Crude Oil fell to 59.17 USD/Bbl on December 2, 2025, down 0.25% from the previous day. Over the past month, Crude Oil's price has fallen 3.08%, and is down 15.40% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on December of 2025.

Brent fell to 63.05 USD/Bbl on December 2, 2025, down 0.19% from the previous day. Over the past month, Brent's price has fallen 2.84%, and is down 14.36% 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 December of 2025.

Heating Oil rose to 2.35 USD/Gal on December 2, 2025, up 0.21% from the previous day. Over the past month, Heating Oil's price has fallen 2.25%, but it is still 6.31% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Heating oil - values, historical data, forecasts and news - updated on December of 2025.

The 2025 annual OPEC basket price stood at ***** U.S. dollars per barrel as of August. This would be lower than the 2024 average, which amounted to ***** U.S. dollars. The abbreviation OPEC stands for Organization of the Petroleum Exporting Countries and includes Algeria, Angola, Congo, Equatorial Guinea, Gabon, Iraq, Iran, Kuwait, Libya, Nigeria, Saudi Arabia, Venezuela, and the United Arab Emirates. The aim of the OPEC is to coordinate the oil policies of its member states. It was founded in 1960 in Baghdad, Iraq. The OPEC Reference Basket The OPEC crude oil price is defined by the price of the so-called OPEC (Reference) basket. This basket is an average of prices of the various petroleum blends that are produced by the OPEC members. Some of these oil blends are, for example: Saharan Blend from Algeria, Basra Light from Iraq, Arab Light from Saudi Arabia, BCF 17 from Venezuela, et cetera. By increasing and decreasing its oil production, OPEC tries to keep the price between a given maxima and minima. Benchmark crude oil The OPEC basket is one of the most important benchmarks for crude oil prices worldwide. Other significant benchmarks are UK Brent, West Texas Intermediate (WTI), and Dubai Crude (Fateh). Because there are many types and grades of oil, such benchmarks are indispensable for referencing them on the global oil market. The 2025 fall in prices was the result of weakened demand outlooks exacerbated by extensive U.S. trade tariffs.

Urals Oil fell to 54.22 USD/Bbl on December 1, 2025, down 0.37% from the previous day. Over the past month, Urals Oil's price has fallen 7.52%, and is down 17.95% 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 Urals Crude.

You are members of the analytic department in one of the Alberta Oil Sands extraction companies. You are given a current project to collect and clean the data and choose, fit and validate the model for further continuous prediction of demand for the company's products. This will allow the company to assess profitability and to set the appropriate volumes of production.

In short, you need to use the historical data of https://www.eia.gov/dnav/pet/hist/rwtcW.htm in its weekly version, and to predict it for the available weeks of 2021, to evaluate the quality of your prediction and to compose a report for your management. Before working with real data, you first check the intended model on simulated data.

Below we suggest the specific steps of analysis for those who like the detailed instructions. However, these steps may be changed by those who prefer free creativity.

The moral that we are trying to learn in this assignment is that it is easy to forecast series generated by a certain family of models. However, it is hard to forecast the real cases.

We will study the necessary material for the whole semester. However, steps in italic, you can start immediately. I suggest you to start early, because the volume is high.

Part 1. Artificial data

1.1. Simulation.

1.1.1. For ARIMA(p, d, q), set p = 2
d = 1
q = 2
phi_1 = -.2
phi_2 = .15
theta_1 = .3
theta_2 = -.1
sd = 0.03
and generate a series of sample size n = 1000, using this model. 1.1.2. Add a linear trend y(t) = b0 + b1*t, using the coefficients intercept b0 = -1 and slope b1= 0.0015. 1.1.3. Apply an exponential function.

