We introduce a profitable trading strategy that can support decision-making in continuous intraday markets for electricity. It utilizes a novel forecasting framework, which generates prediction bands from a pool of path forecasts or approximates them using probabilistic price forecasts. The prediction bands then define a time-dependent price level that, when exceeded, indicates a good trading opportunity. Results for the German intraday market show that, in terms of the energy score, our path forecasts beat two well performing literature benchmarks by over 30%. Moreover, the forecasts provide empirical evidence that the increased computational burden induced by generating realistic price paths is offset by higher trading profits. Still, the proposed approximate and bootstrap-based methods offer a reasonable trade-off — they do not require generating path forecasts and yield only slightly lower profits.

我们引入了一种有利可图的交易策略，可以支持在连续的日内电力市场中进行决策。它利用了一种新颖的预测框架，该框架从路径预测池中生成预测带，或使用概率价格预测对其进行近似。然后，预测带定义了一个与时间相关的价格水平，当超过该水平时，表明一个良好的交易机会。德国盘中市场的结果显示，就能源得分而言，我们的路径预测比两个表现良好的文献基准高出 30% 以上。此外，这些预测提供了经验证据，表明生成现实价格路径导致的计算负担增加被更高的交易利润所抵消。仍然，