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 2025-07-28 about 30-year, maturity, Treasury, interest rate, interest, rate, and USA.

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 July 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 2025-07-18 about 6-month, secondary market, bills, Treasury, interest rate, interest, rate, and USA.

Poland PL: Money Market Rate data was reported at 1.575 % pa in 2017. This records an increase from the previous number of 1.553 % pa for 2016. Poland PL: Money Market Rate data is updated yearly, averaging 5.719 % pa from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 54.300 % pa in 1990 and a record low of 1.553 % pa in 2016. Poland PL: Money Market Rate data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Poland – Table PL.IMF.IFS: Money Market and Policy Rates: Annual.

Graph and download economic data for Overnight Reverse Repurchase Agreements Award Rate: Treasury Securities Sold by the Federal Reserve in the Temporary Open Market Operations (RRPONTSYAWARD) from 2013-09-23 to 2025-07-31 about reverse repos, overnight, securities, Treasury, sales, rate, and USA.

FI: Money Market Rate data was reported at -0.329 % pa in 2017. This records a decrease from the previous number of -0.264 % pa for 2016. FI: Money Market Rate data is updated yearly, averaging 4.391 % pa from Dec 1977 (Median) to 2017, with 41 observations. The data reached an all-time high of 22.990 % pa in 1977 and a record low of -0.329 % pa in 2017. FI: Money Market Rate data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Finland – Table FI.IMF.IFS: Money Market and Policy Rates: Annual.

Graph and download economic data for 1-Year Treasury Bill Secondary Market Rate, Discount Basis from Jul 1959 to Jun 2025 about secondary market, 1-year, bills, Treasury, interest rate, interest, rate, and USA.

Taiwan Commercial Paper Rate: Primary Market: 91 to 180 Days data was reported at 0.690 % pa in Oct 2018. This records an increase from the previous number of 0.640 % pa for Sep 2018. Taiwan Commercial Paper Rate: Primary Market: 91 to 180 Days data is updated monthly, averaging 4.045 % pa from Nov 1980 (Median) to Oct 2018, with 456 observations. The data reached an all-time high of 19.400 % pa in Jul 1981 and a record low of 0.380 % pa in Feb 2010. Taiwan Commercial Paper Rate: Primary Market: 91 to 180 Days data remains active status in CEIC and is reported by Central Bank of the Republic of China. The data is categorized under Global Database’s Taiwan – Table TW.M004: Money Market Interest Rates.

This is a historical measure from Strategic Direction 2023. This indicator measures the number of rental housing units that are considered affordable to households below 80% MFI. These are rental units that are affordable without a subsidy or any incentive from the City of Austin.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: North Darfur, Blue Nile, Northern, Nile, Eastern Darfur, West Kordofan, Gedaref, West Darfur, North Kordofan, South Kordofan, Kassala, Khartoum, White Nile, South Darfur, Red Sea, Sennar, Al Gezira, Central Darfur, Market Average

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Adamawa, Market Average

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.

The Configure Price Quote (CPQ) Market Report is Segmented by Deployment Type (Cloud, On-Premise), End-User Enterprise Size (Large Enterprises, Small and Medium-Sized Enterprises), End-User Industry (Manufacturing, Healthcare and Life Sciences, IT and Telecom, BFSI, and More), Sales Channel (Direct Sales, Independent Software Vendor Channel, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

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.

In 2024, the average price-to-book (P/B) ratio of stocks on the Prime Market of the Tokyo Stock Exchange (TSE) in Japan was ***. The average P/B ratio of stocks on the Standard Market was ***.

Market risk premiums (MRP) measure the expected return on investment an investor looks to make. For potential investors looking to add to their portfolio, the perfect scenario for a risk-based investment would be a high rate of return with as small a risk as possible. There are three main concepts to MRP’s, including required market risk premiums, historical market risk premiums and expected market risk premiums. In 2024, average market risk premiums in Germany stood at *** percent. MRP in Europe As of 2024, Germany had one of the ****** average market risk premium in Europe. At the same time, market risk premiums in Ukraine were almost ***** as high due to the risk of investment involved. Risk free rates Risk free rates are closely associated to market risk premiums and measure the rate of return on an investment with no risk. As there is no risk associated, the rate of return is lower than that of an MRP. Average risk free rates across Europe were relatively low in 2024. The risk free rate of investment in Germany was less than three percent as of 2024.

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.

Brown Group, Inc. (BWNG): Has the Bear Market Hit the Bottom?

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

Explore the complex factors affecting agricultural product prices including weather, supply and demand dynamics, geopolitical events, currency fluctuations, and technology. Discover how these elements lead to price variations in staple grains like wheat, corn, and rice, and how the influence of global events and futures markets provides insight into expected price trends.

Brazil Lending Rate: per Month: Post-Fixed: Individuals: Mortgages with Market Rates: Banco Alfa S.A. data was reported at 0.000 % per Month in 03 Jul 2019. This stayed constant from the previous number of 0.000 % per Month for 02 Jul 2019. Brazil Lending Rate: per Month: Post-Fixed: Individuals: Mortgages with Market Rates: Banco Alfa S.A. data is updated daily, averaging 0.000 % per Month from Jan 2012 (Median) to 03 Jul 2019, with 1867 observations. The data reached an all-time high of 0.000 % per Month in 03 Jul 2019 and a record low of 0.000 % per Month in 03 Jul 2019. Brazil Lending Rate: per Month: Post-Fixed: Individuals: Mortgages with Market Rates: Banco Alfa S.A. data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Interest and Foreign Exchange Rates – Table BR.MB021: Lending Rate: per Month: by Banks: Post-Fixed: Individuals: Mortgages with Market Rates. Lending Rate: Daily: Interest rates disclosed represent the total cost of the transaction to the client, also including taxes and operating. These rates correspond to the average fees in the period indicated in the tables. There are presented only institutions that had granted during the period determined. In general, institutions practicing different rates within the same type of credit. Thus, the rate charged to a customer may differ from the average. Several factors such as the time and volume of the transaction, as well as the guarantees offered, explain the differences between interest rates. Certain institutions grant allowance of the use of the term overdraft. However, this is not considered in the calculation of rates of this type. It should be noted that the overdraft is a modality that has high interest rates. Thus, its use should be restricted to short periods. If the customer needs resources for a longer period, should find ways to offer lower rates. The Brazilian Central Bank publishes these data with a delay about 20 days with relation to the reference period, thus allowing sufficient time for all Financial Institutions to deliver the relevant information. Interest rates presented in this set of tables correspond to averages weighted by the values of transactions conducted in the five working days specified in each table. These rates represent the average effective cost of loans to customers, consisting of the interest rates actually charged by financial institutions in their lending operations, increased tax burdens and operational incidents on the operations. The interest rates shown are the average of the rates charged in the various operations performed by financial institutions, in each modality. In one discipline, interest rates may differ between customers of the same financial institution. Interest rates vary according to several factors, such as the value and quality of collateral provided in the operation, the proportion of down payment operation, the history and the registration status of each client, the term of the transaction, among others . Institutions with “zero” did not operate on modalities for those periods or did not provide information to the Central Bank of Brazil. The Central Bank of Brazil assumes no responsibility for delay, error or other deficiency of information provided for purposes of calculating average rates presented in this

Learn about the current market price for oats, factors influencing prices, demand drivers, impact of COVID-19, and the positive outlook for the oat market. Stay informed about market trends to make informed decisions in buying and selling oats.