71 datasets found
  1. Monthly development Dow Jones Industrial Average Index 2018-2025

    • statista.com
    Updated Jul 22, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Monthly development Dow Jones Industrial Average Index 2018-2025 [Dataset]. https://www.statista.com/statistics/261690/monthly-performance-of-djia-index/
    Explore at:
    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Jun 2025
    Area covered
    United States
    Description

    The value of the DJIA index amounted to ****** at the end of June 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

  2. M

    Broadridge Financial Solutions Price to Free Cash Flow Ratio 2010-2025 | BR

    • macrotrends.net
    csv
    Updated Jul 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). Broadridge Financial Solutions Price to Free Cash Flow Ratio 2010-2025 | BR [Dataset]. https://www.macrotrends.net/stocks/charts/BR/broadridge-financial-solutions/price-fcf
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2010 - 2025
    Area covered
    United States
    Description

    Broadridge Financial Solutions current price to free cash flow ratio as of July 09, 2025 is 26.19. Broadridge Financial Solutions average price to free cash flow ratio for 2024 was 27.07, a 0.07% decline from 2023. Broadridge Financial Solutions average price to free cash flow ratio for 2023 was 27.09, a 41.78% decline from 2022. Broadridge Financial Solutions average price to free cash flow ratio for 2022 was 46.53, a 19.92% decline from 2021. Price to free cash flow ratio can be defined as

  3. Monthly number of unique DeFi users worldwide up to July 2025

    • statista.com
    Updated Jul 22, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Monthly number of unique DeFi users worldwide up to July 2025 [Dataset]. https://www.statista.com/statistics/1297745/defi-user-number/
    Explore at:
    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2018 - Jul 2025
    Area covered
    Worldwide
    Description

    Decentralized Finance users reached a peak of **** million unique users in 2024, whereas figures in 2025 are considerably lower. This according to a network crawling code that tries to measure the number of unique user addresses involved in buying or selling specific projects associated with DeFi. For example, the code lists data fetching commands associated with Uniswap and Aave — two DeFi protocols with a market cap that was higher than one billion U.S. dollars in March 2022. As Decentralized Finance — much like cryptocurrencies or NFTs — are not being tracked by an official government, these procedures try to measure "network activity". Such activity on the Ethereum blockchain/network, the most used blockchain for DeFi, or elsewhere — tend to be the only source of information on the market size of these topics. However, the source does acknowledge the numbers shown are not without their potential flaws. DeFi in 2025 is relatively small-scale Often remarked as a potential breakthrough trend for 2024, the TVL (total value locked) of DeFi in 2025 reveals a market that is much smaller than in 2021. The amount of money stored in Decentralized Finance was worth about ***** billion U.S. dollars by May 2025, compared to *** billion U.S. dollars at the end of 2021. Two reasons can be named for this decline. First, the overall cryptocurrency markets had witnessed several dramatic moments. Prices declined after the crash of stablecoin LUNA, and the sudden collapse of crypto exchange FTX in 2022. In 2023, the United States government handed out one of its largest ever corporates fines to Binance — the world's largest crypto exchange. Second, analysts believe the high yield on U.S. Treasury bonds in 2025 when compared to DeFi yields negatively impacted the young industry — as these bonds pose lower risk than DeFi. DeFi use cases: Supporting crypto investments Decentralized Finance hopes to offer different digital financial services, which are run by a community in a so-called decentralized autonomous organization (DAO) away from banks or governments. These services can include asset management, money lending, or trading, potentially making it possible to offer services that traditional finance cannot do. By May 2025, however, DeFi focused on two main use cases: Liquid staking and money lending. These processes are there to support crypto investors, specifically. The market size of insurance within Decentralized Finance, for example, was much smaller in comparison.

  4. M

    First American Financial Price to Free Cash Flow Ratio 2010-2025 | FAF

    • macrotrends.net
    csv
    Updated Jul 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). First American Financial Price to Free Cash Flow Ratio 2010-2025 | FAF [Dataset]. https://www.macrotrends.net/stocks/charts/FAF/first-american-financial/price-fcf
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2010 - 2025
    Area covered
    United States
    Description

    First American Financial current price to free cash flow ratio as of July 06, 2025 is 11.62. First American Financial average price to free cash flow ratio for 2024 was 18.3, a 35.43% decline from 2023. First American Financial average price to free cash flow ratio for 2023 was 28.34, a 266.62% decline from 2022. First American Financial average price to free cash flow ratio for 2022 was 7.73, a 33.74% increase from 2021. Price to free cash flow ratio can be defined as

  5. g

    World Bank - Sudan - Country economic memorandum : reversing the economic...

