Alternative Data is the Key to Investor Success

Today’s hedge fund managers and analysts are increasingly shifting their gaze toward alternative data as a linchpin asset to drive investment decisions. In fact, seventy-eight percent of hedge funds are currently using or are expecting to use alternative data (per Ernst & Young, up from 52% in 2016).

Hedge funds seek alternative data sets because they want a unique view of the market or a business or industry. Historically, analysis of traditional data – SEC filings, quarterly earnings, press releases, etc. – has been a cornerstone and common denominator of investment strategy. However, alternative data – sources such as survey data, social media networks, app usage of mobile devices, geolocation, customer sentiment, any data that can be sourced from websites – are now a business-critical source of additional valuable insights. Today’s hedge funds are clamoring to be the first to find a unique viewpoint of the market that no one else has. And in order to do so, they need to look no further than the largest source of alternative data: the World Wide Web.

In order to keep pace with the current market, hedge funds need to implement alternative data insights throughout a variety of use cases, occasionally combining data sets to better understand what’s happening to businesses in the market. The first step is to identify the data they want and where it resides on the web. Then, using the data that’s automatically captured and stored, hedge funds can build historical alternative data sets to enable investors to backtest their estimates of the performance of a strategy or model. Because market information is freely available on the web, spanning hundreds of websites, investors also need a way to aggregate their market data. For example, getting financial statements into a usable format for analysis can be daunting, as analysts need hundreds of financial statements to compare data for clients. Therefore, investors must create an automated, continuous stream of corporate operational data without the need to manually comb through multiple websites and online databases. Once these processes are in place, investors can track more unique insights, such as regulatory development of KYC compliance and risk management, by monitoring websites and social media. Additionally, investors can also track customer sentiment by leveraging social media to predict how the activity and buzz around a specific stock or product can impact its performance on the market.

Hedge funds are getting smarter about how they collect and use web data, shifting from traditional web scraping to a more comprehensive Web Data Integration (WDI) approach in order to become more agile with their investment decisions. Web Data Integration is a new approach to acquiring and managing data. WDI focus on data quality and control, treating the entire web data lifecycle as a single, integrated journey. This, in turn, solves many pain points of traditional web scrapers, as WDI solutions deliver high-quality, clean, reliable with little to no resources needed nor risks taken. The data is also automatically rapidly onboarded and integrated into business processes.

With the vast wealth of information available on the web, the way in which investors make use of it takes many shapes and forms. And so, here are a few example of success stories of the various ways hedge funds are using alternative data to flip their respective industries on their heads:

Tracking Product Volume and Average Price: In the automobile market, data providers either do not provide the necessary insights to establish competitive advantage, or they don’t even exist at all. Using alternative data to monitor product volume and price, fund managers are building in-house alternative data platforms that produce unique datasets to perform bottom-up basket analysis of these products.

Understanding Company Health from Prices, Discounts and Reviews: In the retail industry, an investment bank does its due diligence in monitoring a company within its portfolio. After digging deeper into the company’s revenue success using pricing, discount and review data available on the web, the bank discovered the source of the growth stemmed from increased product prices rather than an increase in demand. This, in turn, influenced the bank’s adjustments on the investment rating.

Monitoring Regulatory Approvals to Predict Product Success: After building a solid history of backtesting, an investment bank in the pharmaceuticals space realizes the success of their invested products stems from approvals in a certain geographical region, where the base of the company’s production and consumer base resides. With Web Data Integration, the investment bank can predict launch success by tracking FDA approvals for products in this region daily.

Understanding Historical Trends: A major pipeline manufacturer publishes transmission reports on a daily basis. However, each report goes live on a separate web page, making it challenging to track transmission status over time. A bank that invests in this manufacturer extracts and compiles the separate report webpages into one comprehensive report that clearly tracks trends of transmission volume to inform future investment decisions and ratings.

Predicting Product Adoption: In the healthcare and pharmaceutical space, investment funds monitor online forums and blogs to track adoption of new pharmaceutical launch, tracking sentiment, popularity, influence and usage among consumers. In a similar case, another investment bank monitors how many healthcare practitioners are active providers of their leading product to better understand the market.

The world of alternative data

Without web data, hedge funds and investment banks are at risk of falling behind their competition. Investors now need to think creatively with their data, exploring new frontiers and gold mines of unconventional insights. For investors looking to explore alternative data – web data and more specifically Web Data Integration is a quick, painless solution to rapidly ramping up alternative data efforts.