18 datasets found
  1. T

    Gold - Price Data

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 2, 2025
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    TRADING ECONOMICS (2025). Gold - Price Data [Dataset]. https://tradingeconomics.com/commodity/gold
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Dec 2, 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
    Jan 3, 1968 - Dec 2, 2025
    Area covered
    World
    Description

    Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

  2. G

    Structured Trade and Commodity Finance Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 21, 2025
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    Growth Market Reports (2025). Structured Trade and Commodity Finance Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/structured-trade-and-commodity-finance-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Aug 21, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Structured Trade and Commodity Finance Market Outlook



    According to our latest research, the global Structured Trade and Commodity Finance market size reached USD 5.8 billion in 2024, reflecting robust expansion driven by increasing cross-border trade and evolving financing requirements in the commodities sector. The market is projected to grow at a CAGR of 6.9% during the forecast period, with the overall value expected to reach USD 10.7 billion by 2033. This growth is primarily fueled by the rising demand for complex financing solutions that mitigate risks and optimize working capital, especially for organizations operating in volatile commodity markets.




    One of the key growth drivers for the Structured Trade and Commodity Finance market is the increasing globalization of trade, which has led to more intricate supply chains and a heightened need for tailored financing solutions. As companies seek to expand their operations across borders, they encounter a myriad of risks, including price volatility, geopolitical uncertainties, and regulatory complexities. Structured trade and commodity finance offers customized products such as pre-export finance, inventory finance, and receivables finance, enabling businesses to secure the necessary liquidity while minimizing exposure to risks. Furthermore, the integration of advanced risk assessment tools and digital platforms has enhanced transparency and efficiency, making structured finance increasingly attractive to both large corporates and SMEs.




    Another significant factor contributing to market growth is the ongoing shift in global commodity demand patterns, particularly in emerging economies. Rapid industrialization and urbanization in regions such as Asia Pacific and Latin America have spurred demand for energy, metals, and agricultural commodities, thereby increasing the need for sophisticated financing mechanisms. Structured trade and commodity finance solutions play a pivotal role in bridging the financing gap, enabling producers, traders, and corporates to manage cash flows effectively and seize new market opportunities. The evolving regulatory landscape, with greater emphasis on compliance and sustainability, has further prompted financial institutions to develop innovative products that align with environmental, social, and governance (ESG) criteria.




    Technological advancements are also shaping the future of the Structured Trade and Commodity Finance market. The adoption of blockchain, artificial intelligence, and data analytics is revolutionizing transaction processing, risk management, and credit assessment. These technologies facilitate real-time tracking of goods, enhance fraud detection, and streamline documentation, thereby reducing operational costs and turnaround times. As a result, financial providers are able to offer more flexible and scalable solutions, catering to the diverse needs of corporates, traders, and producers. This technological evolution is expected to further accelerate market growth, as stakeholders seek to capitalize on the benefits of digital transformation.




    From a regional perspective, Asia Pacific continues to lead the Structured Trade and Commodity Finance market, accounting for the largest share in 2024, followed by Europe and North America. The dominance of Asia Pacific is underpinned by its large manufacturing base, burgeoning middle class, and strategic position in global trade networks. Countries such as China and India are major importers and exporters of commodities, driving demand for structured finance solutions. Meanwhile, Europe remains a key hub for commodity trading, with established financial institutions and a strong regulatory framework. North America, with its advanced technological infrastructure and diversified commodity markets, also plays a significant role in the global landscape. Latin America and the Middle East & Africa are emerging as high-growth regions, supported by resource-rich economies and increasing investment in infrastructure and trade facilitation.





