Hedge fund case study | FirstRain

Hedge fund case study

Many of our customers are hedge funds looking to both save time and get an intelligence advantage from the web. They are notoriously secret so we can rarely use their names – but even so they will talk with us and share how they use FirstRain.

Liz (her name has been changed at her request) is an investor relations associate at a hedge fund in Greenwich CT. This is a fund that has a long term horizon and applies private equity style investing to the public markets. She shared how she uses FirstRain with us. Her goal is to quickly and easily find intelligence which may be impacting her firm’s portfolio.

“One of my responsibilities it to generate a daily watch report for our research analysts. Each analyst has Bloomberg on their desk, and access to sell-side research, so they can easily screen for major news stories. My challenge is then to help them find the smaller local news stories that might be impacting our portfolio.

We have found that local news and blogs are helpful for our continuous understanding of industries like restaurants and retail – for example seeing a report like Burger King to close three local Plano TX franchises which might change an analyst’s model or outlook.”

In the past Liz would use Lexis Nexis but, while powerful for specific one-off research projects, it does not have the local news and blog coverage that she needs, and does not have an easy workflow to generate news reports for a set of companies every day.

Liz wanted to find a simple, efficient solution to tracking daily local news and blogs about her firm’s critical investments.

Her solution today is to use FirstRain to monitor about 50 names, looking for local stories to build her daily Watch Report from. She simply uploads the names from excel and turns on a daily email monitor setup for her filters.

She says “We found it very easy to import the tickers and generate a daily email which we use to create our Watch Report from. And FirstRain is a fraction of the cost of traditional content providers like Lexis Nexis, or financial platforms like Bloomberg. In the end it was a simple decision for us, based on ease of use and price”.