On the determinants of data breaches: A cointegration analysis

Abstract

Cyber risks and particularly data breaches constitute one of the new frontiers of risk modeling for insurers across the world. We use the cointegration methodology to uncover the relation between data breaches and Bitcoin-related variables. We perform our analyses on two different datasets of data breaches. In both cases, we provide statistical evidence of a bidirectional lead–lag relation in the short run between the variables under investigation. Moreover, the existence of a cointegrating vector suggests that this relation is likely to persist in the long run. To evaluate the quantitative implications of the relations found, we complement the study with Granger causality tests, impulse response analyses and variance decompositions of the forecasting errors.