An Alternative to Index-Based Gas Sourcing Using Neural Networks

  • Schlueter, Stephan; 
  • Jung, Sejung; 
  • von Doellen, Andreas; 
  • Lee, Wonhee
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

An index on the gas market commonly refers to the average price of a certain trading product, e.g., over the period of one month. Index-based sourcing is a widely-used habit in modern gas business. Risks are reduced by averaging prices over the purchasing period. Due to the significant volume, there have been many attempts to "beat the index", i.e., to design a strategy that, over time, offers cheaper prices than the index. Here, we use neural networks to identify n, n is an element of N, optimal shopping points. Both classification- and forecasting-based strategies are tested to decide on each trading day if gas should be purchased or not. Thereby, we use the Front Month index based on prices from the Dutch Title Transfer Facility as an example. Regarding cumulative performance, all but a very simple myopic algorithm are able to outperform the index. However, each strategy has its flaws and some positive results are due to the price increase during 2021. If one opts for an active sourcing strategy, then a forecasting-based approach is the best choice.

키워드

neural networks; gas trading algorithm; classification; forecasting; TTF prices; STORAGE VALUATION; MONTE-CARLO; MARKET
제목
An Alternative to Index-Based Gas Sourcing Using Neural Networks
저자
Schlueter, Stephan; Jung, Sejung; von Doellen, Andreas; Lee, Wonhee
DOI
10.3390/en15134708
발행일
2022-07
유형
Article
저널명
Energies
권
15
호
13