The Gaussian jump model attempts to alleviate the sparsity of data problem in the relative jump model by assuming a parametric form to the jumps.
we assume there is a mean jump length µ and a jump variance σ 2 , and then the probability of a jump of length i is given by: Some care must be taken in employing this model, since the normal distribution is defined over a continuous space.