A brief look at the use of alternative data in private equity
Introduction
The use of alternative data in private equity is expanding owing to technology advancements and the growing availability of data. With the emergence of big data and machine learning, private equity firms can collect and analyse vast amounts of data from a variety of sources to gain insights that were previously difficult or impossible to obtain.
Advantage: Getting a complete picture
A key characteristic of alternative data is its ability to provide a well-rounded view of a company’s performance and potential. Traditional financial data, such as earnings reports and balance sheets, can provide valuable insights, but they only tell part of the story. By supplementing this data with alternative data, private equity firms gain a more comprehensive understanding of a company’s operations, customer base and competitive landscape.
Advantage: Real-time insights
Another advantage of using alternative data in finance is the provision of real-time insights. Traditional financial data is typically reported on a quarterly or annual basis, which makes it difficult to identify trends or respond quickly to changes in the market. Alternative data such as social media posts, news, earnings call transcripts and credit card transactions can provide real-time insights into consumer behaviour and market trends, allowing private equity firms to make more informed investment decisions.
Use-case examples
Alternative data is becoming increasingly important for private equity firms seeking a market edge. Non-traditional data sources used to evaluate potential investments range from social media data to satellite imagery. The use of alternative data in private equity is relatively new but is becoming a popular data source among investors. This blog underlines some of the approaches and challenges associated with the use of alternative data in the private equity sector.
Web traffic and app usage
One of the key areas where private equity firms use alternative data is in the evaluation of web traffic and app usage. This type of data is particularly useful for evaluating software companies by providing insights into user engagement (whether the application is attracting new users or losing them). For example, SimilarWeb, a web analytics company specialising in web traffic and performance, has tools that provide data on web traffic and app usage, with coverage of a billion daily events across 210+ sectors. Such services offer valuable insights that help companies make informed investment decisions. [1]
Sentiment analysis
Other areas where alternative data in finance is useful are social sentiment and product reviews. Just as marketers use social listening tools to monitor brand perception online, investment firms consider social media data while evaluating stocks. Alternative data provider Thinknum offers Facebook followers data, which tracks check-in counts, “like” numbers and other Facebook data points for over 450,000 companies. By analysing this type of data, investors can gain valuable insights into consumer behaviour and sentiment to make informed decisions. [2]
Satellite imagery
The use of satellite imagery helps private equity firms gain an edge in the information space and boost their market performance. With technology driving opportunities for data collection and analysis, investors with access to superior resources can utilise this alternative data to anticipate earnings news (for example, based on parking lot volume) and earn above-average returns. However, this type of strategy tends to benefit large investors more than individuals, who are often out of the loop.
Panos Patatoukas, a professor at the Haas School of Business, outlines a specific approach in his working paper [3] for formulating a trading strategy based on images from satellite data provider RS Metrics [4]. By analysing parking lot traffic at major retailers such as Walmart, Target, Costco and Whole Foods from 2011 to 2017, investors were able to predict quarterly sales based on year-over-year changes in the number of cars in the parking lots. The addition of images from another satellite data provider Orbital Insight [5] improved the accuracy of these predictions, resulting in a more profitable strategy.
Figure 1: The measurement of car park fill-rates using satellite imagery for Target Corporation (department store company) [3]
Challenges
There are also challenges associated with the use of alternative data in private equity. One of the biggest challenges involves accessing it in a usable form. Alternative data in finance often comes as aggregated datasets or a straight data feed through APIs. Aggregated data is structured and, therefore, easier to work with and slots directly into an investment model. However, these sets are more widespread, have less alpha potential and lack depth. On the other hand, straight data feeds are considered much more valuable than aggregated data but require significant clean-up in order to be usable.
Another challenge associated with the use of alternative data in finance is entity recognition or ticker tagging. Ticker tagging means assigning a company reference or brand alias back to its unique stock symbol and proper name. For example, “Verizon” should be mapped back to VZ and Verizon Communications Inc. Not all references are as direct, and some fund managers also want data mapped to CUSIPs or ISINs.
Conclusion
Alternative data is an important tool for private equity firms seeking a market edge. Its use has become more widespread as investment firms look for new, untapped streams of data. By analysing web traffic, social sentiment, satellite imagery and other types of alternative data, investors can gain valuable insights to drive decision making. However, challenges should be considered while accessing and using such datasets. In the long run, alternative data will likely continue to play a significant role in the private equity sector.
How Acuity Knowledge Partners can help
We help our private equity clients use alternative data by deploying a team of data scientists, engineers and private equity domain specialists. We address challenges or ideas related to the use of alternative data sources in private equity. We also help clients collect, analyse and gain insights from vast amounts of data from a variety of sources to obtain a more comprehensive understanding of a company’s operations, customer base and competitive landscape. We provide support in identifying and monitoring emerging trends, tracking changes in consumer sentiment and market trends, and identifying potential risks and opportunities using alternative data sources such as social media data, satellite imagery and web scraping. Clients would be part of the comprehensive data discovery phase that involves analysing the problem statement to suggest suitable data fields and datasets for acquisition, in the event they do not have a clear understanding of the specific datasets required for the project. With our expertise and experience in this field, private equity firms would be well equipped to make informed investment decisions and gain a strong market edge.
About the Author
Usman is the Chief Data Scientist at Acuity, responsible for AI/ML strategy and implementation for key client relationships. He joined Acuity in 2018 and has over 10 years of experience in delivering analytical and risk management solutions to global capital markets participants using state-of-the-art platforms. Prior to joining Acuity, Usman worked at Lloyds Bank, Goldman Sachs and UBS in front-office and middle-office functions. He holds a Master’s degree in Mathematics and Computer Science from Imperial College London
Originally published at https://www.acuitykp.com