1.2. Exploratory analysis in the order, inverse to the simulation steps.

1.2.1. Divide the generated set into a training set head and a test set tail. 1.2.2. Logarithm the training set series. 1.2.3. Detect a linear trend by regression. Compare the estimated trend parameters to true ones. 1.2.4. Detrend the series. 1.2.5. In the same axes, plot the original ARIMA simulation and the current (trended, exponentiated, logarithmed and finally detrended) series. They should have the same shape, but differ by a bit of shift and stretch. 1.2.6. ARIMA fit. 1.2.6.1. By 3 nested loops over p, d and q between 0 and 3, print all values of AIC in 3 4-by-4-tables. Choose the triple, minimizing AIC. Compare it to the true (p, d, q) triple and comment. 1.2.6.2. Fit the model by auto.arima command. Comment on its choice of p, d and q, comparing to true values and those chosen by triple loop. 1.2.6.3. Leave out those attempts of order estimations and choose the true (p, d, q) triple. Fit ARIMA(2, 1, 2), using the function forecast::Arima, to the training data. 1.2.7. Compare the estimated ARIMA parameters to true ones. Comment on goodness of fit.

1.3. Forecasting the simulated series.

1.3.1. Forecast the testing part of the ARIMA, using forecast::forecast function. 1.3.2. Add the estimated trend. 1.3.3. Exponentiate that trended forecast.

1.4. Evaluation of the results

1.4.1. Plot the forecast values, prediction interval, and the real testing set in the same axes. 1.4.2. Plot acf of the testing set and its prediction, and ccf between them. 1.4.3. Plot the residuals and their acf. 1.4.4. Estimate the forecast error.

Part 2. Real data.

2.1. Data sourcing and visualization.

2.1.1. Read the dataset https://www.kaggle.com/statistics101guy/wti-spot-price-fob-dollars-per-barrel 2.1.2. Plot the series and its acf.

2.2. Exploratory analysis

2.2.1. Divide the series into a training set (up to 2020 inclusively) and testing set (2021). 2.2.2. Logarithm the series. 2.2.3. Estimate the linear trend by the least squares procedure. 2.2.4. Detrend the series. 2.2.5. By “auto.arima” command of “forecast” library, fit ARIMA(p, d, q) to the training data.

2.3. Forecasting in the order, inverse to the exploratory analysis steps

2.3.1. Using the “forecast” function of the “forecast” library, forecast your ARIMA model for the period of testing set. 2.3.2. Extrapolate your linear trend to this period and add it to your ARIMA forecast. 2.3.3. Exponentiate the result.

2.4. Evaluation of the forecast quality

2.4.1. Plot the forecast values, prediction interval, and the real testing set in the same axes. 2.4.2. Plot acf of the testing set and its prediction, and ccf between them. 2.4.3. Plot the residuals and their acf. 2.4.4. Estimate the forecast error. 2.4.5. Comment on the results

Part 3. Reporting

3.1. Compose a business report of about 10 pages length, following the approximate structure:

3.1.1. Title page, listing the group members, project title, school, course, submission date. 3.1.2. Executive summary, containing your view of the problem setting, brief description of the intended analysis and all that usually pertains to this section 3.1.3. Ana...

On October 27, 2025, the Brent crude oil price stood at 65.14 U.S. dollars per barrel, compared to 61.31 U.S. dollars for WTI oil and 67.54 U.S. dollars for the OPEC basket. Oil prices rose slightly that week.Europe's Brent crude oil, the U.S. WTI crude oil, and OPEC's basket are three of the most important benchmarks used by traders as reference for global oil and gasoline prices. Lowest ever oil prices during coronavirus pandemic In 2020, the coronavirus pandemic resulted in crude oil prices hitting a major slump as oil demand drastically declined following lockdowns and travel restrictions. Initial outlooks and uncertainty surrounding the course of the pandemic brought about a disagreement between two of the largest oil producers, Russia and Saudi Arabia, in early March. Bilateral talks between global oil producers ended in agreement on April 13th, with promises to cut petroleum output and hopes rising that these might help stabilize the oil price in the coming weeks. However, with storage facilities and oil tankers quickly filling up, fears grew over where to store excess oil, leading to benchmark prices seeing record negative prices between April 20 and April 22, 2020. How crude oil prices are determined As with most commodities, crude oil prices are impacted by supply and demand, as well as inventories and market sentiment. However, as oil is most often traded in future contracts (where a contract is agreed upon while product delivery will follow in the next two to three months), market speculation is one of the principal determinants for oil prices. Traders make conclusions on how production output and consumer demand will likely develop over the coming months, leaving room for uncertainty. Spot prices differ from futures in so far as they reflect the current market price of a commodity.

