is of particular relevance to our data set, as high levels of volatility persistence are prevalent in Australia. In addition we consider the stability, asymmetry and seasonality of the various performance and risk measures. A survivorship adjustment procedure is also employed in order to assess the impact of survivorship on selectivity, market timing and volatility timing performance.     

Understanding the Economic Factors Influencing Farm Policy Preferences

A survey conducted in Mississippi, Texas, Indiana, and Nebraska elicited producers' preferences for various farm policy changes. This permitted examination of the diversity of preferences that single-state studies have not allowed. Five policy choices, including deficiency payments, loan programs, crop insurance, export programs, and disaster payments were examined. Logit model results predicting producer preferences for each of the five dichotomous policy choices are reported. Explanatory variables based on expected utility theory such as risk aversion, price and yield variability, and price–yield correlation are significant in various models.     

Are the Best Small Companies the Best Investments?

Previous research finds that large companies previously judged to be excellent growth companies have subsequently been poor investments. We examine small companies selected by Business Week on the basis of multiple criteria used in annual articles featuring highly rated growth companies. We study the investment performance over the three years before eleven annual Business Week publications and the three years after publication. We find positive excess returns in the pre‐publication period, but negative excess returns in the post‐publication period. This reversal in investment performance appears to be due to a mean‐reversion tendency in operating performance, in which the earnings and the past rates of return on capital of such companies subsequently decrease significantly.