This paper builds up the capacity of the ordinary backwards Gaussian dispersion (NIG) to fit the profits of bitcoin (BTC). As the principal digital currency made, the conduct of this new resource is described by incredible unpredictability. The absence of a legitimate definition or characterization under existing hypothesis worsens this property so that dangerous periods followed by a quick decrease have been seen along the arrangement, which means bubble scenes. By recognizing the periods where an air pocket rises and crumples, it is conceivable to examine the measurable properties of such fragments. Specifically, changing a hypothetical circulation may assist with deciding better systems to fence against these scenes. The NIG is a fitting up-and-comer in view of its substantial followed property as well as in light of the fact that it has been demonstrated to be shut under convolution, a trademark that can be actualized to gauge multivariate incentive in danger. Utilizing information on the cost of BTC as for seven of the fundamental worldwide monetary standards, the NIG had the option to fit each time portion notwithstanding the air pocket conduct. In the out-of-test tests, the NIG was demonstrated to have a modification like that of a summed up hyperbolic (GH) conveyance. This outcome could fill in as a beginning stage for future investigations with respect to the measurable properties of digital currencies just as their multivariate circulations.