GripNews➤ 高頻交易策略助力電池儲能系統收益最大化
✤ https://arxiv.org/abs/2504.06932
本文研究如何透過高頻日內交易策略，最大化電網規模電池儲能系統的收益。研究人員開發了一種自動化交易策略，該策略考慮了限價訂單簿的動態、市場規則和技術參數，並利用動態規劃方法加速計算。實證結果顯示，相較於每小時或每分鐘重新優化一次，高頻交易能顯著提升收益，最高可達 58% 和 14%。此外，透過演算法的快速性，研究團隊還成功訓練出一個參數化模型，進一步提升收益 8.4%。
+ 這個研究很有意思，證明瞭演算法交易在能源儲存領域的潛力，或許未來可以應用到更廣泛的儲能系統中。
+ 數據顯示高頻交易的優勢非常明顯，但實際應用中可能還需要考慮交易成本和其他實際因素。
#金融科技 #能源交易 #演算法交易
Maximizing Battery Storage Profits via High-Frequency Intraday Trading
Maximizing revenue for grid-scale battery energy storage systems in continuous intraday electricity markets requires strategies that are able to seize trading opportunities as soon as new information arrives. This paper introduces and evaluates an automated high-frequency trading strategy for battery energy storage systems trading on the intraday market for power while explicitly considering the dynamics of the limit order book, market rules, and technical parameters. The standard rolling intrinsic strategy is adapted for continuous intraday electricity markets and solved using a dynamic programming approximation that is two to three orders of magnitude faster than an exact mixed-integer linear programming solution. A detailed backtest over a full year of German order book data demonstrates that the proposed dynamic programming formulation does not reduce trading profits and enables the policy to react to every relevant order book update, enabling realistic rapid backtesting. Our results show the significant revenue potential of high-frequency trading: our policy earns 58% more than when re-optimizing only once every hour and 14% more than when re-optimizing once per minute, highlighting that profits critically depend on trading speed. Furthermore, we leverage the speed of our algorithm to train a parametric extension of the rolling intrinsic, increasing yearly revenue by 8.4% out of sample.