Erdgas fiel am 5. September 2025 auf 3,02 USD/MMBtu, was einem Rückgang um 1,65% gegenüber dem Vortag entspricht. Im Laufe des letzten Monats ist der Preis für Erdgas um 1,74% gesunken, liegt aber immer noch 32,90% höher als vor einem Jahr, gemäß dem Handel mit einem Differenzkontrakt (CFD), der den Benchmark-Markt für diese Ware verfolgt. Diese Werte, historische Daten, Prognosen, Statistiken, Diagramme und ökonomische Kalender - Naturgas - Futures Contract - Preise.

TTF Gas rose to 33.06 EUR/MWh on September 8, 2025, up 3.42% from the previous day. Over the past month, TTF Gas's price has risen 0.19%, but it is still 11.11% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. EU Natural Gas TTF - values, historical data, forecasts and news - updated on September of 2025.

Index Time Series for United States Natural Gas Fund LP. The frequency of the observation is daily. Moving average series are also typically included. The fund invests primarily in futures contracts for natural gas that are traded on the NYMEX, ICE Futures Europe and ICE Futures U.S. (together, "ICE Futures") or other U.S. and foreign exchanges. The Benchmark Futures Contract is the futures contract on natural gas as traded on the New York Mercantile Exchange that is the near month contract to expire, except when the near month contract is within two weeks of expiration.

UK Gas fell to 80.03 GBp/thm on September 9, 2025, down 1.22% from the previous day. Over the past month, UK Gas's price has fallen 1.50%, and is down 6.26% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. UK Natural Gas - values, historical data, forecasts and news - updated on September of 2025.

Futures market is an important part of the financial market, with a high degree of liquidity and leverage effect. However, the futures market is also faced with various risk factors, such as price fluctuations, market shocks, supply and demand changes. In order to better determine the risk correlation between specific futures markets, this paper uses the wavelet transform—quantile Granger causality test method to identify the risk correlation of four major futures markets in the US futures market from the end of January 2009 to the end of March 2023, such as gold, crude oil, soybeans and natural gas. It provides a new perspective and method for the risk correlation identification of the futures market. The results show that futures contracts with different maturities and price fluctuations under different quantiles have a significant impact on risk correlation. Specifically, in 1-month and 6-month futures contracts, the strongest bidirectional risk correlation exists between gold and natural gas (T-statistics -15.94 and 10.92, respectively); In the 1-month futures contract, there is also a strong bidirectional risk association between crude oil and soybeans and natural gas (T-statistics are 6.87, 17.42, -2.05, 7.35, respectively), while in the 6-month futures contract, there is a bidirectional risk association between crude oil and soybeans (T-statistics are -2.49 and 18.374, respectively). However, natural gas has unidirectional risk association with crude oil and soybean (t statistics are 2.7 and -3.35, respectively); There is a bidirectional risk correlation between gold and soybean, that is, the risk correlation between gold and soybean increases with the increase of the degree of price fluctuation; There is a one-way risk association between gold and crude oil, soybean and gold, and crude oil and natural gas (the T-statistic is greater than the critical value of 1.96). In addition, there is a strong bidirectional or unidirectional risk association between all varieties at the 0.95 quantile. The research results of this paper have certain reference value for the supervision, investment and risk management of the futures market. This paper uses the wavelet transform and quantile Granger causality test method to identify the risk correlation of the futures market, providing a new perspective and method for the risk correlation identification of the futures market, and uses relatively new data to ensure the effectiveness of the empirical analysis. However, there are some limitations in this paper, such as the applicability of wavelet transform-quantile Granger causality test method. Future studies can further expand the sample range, compare the effects of different methods, and explore the risk transmission mechanism between different varieties.

Futures market is an important part of the financial market, with a high degree of liquidity and leverage effect. However, the futures market is also faced with various risk factors, such as price fluctuations, market shocks, supply and demand changes. In order to better determine the risk correlation between specific futures markets, this paper uses the wavelet transform—quantile Granger causality test method to identify the risk correlation of four major futures markets in the US futures market from the end of January 2009 to the end of March 2023, such as gold, crude oil, soybeans and natural gas. It provides a new perspective and method for the risk correlation identification of the futures market. The results show that futures contracts with different maturities and price fluctuations under different quantiles have a significant impact on risk correlation. Specifically, in 1-month and 6-month futures contracts, the strongest bidirectional risk correlation exists between gold and natural gas (T-statistics -15.94 and 10.92, respectively); In the 1-month futures contract, there is also a strong bidirectional risk association between crude oil and soybeans and natural gas (T-statistics are 6.87, 17.42, -2.05, 7.35, respectively), while in the 6-month futures contract, there is a bidirectional risk association between crude oil and soybeans (T-statistics are -2.49 and 18.374, respectively). However, natural gas has unidirectional risk association with crude oil and soybean (t statistics are 2.7 and -3.35, respectively); There is a bidirectional risk correlation between gold and soybean, that is, the risk correlation between gold and soybean increases with the increase of the degree of price fluctuation; There is a one-way risk association between gold and crude oil, soybean and gold, and crude oil and natural gas (the T-statistic is greater than the critical value of 1.96). In addition, there is a strong bidirectional or unidirectional risk association between all varieties at the 0.95 quantile. The research results of this paper have certain reference value for the supervision, investment and risk management of the futures market. This paper uses the wavelet transform and quantile Granger causality test method to identify the risk correlation of the futures market, providing a new perspective and method for the risk correlation identification of the futures market, and uses relatively new data to ensure the effectiveness of the empirical analysis. However, there are some limitations in this paper, such as the applicability of wavelet transform-quantile Granger causality test method. Future studies can further expand the sample range, compare the effects of different methods, and explore the risk transmission mechanism between different varieties.