    • gimi9.com
    Updated May 7, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). World Bank - Sudan - Country economic memorandum : reversing the economic decline | gimi9.com [Dataset]. https://gimi9.com/dataset/worldbank_738172/
    Explore at:
    Dataset updated
    May 7, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Sudan
    Description

    Sudan has both the natural resources and the trained manpower to develop a vibrant economy, yet this has not happened. The economy has been moribund for most of the time since independence, and in the past couple of years it has deteriorated at an alarming pace. This report reviews the performance of the Sudanese economy over a fourteen year period (July 1976 to June 1989), highlighting the sluggish growth of economic output, stagnation of export volumes, increasing government deficits, and the accumulation of a large external debt and payment arrears. The review shows that, while exogenous shocks such as droughts, a major flood and many years of civil war have adversely affected economic performance in Sudan, they are by no means solely to blame for Sudan's economic decline. Inappropriate government economic policies have also made significant contributions. The report, therefore, analyzes how government policies have constrained growth and exports, discouraged savings, and produced increasing financial imbalances in the Sudanese economy. The report concludes by providing detailed recommendations for policy reform, and also for tackling some of the long-term natural constraints to growth, such as deforestation and soil degradation in the rainfed agricultural areas. The report stresses that donors will have to be extraordinarily generous to the country if adequate funding is to be found for a reform program that can turn the economy around.

  6. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +9more
    csv, excel, json, xml
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS, United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1928 - Aug 11, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6397 points on August 11, 2025, gaining 0.12% from the previous session. Over the past month, the index has climbed 2.04% and is up 19.69% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on August of 2025.

  7. M

    Raymond James Financial P/S Ratio 2010-2025 | RJF

    • macrotrends.net
    csv
    Updated Jul 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). Raymond James Financial P/S Ratio 2010-2025 | RJF [Dataset]. https://www.macrotrends.net/stocks/charts/RJF/RJF/price-sales
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2010 - 2025
    Area covered
    United States
    Description

    Raymond James Financial current p/s ratio as of July 11, 2025 is 2.16. Raymond James Financial average p/s ratio for 2024 was 1.89, a 11.18% increase from 2023. Raymond James Financial average p/s ratio for 2023 was 1.7, a 8.6% increase from 2022. Raymond James Financial average p/s ratio for 2022 was 1.86, a 1.06% decline from 2021. P/s ratio can be defined as the price to sales or PS ratio is calculated by taking the latest closing price and dividing it by the most recent sales per share number. The PS ratio is an additional way to assess whether a stock is over or under valued and is used primarily in cases where earnings are negative and the PE ratio cannot be utilized.

  8. Security & Commodity Contracts Brokerage in Germany - Market Research Report...

    • ibisworld.com
    Updated Jan 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    IBISWorld (2024). Security & Commodity Contracts Brokerage in Germany - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/germany/industry/security-commodity-contracts-brokerage/1426/
    Explore at:
    Dataset updated
    Jan 12, 2024
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2014 - 2029
    Area covered
    Germany
    Description

    In the past five years, the stock exchange and broker industry has recorded an average annual increase in turnover of 1.9%, meaning that industry turnover in the current year is likely to amount to 1.1 billion euros. This corresponds to an increase of 4.6 % compared to the previous year. Over the past five years, the European Central Bank's zero interest rate policy has made alternative savings products less attractive, as they were hardly able to generate any returns. As a result, retail investors also increasingly invested their money in securities. In view of the coronavirus pandemic, the stock markets initially slumped in 2020, but recovered quickly and have since set new records. In 2020, around 2.7 million more retail investors held shares than in the previous year, which is partly due to the slump in share prices and the associated favourable entry into securities trading as well as people's greater interest in their finances. Online brokers in particular were able to expand their business significantly during the crisis and are particularly popular with younger people, as they offer easy access to the stock market and commission-free trading.In the past year, the outbreak of war in Ukraine led to a renewed slump in share prices. In view of rising inflation, the European Central Bank has also gradually raised the key interest rate since July 2022. This is likely to have a negative impact on the sector, as alternative savings products are becoming more attractive again. The pandemic led to a decline in sales for the exchange offices in the sector, as travelling was only possible to a very limited extent. However, significantly more foreign travellers are likely to come to Germany again this year.In the next five years, the industry is likely to achieve average annual sales growth of 1.8% and reach an industry turnover of 1.2 billion euros by 2028. New technologies such as blockchain and distributed ledger technology are likely to increasingly find their way into the industry. In addition, sustainability issues are likely to become increasingly important and corresponding financial products will be offered. Legislators have already decreed that transparency for investors will increase, making it easier for them to make sustainable investments.

