Northwestern European wholesale natural gas prices: comparison of several parametric and non-parametric forecasting methods

Hamie, Hassan; Hoayek, Anis; Kamel, Michel; Auer, Hans

doi:10.1504/ijgei.2020.108951

Cited by 5 publications

(2 citation statements)

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“…The analysis is then either constrained or governed by statistical assumptions, or solely based on machine learning and numerical techniques that are nonparametric. Two broad categories are thus used in the literature of commodity price prediction: parametric univariate/ multivariate and nonparametric models (Hamie et al, 2020).…”

Section: Measurement Of Predictability Using Parametric Models (Signa...mentioning

confidence: 99%

Measuring the competitiveness of commodity markets using price signals and information theory

Hoayek¹,

Hamie²

2023

Decis. Mak. Appl. Manag. Eng.

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Technological advancements, abrupt changes in market conditions, and political reforms, among other things, necessitate strong regulatory oversight, and accurate measurement of performance related indicators. The more accurate, information rich, and transparent these measurements/signals, the lower the level of uncertainty felt by value chain participants, who are thus able to recognize and observe whether the market’s state is efficient. Its lack, may lead to indecisiveness, translating into false interpretations that could lead to wrong policy directions. This paper provides an ex-post evaluation tool intending to deliver additional insights or quality information that would aid the regulator in assessing the state of the market. The tool is applied to the UK wholesale natural gas market for the period between 2011 and 2020, assessing and testing the market’s weak-form efficiency. It claims that today’s gas prices reflect a specific type of information, primarily past gas prices, and that only new information can help predict future prices. In this manuscript, based solely on a limited and available untapped dataset (day-ahead price time series), and working under the assumption that gas prices are the result of market processes, a variety of information metrics (gas price randomness, distribution of extreme prices, ability to predict prices - based on historical sets) is extracted with the use of suitable mathematical statistical models. A weighted entropy index is then computed, and measures the state of the commodity market. The results indicate that the analysis has helped gain information, thus reducing uncertainty (relative to a pre-analysis) by 86.5 %. Additionally, there is sufficient evidence that the UK natural gas prices are weak-form efficient.

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Section: Measurement Of Predictability Using Parametric Models (Signa...mentioning

confidence: 99%

Measuring the competitiveness of commodity markets using price signals and information theory

Hoayek¹,

Hamie²

2023

Decis. Mak. Appl. Manag. Eng.

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“…The empirical results of [2] reveal a weather effect on the conditional volatility of gas price returns. Others, such as [3][4][5][6], examined the influence of supply and demand fundamentals on gas price volatility, using a multivariate vector autoregressive (VAR) and error correction models (ECM). Consistent with prior research, the authors found that variables such as weather and storage have a major influence on short-term gas price volatility in liberalized European gas markets.…”

Section: State Of the Art Of Existing Literaturementioning

confidence: 99%

Modeling Post-Liberalized European Gas Market Concentration—A Game Theory Perspective

2020

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The question of whether the liberalization of the gas industry has led to less concentrated markets has attracted much interest among the scientific community. Classical mathematical regression tools, statistical tests, and optimization equilibrium problems, more precisely non-linear complementarity problems, were used to model European gas markets and their effect on prices. In this research, the parametric and nonparametric game theory methods are employed to study the effect of the market concentration on gas prices. The parametric method takes into account the classical Cournot equilibrium test, with assumptions on cost and demand functions. However, the non-parametric method does not make any prior assumptions, a factor that allows greater freedom in modeling. The results of the parametric method demonstrate that the gas suppliers’ behavior in Austria and The Netherlands gas markets follows the Nash–Cournot equilibrium, where companies act rationally to maximize their payoffs. The non-parametric approach validates the fact that suppliers in both markets follow the same behavior even though one market is more liquid than the other. Interestingly, our findings also suggest that some of the gas suppliers maximize their ‘utility function’ not by only relying on profit, but also on some type of non-profit objective, and possibly collusive behavior.

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Price forecasting through neural networks for crude oil, heating oil, and natural gas

Jin,

2024

Measurement: Energy

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Northwestern European wholesale natural gas prices: comparison of several parametric and non-parametric forecasting methods

Cited by 5 publications

References 0 publications

Measuring the competitiveness of commodity markets using price signals and information theory

Measuring the competitiveness of commodity markets using price signals and information theory

Modeling Post-Liberalized European Gas Market Concentration—A Game Theory Perspective

Price forecasting through neural networks for crude oil, heating oil, and natural gas

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