Futures market is an important part of the financial market, with a high degree of liquidity and leverage effect. However, the futures market is also faced with various risk factors, such as price fluctuations, market shocks, supply and demand changes. In order to better determine the risk correlation between specific futures markets, this paper uses the wavelet transform—quantile Granger causality test method to identify the risk correlation of four major futures markets in the US futures market from the end of January 2009 to the end of March 2023, such as gold, crude oil, soybeans and natural gas. It provides a new perspective and method for the risk correlation identification of the futures market. The results show that futures contracts with different maturities and price fluctuations under different quantiles have a significant impact on risk correlation. Specifically, in 1-month and 6-month futures contracts, the strongest bidirectional risk correlation exists between gold and natural gas (T-statistics -15.94 and 10.92, respectively); In the 1-month futures contract, there is also a strong bidirectional risk association between crude oil and soybeans and natural gas (T-statistics are 6.87, 17.42, -2.05, 7.35, respectively), while in the 6-month futures contract, there is a bidirectional risk association between crude oil and soybeans (T-statistics are -2.49 and 18.374, respectively). However, natural gas has unidirectional risk association with crude oil and soybean (t statistics are 2.7 and -3.35, respectively); There is a bidirectional risk correlation between gold and soybean, that is, the risk correlation between gold and soybean increases with the increase of the degree of price fluctuation; There is a one-way risk association between gold and crude oil, soybean and gold, and crude oil and natural gas (the T-statistic is greater than the critical value of 1.96). In addition, there is a strong bidirectional or unidirectional risk association between all varieties at the 0.95 quantile. The research results of this paper have certain reference value for the supervision, investment and risk management of the futures market. This paper uses the wavelet transform and quantile Granger causality test method to identify the risk correlation of the futures market, providing a new perspective and method for the risk correlation identification of the futures market, and uses relatively new data to ensure the effectiveness of the empirical analysis. However, there are some limitations in this paper, such as the applicability of wavelet transform-quantile Granger causality test method. Future studies can further expand the sample range, compare the effects of different methods, and explore the risk transmission mechanism between different varieties.

Germany Natural Gas THE rose to 34.33 EUR/MWh on September 4, 2025, up 0.74% from the previous day. Over the past month, Germany Natural Gas THE's price has fallen 5.16%, and is down 5.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Germany Natural Gas THE.

Rolling window estimation of 0.05 quartile approximate component of Granger causal t statistic value matrix for 1 month futures contracts of gold, crude oil, soybean and natural gas.

Gasoline rose to 1.99 USD/Gal on September 9, 2025, up 1.60% from the previous day. Over the past month, Gasoline's price has fallen 4.28%, but it is still 5.64% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - values, historical data, forecasts and news - updated on September of 2025.

0.05 quantile detail components of 6-month futures contracts for gold, crude oil, soybean and natural gas Granger causal t statistic value matrix rolling window estimation.

0.95 quantile detail components of 1-month futures contracts for gold, crude oil, soybeans and natural gas Granger causal t statistic value matrix rolling window estimate.

Brent rose to 66.19 USD/Bbl on September 9, 2025, up 0.26% from the previous day. Over the past month, Brent's price has fallen 0.65%, and is down 4.33% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Brent crude oil - values, historical data, forecasts and news - updated on September of 2025.

Propane rose to 0.71 USD/Gal on September 9, 2025, up 1.47% from the previous day. Over the past month, Propane's price has risen 5.03%, and is up 12.42% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Propane - values, historical data, forecasts and news - updated on September of 2025.

Coal fell to 103.85 USD/T on September 9, 2025, down 1.84% from the previous day. Over the past month, Coal's price has fallen 7.48%, and is down 25.15% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coal - values, historical data, forecasts and news - updated on September of 2025.

Eggs US rose to 2.18 USD/Dozen on September 8, 2025, up 0.94% from the previous day. Over the past month, Eggs US's price has fallen 5.53%, and is down 47.19% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Eggs US.

Urals Oil fell to 59.02 USD/Bbl on September 5, 2025, down 4.28% from the previous day. Over the past month, Urals Oil's price has fallen 9.14%, and is down 25.13% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urals Crude.

Ethanol traded flat at 1.99 USD/Gal on September 9, 2025. Over the past month, Ethanol's price has risen 11.80%, and is up 15.70% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Ethanol - values, historical data, forecasts and news - updated on September of 2025.