Long term historical dataset of the NASDAQ Composite stock market index since 1971. Historical data is inflation-adjusted using the headline CPI and each data point represents the month-end closing value. The current month is updated on an hourly basis with today's latest value.

This statistic shows the stock prices of selected food commodities from January 2, 2020 to February 6, 2025. After the Russian invasion of Ukraine in February 2022, wheat prices increased significantly since both Russia and Ukraine are the key suppliers of the product. With the beginning of 2023, prices of selected food commodities started to decrease, but still stood higher than early-2020 levels.

Corn decreased 3.39 USd/BU or 0.74% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on March of 2025.

This statistic shows the stock prices of selected oil and gas commodities from January 2, 2020 to February 4, 2025. After the Russian invasion of Ukraine in February 2022, energy prices climbed significantly. The highest increase can be observed for natural gas, whose price peaked in August and September 2022. By the beginning of 2023, natural gas price started to decline.

Graph and download economic data for Producer Price Index by Commodity: Lumber and Wood Products: Hardwood Cut Stock and Dimension (WPU08120311) from Jun 1984 to Feb 2025 about floor coverings, stocks, wood, commodities, PPI, inflation, price index, indexes, price, and USA.

This statistic shows the stock prices of selected raw material commodities from January 2, 2020 to Februrary 5, 2025. After the Russian invasion of Ukraine in February 2022, metal prices increased significantly due to disruptions to supply chain and increased demand. Since then, stock values of raw materials started to decrease albeit with some fluctuations.

Explore the key factors affecting NASDAQ soybean futures and options, including supply and demand dynamics, weather conditions, geopolitical events, and economic trends, and understand their impact on prices in this essential agricultural commodities market.

The wheat price stock market is an important component of the agricultural commodities market, providing a platform for farmers, traders, and investors to manage price risks and hedge against fluctuations in wheat prices. This article discusses the factors influencing the price of wheat, the participants in the wheat price stock market, and the role of commodity exchanges in facilitating trading.

Orange Juice decreased 237.26 USd/Lbs or 47.69% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Orange Juice - values, historical data, forecasts and news - updated on March of 2025.

Gold increased 393.93 USD/t oz. or 15.01% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on March of 2025.

Drive your entire business from front to back office with delayed exchange data from Barchart. Our consolidated feeds can power your product, services, with global coverage of commodity prices, stock quotes, and trade executions.

Asset Classes Include: Equities Futures Cash Commodities Forex & Crypto Index Mutual Funds

Gain data-driven insights for informed investment decisions. Access market sentiment data since 2013 and customize the API for seamless integration. Maximize your stock market understanding with comprehensive analytics on global stock indices, and public and private companies. Analyze sentiment trends and investor behavior with confidence.

Sample Dataset - Historical News Sentiment data for your reference.

Key Features:

1. Tick-by-Tick Sentiment: Access detailed market dynamics with tick-by-tick sentiment data.
2. Custom API: Request a customizable API covering over 70,000 tickers, including major FX, commodities, topics, and people.
3. Proven Expertise: Trust our track record since 2013 for historical data on long-term sentiment patterns.
4. Uncover Hidden Insights: Gauge investor sentiment and reveal market opportunities with the custom API.
5. Real-Time Benchmarks: Enhance your strategies with real-time sentiment indicators.
6. Customizable and Flexible Delivery: Tailor the dataset to your requirements and integrate seamlessly into your workflows.

Gain a competitive edge with InfoTrie's Historical Tick-by-Tick Stock Market Sentiment Data. Request access now to elevate your investment strategies and make data-driven decisions.

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Long term dataset showing the annual percentage change of the NASDAQ Composite Index back to 1972. Performance is calculated as the % change from the last trading day of each year from the last trading day of the previous year.

Ten years of daily data for the Dow Jones Industrial Average (DJIA) market index. Each point of the dataset is represented by the daily closing price for the DJIA. Historical data can be downloaded via the red button on the upper right corner of the chart.

Coffee increased 55.82 USd/Lbs or 17.42% since the beginning of 2025, 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 March of 2025.

Market sentiment data provides a glimpse into investor perceptions and emotions driving market movements. Understand whether sentiments are bullish, bearish, or neutral, and use these insights to fine-tune your trading decisions.

1. Explore an extensive database of global market indices.
2. 100+ market indices worldwide, from major stock markets to niche sectors.
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4. A deeper understanding of market sentiment dynamics.
5. Leverage a custom API for over 70,000 tickers, including major FX, commodities, topics, and individuals.
6. Benchmark against real-time market sentiment indicators.
7. 360° Market Dynamics on comprehensive stock market sentiment data.

Mold the dataset to match needs and seamlessly integrate it into various workflows. Count on InfoTrie's proven expertise to deliver accurate and custom stock market data for market analysis.

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More information on : https://infotrie.com/sentiment-analysis/

Historical dataset of nominal and real (inflation-adjusted) gold prices per ounce back to 1915. The series is deflated using the headline Consumer Price Index (CPI) with the most recent month as the base. The current month is updated on an hourly basis with today's latest value.

In 2025, the price of platinum is forecast to hover around 1,150 U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to 1,700 U.S. dollars.

Precious metals

Precious metals are counted among the most valuable commodities worldwide. The most well known such metals are gold, silver and the platinum group metals. A precious metal can be used as an industrial commodity or as an investment. The major areas of application include the following sectors: technology, car-making, industrial manufacturing and jewelry making. Furthermore, gold and silver are used as coinage metals, and gold reserves are held by the central banks of many countries worldwide in order to store value or for use as a redemption medium. The idea behind this procedure is that gold reserves will help secure and stabilize the countries’ respective currencies. At 8,100 tons, the United States is the country with the most extensive stock of gold. It is kept in an underground vault at the New York Federal Reserve Bank.

Russia, the United States, Canada, South Africa and China are the main producers of precious metals. Silver is the most abundant of the metals, followed by gold and palladium. Barrick Gold is the world’s largest gold mining company. The Toronto-based firm produced some five million ounces of gold in 2020. The leading silver producers include Mexico-based Fresnillo, Poland’s KGHM Polska Miedž and the mining giant Glencore. Anglo Platinum and Impala are the key mining companies to produce platinum group metals.

In 2023, Silver prices are expected to settle at around 23.5 U.S. dollars per troy ounce. It is expected to remain the precious metal with the lowest value per ounce. The price of gold is forecast to drop to around 1,663 U.S. dollars per ounce, making it the most expensive precious metal in 2023.

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.

Commodity Index: The Future of Investing?

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

Explore how economic indicators, geopolitical stability, and industrial demand influence silver prices in the stock market and commodities trading. Learn about the impact of central banks' monetary policies and the role of silver in sectors like electronics and clean energy. Discover investment options like silver ETFs and mining stocks to diversify portfolios and manage market volatility.