  9. F

    Data from: Personal Saving Rate

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Personal Saving Rate [Dataset]. https://fred.stlouisfed.org/series/PSAVERT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 31, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Jun 2025 about savings, personal, rate, and USA.

  10. w

    Economic Estimates: Digital Sector Monthly GVA (January 2019 to June 2024)

    • gov.uk
    Updated Dec 17, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department for Science, Innovation and Technology (2024). Economic Estimates: Digital Sector Monthly GVA (January 2019 to June 2024) [Dataset]. https://www.gov.uk/government/statistics/economic-estimates-digital-sector-monthly-gva-january-2019-to-june-2024
    Explore at:
    Dataset updated
    Dec 17, 2024
    Dataset provided by
    GOV.UK
    Authors
    Department for Science, Innovation and Technology
    Description

    Headline findings

    All estimates in this release are presented in 2022 prices and in chained volume measures. Estimates are provisional and subject to planned revisions. The index of estimated monthly GVA shows the growth or decline of the Digital Sector and its subsectors relative to January 2019.

    This current release contains new monthly figures for April 2024 to June 2024 and minor revisions for January 2024 to March 2024.

    Estimates of monthly GVA (£ million) are used to determine percentage changes over the relevant time periods mentioned here.

    • Estimated monthly GVA for the Digital Sector increased by 1.1% between March 2024 and June 2024, while the GVA of the UK is estimated to have increased by 0.4% over the same period.
    • Based on these estimates, the Digital Sector accounted for 7.2% of total UK GVA in June 2024, down from 7.4% in June 2023.
    • In our Economic Estimates: Digital Sector Monthly GVA (to March 2024) release we reported a 0.2% increase in Digital Sector GVA from December 2023 to March 2024. As part of planned revisions to the underlying data in this release, this change in Digital Sector GVA has been revised down to a 0.2% decrease from December 2023 to March 2024.
    • These same revised figures estimate that monthly Digital Sector GVA decreased by 1.8% in the 12 months between March 2023 and March 2024 whilst, over the same period, the estimate for the total UK GVA increased by 0.9%.

    DSIT have recently concluded a consultation on the planned future of the Digital Sector Economic Estimates series - the DSIT response to this consultation can be accessed using this link.

    Released

    26 September 2024

    About this release

    This is a continuation of the Digital Economic Estimates: Monthly GVA series, previously produced by Department for Culture, Media and Sport (DCMS). Responsibility for Digital Sector policy now sits with the Department for Science, Innovation and Technology (DSIT).

    Monthly estimates

    These estimates are Official Statistics, used to provide an estimate of the economic contribution of the Digital Sector, in terms of Gross Value Added (GVA), for the period January 2019 to June 2024. This current release contains new monthly figures for April 2024 to June 2024 and minor revisions for January 2024 to March 2024.

    Estimates are presented in chained volume measures (i.e. have been adjusted for inflation), at 2022 prices, and are seasonally adjusted. These latest monthly estimates should only be used to illustrate general trends, not used as definitive figures.

    You can use these estimates to:

    • Look at relative indicative changes in GVA over time for the Digital Sector and subsectors

    You should not use these estimates to:

    • Quantify GVA for a specific month
    • Measure absolute change in GVA over time
    • Determine findings for sectors that are defined using more detailed industrial classes (due to the data sources only being available at broader industry levels)

    Data sources and technical information

    These findings are calculated based on published Office for National Statistics (ONS) data sources including the Index of Services and Index of Production.