    Product Type Analysis


    &l

  3. time series Data related to financial markets

    • kaggle.com
    zip
    Updated Oct 5, 2023
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    Tuan Kiet "Rinz" Le (2023). time series Data related to financial markets [Dataset]. https://www.kaggle.com/datasets/rinzcsgo/time-series-data-related-to-financial-markets
    Explore at:
    zip(27447 bytes)Available download formats
    Dataset updated
    Oct 5, 2023
    Authors
    Tuan Kiet "Rinz" Le
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Description

    Here’s a brief description of each field:

    timestamp: This is the date and time of the data point. last: This is the last traded price of the security at the given timestamp. bbMiddle, bbLow, bbUp: These are likely related to Bollinger Bands, which are a type of statistical chart characterizing the prices and volatility over time of a financial instrument or commodity. icmkP, icmkten, icmkki: These fields are not immediately clear, they could be specific to the data source or represent some calculated metrics. stTrend, stNum: These could be short-term trend data and related numerical values. macdTrend, macdLine, macdSignal: These are related to the MACD (Moving Average Convergence Divergence) indicator, a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. rsEmTrend, rsEmRsi, rsEmEma: These could be related to the RSI (Relative Strength Index) and EMA (Exponential Moving Average), which are commonly used in technical analysis of stock prices. emSmTrend, emSmShort, emSmLong: These could also be trend data with short and long term values. cciValue: This is likely the Commodity Channel Index, an oscillator used in technical analysis to identify cyclical trends in a security.

  4. D

    Structured Trade And Commodity Finance Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 30, 2025
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    Dataintelo (2025). Structured Trade And Commodity Finance Market Research Report 2033 [Dataset]. https://dataintelo.com/report/structured-trade-and-commodity-finance-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Structured Trade and Commodity Finance Market Outlook



    According to our latest research, the global Structured Trade and Commodity Finance market size reached USD 2.85 trillion in 2024, driven by robust demand for financing solutions across energy, agriculture, and metals sectors. The market is expected to grow at a CAGR of 5.7% from 2025 to 2033, reaching a forecasted value of USD 4.77 trillion by 2033. This growth is fueled by the increasing complexity of global trade, greater commodity price volatility, and the expanding need for risk mitigation and liquidity solutions among corporates, traders, and producers worldwide.




    Several pivotal factors are propelling the growth of the Structured Trade and Commodity Finance market. First, the globalization of supply chains and the expansion of cross-border trade have heightened the demand for sophisticated financing instruments. Structured trade finance products such as pre-export finance, inventory finance, and receivables finance offer tailored solutions that help businesses manage working capital, hedge against price fluctuations, and ensure timely payments. As emerging markets continue to integrate into the global economy, the need for flexible and secure trade finance solutions is becoming increasingly vital, particularly for small and medium-sized enterprises (SMEs) seeking to participate in international trade.




    Another significant growth driver is the heightened volatility in commodity prices, particularly in sectors like energy, metals, and agriculture. This volatility creates both risks and opportunities for market participants, necessitating advanced financial structures to manage exposure, secure funding, and maintain liquidity. The adoption of digital technologies, such as blockchain and artificial intelligence, is also transforming the structured trade and commodity finance landscape by enhancing transparency, reducing transaction times, and mitigating fraud risks. Banks and trade finance institutions are increasingly leveraging these innovations to streamline operations and offer more competitive products, further supporting market expansion.




    Regulatory developments and evolving compliance requirements are also shaping the Structured Trade and Commodity Finance market. Stringent anti-money laundering (AML) regulations, know-your-customer (KYC) mandates, and sustainability considerations are compelling market participants to adopt more robust risk management practices. This has led to increased demand for specialized advisory services and compliance-driven financing structures. At the same time, the growing emphasis on environmental, social, and governance (ESG) criteria is encouraging the development of green finance products within the commodity space, opening new avenues for growth and differentiation among service providers.




    Regionally, Asia Pacific continues to dominate the global market, accounting for over 38% of total market share in 2024, followed by Europe and North America. The rapid industrialization and urbanization in countries like China and India, coupled with strong commodity trade flows and infrastructure investments, are key contributors to the region's leadership. Meanwhile, Latin America and the Middle East & Africa are emerging as attractive markets due to their rich natural resources and increasing participation in global trade networks. Each region presents unique opportunities and challenges, shaped by local regulatory environments, trade policies, and macroeconomic trends.



    Product Type Analysis



    The Product Type segment within the Structured Trade and Commodity Finance market is highly diversified, comprising pre-export finance, inventory finance, receivables finance, export finance, and other specialized products. Pre-export finance remains a cornerstone, particularly for producers and exporters in emerging economies who require upfront capital to initiate production and fulfill large-scale export orders. This financing model is crucial for bridging the gap between the initiation of production and the receipt of export proceeds, enabling businesses to manage cash flow efficiently and seize new market opportunities. The increasing participation of SMEs in global trade has further amplified the demand for pre-export finance, as these entities often lack access to traditional bank credit lines.




