Ten hypothetical price series were simulated according to the factor diffusion process discussed in Barndorff-Nielsen et al. On top of this process we added a jump process, with jump occurrences governed by the Poisson process with 1 expected jump per day and jump magnitude modelled as in Boudt et al. (2008). We assume that prices are only observed when a transaction takes place. The intensity of transactions follows a Poisson process and consequently, the inter transaction times are exponentially distributed. Therefore, we generated the inter transaction times of the price series by an independent exponential distributions with lambda = 0.1, which we keep constant over time. This means we expect one transaction every ten seconds. In a final step, the time series were aggregated to the 5-minute frequency by previous tick aggregation.
data("sample_5minprices_jumps")Boudt, K., C. Croux, and S. Laurent (2008). Outlyingness weighted covariation. Mimeo.