Dataset Description: Microsoft Stock Prices (One Year)

-This dataset contains daily trading information for Microsoft Corporation (MSFT) stock over a one-year period. Each entry represents a single trading day and includes essential stock market data.

Columns and Descriptions:

-**Date:** The trading day in YYYY-MM-DD format.

-**Open:** Stock price at market open.

-**High:** Highest stock price during the day.

-**Low:** Lowest stock price during the day.

-**Close:** Stock price at market close.

-**Volume:** Number of shares traded on that day.

-This dataset is suitable for time series analysis, stock price forecasting, and machine learning projects focused on financial data.

In 2024, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

Experience a decade of NASDAQ market dynamics with this comprehensive historical price dataset from 2014 to 2024.

The NASDAQ Composite is a benchmark index representing the performance of more than 2,500 stocks listed on the NASDAQ stock exchange, encompassing various sectors including technology, healthcare, and finance. This dataset, sourced meticulously from Yahoo Finance, offers daily insights into the index's opening, highest, lowest, and closing prices, along with adjusted close prices and daily volume.

Foreign Direct Investment in the United States increased by 66726 USD Million in the first quarter of 2025. This dataset provides - United States Foreign Direct Investment - actual values, historical data, forecast, chart, statistics, economic calendar and news.

CoinAPI's crypto OHLCV and trade data give you the complete picture of market activity across more than 350 exchanges worldwide. Our candlestick data covers everything from 1-second intervals for scalping to monthly timeframes for trend analysis, ensuring you have the right level of detail for your trading approach.

Each candlestick provides the essential price information traders rely on - open, high, low, and close prices - along with corresponding volume data that shows the market strength behind each move. This combination of price action and trading volume creates the foundation for effective technical analysis and trading decisions.

Getting this data is straightforward - use our WebSocket streams for real-time market monitoring when every second counts, or access historical candlesticks through our REST API when you're conducting deeper market research or backtesting strategies. We maintain comprehensive historical records, giving you the ability to analyze patterns across different market cycles.

Why work with us?

Market Coverage & Data Types: - Full Cryptocurrency Data - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume

Technical Excellence: - 99% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

Whether you're building algorithmic trading systems, conducting research, or creating visualization tools, our real-time and historical candlesticks from exchanges worldwide provide the reliable market data you need

Arlington Asset Investment stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Gold rose to 3,347.78 USD/t.oz on August 12, 2025, up 0.14% from the previous day. Over the past month, Gold's price has risen 0.15%, and is up 35.86% 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.

This dataset contains the monthly historical data of the S&P 500 index from January 1901 to May 2025, collected from Investing.com. The S&P 500 is a stock market index that tracks the performance of 500 large companies listed on stock exchanges in the United States.

It is widely used as a benchmark for the U.S. equity market, representing over 80% of the total market capitalization. This dataset is suitable for:

• Time-series forecasting
• Economic event impact analysis (e.g., wars, recessions, pandemics)
• Financial visualizations in Tableau or Power BI
• Quantitative finance and portfolio management research

Column Descriptions

Potential Use Cases:

• Visualizing market impact of wars, financial crises, and pandemics
• Analyzing long-term trends in the U.S. equity market
• Forecasting future index levels using machine learning
• Annotating economic history alongside market movements

Citation:

Data source: Investing.com

Full historical data for the S&P 500 (ticker ^GSPC), sourced from Yahoo Finance (https://finance.yahoo.com/).

Including Open, High, Low and Close prices in USD + daily volumes.

Info about S&P 500: https://en.wikipedia.org/wiki/S%26P_500

This data file contains the annual weights and returns of the global invested multi-asset market portfolio of Doeswijk, Lam, and Swinkels (2019) "Historical returns of the market portfolio" Review of Asset Pricing Studies

This dataset contains the daily historical stock prices for Apple Inc. (AAPL) over the past year. The data includes key indicators for each trading day, providing insights into the company's stock performance and volatility. It is ideal for financial analysis, predictive modeling, and educational projects focused on time series forecasting, quantitative finance, and machine learning applications.

Data Columns:

-**Date:** The trading date (YYYY-MM-DD)

-**Open:** Stock price at market open (USD)

-**High:** Highest price during the trading day (USD)

-**Low:** Lowest price during the trading day (USD)

-**Close:** Price at market close (USD)

-**Volume:** Number of shares traded

Use Cases:

-Analyzing price trends and volatility for AAPL

-Building forecasting models for future stock prices

-Feature engineering for machine learning or statistical algorithms

-Comparing performance with other stocks or indices

Dataset

This dataset was created by Phuc Le

Contents

Property Investment in China decreased to -11.20 percent in June from -10.70 percent in May of 2025. This dataset includes a chart with historical data for China Property Investment YoY.

Historical Dividends API gives you right away data on dividend payments and dividend calendar. Dividend-paying stocks are often interpreted as a signal for a company's profitability. Successfully performing companies are said to pay dividends to shareholders. The dividend amount of the payment is split into smaller payments made throughout the fiscal year. This happen annually, semi-annually or quarterly. Our historical dividends data is what you need to complete the financial analysis you do on the companies of your choice. It is a valuable tool for making investing decisions and streamlining financial projects. In the upcoming months, ex-dividend date, declaration date and payment date will be added to the data.

