Fitting Rwanda’s Currency Market Returns with the Poisson Compound Model with Normal Inverse Gaussian Jumps

The first step towards developing a reliable forecast for the forex market returns is to find a model that can be used and explains all of the return behavior. The compound Poisson model with the Normal Inverse Gaussian jumps (NIG), geometric Brownian motion (gBm), and the Poisson model with the Gaussian jumps (Norm) are used in this work to fit the market data. The AIC and BIC scores of the models were used to validate them. The model compound Poisson with Normal Inverse Gaussian jumps (NIG) performs better across all currencies than the model Norm and gBm. The data from the Rwandan forex market matches well with a model compound Poisson with Normal Inverse Gaussian jumps (NIG).