In the following paper, we examine the problem of the intensity estimation of transaction arrivals in the intraday electricity markets. Assuming the inter-arrival times distribution and considering multiple intensity function types, we utilize a maximum likelihood estimation.
A rolling window forecasting study of future transaction arrival times is conducted in order to gain significant insights to the performance of the considered models. We analyse both the in-sample characteristics and the forecasting efficiency. In the forecasting part, artificial trajectories are simulated and then evaluated by calculating the $mathcal{L}^1$ and $mathcal{L}^2$ norms of the difference between their counting processes and the realized one. The study presented in this paper is conducted based on the German Intraday Continuous electricity market data, but this method can be easily applied to any other continuous intraday electricity market.