Monthly average retail prices for gasoline and fuel oil for Canada, selected provincial cities, Whitehorse and Yellowknife. Prices are presented for the current month and previous four months. Includes fuel type and the price in cents per litre.

Palm Oil rose to 4,134 MYR/T on December 2, 2025, up 1.00% from the previous day. Over the past month, Palm Oil's price has risen 0.46%, but it is still 18.56% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Palm Oil - values, historical data, forecasts and news - updated on December of 2025.

As of August 2025, the average annual price of Brent crude oil stood at 71.3 U.S. dollars per barrel. This is over nine U.S. dollars lower than the 2024 average. Brent is the world's leading price benchmark for Atlantic basin crude oils. Crude oil is one of the most closely observed commodity prices as it influences costs across all stages of the production process and consequently alters the price of consumer goods as well. What determines crude oil benchmarks? In the past decade, crude oil prices have been especially volatile. Their inherent inelasticity regarding short-term changes in demand and supply means that oil prices are erratic by nature. However, since the 2009 financial crisis, many commercial developments have greatly contributed to price volatility, such as economic growth by BRIC countries like China and India, and the advent of hydraulic fracturing and horizontal drilling in the U.S. The outbreak of the coronavirus pandemic and the Russia-Ukraine war are examples of geopolitical events dictating prices. Light crude oils - Brent and WTI Brent Crude is considered a classification of sweet light crude oil and acts as a benchmark price for oil around the world. It is considered a sweet light crude oil due to its low sulfur content and low density and may be easily refined into gasoline. This oil originates in the North Sea and comprises several different oil blends, including Brent Blend and Ekofisk crude. Often, this crude oil is refined in Northwest Europe. Another sweet light oil often referenced alongside UK Brent is West Texas Intermediate (WTI). WTI oil prices amounted to 76.55 U.S. dollars per barrel in 2024.

📝 Dataset Overview: This dataset represents real-world, enhanced transactional data from Timac Global Concept, one of Nigeria’s prominent players in fuel and petroleum distribution. It includes comprehensive sales records across multiple stations and product categories (AGO, PMS, Diesel, Lubricants, LPG), along with revenue and shift-based operational tracking.

The dataset is ideal for analysts, BI professionals, and data science students aiming to explore fuel economy trends, pricing dynamics, and operational analytics.

🔍 Dataset Features: Column Name Description Date Transaction date Station_Name Name of the fuel station AGO_Sales (L) Automotive Gas Oil sold in liters PMS_Sales (L) Premium Motor Spirit sold in liters Lubricant_Sales (L) Lubricant sales in liters Diesel_Sales (L) Diesel sold in liters LPG_Sales (kg) Liquefied Petroleum Gas sold in kilograms Total_Revenue (₦) Total revenue generated in Nigerian Naira AGO_Price Price per liter of AGO PMS_Price Price per liter of PMS Lubricant_Price Unit price of lubricants Diesel_Price Price per liter of diesel LPG_Price Price per kg of LPG Product_Category Fuel product type Shift Work shift (e.g., Morning, Night) Supervisor Supervisor in charge during shift Weekday Day of the week for each transaction

🎯 Use Cases: Build Power BI dashboards to track fuel sales trends and shifts

Perform revenue forecasting using time series models

Analyze price dynamics vs sales volume

Visualize station-wise performance and weekday sales patterns

Conduct operational audits per supervisor or shift

🧰 Best Tools for Analysis: Power BI, Tableau

Python (Pandas, Matplotlib, Plotly)

Excel for pivot tables and summaries

SQL for fuel category insights

👤 Created By: Fatolu Peter (Emperor Analytics) Data analyst focused on real-life data transformation in Nigeria’s petroleum, healthcare, and retail sectors. This is Project 11 in my growing portfolio of end-to-end analytics challenges.

