The main stock market index of United States, the US500, rose to 6397 points on August 11, 2025, gaining 0.12% from the previous session. Over the past month, the index has climbed 2.04% and is up 19.69% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on August of 2025.

The curated dataset consists of comprehensive financial data covering NASDAQ stocks, currency exchange rates, and cryptocurrency prices. The data spans from January 1, 2003, to June 11, 2023, and includes the following key features: 'Open', 'High', 'Low', 'Close', 'Volume', 'Year', and 'YTD Gain'.

Open: This column represents the opening price of the stock or the exchange rate at the beginning of the trading day. It indicates the initial value at which trading starts.

High: The 'High' column signifies the highest price or exchange rate reached during the trading day. It indicates the peak value observed during the trading period.

Low: The 'Low' column captures the lowest price or exchange rate recorded during the trading day. It indicates the minimum value observed during the trading period.

Close: This column represents the closing price of the stock or the exchange rate at the end of the trading day. It indicates the final value at which trading concludes.

Volume: The 'Volume' column denotes the total number of shares or units traded during the day. It reflects the level of activity or liquidity in the market.

Year: The 'Year' column identifies the specific year to which each data point corresponds. It enables analysis and comparison based on yearly trends.

YTD Gain: The 'YTD Gain' column provides the Year-to-Date gain percentage for each stock, currency, or cryptocurrency. It calculates the percentage change in value from the start of the year to the current date. This metric helps assess the performance of assets within a given year.

The dataset offers valuable insights and opportunities for analysis, research, and decision-making in the financial domain. It can be utilized in several ways:

Market Analysis: The dataset enables thorough analysis of NASDAQ stocks, currency markets, and cryptocurrencies. By examining price movements, trading volumes, and yearly trends, analysts can gain a comprehensive understanding of market dynamics.

Investment Strategies: Investors can leverage the dataset to develop and test investment strategies. The historical data, including opening, closing, high, and low prices, combined with the 'YTD Gain' metric, allows for the identification of potential investment opportunities.

Risk Management: Risk managers can utilize the dataset to evaluate and manage portfolio risk. By examining historical data and analyzing volatility and 'YTD Gain,' risk exposure can be assessed and appropriate risk management strategies can be implemented.

Academic Research: The dataset provides a valuable resource for researchers in the fields of finance, economics, and data science. It allows for empirical analysis, modeling, and the testing of hypotheses related to stock markets, currency markets, and cryptocurrencies.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

Use our Stock Market dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

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.

What are the most successful trading algorithms? (NSE RBLBANK Stock Forecast)

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

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of ETH-EUR pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.

US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.

US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.

End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.

Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.

Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

This dataset is about book subjects. It has 3 rows and is filtered where the books is The big trade : simple strategies for maximum market returns. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

We offer three easy-to-understand packages to fit your business needs. Visit intrinio.com/pricing to compare packages.

Bronze

The Bronze package is ideal for developing your idea and prototyping your platform with high-quality EOD options prices sourced from OPRA.

When you’re ready for launch, it’s a seamless transition to our Silver package for delayed options prices, Greeks and implied volatility, and unusual options activity, plus delayed equity prices.

• Latest EOD OPRA options prices

Exchange Fees & Requirements:

This package requires no paperwork or exchange fees.

Bronze Benefits:

• Web API access
• 300 API calls/minute limit
• File downloads
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support

Silver

The Silver package is ideal for clients that want delayed options data for their platform, or for startups in the development and testing phase. You’ll get 15-minute delayed options data, Greeks, implied volatility, and unusual options activity, plus the latest EOD options prices and delayed equity prices.

You can easily move up to the Gold package for real-time options and equity prices, additional access methods, and premium support options.

• 15-minute delayed OPRA options prices, Greeks & IV
• 15-minute delayed OPRA unusual options activity
• Latest EOD OPRA options prices
• 15-minute delayed equity prices
• Underlying security reference data

Exchange Fees & Requirements:

If you subscribe to the Silver package and will not display the data outside of your firm, you’ll need to fill out a simplified exchange agreement and send it back to us. There are no exchange fees and we can provide immediate access to the data.

If you subscribe to the Silver package and will display the data outside of your firm, we’ll work with your team to submit the correct paperwork to OPRA for approval. Once approved, OPRA will bill exchange fees directly to your firm – typically $600-$2000/month depending on your use case. These fees are the same no matter what data provider you use. Per-user reporting is not required, so there are no variable per user fees.

