Case studies in Bayesian screening for time-varying model structure: the partition problem
Case studies in Bayesian screening for time-varying model structure: the partition problem
This chapter presents two case studies involving the problem of time-varying model uncertainty for many different time series observed in parallel. In the first case study, time-varying graphical structure is identified in the covariance of asset returns from major European equity indices from 2006–2010. This structure has important implications for quantifying the notion of financial contagion, a term often mentioned in the context of the European sovereign debt crisis of this period. The second case study screens a large database of historical corporate performance to identify specific firms with good (or bad) streaks of performance. The goals in these analyses are: to argue for the existence of non-trivial dynamic structure in each dataset; to draw parallels between the case studies, both of which exemplify the partition problem; and to identify certain aspects of each model that must be generalized in future work if these case studies are to provide a useful template for other datasets.
Keywords: time-varying model uncertainty, time series, dataset, dynamic structure, partition problem
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