✅ LinkedIn Post: ⛽ New Dataset Alert – Fuel Economy & Sales Data Now on Kaggle! 📊 Timac Fuel Distribution & Revenue Dataset (Nigeria – 500 Records) 🔗 Explore the data here

Looking to practice business analytics, revenue forecasting, or operational dashboards?

This dataset contains:

Daily sales of AGO, PMS, Diesel, LPG & Lubricants

Revenue breakdowns by station

Shift & supervisor tracking

Fuel prices across product categories

You can use this to: ✅ Build Power BI sales dashboards ✅ Create fuel trend visualizations ✅ Analyze shift-level profitability ✅ Forecast revenue using Python or Excel

Let’s put real Nigerian data to real analytical work. Tag me when you build with it—I’d love to celebrate your work!

FuelAnalytics #KaggleDatasets #PowerBI #PetroleumIndustry #NigeriaData #RevenueForecasting #EmperorAnalytics #FatoluPeter #Project11 #TimacGlobal #RealWorldData

China’s crude oil import has increased sharply since 2002. Its expenditure on oil import now accounts for around 10% of its total commodity import. Thus, there is potential imported inflation or deflation due to oil price fluctuations and China’s central bank may respond to it. We quantitatively analyze the impact of oil prices on China’s benchmark interest rate and monetary supply by a 6-variable structural vector auto-regression model. We draw that: 1) In response to an increase of oil price, China’s central bank generally upgrades interest rate. If oil price rises by 10 US dollars, the 6-month lending base rate will increase by around 0.13 percentage point in 3 months. 2) The effects of price shocks deepen after the oil pricing reform, and specifically, it can explain 19.8% of the variations in monetary policies in one year after October 2008, compared with the 0.83% before October 2001.

Russia Average World Price: Crude Oil: Urals: per 1 Barrel data was reported at 91.200 USD/Barrel in Mar 2019. This records an increase from the previous number of 80.700 USD/Barrel for Feb 2019. Russia Average World Price: Crude Oil: Urals: per 1 Barrel data is updated monthly, averaging 58.745 USD/Barrel from Jun 2000 (Median) to Mar 2019, with 226 observations. The data reached an all-time high of 129.710 USD/Barrel in Jul 2008 and a record low of 18.200 USD/Barrel in Nov 2001. Russia Average World Price: Crude Oil: Urals: per 1 Barrel data remains active status in CEIC and is reported by Ministry of Finance of the Russian Federation. The data is categorized under Global Database’s Russian Federation – Table RU.PC002: Average World Prices, Crude Oil Export Price, Crude Oil Export Duty.

Monthly and long-term Venezuela data: historical series and analyst forecasts curated by FocusEconomics.

Nigeria Crude Oil Price: Bonny Light: per Barrel data was reported at 65.350 USD/Barrel in 26 Nov 2025. This records an increase from the previous number of 65.050 USD/Barrel for 25 Nov 2025. Nigeria Crude Oil Price: Bonny Light: per Barrel data is updated daily, averaging 67.540 USD/Barrel from Oct 2009 (Median) to 26 Nov 2025, with 3752 observations. The data reached an all-time high of 139.410 USD/Barrel in 08 Mar 2022 and a record low of 7.150 USD/Barrel in 21 Apr 2020. Nigeria Crude Oil Price: Bonny Light: per Barrel data remains active status in CEIC and is reported by Central Bank of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.P: Crude Oil Price. [COVID-19-IMPACT]

Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data was reported at 1,070.597 USD/Metric Ton in Feb 2025. This records an increase from the previous number of 1,039.440 USD/Metric Ton for Jan 2025. Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data is updated monthly, averaging 678.477 USD/Metric Ton from Jan 2014 (Median) to Feb 2025, with 134 observations. The data reached an all-time high of 1,652.529 USD/Metric Ton in Mar 2022 and a record low of 435.238 USD/Metric Ton in Nov 2018. Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Indonesia Premium Database’s Monetary – Table ID.KAI002: Financial System Statistics: Macroeconomic Indicator.

