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Using FMI Transaction Data in Simulations: Less Is More?
Abstract
In this chapter the authors provide a method to aggregate large value payment system transaction data for executing simulations with the Bank of Finland payment simulator. When transaction data sets get large, simulation may become too time consuming in terms of computer power. Therefore, insufficient data from a statistical point of view can be processed. The method described in this chapter provides a solution to this statistical problem. In order to work around this problem the authors provide a method to aggregate transaction data set in such a way that it does not compromise the outcome of the simulation significantly. Depending on the type of simulations only a few business days or up to a year of data is required. In case of stress scenario analysis, in which e.g. liquidity position of banks deteriorates, long time series are preferred as business days can differ substantially. As an example this chapter shows that aggregating all low value transactions in the Dutch part of TARGET2 will not lead to a significantly different simulation outcome.
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