Forex Symbols

Finage offers you more than 1300+ forex data as real-time.

With Finage, you can react to the forex data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 15-year historical data API.

Commodities Bonds Metals Forex You can view the full FX market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_FX_Symbol_List.pdf

This dataset provides comprehensive access to financial market data from Google Finance in real-time. Get detailed information on stocks, market quotes, trends, ETFs, international exchanges, forex, crypto, and related news. Perfect for financial applications, trading platforms, and market analysis tools. The dataset is delivered in a JSON format via REST API.

Gain exclusive access to specialist Foreign Exchange (FX) data, and the tools to manage trading analysis, risk and operations with LSEG's FX Pricing Data.

Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.

At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.

We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.

About 3 years of news and market data in FOREX and CryptoCurrencies Markets.

Data collected and formatted by Justin Timperio: "In my exploration of world of big data and I became curious about tick data. Tick data is extremely granular and provides a great challenge for those looking to work on their optimization skills due to its size. Unfortunately, market data is almost always behind a pay wall or de-sampled to the point of uselessness. After discovering the Dukascopy api, I knew I wanted to make this data available for all in a more accessible format." Total Line Count: 8,495,770,706 Total Data Points: 33,983,082,824 Total Decompressed Size: 501 GB

Introducing our comprehensive economic calendar, your ultimate resource for tracking major global economic events and their impact on currency and stock market prices. With a vast array of fields including event name, country, previous and current values, and more, our calendar provides you with essential data to make informed financial decisions. Stay ahead of the curve with our real-time updates, ensuring you have access to the latest information every 15 minutes. With this powerful tool at your fingertips, you can confidently navigate the dynamic world of economic events and seize opportunities for success. Don't miss out on this essential resource for staying informed and making calculated moves in the market.

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

Get access FX derivatives pricing analytics from LSEG to analyze FX forwards, FX swaps, non-delivrable forwards, FX options and more. Find out more.

The dataset is an extract of the Binance trading platform using the public REST API. It contains data covering the btcusdt historical market data for the year 2022, using the monthly chart frame. It's ideal for analysts who want a quick peek at historical crypto trading data for data exploration.

Browse LSEG's market-leading global Pricing and Market Data for the financial markets, providing the broadest range of cross-asset market and pricing data.

The market observed FX forward spreads cannot be used to value FX products directly. Instead, one needs to construct FX yield curves by bootstrapping FX forward spreads along with interest rate curves. The derived FX yield curves are essential for pricing FX instruments - forecasting FX rates and discounting currency payoffs. FinPricing provides FX yield curves in 36 currencies.

Context

Bitcoin is the longest running and most well known cryptocurrency, first released as open source in 2009 by the anonymous Satoshi Nakamoto. Bitcoin serves as a decentralized medium of digital exchange, with transactions verified and recorded in a public distributed ledger (the blockchain) without the need for a trusted record keeping authority or central intermediary. Transaction blocks contain a SHA-256 cryptographic hash of previous transaction blocks, and are thus "chained" together, serving as an immutable record of all transactions that have ever occurred. As with any currency/commodity on the market, bitcoin trading and financial instruments soon followed public adoption of bitcoin and continue to grow. Included here is historical bitcoin market data for select bitcoin exchanges where trading takes place. Happy (data) mining!

CSV files for select bitcoin exchanges for the time period of September 2011 to June 2024, with updates of OHLC (Open, High, Low, Close), Volume in BTC and indicated currency, and weighted bitcoin price. Timestamps are in Unix time. Timestamps without any trades or activity have their data fields filled with NaNs. If a timestamp is missing, or if there are jumps, this may be because the exchange (or its API) was down, the exchange (or its API) did not exist, or some other unforeseen technical error in data reporting or gathering. All effort has been made to deduplicate entries and verify the contents are correct and complete to the best of my ability, but obviously trust at your own risk.

Acknowledgements and Inspiration

Bitcoin charts for the data. The various exchange APIs, for making it difficult or unintuitive enough to get OHLC and volume data that I set out on this data scraping project. Satoshi Nakamoto and the novel core concept of the blockchain, as well as its first execution via the bitcoin protocol. I'd also like to thank viewers like you! Can't wait to see what code or insights you all have to share.

The Real-time Candlestick OHLC API provides current candlestick data that covers all major stock exchanges including NYSE, NASDAQ, LSE, Euronext to NSE of India, TSE, and a few more. Users can choose from candlestick data with 1 min, 2 min, 5 min, 15 min, 30 min, 1 hour, 4 hour, 1 day, 1 week, 1 month and 1 year interval. By using the real-time candlestick OHLC data, they can visualize data on candlestick charts and build financial products.

Extensive and dependable pricing information spanning the entire range of financial markets. Encompassing worldwide coverage from stock exchanges, trading platforms, indicative contributed prices, assessed valuations, expert third-party sources, and our enhanced data offerings. User-friendly request-response, bulk access, and tailored desktop interfaces to meet nearly any organizational or application data need. Worldwide, real-time, delayed streaming, intraday updates, and meticulously curated end-of-day pricing information.

