78 resultados para futures markets


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To better understand the nature of temporary spatial clusters (TSC’s) in industrial marketing settings, this conceptual paper first provides a theoretical synthesis of spatial understanding from the industrial marketing (IM) and economic geography (EG) fields, focusing particularly on Doreen Massey’s work on relational space. This leads to a conceptual schema for organizing the IM literature in terms of spatiality, and which also helps clarify the ontological nature of TSCs. We then move to introduce the notion of institutional boundary-work, drawing on the work of Thomas Gieryn, and Andrea Brighenti’s examination of territorology, to conceptualize the activities of market actors engaged in the ongoing social accomplishment of TSCs. Such activities, we suggest, involve these actors ‘marching’ boundaries to assume network influence and maintain market order in IM settings. In summary, therefore, our paper addresses two fundamental questions: i) How do we conceptualize the form of TSCs in IM settings? And, ii) what function(s) are TSCs performing (and how is this being undertaken) in IM? The paper closes by providing methodological guidance for how a research agenda on TSCs within IM activity might be developed, followed by a summary of the managerial implications that emerge from our theorizations.

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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.