Silver Benefits:

• Assistance with OPRA paperwork
• Web API access
• 2,000 API calls/minute limit
• File downloads
• Access to third-party datasets via Intrinio API (additional fees required)
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support
• Concierge customer success team
• Comarketing & promotional initiatives

Gold

The Gold package is ideal for funded companies that are in the growth or scaling stage, as well as institutions that are innovating within the fintech space. This full-service solution offers real-time options prices, Greeks and implied volatility, and unusual options activity, as well as the latest EOD options prices and real-time equity prices.

You’ll also have access to our wide range of modern access methods, third-party data via Intrinio’s API with licensing assistance, support from our team of expert engineers, custom delivery architectures, and much more.

• Real-time OPRA options prices, Greeks & IV
• Real-time OPRA unusual options activity
• Latest EOD OPRA options prices
• Real-time equity prices
• Underlying security reference data

Exchange Fees & Requirements:

If you subscribe to the Gold package, we’ll work with your team to submit the correct paperwork to OPRA for approval. Once approved, OPRA will bill exchange fees directly to your firm – typically $600-$2000/month depending on your use case. These fees are the same no matter what data provider you use. Per-user reporting is required, with an associated variable per user fee.

Gold Benefits:

• Assistance with OPRA paperwork
• Web API access
• 2,000 API calls/minute limit
• WebSocket access (additional fee)
• Customizable access methods (Snowflake, FTP, etc.)
• Access to third-party datasets via Intrinio API (additional fees required)
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support
• Concierge customer success team
• Comarketing & promotional initiatives
• Access to engineering team

Platinum

Don’t see a package that fits your needs? Our team can design a premium custom package for your business.

Japan's main stock market index, the JP225, rose to 41820 points on August 8, 2025, gaining 1.85% from the previous session. Over the past month, the index has climbed 5.02% and is up 19.40% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on August of 2025.

OTC Commodity Trading Platform Market Outlook

As of 2023, the global market size for OTC commodity trading platforms is valued at approximately USD 2.5 billion and is expected to reach around USD 6.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.2% during the forecast period. The rapid digitalization of trading activities and the increasing complexity of commodity markets serve as significant drivers of this robust market expansion.

One of the primary growth factors for the OTC commodity trading platform market is the increasing reliance on digital technologies to streamline and optimize trading operations. With advancements in Artificial Intelligence (AI) and blockchain technology, trading platforms are now equipped with more sophisticated tools for risk management, data analytics, and transaction security. These innovations are particularly vital in the OTC (Over-The-Counter) markets, where trades are not standardized and require bespoke solutions for each transaction.

Another driving force is the rising demand for commodities as alternative investment assets. As financial markets become more volatile, investors are diversifying their portfolios to include commodities like gold, crude oil, and agricultural products. This diversification trend has led to a surge in the number of individual traders and financial institutions utilizing OTC trading platforms to facilitate their trades. Consequently, the need for platforms that offer reliable, real-time data and efficient trade execution has never been higher.

Regulatory changes and the increasing globalization of commodity markets also contribute to market growth. Stricter regulatory frameworks require more transparent and compliant trading practices, which these advanced platforms are well-equipped to offer. Additionally, as commodity markets become more interconnected globally, there is a heightened need for platforms that can handle multi-currency transactions, cross-border trades, and compliance with different regional regulations.

Regionally, North America currently holds a dominant market share due to its advanced financial infrastructure and high adoption rate of digital trading solutions. However, the Asia Pacific region is projected to exhibit the highest growth rate over the forecast period. The rapid industrialization and growing awareness of digital trading solutions in countries like China and India are key contributors to this regional surge.

Component Analysis

In the OTC commodity trading platform market, components are primarily classified into software and services. The software segment dominates the market due to the integral role that advanced software solutions play in facilitating complex trading operations. Modern software platforms offer a range of functionalities, from real-time market data analysis to automated trading and risk management. These capabilities are essential for traders looking to optimize their strategies and maximize returns in volatile markets.

The services segment, while smaller in comparison, is equally critical. It encompasses a broad range of offerings, including consulting, implementation, training, and managed services. As trading platforms become more complex and integrated with other financial systems, the need for expert services to ensure seamless operation and compliance with regulatory standards becomes increasingly important. Traders and financial institutions often rely on these services to gain a competitive edge and mitigate operational risks.

Within the software segment, there is a growing trend towards the integration of AI and machine learning algorithms. These technologies enable platforms to provide predictive analytics, enhance decision-making capabilities, and offer personalized trading strategies. The incorporation of blockchain technology for transaction security and transparency is another noteworthy trend, aimed at reducing fraud and enhancing trust in OTC markets.