    These data sources are available for industrial ‘divisions’, whereas the Digital Sector is defined using more detailed industrial ‘classes’. This represents a significant limitation to this statistical series; the implications of which are discussed furt

  11. Dodd Frank financial reform at the Commodity Futures Trading Commission...

    • zenodo.org
    • data.niaid.nih.gov
    • +1more
    bin, txt
    Updated Jan 11, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Konrad Posch; Konrad Posch; Thomas Nath; J. Nicholas Ziegler; Thomas Nath; J. Nicholas Ziegler (2024). Dodd Frank financial reform at the Commodity Futures Trading Commission (CFTC): Public comments, January 14th, 2010 – July 16th, 2014 [Dataset]. http://doi.org/10.6078/d1610g
    Explore at:
    bin, txtAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Konrad Posch; Konrad Posch; Thomas Nath; J. Nicholas Ziegler; Thomas Nath; J. Nicholas Ziegler
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Measurement technique
    <p>This dataset was exported by the CFTC from their internal database of public comments in response to NPRMs. The uploaded file is the exact raw data generated by the CTFC and provided to the authors.</p> <p>An updated version of the data file including the author's classifications based on the organization value will be uploaded when the related work is accepted for publication.</p>
    Description

    This dataset includes a complete record of the 36,066 public comments submitted to the Commodity Futures Trading Commission (CFTC) in response to notices of proposed rule-making (NPRMs) implementing the Dodd-Frank Act over a 42-month period (January 14, 2010 to July 16, 2014). The data was exported from the agency's internal database by the CFTC and provided to the authors by email correspondence following a cold call to the CFTC public relations department. The source internal database is maintained by the CFTC as part of its internal compliance with the Administrative Procedures Act (APA) and includes all rule-making notices that appear in the Federal Register. Owing to the salience and publicity of the Dodd-Frank Act, the CFTC made a special tag in its database for all comments submitted in response to rules proposed under the authority of the Dodd-Frank Act. This database thus includes all comments which the CFTC considers relevant to the Dodd-Frank reform.

    In short, the CFTC gave the authors all comments related to the implementation of Dodd-Frank that it received between January 14th, 2010 and July 16th, 2014.

    Please note that this dataset includes only public domain data from the CFTC (under the stipulations of the APA, all comments must be published in the Federal Register and thus become public domain information). It should be noted that the CFTC does have additional meta-data which they declined to rovide (i.e. IP addresses for commenters and other personally identifiable information) which they noted could be obtained through a Freedom of Information Act (FOIA) request. We did not pursue this avenue, but future researchers interested in, for example, the geographic distribution of commenters could request such data by using a FOIA request.

  12. S&P 500 performance during major crashes as of August 2020

    • statista.com
    Updated Mar 20, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). S&P 500 performance during major crashes as of August 2020 [Dataset]. https://www.statista.com/statistics/1175227/s-and-p-500-major-crashes-change/
    Explore at:
    Dataset updated
    Mar 20, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of August 2020, the S&P 500 index had lost ** percent of its value due to the COVID-19 pandemic. However, the Great Crash, which began with Black Tuesday, remains the most significant loss in value in its history. That market crash lasted for 300 months and wiped ** percent off the index value.

  13. m

    Data for: Short- and long-run determinants of the price behavior of US clean...

    • data.mendeley.com
    Updated Jan 17, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Walid Ahmed (2023). Data for: Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach [Dataset]. http://doi.org/10.17632/x9m5d786n9.1
    Explore at:
    Dataset updated
    Jan 17, 2023
    Authors
    Walid Ahmed
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset covers the period from July 01, 2015 to December 02, 2022. It includes daily frequency time series for a set of 27 variables. Description of the variables and sources of data are given in the paper. The command code file includes commands for carrying out the empirical analysis using STATA 17. Some parts of the analysis have been performed using drop-down menus.

  14. M

    CNA Financial Price to Free Cash Flow Ratio 2010-2025 | CNA

    • macrotrends.net
    csv
    Updated Jul 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    MACROTRENDS (2025). CNA Financial Price to Free Cash Flow Ratio 2010-2025 | CNA [Dataset]. https://www.macrotrends.net/stocks/charts/CNA/cna-financial/price-fcf
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2010 - 2025
    Area covered
    United States
    Description

    CNA Financial current price to free cash flow ratio as of July 06, 2025 is 4.77. CNA Financial average price to free cash flow ratio for 2024 was 5.29, a 14.5% decline from 2023. CNA Financial average price to free cash flow ratio for 2023 was 4.62, a 10.26% increase from 2022. CNA Financial average price to free cash flow ratio for 2022 was 4.19, a 26.36% increase from 2021. Price to free cash flow ratio can be defined as

  15. d

    Australian dairy: financial performance of dairy farms, 2014-15 to 2016-17

    • data.gov.au
    • data.wu.ac.at
    pdf, xml
    Updated Aug 9, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Australian Bureau of Agricultural and Resource Economics and Sciences (2023). Australian dairy: financial performance of dairy farms, 2014-15 to 2016-17 [Dataset]. https://data.gov.au/data/dataset/pb_ffpdryd9aas20170518
    Explore at:
    xml, pdfAvailable download formats
    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Australian Bureau of Agricultural and Resource Economics and Sciences
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Australia
    Description

    Overview
    This report presents the detailed financial performance estimates of dairy farmers in 2014-15, 2015-16 and 2016-17, and discusses incomes, investment, farm debt, and costs of production in a historical context. The report draws on data from the ABARES annual Australian Dairy Industry Survey (ADIS).

