Food price increases hit the egg category the hardest between December 2021 and December 2024 in the United States. The price of eggs increased by **** percent in 2024.

Natural gas rose to 4.94 USD/MMBtu on December 3, 2025, up 2.04% from the previous day. Over the past month, Natural gas's price has risen 13.71%, and is up 62.29% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on December of 2025.

Coffee fell to 408.66 USd/Lbs on December 2, 2025, down 0.95% from the previous day. Over the past month, Coffee's price has risen 0.50%, and is up 38.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on December of 2025.

Stock Price Time Series for Rising Nonferrous Metals Share Co Ltd. Rising Nonferrous Metals Share Co.,Ltd. engages in the mining, smelting separation, deep processing, and trading of rare earth and non-ferrous metals in China. Its products include rare earth concentrates, minerals, mixed rare earths, rare earth oxides, and rare earth permanent magnet materials, as well as tungsten and other products. Rising Nonferrous Metals Share Co.,Ltd. was founded in 1993 and is based in Guangzhou, China.

Several states in the United States are expected to incur costs associated to sea-level rise adaptation measures by 2040. Florida will be the most impacted state; it is forecast that adaptation costs due to sea-level rise will reach almost ** billion U.S. dollars.

This dataset contains the predicted prices of the asset Infinity Rising over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Statista estimates have created a hypothetical forecast of the potential cost to residential real estate due to rising sea-levels if no further action is taken to mitigate risks across Europe. The estimate, which takes 2020 estimates into account for total populations, populations below locked-in seas levels, the number of residential buildings in at-risk areas and the average size and cost of real estate by city. The scenario measures lower and upper estimates for global average temperature changes by 2100. Far more can be learnt on the potential costs to real estate in Europe through sea-level rises in our report. As well as giving easy to digest figures, the report also covers a global perspective and how each city is combating the growing threat of coastal and river flooding due to climate change.

This dataset contains the predicted prices of the asset Rising Phoenix over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Gold Resource Corp. (GORO) Sees Promising Outlook Amidst Rising Metal Prices

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Index Time Series for Fidelity® Dividend ETF for Rising Rates. The frequency of the observation is daily. Moving average series are also typically included. The fund normally invests at least 80% of assets in securities included in the underlying index and in depository receipts representing securities included in the underlying index. The underlying index is designed to reflect the performance of stocks of large and mid-capitalization dividend-paying companies that are expected to continue to pay and grow their dividends and have a positive correlation of returns to increasing 10-year U.S. Treasury yields.

U.S. consumers noticed price increases in a range of venues in the six months leading up to the fall of 2022. More than ** percent of respondents perceived price increases in supermarkets, while another ** percent noticed them in restaurants. In contrast, ** percent said they noticed price increases in furniture stores.

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.

The rate at which prices for goods and services are generally rising and, as a result, currency's purchasing power is declining is known as inflation. Central banks attempt to limit inflation—and avoid deflation—in order to keep the economy running smoothly. Each unit of currency may purchase fewer products and services as prices rise. This results in a reduction in the actual value of money, a process that impacts every level of the economy, from consumers to governments. The percentage change in the cost of a basket of goods and services over a certain time period, often a year, is measured by the inflation rate. It’s a key metric for assessing the health of an economy, showing how much more expensive everyday goods and services have become. The change in the average price level of a basket of goods and services over a year is represented by the inflation rate average consumer prices (annual per cent change). It’s calculated by taking the average of prices across all months of a given year compared to the previous year. This metric is determined by averaging monthly price data and comparing it to the average of the previous year. It provides a broader view of inflation trends across a longer time frame, smoothing out any short-term volatility. The Inflation rate, end of period consumer prices (annual per cent change) reflects the price level change from the end of one period (typically December) to the end of the next period (the following December). Instead of taking an average, this rate focuses on the price level at a specific point in time, providing a snapshot of inflation. It’s calculated by comparing the Consumer Price Index (CPI) of the final month of the year with the CPI of the last month of the previous year.

According to a survey conducted in March 2024, 45 percent of U.S. Generation Z consumers were purchasing meat/poultry/fish less often due to rising prices and/or supply shortages. Another 44 percent were purchasing snacks/desserts less often for the same reason.

Discover the booming silver market's future! This comprehensive analysis reveals a CAGR exceeding 5%, driven by jewelry, electronics, and investment demand. Explore key trends, restraints, and regional breakdowns for the period 2019-2033. Learn which companies are leading the charge and how this precious metal's future is shaping up. Recent developments include: April 2023: Impact Silver Corp. announced the completion of the share purchase and sale agreement with Consolidated Zinc Limited of Australia, the purchase of all outstanding shares of its subsidiary, Minera Latin America Zinc S.A.P.I de C.V., which holds a 100% interest in the high-grade, Plomosas zinc-lead-silver mine in the state of Chihuahua, northern Mexico. The agreement consists of a total price of USD 6 million out of which USD 3 million is to be given in cash and the balance in the form of IMPACT shares., March 2023: Pan American Silver Corp announced the USD 4.8 billion acquisition of all the issued and outstanding common shares of Yamana Gold, following the sale by Yamana of its Canadian assets, including certain subsidiaries and partnerships. With this acquisition, the company expects a material increase in the production of silver and gold, while also continuing to provide a preferred way to invest in silver through large silver mineral reserves and growth opportunities.. Key drivers for this market are: Increasing Demand for Silver in Industrial and Electrical Applications, Rising Demand for Silver in Jewelry and Silverware. Potential restraints include: Increasing Demand for Silver in Industrial and Electrical Applications, Rising Demand for Silver in Jewelry and Silverware. Notable trends are: Electrical and Electronics Application to Dominate.

Dataset Description: The Rise of Nvidia Stocks

This dataset provides a comprehensive analysis of Nvidia’s stock performance over time, covering key financial data such as stock prices, dividends, and stock splits. Nvidia, a global leader in GPU technology and AI innovation, has experienced significant growth in recent years, making this dataset valuable for financial analysis and investment research.

Key Components:

Daily Stock Prices: This section contains daily open, high, low, close prices, and trading volume for Nvidia (NVDA), enabling users to analyze market trends and price fluctuations over time.

Stock Dividends: Historical dividend data is included, providing insights into Nvidia’s dividend payout history and shareholder returns, useful for evaluating long-term investment potential.

Stock Splits: Details on Nvidia's stock splits, including split dates and ratios, are provided to help understand how the company has adjusted its share structure to accommodate growth and investor demand.

Purpose:

This dataset is designed for financial analysts, investors, and researchers interested in understanding Nvidia’s financial trajectory and market performance. By analyzing stock price trends, dividend history, and split records, users can gain valuable insights to make informed investment decisions and track Nvidia’s growth in the semiconductor industry.

Data Sources:

Alpha Vantage: Used to retrieve daily stock price and dividend data via their API for accurate and up-to-date financial metrics.

The price of paper is represented by a Bureau of Labor Statistics index that measures the prices received by paper manufacturers for their products. The index has a base year of 1982.

HRC Steel fell to 891.06 USD/T on December 2, 2025, down 0.88% from the previous day. Over the past month, HRC Steel's price has risen 5.08%, and is up 29.14% 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 HRC Steel.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Tech Tide Rising: Can Technology Stocks Ride the Wave?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This dataset contains the predicted prices of the asset Rise of PNUT over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.