Graph and download economic data for Market Yield on U.S. Treasury Securities at 30-Year Constant Maturity, Quoted on an Investment Basis (DGS30) from 1977-02-15 to 2025-11-28 about 30-year, maturity, Treasury, interest rate, interest, rate, and USA.

TraditionData’s Interest Rate Swaps service offers comprehensive coverage across 33 currencies, focusing on portfolio interest rate risk management and yield enhancement. This service includes:

• Real-time, intraday, and end-of-day pricing for interest rate markets.
• Datasets sourced directly from Tradition’s brokerage desks.
• Flexible data content and delivery method.
• Beneficial for managing interest rate risk, enhancing yields, improving diversification, hedging interest rate exposure, and creating synthetic positions.

For further details, you can visit TraditionData Interest Rate Swaps.

Use our Stock prices 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.

Euro Area - Day-to-day money market interest rates was -0.49% in December of 2021, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Euro Area - Day-to-day money market interest rates - last updated from the EUROSTAT on December of 2025. Historically, Euro Area - Day-to-day money market interest rates reached a record high of -0.48% in August of 2021 and a record low of -0.49% in December of 2021.

Graph and download economic data for 6-Month Treasury Bill Secondary Market Rate, Discount Basis (WTB6MS) from 1958-12-12 to 2025-10-24 about 6-month, secondary market, bills, Treasury, interest rate, interest, rate, and USA.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 93 companies listed on the Bucharest Stock Exchange* (XBSE) in Romania. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Romania:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Romania:

Bucharest Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Bucharest Stock Exchange. This index provides an overview of the overall market performance in Romania.

Bucharest Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Bucharest Stock Exchange. This index reflects the performance of international companies operating in Romania.

Company A: A prominent Romanian company with diversified operations across various sectors, such as manufacturing, technology, or finance. This company's stock is widely traded on the Bucharest Stock Exchange.

Company B: A leading financial institution in Romania, offering banking, insurance, or investment services. This company's stock is actively traded on the Bucharest Stock Exchange.

Company C: A major player in the Romanian energy or consumer goods sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Bucharest Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Romania, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Romania ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Romania ?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Romania exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH,...

The "Stock Market Dataset for AI-Driven Prediction and Trading Strategy Optimization" is designed to simulate real-world stock market data for training and evaluating machine learning models. This dataset includes a combination of technical indicators, market metrics, sentiment scores, and macroeconomic factors, providing a comprehensive foundation for developing and testing AI models for stock price prediction and trading strategy optimization.

Key Features Market Metrics:

Open, High, Low, Close Prices: Daily stock price movement. Volume: Represents the trading activity during the day. Technical Indicators:

RSI (Relative Strength Index): A momentum oscillator to measure the speed and change of price movements. MACD (Moving Average Convergence Divergence): An indicator to reveal changes in strength, direction, momentum, and duration of a trend. Bollinger Bands: Upper and lower bands around a stock price to measure volatility. Sentiment Analysis:

Sentiment Score: Simulated sentiment derived from financial news and social media, ranging from -1 (negative) to 1 (positive). Macroeconomic Factors:

GDP Growth: Indicates the overall health and growth of the economy. Inflation Rate: Reflects changes in purchasing power and economic stability. Target Variable:

Buy/Sell Signal: Binary classification (1 = Buy, 0 = Sell) based on price movement thresholds, simulating actionable trading decisions. Use Cases AI Model Training: Ideal for building stock prediction models using LSTM, Gradient Boosting, Random Forest, etc. Trading Strategy Optimization: Enables testing of trading algorithms and strategies in a simulated environment. Sentiment Analysis Research: Useful for understanding how sentiment influences stock movements. Feature Engineering and Selection: Provides a diverse set of features for experimentation with advanced techniques like PCA and LDA. Dataset Highlights Synthetic Yet Realistic: Carefully designed to mimic real-world financial data trends and relationships. Comprehensive Coverage: Includes key indicators and metrics used by traders and analysts. Scalable: Suitable for use in both small-scale academic projects and larger AI-driven trading platforms. Accessible for All Levels: The intuitive structure ensures that even beginners can utilize this dataset for financial machine learning applications. File Format The dataset is provided in CSV format, where:

Rows represent individual trading days. Columns represent features (technical indicators, market metrics, etc.) and the target variable. Acknowledgments This dataset is synthetically generated and is intended for research and educational purposes. It is not based on real market data and should not be used for actual trading.

Track real-time 1 Year Treasury Rate yields and explore historical trends from year start to today. View interactive yield curve data with YCharts.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

Graph and download economic data for Average Rate on 3-Month Negotiable Certificates of Deposit (Secondary Market), Quoted on an Investment Basis (DISCONTINUED) (DCD90) from 1964-06-11 to 2013-06-28 about CD, secondary market, 3-month, interest rate, interest, rate, and USA.

View LSEG's ICE Data Pricing and Reference Data, and find real-time market data, time-sensitive pricing, and reference data for securities trading.

Track real-time 2 Year Treasury Rate yields and explore historical trends from year start to today. View interactive yield curve data with YCharts.

Interest rates on the money market and capital market. The figures are available on a daily basis for the current half year.

TraditionData’s Swaptions Market Data service offers comprehensive market coverage for swaptions across multiple currencies.

• Provides datasets for At-the-Money (ATM) and Out-of-the-Money (OTM) vol surfaces.
• Real-time, intraday, and end-of-day prices available for interest rate markets.
• Service is tailored with focused and granular packages based on region and product.