Snapshot img

E-Brokerage Market Size 2025-2029

The e-brokerage market size is forecast to increase by USD 7.39 billion, at a CAGR of 7.9% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing proliferation of internet access worldwide. This expansion is fueled by the convenience and accessibility that e-brokerage platforms offer, enabling investors to manage their portfolios remotely and execute trades in real-time. Another key trend shaping the market is the rising demand for customization and personalization in e-brokerage solutions. As investors seek more tailored services to meet their unique needs, e-brokerage providers are responding by offering personalized investment advice, customizable interfaces, and a wide range of financial instruments. However, the market also faces notable challenges. With the increasing popularity of e-brokerage platforms, cybersecurity risks have become a significant concern. As more investors turn to digital channels for their financial needs, the threat of data breaches, hacking, and other cyber attacks grows. E-brokerage providers must invest heavily in robust cybersecurity measures to protect their platforms and their clients' sensitive information. Additionally, regulatory compliance remains a complex and ever-evolving challenge for e-brokerage firms, requiring significant resources and expertise to navigate the intricacies of various financial regulations. These challenges, while daunting, present opportunities for e-brokerage providers that can effectively address these issues and provide a secure, reliable, and personalized platform for their clients.

What will be the Size of the E-Brokerage Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, with dynamic market dynamics shaping its various sectors. Investment products and services are increasingly integrated, offering users a comprehensive platform for financial management. Mobile app development is a key focus, enabling seamless trading and real-time data access. Cryptocurrency trading is gaining popularity, requiring advanced technology and robust security protocols. Market data and educational resources are essential components, empowering users with the tools for fundamental analysis and financial modeling. User experience is paramount, with customer support, account management, and portfolio optimization ensuring client satisfaction. Order routing and management systems facilitate efficient trade execution, while fractional shares and commission structures cater to diverse investment strategies. Data analytics and technical analysis provide valuable insights, driving informed decisions. High-frequency trading and algorithmic trading require advanced API integration and direct market access. Risk management and tax optimization are crucial, with real-time data and automated trading offering enhanced control. Client onboarding and account minimums are essential considerations, with various brokerage services catering to different customer segments. Wealth management and retirement planning require a holistic approach, incorporating estate planning and dividend reinvestment. Security breaches and data encryption are ongoing concerns, with robust security protocols essential for safeguarding sensitive information. Investment products and trading platforms continue to expand, offering users a wide range of options, including futures trading and forex trading. Charting tools and social trading provide additional resources for informed decision-making. The market's continuous dynamism ensures a constantly evolving landscape, requiring adaptability and innovation.

How is this E-Brokerage Industry segmented?

The e-brokerage industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. Service TypeFull time brokerDiscounted brokerApplicationIndividual investorInstitutional investorOwnershipPrivately heldPublicly heldPlatformWeb-basedMobile appsDesktopAssest TypeEquitiesBondsDerivativesCryptocurrenciesGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyThe NetherlandsUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Service Type Insights

The full time broker segment is estimated to witness significant growth during the forecast period.In the dynamic world of E-brokerage, full-time brokers play a pivotal role in facilitating the trade of various financial securities for clients. These licensed professionals, regulated by bodies like the SEC and FCA, work closely with individuals, institutions, and corporations to understand t

Snapshot img

Algorithmic Trading Market Size 2025-2029

The algorithmic trading market size is forecast to increase by USD 18.74 billion, at a CAGR of 15.3% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing demand for market surveillance and regulatory compliance. Advanced technologies, such as machine learning and artificial intelligence, are revolutionizing trading strategies, enabling faster and more accurate decision-making. However, this market's landscape is not without challenges. In the Asia Pacific region, for instance, the widening bid-ask spread poses a significant obstacle for algorithmic trading firms, necessitating innovative solutions to mitigate this issue. As market complexity increases, players must navigate these challenges to capitalize on the opportunities presented by this dynamic market.
Companies seeking to succeed in this space must invest in advanced technologies, maintain regulatory compliance, and develop strategies to address regional challenges, ensuring their competitive edge in the ever-evolving algorithmic trading landscape.

What will be the Size of the Algorithmic Trading Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic and ever-evolving world of algorithmic trading, market activities continue to unfold with intricacy and complexity. Order management systems, real-time data processing, and sharpe ratio are integral components, enabling traders to optimize returns and manage risk tolerance. Regulatory frameworks and compliance regulations shape the market landscape, with cloud computing and order routing facilitating seamless integration of data analytics and algorithmic strategies. Natural language processing and market data feeds inform trading decisions, while trading psychology and sentiment analysis provide valuable insights into market sentiment. Position sizing, technical analysis, and profitability metrics are essential for effective portfolio optimization and asset allocation.

