This dataset contains the monthly nominal yields of 10-year US Treasury bonds, sourced from the Board of Governors of the Federal Reserve System (FRED).

The 10-year Treasury yield is widely regarded as a benchmark for long-term interest rates in the United States. It reflects investor sentiment about economic growth, inflation expectations, and monetary policy. Analysts, economists, and investors often use this indicator to track shifts in the bond market and assess the overall economic outlook.

Why This Matters

• Economic Indicator. Serves as a proxy for long-term borrowing costs.
• Market Benchmark. Affects pricing of mortgages, corporate debt, and other financial instruments.
• Policy Insights. Closely monitored by the Federal Reserve, economists, and policymakers for clues about inflation and growth.

Potential Use Cases

• Time series analysis and forecasting of interest rates.
• Studying the relationship between bond yields, stock markets, and economic cycles.
• Macro-financial research, portfolio risk management, and policy analysis.

As of July 18, 2025, the major economy with the highest yield on 10-year government bonds was Turkey, with a yield of ** percent. This is due to the risks investors take when investing in Turkey, notably due to high inflation rates potentially eradicating any profits made when using a foreign currency to investing in securities denominated in Turkish lira. Of the major developed economies, United Kingdom had one the highest yield on 10-year government bonds at this time with **** percent, while Switzerland had the lowest at **** percent. How does inflation influence the yields of government bonds? Inflation reduces purchasing power over time. Due to this, investors seek higher returns to offset the anticipated decrease in purchasing power resulting from rapid price rises. In countries with high inflation, government bond yields often incorporate investor expectations and risk premiums, resulting in comparatively higher rates offered by these bonds. Why are government bond rates significant? Government bond rates are an important indicator of financial markets, serving as a benchmark for borrowing costs, interest rates, and investor sentiment. They affect the cost of government borrowing, influence the price of various financial instruments, and serve as a reflection of expectations regarding inflation and economic growth. For instance, in financial analysis and investing, people often use the 10-year U.S. government bond rates as a proxy for the longer-term risk-free rate.

Norway Government Bond Yield: Oslo Stock Exchange: Month End: 6 Months data was reported at 0.853 % pa in Oct 2018. This records an increase from the previous number of 0.804 % pa for Sep 2018. Norway Government Bond Yield: Oslo Stock Exchange: Month End: 6 Months data is updated monthly, averaging 2.010 % pa from Aug 2001 (Median) to Oct 2018, with 207 observations. The data reached an all-time high of 7.210 % pa in May 2002 and a record low of 0.386 % pa in Nov 2017. Norway Government Bond Yield: Oslo Stock Exchange: Month End: 6 Months data remains active status in CEIC and is reported by Oslo Stock Exchange. The data is categorized under Global Database’s Norway – Table NO.M008: Government Bonds Yield.

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.

The yield on US 30 Year Bond Yield rose to 4.76% on December 2, 2025, marking a 0.02 percentage points increase from the previous session. Over the past month, the yield has edged up by 0.06 points and is 0.35 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 December of 2025.

The spread between 10–year and two–year U.S. Treasury bond yields reached a positive value of 0.49 percent in June 2025. The 10–year minus two–year Treasury bond spread is generally considered to be an advance warning of severe weakness in the stock market. Negative spreads occurred prior to the recession of the early 1990s, the tech-bubble crash in 2000–2001, and the financial crisis of 2007–2008.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 20-Year Constant Maturity, Quoted on an Investment Basis (DGS20) from 1962-01-02 to 2025-11-28 about 20-year, maturity, Treasury, interest rate, interest, rate, and USA.

This dataset captures multi-market financial indicators that can be used to study financial crises, market stress, and economic stability. It integrates simulated data from stock, bond, and foreign exchange (forex) markets, along with volatility metrics and a binary crisis label.

The dataset provides a comprehensive view of cross-market behavior and is suitable for tasks such as crisis detection, financial risk analysis, and market interdependence studies.

Key Features Time Series Coverage:

Daily data over ~1,000 days for multiple countries

Stock Market Indicators:

Stock_Index → Simulated stock market index values

Stock_Return → Daily percentage change in stock index

Stock_Volatility → 5-day rolling standard deviation of stock returns

Bond Market Indicators:

Bond_Yield → Simulated 10-year government bond yield

Bond_Yield_Spread → Difference between long-term and short-term yields

Bond_Volatility → Simulated volatility in bond yields

Forex Market Indicators:

FX_Rate → Simulated currency exchange rate

FX_Return → Daily percentage change in exchange rate

FX_Volatility → 5-day rolling standard deviation of forex returns

Global Market Stress Indicator:

VIX → Simulated volatility index representing market stress

Target Variable:

Crisis_Label → Binary flag indicating market condition (0 = Normal, 1 = Crisis)

File Information Format: CSV

Rows: ~3,000 (1,000 days × 3 countries)

Columns: 13 (including target label)

Use Cases:

Financial crisis detection

Market stress and contagion analysis

Cross-market economic studies

Norway Government Bond Yield: Oslo Stock Exchange: Month End: 3 Months data was reported at 0.832 % pa in Oct 2018. This records an increase from the previous number of 0.771 % pa for Sep 2018. Norway Government Bond Yield: Oslo Stock Exchange: Month End: 3 Months data is updated monthly, averaging 1.880 % pa from Aug 2001 (Median) to Oct 2018, with 207 observations. The data reached an all-time high of 7.220 % pa in Jul 2002 and a record low of 0.385 % pa in Dec 2017. Norway Government Bond Yield: Oslo Stock Exchange: Month End: 3 Months data remains active status in CEIC and is reported by Oslo Stock Exchange. The data is categorized under Global Database’s Norway – Table NO.M008: Government Bonds Yield.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 1-Month Constant Maturity, Quoted on an Investment Basis (DGS1MO) from 2001-07-31 to 2025-12-01 about 1-month, bills, maturity, Treasury, interest rate, interest, rate, and USA.

