A Stochastic Volatility Model With Markov Switching

This article presents a new way of modeling time-varying volatility. We generalize the usual stochastic volatility models to encompass regime-switching properties. The unobserved state variables are governed by a first-order Markov process. Bayesian estimators are constructed by Gibbs sampling. High-, medium- and low-volatility states are identified for the Standard and Poor's 500 weekly return data. Persistence in volatility is explained by the persistence in the low- and the medium-volatility states. The high-volatility regime is able to capture the 1987 crash and overlap considerably with four U.S. economic recession periods.     

The inclusion of ergonomic tools in the informational, conceptual and preliminary phases of the product design methodology

The process of product development has received special attention as it is being recognized as a source of competitive gain. Through its systematic use companies reduce costs, increase quality and decrease development time. However, one can find products being launched on the market that cause dissatisfaction to its users, and in consequence if the customer feels harmed or injured he will no longer purchase a product from the same brand. This in regard only to the commercial aspect; usually the danger of an accident or injury is not even thought about. This paper is the basis of the dissertation master's degree and used a literature research to build the repertoire, analyzing the methodologies applied by product design engineers, designers and ergonomists. The analysis results demonstrate the inefficiency of the design methodologies ergonomic issues. The contribution of this work lies in the suggestion to include ergonomic tools in all phases of product development and the presentation of a table with the tools that points out its most suitable time of application and results.