Use Cases - Financial Analysis

How Leading Investment and Financial Advisory Firms Use Crawled Online News Data to Predict the Market

Tap into high-quality alternative data

Today’s leading analysts and investment managers are looking beyond traditional data sources such as shareholder reports, and exploring a multitude new information that modern technology can provide. This is often referred to as alternative data, a term which encapsulates everything from weather data through mobile device signals to public records – anything that a savvy financial analyst can use to gain insight into a company’s past, present and (most importantly) future performance.

One of the most exciting sources of alternative data is the world wide web, and specifically online news: the troves of information published on the internet about a company, its management and the markets in which it operates. Besides the wealth of information, the digital format in which these texts are published make them relatively easy to scan and mine for insights using big data analytics tools.

The Online News Archive is the world’s most comprehensive source of crawled, machine-readable news data, featuring millions of articles from thousands of sources, with new ones being added everyday. Leading financial companies and institutions worldwide use this data to better predict the market – and now you can too.

Traveling back in time to predict the future

Despite the major advantages (from an analyst’s perspective) of digital news content, one major drawback is its ephemeral nature. Articles can be changed, sent to an inaccessible archive page, or deleted from existence at a publication’s whim, obscuring or distorting one’s view of a certain topic.

With the Online News Archive, this ceases to be an issue. Every news story and article is crawled, indexed and transformed into JSON or XML formats that make it easy to extract on-demand. You can easily build custom datasets based on keywords, publications or periods of time – giving you the full picture of what yesterday’s papers wrote about today’s companies, towards accurately predicting how these companies will perform tomorrow.

Cut the guesswork out from your financial models

Access to rich news data (dating back from December 2014) is a powerful tool to test your hypotheses on past data. Now you can minimize the risk of costly mistakes by examining the accuracy of your predictive models, applying them to similar datasets extracted in previous time frames, and verifying your findings with traditional data sources such as stock ticker prices

Ready to get started?

The Online News Archive lets you build your first dataset in seconds. Getting started is as simple as creating a free account.

Use Cases - Financial Analysis

How Leading Investment and Financial Advisory Firms Use Crawled Online News Data to Predict the Market

Tap into high-quality alternative data

Today’s leading analysts and investment managers are looking beyond traditional data sources such as shareholder reports, and exploring a multitude new information that modern technology can provide. This is often referred to as alternative data, a term which encapsulates everything from weather data through mobile device signals to public records – anything that a savvy financial analyst can use to gain insight into a company’s past, present and (most importantly) future performance.

One of the most exciting sources of alternative data is the world wide web, and specifically online news: the troves of information published on the internet about a company, its management and the markets in which it operates. Besides the wealth of information, the digital format in which these texts are published make them relatively easy to scan and mine for insights using big data analytics tools.

The Online News Archive is the world’s most comprehensive source of crawled, machine-readable news data, featuring millions of articles from thousands of sources, with new ones being added everyday. Leading financial companies and institutions worldwide use this data to better predict the market – and now you can too.

Traveling back in time to predict the future

Despite the major advantages (from an analyst’s perspective) of digital news content, one major drawback is its ephemeral nature. Articles can be changed, sent to an inaccessible archive page, or deleted from existence at a publication’s whim, obscuring or distorting one’s view of a certain topic.

With the Online News Archive, this ceases to be an issue. Every news story and article is crawled, indexed and transformed into JSON or XML formats that make it easy to extract on-demand. You can easily build custom datasets based on keywords, publications or periods of time – giving you the full picture of what yesterday’s papers wrote about today’s companies, towards accurately predicting how these companies will perform tomorrow.

Cut the guesswork out from your financial models

Access to rich news data (dating back from December 2014) is a powerful tool to test your hypotheses on past data. Now you can minimize the risk of costly mistakes by examining the accuracy of your predictive models, applying them to similar datasets extracted in previous time frames, and verifying your findings with traditional data sources such as stock ticker prices

Ready to get started?

The Online News Archive lets you build your first dataset in seconds. Getting started is as simple as creating a free account.

Request a Demo

Have one of our data consultants demonstrate how to work with crawled online news

Get Started

Create your free account and access the news archive to easily extract historical news data