Trading
Trading refers to buying and selling of stocks, contracts, or commodities through an exchange. Data on stock prices and other market indictors is often used by investors to make their decisions. Done correctly, use of data helps increase ROI and lowers risk on investments.
Our Data Partners
TopStonks: Social Buzz and Sentiment from the Most Popular Stock and Crypto Trading Forums
by Topstonks
500K comments
USA covered
2 years of historical data
TopStonks saves investors time by summarizing the conversation on alternative stock forums, and surfacing the best signals. We have been structuring, and pre...
Option Skew and price compression for stocks and indexes - tickerized by Trading Volatility
by Trading Volatility
1.15K Securities
2 countries covered
24 months of historical data
Trading Volatility's daily measurements of options skew, price compression, and option put/call ratios for evaluation of sentiment within the U.S. equity opt...
Gamma Exposure (GEX) measurement of US companies and indexes - tickerized by Trading Volatility
by Trading Volatility
1.15K Securities
2 countries covered
24 months of historical data
Trading Volatility's daily measurements consist of Naive Gamma Exposure and Skew-Adjusted Gamma Exposure for understanding of option-driven trading flows in ...
99.9% individual trades on the market
198 countries covered
10 years of historical data
Count is a trading metric allowing to identify traffic and trading structure when used alongside VWAP and OHLCV. It allows users who are not keen / equipped ...
Cryptrata Crypto Trade Data | Binance Coin - USD - All Historic Trades, Tick by Tick (BNB / USDT)
by Cryptrata
200M Trades and counting
100% Gapless Binance Trade History until yesterday
249 countries covered
All historic aggregates trades for the BNB-USDT pair from the Binance exchange, tick by tick until yesterday.
Other trade pairs on request.
TraderMade Live & Historical Forex & CFD REST API - "Enterprise-XL" Plan (1,250,000 requests per month)
by TraderMade
65K lines of tick data per day per currency pair
249 countries covered
35 years of historical data
TraderMade's institutional aggregated feed of live & historical pricing gives a trusted and non-skewed dataset. Perfect for price verification, back-testing ...
Woodseer Global
Based in United Kingdom
Using our systematic alorithm+analyst approach since 2016 we provide accuracy at scale.
Securities
Backtestable history
Forecast horizon
Exchange Data International
Based in United Kingdom
With EDI you get high quality, affordable financial data customized to precisely fit your operational requirements.
Certified
Certified
Meteomatics
Based in Switzerland
Meteomatics weather API delivers fast, direct, simple access to an extensive range of global weather and environmental data.
A single API endpoint to acce...
Wult.io
Based in Denmark
We provide companies with an advanced data collection and enrichment tool. We have a number of predefined and collected datasets or you can define you own ba...
Fable Data
Based in United Kingdom
Fable Data is a leading provider of European consumer spend data, delivering high-quality, real-time, anonymised data on the performance of the economy into ...
Accounts in our panel
Merchants in our coverage
Market-leading latency
TraderMade
Based in United Kingdom
TraderMade Is a Market-Leading Vendor of Data, Analytics & Charting Applications Within The Financial Markets.
https://tradermade.com/
with 99.9% uptime
Institutional clients
50+ years in-house experience
Frequently Asked Questions about Trading
Learn everything about Trading. Understand data sources, popular use cases, and data quality.
What is data-driven trading?
Data-driven trading means the selling and buying of assets based on insights from big data. Many events like stock price fluctuations, and overall market movements can be predicted with the right insights from the market.
Why use data in trading?
Data is being used in trading strategies to mitigate risks and identify profitable investment opportunities. It helps investors make predictions about the market and identify assets that are undervalued in potential.