Access CME futures and options data for interest rate markets, including U.S. Treasuries, SOFR, Federal Funds, ESTR, and more with Databento's APIs or web portal.

Our continuous contract symbology is a notation that maps to an actual, tradable instrument on any given date. The prices returned are real, unadjusted prices. We do not create a synthetic time series by adjusting the prices to remove jumps during rollovers.

In 2023, 3-Month SOFR (Secured Overnight Financing Rate) futures had the highest trading volume of all exchange-traded interest rate derivatives in 2023, with 809 million contracts traded on the CME. 10-year Treasury Notes futures followed, with 498 million contracts traded on the same exchange.

United States Open Interest: CBOT: Financial Futures: Interest Rate Swap: 10 Years data was reported at 0.000 Contract in May 2018. This stayed constant from the previous number of 0.000 Contract for Apr 2018. United States Open Interest: CBOT: Financial Futures: Interest Rate Swap: 10 Years data is updated monthly, averaging 13,704.000 Contract from Oct 2001 (Median) to May 2018, with 200 observations. The data reached an all-time high of 66,730.000 Contract in Aug 2007 and a record low of 0.000 Contract in May 2018. United States Open Interest: CBOT: Financial Futures: Interest Rate Swap: 10 Years data remains active status in CEIC and is reported by CME Group. The data is categorized under Global Database’s United States – Table US.Z022: CBOT: Futures: Open Interest.

Browse BTIC on Adjusted Interest Rate FTSE-100 Total Return Declared Dividend Index Futures (AFT) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

The CME Group Market Data Platform (MDP) 3.0 disseminates event-based bid, ask, trade, and statistical data for CME Group markets and also provides recovery and support services for market data processing. MDP 3.0 includes the introduction of Simple Binary Encoding (SBE) and Event Driven Messaging to the CME Group Market Data Platform. Simple Binary Encoding (SBE) is based on simple primitive encoding, and is optimized for low bandwidth, low latency, and direct data access. Since March 2017, MDP 3.0 has changed from providing aggregated depth at every price level (like CME's legacy FAST feed) to providing full granularity of every order event for every instrument's direct book. MDP 3.0 is the sole data feed for all instruments traded on CME Globex, including futures, options, spreads and combinations. Note: We classify exchange-traded spreads between futures outrights as futures, and option combinations as options.

Origin: Directly captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 10 Years data was reported at 0.000 Contract in May 2018. This stayed constant from the previous number of 0.000 Contract for Apr 2018. United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 10 Years data is updated monthly, averaging 26,040.500 Contract from Oct 2001 (Median) to May 2018, with 200 observations. The data reached an all-time high of 209,087.000 Contract in Jun 2009 and a record low of 0.000 Contract in May 2018. United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 10 Years data remains active status in CEIC and is reported by CME Group. The data is categorized under Global Database’s United States – Table US.Z021: CBOT: Futures: Turnover.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Secured Overnight Financing Rate (SOFR) from 2018-04-03 to 2025-06-27 about financing, overnight, securities, rate, and USA.

United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 5 Years data was reported at 0.000 Contract in May 2018. This stayed constant from the previous number of 0.000 Contract for Apr 2018. United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 5 Years data is updated monthly, averaging 11,527.000 Contract from Jun 2002 (Median) to May 2018, with 192 observations. The data reached an all-time high of 231,912.000 Contract in Jun 2009 and a record low of 0.000 Contract in May 2018. United States Turnover: CBOT: Financial Futures: Interest Rate Swap: 5 Years data remains active status in CEIC and is reported by CME Group. The data is categorized under Global Database’s USA – Table US.Z021: CBOT: Futures: Turnover.

The STLFSI4 measures the degree of financial stress in the markets and is constructed from 18 weekly data series: seven interest rate series, six yield spreads and five other indicators. Each of these variables captures some aspect of financial stress. Accordingly, as the level of financial stress in the economy changes, the data series are likely to move together.

How to Interpret the Index: The average value of the index, which begins in late 1993, is designed to be zero. Thus, zero is viewed as representing normal financial market conditions. Values below zero suggest below-average financial market stress, while values above zero suggest above-average financial market stress.

More information: The STLFSI4 is the third revision (i.e., STLFSI3 (https://fred.stlouisfed.org/series/STLFSI3) and STLFSI2 (https://fred.stlouisfed.org/series/STLFSI2) of the original STLFSI (https://fred.stlouisfed.org/series/STLFSI). Whereas the STLFSI3 used the past 90-day average backward-looking secured overnight financing rate (SOFR) (https://fred.stlouisfed.org/series/SOFR90DAYAVG) in two of their yield spreads, the STLFSI4 uses the 90-day forward-looking SOFR (https://www.cmegroup.com/market-data/cme-group-benchmark-administration/term-sofr.html) in its place. For more information, see "The St. Louis Fed’s Financial Stress Index, Version 4.0" (https://fredblog.stlouisfed.org/2022/11/the-st-louis-feds-financial-stress-index-version-4/). For information on earlier STLFSIs, see "Measuring Financial Market Stress" (https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf), "The St. Louis Fed’s Financial Stress Index, Version 2.0." (https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/), and "The St. Louis Fed’s Financial Stress Index, Version 3.0" (https://fredblog.stlouisfed.org/2022/01/the-st-louis-feds-financial-stress-index-version-3-0/).

Sharp economic volatility, the continued effects of high interest rates and mixed sentiment among investors created an uneven landscape for stock and commodity exchanges. While trading volumes soared in 2020 due to the pandemic and favorable financial conditions, such as zero percent interest rates from the Federal Reserve, the continued effects of high inflation in 2022 and 2023 resulted in a hawkish pivot on interest rates, which curtailed ROIs across major equity markets. Geopolitical volatility amid the Ukraine-Russia and Israel-Hamas wars further exacerbated trade volatility, as many investors pivoted away from traditional equity markets into derivative markets, such as options and futures to better hedge on their investment. Nonetheless, the continued digitalization of trading markets bolstered exchanges, as they were able to facilitate improved client service and stronger market insights for interested investors. Revenue grew an annualized 0.1% to an estimated $20.9 billion over the past five years, including an estimated 1.9% boost in 2025. A core development for exchanges has been the growth of derivative trades, which has facilitated a significant market niche for investors. Heightened options trading and growing attraction to agricultural commodities strengthened service diversification among exchanges. Major companies, such as CME Group Inc., introduced new tradeable food commodities for investors in 2024, further diversifying how clients engage in trades. These trends, coupled with strengthened corporate profit growth, bolstered exchanges’ profit. Despite current uncertainty with interest rates and the pervasive fear over a future recession, the industry is expected to do well during the outlook period. Strong economic conditions will reduce investor uncertainty and increase corporate profit, uplifting investment into the stock market and boosting revenue. Greater levels of research and development will expand the scope of stocks offered because new companies will spring up via IPOs, benefiting exchange demand. Nonetheless, continued threat from substitutes such as electronic communication networks (ECNs) will curtail larger growth, as better technology will enable investors to start trading independently, but effective use of electronic platforms by incumbent exchange giants such as NASDAQ Inc. can help stem this decline by offering faster processing via electronic trade floors and prioritizing client support. Overall, revenue is expected to grow an annualized 3.5% to an estimated $24.8 billion through the end of 2031.