Can I Use the News API for Financial Analysis?

Data feeds have many different applications, one of which is targeted to financial markets. For example, traders engaged in high-frequency trading would require real-time updates to financial market data. Since the data must be extremely reliable, these feeds are known to be highly reliable and fast. Bloomberg’s B-PIPE data feed, Thomas Reuters’ Matching Binary Multicast Feed and EBS Brokertec’s Ultra are all reputable high-speed data feeds for the financial market.

But these high-speed data feeds don’t necessarily give you the 360 degree view you are looking for that can help you predict the future behavior of stocks, companies and individuals.

Webhose’s News API has a financial application that enables businesses to gain a broader perspective of the financial market without relying solely on data related to stock performance trends. Stay one step ahead of the market with data from global news, forums, e-commerce sites and blogs from the financial markets to make better data-driven investment decisions. You’ll also be able to better test your predictive models with real-world data.

Be Part of the Next Generation of Data-Driven Investment

Today, AI is responsible for over two-thirds of the financial transactions in the world — thanks in part to these large datasets. Earlier AI efforts started with rule-based coding, while today’s AI financial analysis is based on machine learning with data as a starting point.

But that means you need to rely on a service that can not only successfully and accurately extract data at scale but can also adapt to web data pattern changes such as website designs that alter data fields. New data and updates should be continually added to existing datasets to ensure machine learning programs stay up-to-date and your results remain accurate. These are some of the reasons why data preparation can take up to four times as long as the machine learning process.

That’s why a web data provider that delivers both the volume and diversity of data in structured, machine-readable form can bring your organization successful AI outcomes, which in the financial world, lead to increased opportunities and the reduction of risk.

Identify Market Patterns and Discover Investment Opportunities

Predictive analysis and risk modeling algorithms are only as good as their data. Webhose’s ability to crawl and extract both new and historical data offers a more accurate set of data points. Think of it like being able to go back in time to access data and signals of stocks you know that would soon crash or skyrocket in value. But in order to do this you need a dataset large enough to build a mathematical model that has a good chance of accurately predicting the outcome in future datasets.

With our Archived Web Data you can test your predictive models by applying them at a certain point in the past with our massive repository of data that gives you access to over 10 years of crawled data from thousands of online websites. While real-time data for financial analysis is essential, you may also need historical data to fill in the gaps or create a benchmark for your data. Our huge repository of data that goes back to January 2008 includes over 100 terabytes of historical content delivered to you in structured, machine-readable XML or JSON formats from millions of websites that can then easily mine data for analytical insights. Advanced filters deliver you the datasets you need for granular analysis.  

In addition, Webhose’s near real-time News API allows you to search through news, blogs and message boards and write a Boolean query that filters your results according to performance score (based on its viral success), country, language, social signals, sentiment.

Want to Learn More?

Gain insight, improve your predictive analytics and risk models  and test your financial hypotheses with Webhose’s  News API.


Ran Geva

Ran Geva is the co-founder and CEO of, a leading web data provider used by hundreds of data analytics, cybersecurity and web monitoring companies worldwide. Before co-founding, he was the co-founder of Buzilla Ltd, a web monitoring and analytics company that helps brands track, monitor, analyze and extract insight from online content.

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