We use point processes to analyze market order arrivals on the intraday market for hourly electricity deliveries in Germany in the second quarter of 2015. As we distinguish between buys and sells, we work in a multivariate setting. We model the arrivals with a Hawkes process whose baseline intensity comprises either only an exponentially increasing component or a constant in addition to the exponentially increasing component, and whose excitation decays exponentially. Our goodness-of-fit tests indicate that the models where the intensity of each market order type is excited at least by events of the same type are the most promising ones. Based on the Akaike information criterion, the model without a constant in the baseline intensity and only self-excitation is selected in almost 50% of the cases on both market sides. The typical jump size of intensities in case of the arrival of a market order of the same type is quite large, yet rather short lived. Diurnal patterns in the parameters of the baseline intensity and the branching ratio of self-excitation are observable. Contemporaneous relationships between different parameters such as the jump size and decay rate of self and cross-excitation are found.

中文翻译：

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使用霍克斯过程模拟德国日内电力市场上的市场订单到达

我们使用点过程来分析2015年第二季度德国每小时电力交付的日内市场上的市场订单到达。由于我们区分了买和卖，因此我们在多变量环境中工作。我们用霍克斯过程对到达进行建模，该过程的基线强度仅包括指数增加的分量或除指数增加的分量之外的常数，并且其激发呈指数衰减。我们的拟合优度测试表明，至少每个类型的事件都激发每种市场订单类型强度的模型是最有前途的。根据Akaike信息标准，在双方市场中几乎有50％的案例中选择的模型没有基线强度恒定且仅具有自激励功能。同一类型的市场订单到来时，强度的典型跳跃幅度很大，但寿命却很短。可以观察到基线强度和自激支化率参数的日变化。发现不同参数之间的同时关系，例如自跳和交叉激励的跳跃大小和衰减率。