Title: Nonparametric permutation-based testing and ranking on multivariate time data
Authors: Livio Corain - University of Padova (Italy) [presenting]
Abstract: Based on the concept of multivariate stochastic dominance, the aim is to propose a nonparametric and permutation-based method for testing and ranking on multivariate time data. By using either fixed or moving blocks, the proposed methodology provide a flexible and less demanding in terms of underlying assumptions tool to infer on the presence of possible stochastic dominances that may take place among a set of several multivariate populations. Via a Monte Carlo simulation study, we investigate the properties of the proposed testing and ranking method where we prove its validity under different random distributions and type of dependencies and correlation structures. From the practical point of view, the proposed methodology can be effective to face some real problems in Econometrics and Finance. Finally, we present and application to a macroeconomic analysis of an industrial sector.