For a detailed exploration, visit Swaptions Market Data.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 5-Year Constant Maturity, Quoted on an Investment Basis (WGS5YR) from 1962-01-05 to 2025-11-28 about maturity, Treasury, 5-year, interest rate, interest, rate, and USA.

Mali ML: Money Market Rate data was reported at 5.091 % pa in 2017. This records an increase from the previous number of 4.607 % pa for 2016. Mali ML: Money Market Rate data is updated yearly, averaging 4.764 % pa from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 5.398 % pa in 2008 and a record low of 3.833 % pa in 2013. Mali ML: Money Market Rate data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Mali – Table ML.IMF.IFS: Money Market and Policy Rates: Annual.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 214 companies listed on the Panama Stock Exchange (XPTY) in Panama. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

‍

Top 5 used data fields in the End-of-Day Pricing Dataset for Panama:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

‍

Top 5 financial instruments with End-of-Day Pricing Data in Panama:

Panamanian Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Panamanian Stock Exchange (Bolsa de Valores de Panamá). This index provides an overview of the overall market performance in Panama.

Panamanian Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Panamanian Stock Exchange. This index reflects the performance of international companies operating in Panama.

Company A: A prominent Panamanian company with diversified operations across various sectors, such as shipping, logistics, or finance. This company's stock is widely traded on the Panamanian Stock Exchange.

Company B: A leading financial institution in Panama, offering banking, insurance, or investment services. This company's stock is actively traded on the Panamanian Stock Exchange.

Company C: A major player in the Panamanian energy or real estate sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Panamanian Stock Exchange.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Panama, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Panama ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Panama?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Panama exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direc...

Actual value and historical data chart for China Annual Percentage Growth Rate Of GDP At Market Prices Based On Constant 2010 Us Dollars

The Emerging Markets Bond Index (EMBI), commonly known as "riesgo país" in Spanish speaking countries, is a weighted financial benchmark that measures the interest rates paid each day by a selected portfolio of government bonds from emerging countries. It is measured in base points, which reflect the difference between the return rates paid by emerging countries' government bonds and those offered by U.S. Treasury bills. This difference is defined as "spread". Which Latin American country has the highest risk bonds? As of September 19, 2024, Venezuela was the Latin American country with the greatest financial risk and highest expected returns of government bonds, with an EMBI spread of around 254 percent. This means that the annual interest rates paid by Venezuela's sovereign debt titles were estimated to be exponentially higher than those offered by the U.S. Treasury. On the other hand, Brazil's EMBI reached 207 index points at the end of August 2023. In 2023, Venezuela also had the highest average EMBI in Latin America, exceeding 40,000 base points. The impact of COVID-19 on emerging market bonds The economic crisis spawned by the coronavirus pandemic heavily affected the financial market's estimated risks of emerging governmental bonds. For instance, as of June 30, 2020, Argentina's EMBI spread had increased more than four percentage points in comparison to January 30, 2020. All the Latin American economies measured saw a significant increase of the EMBI spread in the first half of the year.

The Finance sector's operating environment was previously characterised by record-low interest rates. Nonetheless, high inflation prompted the Reserve Bank of Australia (RBA) to hike the cash rate from May 2022 onwards. This shift allowed financial institutions to impose higher loan charges, propelling their revenue. Banks raised interest rates quicker than funding costs in the first half of 2022-23, boosting net interest margins. However, sophisticated competition and digital disruption have reshaped the sector and nibbled at the Big Four's dominance, weighing on ADIs' performance. In the first half of 2025, the fierce competition has forced ADIs to trim lending rates even ahead of RBA moves to protect their slice of the mortgage market. Higher cash rates initially widened net interest margins, but the expiry of cheap TFF funding and a fierce mortgage war are now compressing spreads, weighing on ADIs' profitability. Although ANZ's 2024 Suncorp Bank takeover highlights some consolidation, the real contest is unfolding in tech. Larger financial institutions are combatting intensified competition from neobanks and fintechs by upscaling their technology investments, strengthening their strategic partnerships with cloud providers and technology consulting firms and augmenting their digital offerings. Notable examples include the launch of ANZ Plus by ANZ and Commonwealth Bank's Unloan. Meanwhile, investor demand for rental properties, elevated residential housing prices and sizable state-infrastructure pipelines have continued to underpin loan growth, offsetting the drag from weaker mortgage affordability and volatile business sentiment. Overall, subdivision revenue is expected to rise at an annualised 8.3% over the five years through 2024-25, to $524.6 billion. This growth trajectory includes an estimated 4.8% decline in 2024-25 driven by rate cuts in 2025, which will weigh on income from interest-bearing assets. The Big Four banks will double down on technology investments and partnerships to counter threats from fintech startups and neobanks. As cybersecurity risks and APRA regulations evolve, financial institutions will gear up to strengthen their focus on shielding sensitive customer data and preserving trust, lifting compliance and operational costs. In the face of fierce competition, evolving regulations and shifting customer preferences, consolidation through M&As is poised to be a viable trend for survival and growth, especially among smaller financial institutions like credit unions. While rate cuts will challenge profitability within the sector, expansionary economic policies are poised to stimulate business and mortgage lending activity, presenting opportunities for strategic growth in a dynamic market. These trends are why Finance subdivision revenue is forecast to rise by an annualised 1.1% over the five years through the end of 2029-30, to $554.9 billion