    This report is a collation of chapters that have been previously published online.

    Farm financial performance (published 18 May 2017) This chapter presents estimates of the incomes, profits, costs and rates of return for dairy farms. Key Issues
    Average farm cash income of Australian dairy farms is projected to decrease by around 18 per cent in 2016-17 to $105,000 per farm. Farm cash income in 2016-17 is projected to be an estimated 8 per cent lower than the average between 2000-01 and 2015-16 (in real terms*). The expected decrease in incomes is a result of reduced milk production per farm and lower milk receipts due to low prices.

    • Note: real dollar values are adjusted to remove the effect of inflation.

    Farm debt and equity (published 12 July 2017) This chapter presents estimates of the debt, equity, and debt-servicing capacity for dairy farms. Key Issues
    Average farm debt of Australian dairy farms is estimate to have increased by around 2 per cent to $956,000 in 2015-16 (in 2016–17 dollars). Average dairy farm debt is projected to decrease by around 6 per cent in 2016-17. The average equity ratio of dairy farms at the national level declined from 85 per cent in 2004-05 to an estimated 79 per cent in 2015-16. The proportion of farm receipts needed to fund interest payments is projected to fall to just under 7 per cent in 2016-17.

    Farm capital and investment (published 8 August 2017) This chapter presents estimates of farm capital and farm investment for dairy farms. Key Issues
    The total value of capital for Australian dairy farms increased by 40 per cent in real terms from 2000-01 to 2015-16. On a per farm basis, total capital increased by 133 per cent to around $4.5 million per farm in 2015-16. The average value of land and fixed improvements per hectare for dairy farms increased by 76 per cent from 2000-01 to 2015-16, with an average annual return on land appreciation of 3.9 per cent.

    Physical characteristics (published 9 November 2017) This chapter presents estimates of physical characteristics for dairy farms. Key Issues
    From 2000-01 to 2015-16 the number of Australian dairy farms fell by 45 per cent. Although most of this decline was in Victoria, the largest percentage decline was in Queensland. The concentration of Australian milk production among the states has shifted considerably, with Victoria and Tasmania expanding their milk production and all other states contracting since 2000-01. Total milk production increased in Tasmania from 2000-01 to 2015-16 but decline in all other states.

  16. T

    Brazil FGV Consumer Confidence

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Jul 25, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2025). Brazil FGV Consumer Confidence [Dataset]. https://tradingeconomics.com/brazil/economic-optimism-index
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jul 25, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Sep 30, 2005 - Jul 31, 2025
    Area covered
    Brazil
    Description

    Economic Optimism Index in Brazil increased to 86.70 points in July from 85.90 points in June of 2025. This dataset provides - Brazil Economic Optimism Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  17. DeFi TVL of multiple blockchains combined as of July 22, 2025

    • statista.com
    Updated Jul 22, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). DeFi TVL of multiple blockchains combined as of July 22, 2025 [Dataset]. https://www.statista.com/statistics/1272181/defi-tvl-in-multiple-blockchains/
    Explore at:
    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The market size of decentralized finance market size declined to less than ** billion U.S. dollars come April 2023. This is a significant change from 2021, when the size of the decentralized finance market reached heights it had not reached before. The DeFi market was especially impacted by the crash for Terra (LUNA) and its stablecoin TerraUSD (UST) in May 2022 - with uncertainty still being present in June 2022 when coins such as USDD lost their peg to the U.S. dollar. Moreover, a declining crypto market also impacts DeFi. As Ethereum is the main blockchain powering transactions for decentralized finance, price developments of this particular cryptocurrency can have a big impact. As of July 22, 2025, the market size has increased significantly to approximately ****** billion U.S. dollars.