If you are interested to learn more, check out the company website: https://tradefeeds.com/historical-dividends-api/

Backtesting Tools Market Outlook

The global backtesting tools market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.3% during the forecast period. The increasing adoption of algorithmic trading and the need for robust risk management solutions are key drivers fueling this growth.

The market for backtesting tools is buoyed by the rising prominence of algorithmic trading, driven by technological advancements and the demand for automated trading solutions. Algorithmic trading requires sophisticated tools to simulate trading strategies in historical data before deploying them in live markets. This need for precision and reliability in trading strategies is pushing financial institutions and individual traders to adopt advanced backtesting tools. Additionally, the increasing availability of historical market data enhances the accuracy and effectiveness of these tools, further promoting market growth.

Another significant growth factor is the heightened focus on risk management across financial institutions. Financial markets are inherently volatile, and institutions are increasingly recognizing the importance of robust risk management frameworks to safeguard against potential losses. Backtesting tools enable these institutions to assess risk by evaluating how trading strategies would have performed under past market conditions. This capability is crucial for banks, hedge funds, and investment firms to ensure their strategies are resilient and capable of withstanding adverse market scenarios.

Furthermore, regulatory requirements are also propelling the adoption of backtesting tools. Financial regulators across the globe are mandating rigorous testing of trading strategies to ensure market stability and protect investors. Compliance with these regulations necessitates the use of sophisticated backtesting tools that can provide detailed insights into trading performance and potential risks. As a result, financial institutions are investing in advanced backtesting solutions to meet regulatory standards and enhance their strategic decision-making processes.

Regionally, the North American market is expected to lead the growth of backtesting tools, owing to the high concentration of financial institutions, hedge funds, and ongoing advancements in financial technology. The Asia Pacific region is also anticipated to witness significant growth due to the expanding financial markets and increasing adoption of algorithmic trading. Europe, with its stringent regulatory environment, will continue to see steady adoption, while Latin America and the Middle East & Africa regions are gradually catching up as financial markets in these areas develop.

Component Analysis

The backtesting tools market is segmented by components into software and services. The software segment encompasses various types of backtesting platforms designed to simulate trading strategies using historical data. This segment holds a substantial share of the market, driven by the continuous need for reliable and sophisticated tools that can accurately backtest a myriad of trading strategies. Financial institutions and individual traders predominantly invest in these software solutions to gain a competitive edge and ensure their trading models are robust and profitable.

The services segment, although smaller compared to the software segment, plays a critical role in the market. Services include consulting, implementation, and support services that assist users in setting up and effectively utilizing backtesting tools. With the complexity of financial markets and trading strategies, the demand for expert guidance to navigate these tools is growing. Financial institutions often rely on these services to tailor the backtesting tools to their specific needs, ensuring optimal performance and compliance with industry standards.

The synergy between software and services is essential for the holistic adoption of backtesting tools. While software provides the core functionality, services ensure that users can fully leverage the capabilities of the software. This integrated approach not only enhances the user experience but also drives the overall growth of the market. Companies offering comprehensive solutions that combine both software and services are well-positioned to capitalize on this growing market.

Moreover, advancements in technology are continuously shaping the software segment. The integration of machine learni

Graph and download economic data for Gross Private Domestic Investment (GPDI) from Q1 1947 to Q2 2025 about investment, gross, domestic, private, GDP, and USA.

This dataset provides historical stock price data for the BSE 500 index over a period of 10 years (31/03/2014 - 01/04/2024). It includes daily information such as opening price, closing price, highest price, and lowest price for each trading day.

Foreign Direct Investment in India increased by 7173 USD Million in May of 2025. This dataset provides - India Foreign Direct Investment - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Total-Cashflows-From-Investing-Activities Time Series for V2X Inc. V2X, Inc. provides critical mission solutions and support services to defense customers worldwide. It offers a suite of integrated solutions across the operations and logistics, aerospace, training, and technology markets to national security, defense, civilian, and international clients. The company was incorporated in 2014 and is headquartered in Reston, Virginia. V2X, Inc. is a subsidiary of Vertex Aerospace Holdco LLC.

Total-Cashflows-From-Investing-Activities Time Series for Fastly Inc. Fastly, Inc. operates an edge cloud platform for processing, serving, and securing its customer's applications in the United States, the Asia Pacific, Europe, and internationally. The edge cloud is a category of Infrastructure as a Service that enables developers to build, secure, and deliver digital experiences at the edge of the internet. The company offers network services to speed up and optimize the delivery of web and application traffic; content delivery network, such as dynamic site acceleration, origin shield, instant purge, surrogate keys, programmatic control, content compression, reliability features, fanout, domainr, privacy, and modern protocols and performance services; and video/ streaming solutions and services, including live streaming, live event monitoring, video on demand, and media shield. It also provides security solutions, such as DDoS protection, next-gen WAF, bot management, API and ATO protection, advanced rate limiting, privacy, and compliance services; load balancing; image optimization; transport layer security (TLS), platform TLS, and certainly; compute: observability; and origin connect. In addition, the company offers professional services comprising managed and response security services; managed CDN; and support plans services. It serves customers operating in digital publishing, media, technology, online education, travel and hospitality, and financial services industries. The company was formerly known as SkyCache, Inc. and changed its name to Fastly, Inc. in May 2012. Fastly, Inc. was incorporated in 2011 and is headquartered in San Francisco, California.