Market making, automated trading platforms, and foreign exchange are sectors that significantly benefit from these advancements. Return on investment, risk management, and execution algorithms are crucial for maximizing profits and minimizing losses. Machine learning models and deep learning algorithms are increasingly being adopted for trend following and mean reversion strategies. Trading signals, latency optimization, and trading indicators are essential tools for high-frequency traders, ensuring efficient trade execution and profitability. Network infrastructure and api integration are vital for ensuring low latency and reliable connectivity, enabling traders to capitalize on market opportunities in real-time. The ongoing integration of these technologies and techniques continues to reshape the market, offering new opportunities and challenges for traders and investors alike.

How is this Algorithmic Trading Industry segmented?

The algorithmic trading industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Solutions
  Services


End-user

  Institutional investors
  Retail investors
  Long-term investors
  Short-term investors


Deployment

  Cloud
  On-premise
  Cloud
  On-premise


Type

  Foreign Exchange (FOREX)
  Stock Markets
  Exchange-Traded Fund (ETF)
  Bonds
  Cryptocurrencies
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

The solutions segment is estimated to witness significant growth during the forecast period.

The market encompasses a range of solutions, primarily software, employed by traders for automated trading. Algorithmic trading, characterized by the execution of large orders using pre-programmed software, is a common practice among proprietary trading firms, hedge funds, and investment banks. High-frequency trading (HFT) relies heavily on these software solutions for speed and efficiency. The integration of advanced software in trading systems allows traders to optimize price, timing, and quantity, ultimately increasing profitability. companies offer a diverse array of software solutions, catering to various investment objectives and risk tolerances. Market making, mean reversion, trend following, and machine learning models are among the algorithmic strategies employed.

Real-time data processing, sentiment analysis, and position sizing are integral components of these solutions. Network infrastructure,

The Algorithmic Trading market is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 8.53% from 2025 to 2033. This expansion is fueled by several key factors. Increased adoption of high-frequency trading (HFT) strategies by institutional investors seeking enhanced speed and efficiency in execution is a major driver. The rising availability of sophisticated analytical tools and advanced technologies, including artificial intelligence (AI) and machine learning (ML), empowers traders to develop more complex and effective algorithms. Furthermore, the growing demand for automated trading solutions amongst retail investors, facilitated by the proliferation of user-friendly trading platforms, is contributing significantly to market growth. Regulatory changes impacting market transparency and data availability, while potentially posing challenges in some instances, are simultaneously fostering innovation in algorithmic trading strategies. The market is segmented by trading strategy (e.g., arbitrage, statistical arbitrage, and market making), asset class (equities, derivatives, forex), and deployment mode (cloud, on-premise). The competitive landscape is characterized by a mix of established players, such as Thomson Reuters and Refinitiv, alongside specialized technology providers like MetaQuotes Software Corp and Kuberre Systems Inc. These firms are engaged in a constant race to improve the speed, accuracy, and sophistication of their algorithmic trading platforms. The market is geographically diverse, with North America and Europe currently holding significant market share; however, rapid growth is anticipated in Asia-Pacific and other emerging markets driven by increasing technological adoption and financial market development. While challenges such as cybersecurity threats and the potential for market manipulation remain, the overall outlook for algorithmic trading remains positive, indicating substantial growth opportunities in the coming years. The estimated market size in 2025 is conservatively projected to be $50 Billion USD, based on extrapolation of the CAGR and existing market dynamics. This figure reflects the substantial investments and technological advancements shaping this dynamic sector. Recent developments include: June 2023: DoubleVerify, one of the leading software platforms for digital media measurement, data, and analytics, announced the launch of DV Algorithmic Optimizer, an advanced measure and optimization offering with Scibids, one of the global leaders in artificial intelligence (AI) for digital marketing. The combination of DV's proprietary attention signals and Scibids' AI-powered ad decisioning enables advertisers to identify the performing inventory that maximizes business outcomes and advertising ROI without sacrificing scale., June 2023: KuCoin Futures has announced its recent API partnership with Kryll, one of the leading automated trading bot creation platforms. This innovative collaboration aims to revolutionize futures trading by integrating Kryll's algorithmic trading bots and TradingView signal features into the KuCoin Futures platform.. Key drivers for this market are: Rising Demand for Fast, Reliable, and Effective Order Execution, Growing Demand for Market Surveillance Augmented by Reduced Transaction Costs. Potential restraints include: Rising Demand for Fast, Reliable, and Effective Order Execution, Growing Demand for Market Surveillance Augmented by Reduced Transaction Costs. Notable trends are: On-cloud Deployment Segment is expected to drive the Market Growth.

Context

Howdy folks!

I have prepared a starter dataset for time series practice. This is my 1st upload. Any questions/feedback are welcome.

Content

• The data was prepared using Alpha Vantage API
• The data represents historical daily time series for a digital currency (BTC) traded on the Saudi market (SAR/Sudi Riyal)
• Prices and volumes are quoted in both SAR & USD.
• Data date range: 2018-05-11 to 30.01.2021

Task: Use the past to predict the future!

• Check Tasks tab

Acknowledgements

Special thanks to all my instructors and friends at GA.