Multiple breaks detection in financial interval-valued time series
Multiple structural breaks detection for Interval-Valued Time Series (IVTS) is undoubtedly relevant under
practical perspectives and challenging under the point of view of the analysis of expert systems. In this
respect, financial time series usually show high variability and outliers; moreover, they often exhibit the
property of being of high frequency nature; thus, it is naturally advisable to consider them as IVTS type
for a given time unit. Despite this relevance, scarce effort has been spent by scholars to apply the methodological