Pop-management: a literatura popular de gestão no Brasil

Nesta pesquisa, investiga-se e analisa-se o fenômeno da literatura de pop-management, propondo-se uma reflexão sobre seu papel na divulgação e legitimação de novas idéias e práticas de gestão empresarial. A literatura de pop-management compreende livros e revistas de consumo rápido, produzida pela mídia de negócios. A mídia de negócios faz parte da industria do management, junto com as empresas de consultoria, os gurus empresariais e as escolas de negócios. A pesquisa compreende três trilhas de trabalho: (1) uma investigação sobre o tema junto a publicações acadêmicas, (2) entrevistas com chefes de redação e editores e (3) análise de conteúdo de algumas publicações locais e internacionais. Conclui-se com uma reflexão acerca das características da literatura popular de gestão e seus impactos sobre as organizações e o indivíduo.

Exploratory semiparametric analysis of two-dimensional diffusions in finance

We examine bivariate extensions of Aït-Sahalia’s approach to the estimation of univariate diffusions. Our message is that extending his idea to a bivariate setting is not straightforward. In higher dimensions, as opposed to the univariate case, the elements of the Itô and Fokker-Planck representations do not coincide; and, even imposing sensible assumptions on the marginal drifts and volatilities is not sufficient to obtain direct generalisations. We develop exploratory estimation and testing procedures, by parametrizing the drifts of both component processes and setting restrictions on the terms of either the Itô or the Fokker-Planck covariance matrices. This may lead to highly nonlinear ordinary differential equations, where the definition of boundary conditions is crucial. For the methods developed, the Fokker-Planck representation seems more tractable than the Itô’s. Questions for further research include the design of regularity conditions on the time series dependence in the data, the kernels actually used and the bandwidths, to obtain asymptotic properties for the estimators proposed. A particular case seems promising: “causal bivariate models” in which only one of the diffusions contributes to the volatility of the other. Hedging strategies which estimate separately the univariate diffusions at stake may thus be improved.