As of July 22, 2025, the yield for a ten-year U.S. government bond was 4.38 percent, while the yield for a two-year bond was 3.88 percent. This represents an inverted yield curve, whereby bonds of longer maturities provide a lower yield, reflecting investors' expectations for a decline in long-term interest rates. Hence, making long-term debt holders open to more risk under the uncertainty around the condition of financial markets in the future. That markets are uncertain can be seen by considering both the short-term fluctuations, and the long-term downward trend, of the yields of U.S. government bonds from 2006 to 2021, before the treasury yield curve increased again significantly in the following years. What are government bonds? Government bonds, otherwise called ‘sovereign’ or ‘treasury’ bonds, are financial instruments used by governments to raise money for government spending. Investors give the government a certain amount of money (the ‘face value’), to be repaid at a specified time in the future (the ‘maturity date’). In addition, the government makes regular periodic interest payments (called ‘coupon payments’). Once initially issued, government bonds are tradable on financial markets, meaning their value can fluctuate over time (even though the underlying face value and coupon payments remain the same). Investors are attracted to government bonds as, provided the country in question has a stable economy and political system, they are a very safe investment. Accordingly, in periods of economic turmoil, investors may be willing to accept a negative overall return in order to have a safe haven for their money. For example, once the market value is compared to the total received from remaining interest payments and the face value, investors have been willing to accept a negative return on two-year German government bonds between 2014 and 2021. Conversely, if the underlying economy and political structures are weak, investors demand a higher return to compensate for the higher risk they take on. Consequently, the return on bonds in emerging markets like Brazil are consistently higher than that of the United States (and other developed economies). Inverted yield curves When investors are worried about the financial future, it can lead to what is called an ‘inverted yield curve’. An inverted yield curve is where investors pay more for short term bonds than long term, indicating they do not have confidence in long-term financial conditions. Historically, the yield curve has historically inverted before each of the last five U.S. recessions. The last U.S. yield curve inversion occurred at several brief points in 2019 – a trend which continued until the Federal Reserve cut interest rates several times over that year. However, the ultimate trigger for the next recession was the unpredicted, exogenous shock of the global coronavirus (COVID-19) pandemic, showing how such informal indicators may be grounded just as much in coincidence as causation.

The yield on US 10 Year Note Bond Yield rose to 4.12% on December 2, 2025, marking a 0.02 percentage points increase from the previous session. Over the past month, the yield has remained flat, and it is 0.11 points lower 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 December 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.

Dow Jones Industrials Index Forecast: Mixed Signals Ahead

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

Track real-time 10 Year Treasury Rate yields and explore historical trends from year start to today. View interactive yield curve data with YCharts.

The yield on France 10Y Bond Yield rose to 3.49% on December 1, 2025, marking a 0.07 percentage points increase from the previous session. Over the past month, the yield has edged up by 0.04 points and is 0.57 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 December of 2025.

As of December 30, 2024, ** economies reported a negative value for their ten year minus two year government bond yield spread: Ukraine with a negative spread of ***** percent; Turkey, with a negative spread of 1332 percent; Nigeria with **** percent; and Russia with **** percent. At this time, almost all long-term debt for major economies was generating positive yields, with only the most stable European countries seeing smaller values. Why is an inverted yield curve important? Often called an inverted yield curve or negative yield curve, a situation where short term debt has a higher yield than long term debt is considered a main indicator of an impending recession. Essentially, this situation reflects an underlying belief among a majority of investors that short term interest rates are about to fall, with the lowering of interest rates being the orthodox fiscal response to a recession. Therefore, investors purchase safe government debt at today's higher interest rate, driving down the yield on long term debt. In the United States, an inverted yield curve for an extended period preceded (almost) all recent recessions. The exception to this is the economic downturn caused by the coronavirus (COVID-19) pandemic – however, the U.S. ten minus two year spread still came very close to negative territory in mid-2019. Bond yields and the coronavirus pandemic The onset of the coronavirus saw stock markets around the world crash in March 2020. This had an effect on bond markets, with the yield of both long term government debt and short term government debt falling dramatically at this time – reaching negative territory in many countries. With stock values collapsing, many investors placed their money in government debt – which guarantees both a regular interest payment and stable underlying value - in contrast to falling share prices. This led to many investors paying an amount for bonds on the market that was higher than the overall return for the duration of the bond (which is what is signified by a negative yield). However, the calculus is that the small loss taken on stable bonds is less that the losses likely to occur on the market. Moreover, if conditions continue to deteriorate, the bonds may be sold on at an even higher price, partly offsetting the losses from the negative yield.

The yield on India 10Y Bond Yield eased to 6.52% on December 2, 2025, marking a 0.06 percentage points decrease from the previous session. Over the past month, the yield has fallen by 0.03 points and is 0.24 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 December 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.

What is the stock market doing today?

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.

WIG20 Index: A Polish Stock Market Mystery?

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.

AEX Index: Is Dutch Equity Market Ready for Growth?

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