    Inventory fina

  5. T

    Cocoa - Price Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +14more
    csv, excel, json, xml
    Updated Dec 2, 2025
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    TRADING ECONOMICS (2025). Cocoa - Price Data [Dataset]. https://tradingeconomics.com/commodity/cocoa
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Dec 2, 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
    Jul 1, 1959 - Dec 1, 2025
    Area covered
    World
    Description

    Cocoa fell to 5,359.52 USD/T on December 1, 2025, down 0.82% from the previous day. Over the past month, Cocoa's price has fallen 18.29%, and is down 41.61% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cocoa - values, historical data, forecasts and news - updated on December of 2025.

  6. Oil, Gas & Other Fuels Futures Data

    • kaggle.com
    zip
    Updated Jun 25, 2024
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    Guillem SD (2024). Oil, Gas & Other Fuels Futures Data [Dataset]. https://www.kaggle.com/datasets/guillemservera/fuels-futures-data
    Explore at:
    zip(1268927 bytes)Available download formats
    Dataset updated
    Jun 25, 2024
    Authors
    Guillem SD
    License

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

    Description

    This dataset provides comprehensive and up-to-date information on futures related to oil, gas, and other fuels. Futures are financial contracts obligating the buyer to purchase and the seller to sell a specified amount of a particular fuel at a predetermined price and future date.

    Use Cases: 1. Trend Analysis: Scrutinize patterns and price fluctuations to anticipate future market directions in the energy sector. 2. Academic Research: Delve into the historical behavior of oil and gas prices and understand the influence of global events on these commodities. 3. Trading Strategies: Develop and test trading tactics based on the dynamics of oil, gas, and other fuel futures. 4. Risk Management: Utilize the dataset for hedging and risk management for corporations involved in the extraction, refining, or trading of fuels.

    Dataset Image Source: Photo by Pixabay: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

    Column Descriptions: 1. Date: The date when the data was documented. Format: YYYY-MM-DD. 2. Open: Market's opening price for the day. 3. High: Peak price during the trading window. 4. Low: Lowest traded price during the day. 5. Close: Price at which the market closed. 6. Volume: Number of contracts exchanged during the trading period. 7. Ticker: The unique market quotation symbol for the future. 8. Commodity: Specifies the type of fuel the future contract pertains to (e.g., crude oil, natural gas).

  7. I

    Indonesia International Indicators: International Commodity Price: Crude...

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) [Dataset]. https://www.ceicdata.com/en/indonesia/financial-system-statistics-macroeconomic-indicator/international-indicators-international-commodity-price-crude-palm-oil-cpo
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Indonesia
    Description

    Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data was reported at 1,070.597 USD/Metric Ton in Feb 2025. This records an increase from the previous number of 1,039.440 USD/Metric Ton for Jan 2025. Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data is updated monthly, averaging 678.477 USD/Metric Ton from Jan 2014 (Median) to Feb 2025, with 134 observations. The data reached an all-time high of 1,652.529 USD/Metric Ton in Mar 2022 and a record low of 435.238 USD/Metric Ton in Nov 2018. Indonesia International Indicators: International Commodity Price: Crude Palm Oil (CPO) data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Indonesia Premium Database’s Monetary – Table ID.KAI002: Financial System Statistics: Macroeconomic Indicator.

  8. G

    Digital Commodity Exchange Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 4, 2025
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    Growth Market Reports (2025). Digital Commodity Exchange Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/digital-commodity-exchange-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Aug 4, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Digital Commodity Exchange Market Outlook



    As per our latest research, the global Digital Commodity Exchange market size reached USD 6.7 billion in 2024, and is expected to grow at a robust CAGR of 13.2% from 2025 to 2033. By the end of the forecast period, the market is anticipated to achieve a value of USD 20.1 billion by 2033. This remarkable growth trajectory is driven by increasing digitization of commodity trading platforms, the rising adoption of blockchain for secure and transparent transactions, and the expanding participation of retail and institutional investors in digital commodity trading.