  18. Eurobarometer 72.1: Poverty and Social Exclusion, Social Services, Climate...

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated Aug 10, 2010
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Papacostas, Antonis (2010). Eurobarometer 72.1: Poverty and Social Exclusion, Social Services, Climate Change, and the National Economic Situation and Statistics, August-September 2009 [Dataset]. http://doi.org/10.3886/ICPSR28185.v1
    Explore at:
    delimited, stata, ascii, sas, spssAvailable download formats
    Dataset updated
    Aug 10, 2010
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Papacostas, Antonis
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/28185/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/28185/terms

    Time period covered
    Aug 28, 2009 - Sep 17, 2009
    Area covered
    Austria, Belgium, Slovenia, Luxembourg, Greece, Spain, Denmark, Germany, Europe, Hungary
    Description

    This round of Eurobarometer surveys diverged from the Standard Eurobarometer measures and queried respondents on the following major areas of focus: (1) poverty and social exclusion, (2) social services, (3) climate change, and (4) the national economic situation and statistics. For the first major focus, poverty and social exclusion, respondents were queried about their own definition of poverty, the extent of poverty in their area, trends in the growth or decline of poverty in their area and in the world, social and personal causes of poverty and homelessness, and negative effects of poverty. Questions also included the risk of poverty for themselves and others, the importance of governmental wealth redistribution, social tension between groups, trust in individual people, trust in and reliability of institutions in fighting poverty, minimal acceptable living standards, and the level of homelessness in their area. In addition, respondents were queried on their ability to keep their job, the relationship between their job and their family, their own personal aid to help the poor, access to financial services, the respondents' satisfaction with life, and the respondents' own living conditions and income. For the second major focus, social services, respondents were asked about such services as long term care, childcare, public employment, social housing, and social assistance. Questions focused on how much they or others around them use social services, the quality and affordability of social services, preferences for elderly care and childcare, the prioritization of group assistance, and the financing of social services. For the third major focus, climate change, respondents were asked about the seriousness of climate change, governmental attempts to fight climate change, personal actions taken to fight climate change, and the relationship between environmental protection and economic growth. Finally, for the fourth major focus, the national economic situation and statistics, respondents were asked to estimate their country's official growth rate, inflation rate, and unemployment rate, and were asked to give their opinions on the importance and trustworthiness of economic statistics. Respondents were also queried on the employment and economic situations in their country. Demographic and other background information includes left-right political placement, occupation, age, gender, marital status, age at completion of full-time education, household composition, ownership of a fixed or a mobile telephone and other durable goods, internet usage, financial situation, level in society, minority group affiliation, region of residence, type and size of locality, and language of interview (in select countries).

  19. L

    Lithuania Economic growth, quarterly, June, 2025 - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Nov 3, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Globalen LLC (2020). Lithuania Economic growth, quarterly, June, 2025 - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Lithuania/economic_growth_q_on_q/
    Explore at:
    xml, csv, excelAvailable download formats
    Dataset updated
    Nov 3, 2020
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 30, 1995 - Jun 30, 2025
    Area covered
    Lithuania
    Description

    Economic growth, quarterly in Lithuania, June, 2025 The most recent value is 0.2 percent as of Q2 2025, a decline compared to the previous value of 0.6 percent. Historically, the average for Lithuania from Q2 1995 to Q2 2025 is 1 percent. The minimum of -12.2 percent was recorded in Q1 2009, while the maximum of 6 percent was reached in Q3 2020. | TheGlobalEconomy.com

  20. f

    Distribution and association of socio-economic characteristics and income...

    • plos.figshare.com
    xls
    Updated Jun 15, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nahrin Rahman Swarna; Iffat Anjum; Nimmi Nusrat Hamid; Golam Ahmed Rabbi; Tariqul Islam; Ezzat Tanzila Evana; Nazia Islam; Md. Israt Rayhan; KAM Morshed; Abu Said Md. Juel Miah (2023). Distribution and association of socio-economic characteristics and income downfall. [Dataset]. http://doi.org/10.1371/journal.pone.0266014.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Nahrin Rahman Swarna; Iffat Anjum; Nimmi Nusrat Hamid; Golam Ahmed Rabbi; Tariqul Islam; Ezzat Tanzila Evana; Nazia Islam; Md. Israt Rayhan; KAM Morshed; Abu Said Md. Juel Miah
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Distribution and association of socio-economic characteristics and income downfall.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Monthly development Dow Jones Industrial Average Index 2018-2025 [Dataset]. https://www.statista.com/statistics/261690/monthly-performance-of-djia-index/
Organization logo

Monthly development Dow Jones Industrial Average Index 2018-2025

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 22, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Jan 2018 - Jun 2025
Area covered
United States
Description

The value of the DJIA index amounted to ****** at the end of June 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

Search
Clear search
Close search
Google apps
Main menu