The services segment is witnessing an upsurge in demand for managed services, particularly among small and medium-sized enterprises (SMEs) that may lack the in-house expertise to manage complex trading operations. Managed services offer a cost-effective solution by outsourcing the management of the trading platform to specialized providers. This trend is expected to continue as more SMEs enter the OTC commodity trading space.

Overall, the component analysis underscores the critical importance of both software and services in the OTC commod

Brazil's main stock market index, the IBOVESPA, fell to 135913 points on August 8, 2025, losing 0.45% from the previous session. Over the past month, the index has declined 1.14%, though it remains 4.06% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Brazil. Brazil Stock Market (BOVESPA) - values, historical data, forecasts and news - updated on August of 2025.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date exports using the North American Industry Classification System (NAICS). The NAICS endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

Gold rose to 3,397.28 USD/t.oz on August 8, 2025, up 0.06% from the previous day. Over the past month, Gold's price has risen 2.52%, and is up 39.77% compared to the same time last year, 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 August of 2025.

Market Inside is a global leader in providing import export data informAation and analytics for major industries and markets. We accelerate business progress by delivering essential intelligence that unlocks opportunities and fosters growth.

Our database contains: • 220+ Countries’ Global Trade Data • 2.5+ Billion Shipment Records • 100+ Million Import-Export Companies • 40+ Million Decision Maker Direct Phone Numbers • 50+ Million Decision Maker Direct Email Addresses

By using our dashboard, customers can access: • Bill of lading data by HS Code or product description. • Product specifications like brand, model, type, etc. • Company information like name, size, location and so on. • Companies’ business information such as market share, industry, etc. • Contacts data including name & profile of employees and phone numbers & email addresses of key decision makers. • Location data like origin country, destination and port of loading & unloading. • Our import export data can be used by investors, private equity firms, hedge funding corporations, government agencies, environmental studies agencies, universities, private and government companies to track, analyze, research and gain better insights of global trade of more than 10M+ Commodities.

This dataset presents an extensive record of daily historical stock prices for Tesla, Inc. (TSLA), one of the world’s most innovative and closely watched electric vehicle and clean energy companies. The data was sourced from Yahoo Finance, a widely used and trusted provider of financial market data, and covers a significant period spanning from Tesla’s initial public offering (IPO) to the most recent date available at the time of extraction.

The dataset includes critical trading metrics for each market day, such as the opening price, highest and lowest prices of the day, closing price, adjusted closing price (accounting for dividends and splits), and total trading volume. This rich dataset supports a variety of use cases, including financial market analysis, investment research, time series forecasting, development and backtesting of trading algorithms, and educational projects in data science and finance.

Dataset Features

• Date: The calendar date for each trading session (in YYYY-MM-DD format)
• Open: The opening price of TSLA shares at the start of the trading day
• High: The highest price reached during the trading session
• Low: The lowest price reached during the trading session
• Close: The last price at which the stock traded during the day
• Adj Close: The closing price adjusted for corporate actions (splits, dividends, etc.)
• Volume: The total number of TSLA shares traded on that day

Source and Collection Details

• Source: Yahoo Finance - Tesla (TSLA) Historical Data
• Collection Method: Data was downloaded using Yahoo Finance's CSV export feature for accuracy and completeness.
• Time Range: Covers from Tesla’s IPO (June 2010) to the most recent available trading day.
• Data Integrity: Minimal cleaning was performed—dates were standardized, and any duplicate or empty rows were removed; all values remain as originally reported by Yahoo Finance.

Example Use Cases

• Stock Price Prediction: Train and test time series models (ARIMA, LSTM, Prophet, etc.) to forecast Tesla’s stock prices.
• Algorithmic Trading: Backtest and evaluate trading strategies using historical price and volume data.
• Market Trend Analysis: Analyze price trends, volatility, and return rates over different periods.
• Event Study: Investigate the impact of major announcements (e.g., product launches, earnings releases) on TSLA stock price.
• Educational Projects: Use as a hands-on resource for learning finance, statistics, or machine learning.

License & Acknowledgments

• Intended Use: This dataset is provided for academic, research, and personal projects. For commercial or investment use, please verify data accuracy and consult Yahoo Finance’s terms of use.
• Acknowledgment: Data sourced from Yahoo Finance. All trademarks and copyrights belong to their respective owners.