UPDATES

Data is now available from 2004 to may 2021. NULL values are now replaces with -99999 ANP official website has monthly data until Feb 2022, but since this dataset is weekly organized it will be update to 2022 values as soon as this information is available.

The Data

The National Agency of Petroleum, Natural Gas and Bio fuels (ANP in Portuguese) releases weekly reports of gas, diesel and other fuels prices used in transportation across the country. These datasets bring the mean value per liter, number of gas stations analyzed and other information grouped by regions and states across the country.

Source

As stated before, these datasets are provided by ANP, and are regularly updated with new dates and information - which can be retrieved here (in portuguese).

What can be done with this?

• How different regions of Brazil saw their gas prices change?
• Within a region, which states increased more their prices?
• Which states are the cheapest (or most expensive) for different types of fuels?

Gasoline fell to 1.86 USD/Gal on December 2, 2025, down 0.53% from the previous day. Over the past month, Gasoline's price has fallen 2.79%, and is down 4.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - values, historical data, forecasts and news - updated on December of 2025.

Algeria Export Price: Annual: Crude Oil data was reported at 334.600 USD/Barrel in 2023. This records an increase from the previous number of 103.700 USD/Barrel for 2022. Algeria Export Price: Annual: Crude Oil data is updated yearly, averaging 65.700 USD/Barrel from Dec 2001 (Median) to 2023, with 23 observations. The data reached an all-time high of 334.600 USD/Barrel in 2023 and a record low of 24.300 USD/Barrel in 2001. Algeria Export Price: Annual: Crude Oil data remains active status in CEIC and is reported by General Directorate of Customs. The data is categorized under Global Database’s Algeria – Table DZ.P002: Export Price of Hydrocarbon.

Explore the latest data on Bahrain's oil and non-oil sector GDP at current and constant prices. Gain insights into key economic indicators such as Net Exports, Gross Domestic Saving, and GNI per capita. Access the dataset now!

Net Current Transfer From Abroad, Oil sector GDP, Oil sector % of GDP, Total Final Consumption : Government, Total Final Consumption : Government (Annual Growth), Constant prices, GNDI Per capita (BD), Total Final Consumption : Private (Annual Growth), Total Final Consumption, Net Primary Income and Current Transfer (as % of GDP), Government % of GDP, Non-oil sector % of GDP, Change in Stocks, Population, Gross Fixed Capital Formation : Government, GDP per capita (BD), Gross National Disposable Income (GNDI), Domestic Saving, Gross (% of GDP), Gross Domestic Product (GDP), National Saving, Gross (% of GDP), Net Exports Goods & Services (% of GDP), Gross Fixed Capital Formation : Private, Current Prices, Total Final Consumption % of GDP, Domestic Saving, Gross, Non-oil sector GDP, Total Final Consumption (Annual Growth), Imports of Goods & Services, Oil sector (Annual Growth), National Saving, Gross, GNI per capita (BD), Non-oil sector (Annual Growth), Total Final Consumption : Private, Gross Fixed Capital Formation : Government (% of GDP), Gross Fixed Capital Formation : Private (% of GDP), Net Exports of Goods & Services, Gross National Income (GNI), Private % of GDP, Gross Fixed Capital Formation, Imports of Goods & Services (% of GDP), Gross Fixed Capital Formation (% of GDP), Exports of Goods & Services (% of GDP), Net Lending/Borrowing, BD Million, %, Exports of Goods & Services, Net Primary Income from Abroad, National Accounts, Oil Sector, Non-oil, final consumption, GFCF, exports, imports, Gross Domestic Saving, Gross National Saving, Per capita, GNI, GDI, lending, borrowing, Current prices, Constant prices, Bahrain National Accounts Annual Report

BahrainFollow data.kapsarc.org for timely data to advance energy economics research..