The yield on US 10 Year Note Bond Yield eased to 4.22% on August 1, 2025, marking a 0.15 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.06 points, though it remains 0.43 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 10 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on August of 2025.

The yield on US 30 Year Bond Yield eased to 4.84% on August 1, 2025, marking a 0.06 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.02 points and is 0.73 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. United States 30 Year Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

The yield on China 10Y Bond Yield eased to 1.71% on August 1, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.07 points, though it remains 0.41 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. China 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

The yield on Japan 10Y Bond Yield eased to 1.55% on August 1, 2025, marking a 0 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.12 points and is 0.59 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Japan 10 Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

A $1.15 billion municipal bond sale will fund a new tire factory in Oklahoma, offering high-yield, tax-free bonds to qualified investors.

Mars Inc. executes the year's largest bond sale at $26 billion, funding its acquisition of Kellanova and marking an expansion in the food industry.

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.

ENX: Steady Returns in the Municipal Bond Market?

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

Tata Steel is re-entering the corporate bond market after a year, aiming to issue bonds to raise 30 billion rupees with flexible maturities.

The yield on Germany 10Y Bond Yield eased to 2.67% on August 1, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.05 points and is 0.51 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Germany 10-Year Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

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.

Ishares USD Green Bond ETF: Greening the Bond Market?

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

Bridgestone Corporation reduces its bond offering to 50 billion yen in response to a challenging market environment, reflecting cautious investor sentiment.

The yield on Russia 10Y Bond Yield rose to 14.10% on August 1, 2025, marking a 0.05 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.53 points and is 1.35 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Russia 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

The yield on France 10Y Bond Yield eased to 3.34% on August 1, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.02 points and is 0.38 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. France 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

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.

ESG: Advanced Choice for Corporate Bond 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

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 bonds in stocks?

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

Introduction

The global debt financing market is poised for substantial growth, projected to increase from USD 25.6 billion in 2023 to USD 73.3 billion by 2033. This growth represents a compound annual growth rate (CAGR) of 11.1% during the forecast period from 2024 to 2033.

Debt financing, which involves borrowing capital through loans, bonds, and other financial instruments, is becoming increasingly vital for businesses seeking capital for expansion, innovation, or restructuring. As organizations face rising capital demands, debt financing offers a flexible option to secure funds without diluting ownership.

The yield on India 10Y Bond Yield eased to 6.37% on August 1, 2025, marking a 0 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.03 points, though it remains 0.53 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. India 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

The yield on Canada 10Y Bond Yield eased to 3.39% on August 1, 2025, marking a 0.08 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.03 points and is 0.39 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Canada 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.

Stocks pause after a rally due to trade war concerns and rising Treasury yields. Key focus on Nvidia earnings and inflation data.

The yield on Norway 10Y Bond Yield eased to 3.93% on August 1, 2025, marking a 0.04 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.10 points and is 0.66 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Norway 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on August of 2025.