    The primary growth factor for the Digital Commodity Exchange market is the ongoing digital transformation across global financial and commodity markets. Traditional commodity exchanges have faced limitations in terms of accessibility, transparency, and efficiency, prompting a shift toward digital platforms that leverage advanced technologies such as blockchain, artificial intelligence, and cloud computing. These innovations have enabled real-time trading, improved price discovery, and enhanced risk management, making digital commodity exchanges more attractive to a broader range of participants. Furthermore, the integration of digital wallets and automated settlement systems has significantly reduced transaction costs and processing times, further fueling market expansion.



    Another significant driver is the diversification of commodity types traded on digital exchanges. While energy and metals have traditionally dominated commodity markets, digital platforms have enabled seamless trading in agricultural commodities, carbon credits, and even emerging asset classes such as rare earth elements and digital assets. This diversification caters to the evolving needs of institutional investors seeking portfolio hedging and risk mitigation, as well as retail traders looking for new investment opportunities. The flexibility and scalability offered by digital commodity exchanges have also encouraged governments and regulatory bodies to support the development of robust digital trading infrastructures, thereby strengthening market confidence and participation.



    Moreover, the increasing globalization of trade and the need for cross-border commodity transactions have amplified the demand for digital commodity exchanges. These platforms facilitate seamless trading across geographies, overcoming the barriers posed by traditional exchange models. The adoption of cloud-based deployment models has further enhanced the scalability and accessibility of digital exchanges, enabling market participants from emerging economies to participate in global commodity trading. The convergence of regulatory support, technological advancements, and growing investor awareness is expected to sustain the strong growth momentum of the Digital Commodity Exchange market throughout the forecast period.



    Regionally, North America and Asia Pacific are leading the adoption of digital commodity exchanges, supported by mature financial infrastructures, high digital literacy, and proactive regulatory frameworks. Europe is also witnessing rapid growth, driven by increasing demand for sustainable and transparent commodity trading practices. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, fueled by investments in digital infrastructure and the growing importance of commodities in their economies. As digital commodity exchanges continue to evolve, regional dynamics will play a crucial role in shaping the competitive landscape and future growth prospects of the market.





    Component Analysis



    The component segment of the Digital Commodity Exchange market is bifurcated into platform and services. The platform segment encompasses the core trading infrastructure, including order matching engines, user interfaces, and blockchain-based settlement layers. These platforms form the backbone of digital commodity exchanges, enabling seamless execution of trades, real-time price discovery, and secure custody of digital

  9. m

    Bright Smart Securities & Commodities Group Ltd - Price-To-Sales-Ratio

    • macro-rankings.com
    csv, excel
    Updated Mar 15, 2023
    + more versions
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    macro-rankings (2023). Bright Smart Securities & Commodities Group Ltd - Price-To-Sales-Ratio [Dataset]. https://www.macro-rankings.com/markets/stocks/1428-hk/key-financial-ratios/valuation/price-to-sales-ratio
    Explore at:
    csv, excelAvailable download formats
    Dataset updated
    Mar 15, 2023
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    hong kong
    Description

    Price-To-Sales-Ratio Time Series for Bright Smart Securities & Commodities Group Ltd. Bright Smart Securities & Commodities Group Limited, an investment holding company, provides financial services in Hong Kong. It operates through three segments: Securities Broking, Commodities and Futures Broking, and Bullion Trading. The company offers broking services in traded securities, commodities, and future contracts; margin and IPO financing services; trading services in traded bullion contracts; leveraged foreign exchange trading services; administrative services; and asset management services. It also engages in the production and broadcast of finance programs. Bright Smart Securities & Commodities Group Limited was founded in 1995 and is headquartered in Central, Hong Kong.

  10. T

    Coffee - Price Data

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 2, 2025
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    TRADING ECONOMICS (2025). Coffee - Price Data [Dataset]. https://tradingeconomics.com/commodity/coffee
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Dec 2, 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
    Aug 16, 1972 - Dec 2, 2025
    Area covered
    World
    Description

    Coffee fell to 408.66 USd/Lbs on December 2, 2025, down 0.95% from the previous day. Over the past month, Coffee's price has risen 0.50%, and is up 38.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on December of 2025.

