The yield on 10 Year TIPS Yield eased to 1.98% on July 10, 2025, marking a 0 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.14 points, though it remains 0.04 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 10 Year TIPS Yield.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 5-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (DFII5) from 2003-01-02 to 2025-07-10 about TIPS, maturity, securities, Treasury, interest rate, interest, real, 5-year, rate, and USA.

The yield on 5 Year TIPS Yield rose to 1.51% on July 10, 2025, marking a 0.01 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.20 points and is 0.44 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 5 Year TIPS Yield.

The yield on 30 Year TIPS Yield rose to 2.58% on July 3, 2025, marking a 0.03 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.03 points, though it remains 0.33 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 30 Year TIPS Yield.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 30-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (WFII30) from 2010-02-26 to 2025-07-04 about TIPS, 30-year, maturity, securities, Treasury, interest rate, interest, real, rate, and USA.

Graph and download economic data for Treasury Long-Term Average (Over 10 Years), Inflation-Indexed (DLTIIT) from 2000-01-03 to 2025-07-10 about TIPS, long-term, Treasury, yield, interest rate, interest, real, rate, and USA.

The yield curve, also called the term structure of interest rates, refers to the relationship between the remaining time-to-maturity of debt securities and the yield on those securities. Yield curves have many practical uses, including pricing of various fixed-income securities, and are closely watched by market participants and policymakers alike for potential clues about the markets perception of the path of the policy rate and the macroeconomic outlook. This page provides daily estimated real yield curve parameters, smoothed yields on hypothetical TIPS, and implied inflation compensation, from 1999 to the present. Because this is a staff research product and not an official statistical release, it is subject to delay, revision, or methodological changes without advance notice.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 20-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (DFII20) from 2004-07-27 to 2025-07-10 about 20-year, TIPS, maturity, securities, Treasury, interest rate, interest, real, rate, and USA.

Treasury Inflation-Protected Securities, also known as TIPS, are securities whose principal is tied to the Consumer Price Index. With inflation, the principal increases. With deflation, it decreases. When the security matures, the U.S. Treasury pays the original or adjusted principal, whichever is greater.

These rates are commonly referred to as "Real Constant Maturity Treasury" rates, or R-CMTs. Real yields on Treasury Inflation Protected Securities (TIPS) at "constant maturity" are interpolated by the U.S. Treasury from Treasury's daily real yield curve. These real market yields are calculated from composites of secondary market quotations obtained by the Federal Reserve Bank of New York. The real yield values are read from the real yield curve at fixed maturities, currently 5, 7, 10, 20, and 30 years. This method provides a real yield for a 10 year maturity, for example, even if no outstanding security has exactly 10 years remaining to maturity. Dataset updated daily every weekday.

The Average Interest Rates on U.S. Treasury Securities dataset provides average interest rates on U.S. Treasury securities on a monthly basis. Its primary purpose is to show the average interest rate on a variety of marketable and non-marketable Treasury securities. Marketable securities consist of Treasury Bills, Notes, Bonds, Treasury Inflation-Protected Securities (TIPS), Floating Rate Notes (FRNs), and Federal Financing Bank (FFB) securities. Non-marketable securities consist of Domestic Series, Foreign Series, State and Local Government Series (SLGS), U.S. Savings Securities, and Government Account Series (GAS) securities. Marketable securities are negotiable and transferable and may be sold on the secondary market. Non-marketable securities are not negotiable or transferrable and are not sold on the secondary market. This is a useful dataset for investors and bond holders to compare how interest rates on Treasury securities have changed over time.

Graph and download economic data for 20-Year 2-3/8% Treasury Inflation-Indexed Bond, Due 1/15/2027 (DTP20J27) from 2010-01-04 to 2025-07-11 about 20-year, TIPS, bonds, Treasury, interest rate, interest, real, rate, and USA.

These rates are the daily secondary market quotation on the most recently auctioned Treasury Bills for each maturity tranche (4-week, 13-week, 26-week, and 52-week) that Treasury currently issues new Bills. Market quotations are obtained at approximately 3:30 PM each business day by the Federal Reserve Bank of New York. The Bank Discount rate is the rate at which a Bill is quoted in the secondary market and is based on the par value, amount of the discount and a 360-day year. The Coupon Equivalent, also called the Bond Equivalent, or the Investment Yield, is the bill's yield based on the purchase price, discount, and a 365- or 366-day year. The Coupon Equivalent can be used to compare the yield on a discount bill to the yield on a nominal coupon bond that pays semiannual interest.

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 iBonds Oct 2026 Term TIPS ETF: Inflation Protection in Sight?

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

Long Term Real Rate Average: The Long-Term Real Rate Average is the unweighted average of bid real yields on all outstanding TIPS with remaing maturities of more than 10 years and is intended as a proxy for long-term real rates.

Graph and download economic data for 30-Year 2-1/8% Treasury Inflation-Indexed Bond, Due 2/15/2041 (DTP30F41) from 2011-02-23 to 2025-07-11 about TIPS, 30-year, bonds, Treasury, interest rate, interest, real, rate, and USA.

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.

Octane-Boosted Returns with iShares iBonds Term TIPS ETF?

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.

TIP TEAMINVEST PRIVATE GROUP LIMITED

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

Graph and download economic data for Market Yield on U.S. Treasury Securities at 7-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (DFII7) from 2003-01-02 to 2025-07-10 about 7-year, TIPS, maturity, securities, Treasury, interest rate, interest, real, rate, and USA.

Graph and download economic data for 10-Year Real Interest Rate (REAINTRATREARAT10Y) from Jan 1982 to Jun 2025 about 10-year, interest rate, interest, real, rate, and USA.