A continuous-time model for reinvestment risk in bond markets

When comparing standard bond market models with practice we observe that, whereas the literature places no restrictions on the time to maturity of traded bonds, this is actually the case in practice. Hence, standard models ignore the reinvestment risk present in practice when considering contacts with longer time to maturity than the longest bond traded in the market. In this paper we propose a model including this reinvestment risk. We place a restriction on the bonds traded in the market by limiting the time to maturity of traded bonds. At fixed times, new bonds are issued in the market, thus extending the time of maturity of traded bonds. The initial prices of the new bonds issued in the market depend on the information generated by the market and a stochastic variable independent thereof describing the reinvestment risk. In order to quantify and control the reinvestment risk we apply the criterion of risk-minimization.     

Seeking the Ideal Level of Design Newness: Consumer Response to Radical and Incremental Product Design

To develop successful new products, new product development managers need to have a thorough understanding of the consumer adoption process, specifically in how consumers evaluate new products. This research examines the value of product design for consumers' evaluation of radical and incremental innovations. The primary goal was to empirically test how design newness affects consumer response to product innovations. Design newness (also referred to as novelty or atypicality) is defined as the deviation in a product design from the current design state of a certain product category. Although prior research has suggested that higher levels of design newness may have a positive effect on consumers' evaluations of new products, higher levels of design newness may also have negative consequences for consumer response to radical innovations. An experimental context (n = 130) using systematically designed products for three product categories was used to test how consumers respond to high and low levels of design newness for both radical and incremental innovations. The findings show that for radical innovations, embodying the product in a design with a low (versus high) level of design newness led to more positive evaluations and less learning‐cost inferences. Because the functional attributes of a radical innovation are incongruent to existing products, consumers find it difficult to access the relevant product category schema in order to transfer knowledge to the new product. Because of this poor knowledge transfer, consumers may feel that they lack the ability to make effective use of the radical innovation, resulting in greater learning costs. In this case, a product design with a low level of design newness can provide consumers with a frame of reference for understanding the radical innovation. Contrasting this result, no difference was found between a low and a high level of design newness for incremental innovations. For incremental innovations, by definition the functional attributes characteristic to the innovation are highly comparable with those products that are already stored in consumers' memory. Thus, there is no need for an additional reconfirmation of the preexisting schema through product design, and consumers are able to access the relevant schema regardless of the level of design newness inherent in the product. These findings are integrated into a discussion of the managerial implications and the potential avenues for future research.     

Dealing with the devil of deviation: managing uncertainty during product development execution

This paper examines deviations in complex product development. Based on an extensive case study, using participant observations, interviews, and data from deviation reports, it illustrates the causes, procedures, management challenges of deviations, and organizational roles devoted to deviation management. Based on the rich data material, it furthermore proposes a typology of deviations developed for a better understanding of this significant empirical phenomenon.     

Risk Management for Grain Processors and “Copulas”

The importance of calibrating hedging strategies for processors has escalated primarily due to the sharply increased volatility of futures, product, and by‐product prices. The purpose of this paper is to analyze price risk‐management strategies for wheat flour milling using copula distributions. While the application is for flour milling, it has similarities with other processing industries which confront one or more ingredients, one or more outputs, and futures for one of the commodities and/or products. The paper develops utility maximizing models encompassing expected return and risk. Alternative scenarios are evaluated. First, the models were used to derive optimal hedge ratios, as well as various measures of risk and return under alternative scenarios, and hedge durations. The results indicated hedge ratios are typically less than 1. The hedge ratios for the Mean‐value‐at‐risk (M‐VaR)‐Copula model increased with greater durations. Second, the VaR for the M‐VaR‐Copula was in most cases less than the noncopula specifications. Thus, noncopula models may over state risk as represented by VaR.