  11. Data from: Macroeconomic Time Series for the United States, United Kingdom,...

    • icpsr.umich.edu
    ascii, sas, spss +1
    Updated Mar 26, 2007
    + more versions
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    National Bureau of Economic Research (2007). Macroeconomic Time Series for the United States, United Kingdom, Germany, and France [Dataset]. http://doi.org/10.3886/ICPSR07644.v2
    Explore at:
    spss, sas, stata, asciiAvailable download formats
    Dataset updated
    Mar 26, 2007
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    National Bureau of Economic Research
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/7644/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7644/terms

    Time period covered
    1785 - 1968
    Area covered
    Germany, France, United Kingdom, United States, Global
    Description

    This collection contains an array of economic time series data pertaining to the United States, the United Kingdom, Germany, and France, primarily between the 1920s and the 1960s, and including some time series from the 18th and 19th centuries. These data were collected by the National Bureau of Economic Research (NBER), and they constitute a research resource of importance to economists as well as to political scientists, sociologists, and historians. Under a grant from the National Science Foundation, ICPSR and the National Bureau of Economic Research converted this collection (which existed heretofore only on handwritten sheets stored in New York) into fully accessible, readily usable, and completely documented machine-readable form. The NBER collection -- containing an estimated 1.6 million entries -- is divided into 16 major categories: (1) construction, (2) prices, (3) security markets, (4) foreign trade, (5) income and employment, (6) financial status of business, (7) volume of transactions, (8) government finance, (9) distribution of commodities, (10) savings and investments, (11) transportation and public utilities, (12) stocks of commodities, (13) interest rates, and (14) indices of leading, coincident, and lagging indicators, (15) money and banking, and (16) production of commodities. Data from all categories are available in Parts 1-22. The economic variables are usually observations on the entire nation or large subsets of the nation. Frequently, however, and especially in the United States, separate regional and metropolitan data are included in other variables. This makes cross-sectional analysis possible in many cases. The time span of variables in these files may be as short as one year or as long as 160 years. Most data pertain to the first half of the 20th century. Many series, however, extend into the 19th century, and a few reach into the 18th. The oldest series, covering brick production in England and Wales, begins in 1785, and the most recent United States data extend to 1968. The unit of analysis is an interval of time -- a year, a quarter, or a month. The bulk of observations are monthly, and most series of monthly data contain annual values or totals.

  12. D

    Commodity Hedging APIs For Corporate Banking Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 30, 2025
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    Dataintelo (2025). Commodity Hedging APIs For Corporate Banking Market Research Report 2033 [Dataset]. https://dataintelo.com/report/commodity-hedging-apis-for-corporate-banking-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Commodity Hedging APIs for Corporate Banking Market Outlook



    As per the latest research, the global Commodity Hedging APIs for Corporate Banking market size reached USD 1.32 billion in 2024, registering a robust growth with a CAGR of 11.8% from 2025 to 2033. The market is projected to reach USD 3.55 billion by 2033, driven by the increasing demand for real-time risk management, automation, and compliance in commodity trading and treasury operations. The surge in digital transformation initiatives within the banking sector and the need for seamless integration between corporate banking systems and commodity trading platforms are significant growth factors propelling this market.



    The primary growth driver for the commodity hedging APIs for corporate banking market is the intensifying volatility in global commodity prices, compelling corporates to adopt advanced risk mitigation tools. As commodity prices fluctuate due to geopolitical tensions, supply chain disruptions, and macroeconomic uncertainties, banks are under pressure to offer more sophisticated hedging solutions to their corporate clients. Commodity hedging APIs enable real-time data exchange and automation of hedging strategies, allowing corporates to respond swiftly to market movements. This capability not only enhances risk management but also provides a competitive edge to banks that can offer such technologically advanced services, thereby fueling the market’s expansion.



    Another significant factor contributing to the market’s growth is the rapid digitalization of the corporate banking sector. Financial institutions are increasingly investing in API-driven architectures to modernize their service offerings, streamline operations, and foster connectivity across diverse financial ecosystems. Commodity hedging APIs facilitate seamless integration with existing banking platforms, treasury management systems, and trading desks, resulting in improved efficiency and reduced operational overheads. The ability to deliver customizable and scalable solutions through APIs is particularly attractive to banks serving multinational corporations with complex hedging requirements across multiple commodities and geographic regions.



    Regulatory compliance is also a critical driver in the adoption of commodity hedging APIs within corporate banking. Stringent regulations around transparency, reporting, and risk management in commodity markets have necessitated the deployment of automated and auditable solutions. APIs empower banks to automate compliance workflows, monitor exposures in real-time, and generate comprehensive audit trails for regulatory reporting. This not only minimizes the risk of non-compliance and associated penalties but also instills greater confidence among corporate clients regarding the integrity and reliability of their hedging operations. As regulatory frameworks evolve, the demand for flexible and up-to-date API solutions is expected to grow further, supporting sustained market expansion.



    From a regional perspective, North America currently leads the global commodity hedging APIs for corporate banking market, accounting for the largest share due to its advanced financial infrastructure and early adoption of fintech innovations. However, Asia Pacific is anticipated to exhibit the fastest growth rate over the forecast period, driven by the rapid expansion of commodity markets, increasing cross-border trade, and the ongoing digital transformation of banking services in emerging economies. Europe remains a significant market, supported by the presence of major multinational banks and a strong regulatory framework promoting transparency and risk management in commodity trading. Meanwhile, Latin America and the Middle East & Africa are gradually catching up, as local banks and corporates recognize the benefits of API-driven hedging solutions for managing currency and commodity price risks in volatile markets.



    Component Analysis



    The component segment of the commodity hedging APIs for corporate banking market is bifurcated into software and services. Software solutions form the backbone of the market, offering banks and their corporate clients robust platforms for automating commodity hedging operations, integrating with trading desks, and ensuring seamless connectivity with internal risk management systems. These software APIs are designed to support a wide range of commodities, from energy to metals and agricultural products, providing real-time analytics, pricing feeds, and automated trade execution capabil

  13. Year-end price of gold per troy ounce 1990-2025

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Year-end price of gold per troy ounce 1990-2025 [Dataset]. https://www.statista.com/statistics/274001/gold-price-per-ounce-since-1978/
    Explore at:
    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The price of gold per troy ounce increased considerably between 1990 and 2025, despite some fluctuations. A troy ounce is the international common unit of weight used for precious metals and is approximately **** grams. At the end of 2024, a troy ounce of gold cost ******* U.S. dollars. As of * June 2025, it increased considerably to ******** U.S. dollars. Price of – additional information In 2000, the price of gold was at its lowest since 1990, with a troy ounce of gold costing ***** U.S. dollars in that year. Since then, gold prices have been rising and after the economic crisis of 2008, the price of gold rose at higher rates than ever before as the market began to see gold as an increasingly good investment. History has shown, gold is seen as a good investment in times of uncertainty because it can or is thought to function as a good store of value against a declining currency as well as providing protection against inflation. However, unlike other commodities, once gold is mined it does not get used up like other commodities (for example, such as gasoline). So while gold may be a good investment at times, the supply demand argument does not apply to gold. Nonetheless, the demand for gold has been mostly consistent.

  14. OTC Real Time Contributed Data

    • lseg.com
    Updated Oct 14, 2025
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    LSEG (2025). OTC Real Time Contributed Data [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/pricing-and-market-data/otc-real-time-contributed-data
    Explore at:
    csv,delimited,gzip,json,python,user interface,xml,zip archiveAvailable download formats
    Dataset updated
    Oct 14, 2025
    Dataset provided by
    London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
    Authors
    LSEG
    License

    https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

    Description

    Gain strategic OTC real time contributions from sell side desks across money market, foreign exchange, commodities and energy, and equity.

  15. m

    CME Group Inc - Price-To-Book-Ratio

    • macro-rankings.com
    csv, excel
    Updated Aug 23, 2025
    + more versions
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    macro-rankings (2025). CME Group Inc - Price-To-Book-Ratio [Dataset]. https://www.macro-rankings.com/Markets/Stocks/CME-NASDAQ/Key-Financial-Ratios/Valuation/Price-To-Book-Ratio
    Explore at:
    excel, csvAvailable download formats
    Dataset updated
    Aug 23, 2025
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    united states
    Description

    Price-To-Book-Ratio Time Series for CME Group Inc. CME Group Inc., together with its subsidiaries, operates contract markets for the trading of futures and options on futures contracts worldwide. It offers futures and options products based on interest rates, equity indexes, foreign exchange, agricultural commodities, energy, and metals, as well as fixed income and foreign currency trading services. The company provides clearing house services, including clearing, settling, and guaranteeing futures and options contracts, and cleared swaps products traded through its exchanges; and trade processing and risk mitigation services. In addition, the company offers a range of market data services, including real-time and historical data services. It serves professional traders, financial institutions, institutional and individual investors, corporations, manufacturers, producers, governments, and central banks. The company was formerly known as Chicago Mercantile Exchange Holdings Inc. and changed its name to CME Group Inc. in July 2007. The company was founded in 1898 and is headquartered in Chicago, Illinois.

  16. Brent crude oil price annually 1976-2025

    • statista.com
    Updated Oct 2, 2025
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    Statista (2025). Brent crude oil price annually 1976-2025 [Dataset]. https://www.statista.com/statistics/262860/uk-brent-crude-oil-price-changes-since-1976/
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    Dataset updated
    Oct 2, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of August 2025, the average annual price of Brent crude oil stood at 71.3 U.S. dollars per barrel. This is over nine U.S. dollars lower than the 2024 average. Brent is the world's leading price benchmark for Atlantic basin crude oils. Crude oil is one of the most closely observed commodity prices as it influences costs across all stages of the production process and consequently alters the price of consumer goods as well. What determines crude oil benchmarks? In the past decade, crude oil prices have been especially volatile. Their inherent inelasticity regarding short-term changes in demand and supply means that oil prices are erratic by nature. However, since the 2009 financial crisis, many commercial developments have greatly contributed to price volatility, such as economic growth by BRIC countries like China and India, and the advent of hydraulic fracturing and horizontal drilling in the U.S. The outbreak of the coronavirus pandemic and the Russia-Ukraine war are examples of geopolitical events dictating prices. Light crude oils - Brent and WTI Brent Crude is considered a classification of sweet light crude oil and acts as a benchmark price for oil around the world. It is considered a sweet light crude oil due to its low sulfur content and low density and may be easily refined into gasoline. This oil originates in the North Sea and comprises several different oil blends, including Brent Blend and Ekofisk crude. Often, this crude oil is refined in Northwest Europe. Another sweet light oil often referenced alongside UK Brent is West Texas Intermediate (WTI). WTI oil prices amounted to 76.55 U.S. dollars per barrel in 2024.

  17. T

    Lithium - Price Data

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 26, 2025
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    TRADING ECONOMICS (2025). Lithium - Price Data [Dataset]. https://tradingeconomics.com/commodity/lithium
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Nov 26, 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
    May 10, 2017 - Dec 2, 2025
    Area covered
    World
    Description

    Lithium rose to 94,400 CNY/T on December 2, 2025, up 0.05% from the previous day. Over the past month, Lithium's price has risen 16.54%, and is up 20.64% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lithium - values, historical data, forecasts and news - updated on December of 2025.

  18. T

    Cotton - Price Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 3, 2025
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    TRADING ECONOMICS (2025). Cotton - Price Data [Dataset]. https://tradingeconomics.com/commodity/cotton
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Dec 3, 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 1, 1913 - Dec 2, 2025
    Area covered
    World
    Description

    Cotton fell to 61.55 USd/Lbs on December 2, 2025, down 2.03% from the previous day. Over the past month, Cotton's price has fallen 6.28%, and is down 13.31% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cotton - values, historical data, forecasts and news - updated on December of 2025.

  19. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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TRADING ECONOMICS (2025). Gold - Price Data [Dataset]. https://tradingeconomics.com/commodity/gold

Gold - Price Data

Gold - Historical Dataset (1968-01-03/2025-12-02)

Explore at:
excel, csv, json, xmlAvailable download formats
Dataset updated
Dec 2, 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
Jan 3, 1968 - Dec 2, 2025
Area covered
World
Description

Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

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