Perspectives

Seeking to boost alpha generation?

Use alternative data

Meet alternative data: An integral component in an investment managers’ toolkit to unlock market insights.

April 4, 2018

A blog post by Ankur Gajjaria, senior analyst, Deloitte Support Services India Private Limited.

Quantitative hedge funds, which account for 34 percent of hedge fund assets, are at the forefront of using alternative data for alpha generation.1 In fact, many quant hedge funds now are placing alternative data analytics at the crux of their alpha generation process. These alternative data sets cover structured or unstructured non-financial data, including satellite imagery, weather patterns, credit card transactions, web traffic, and social media sentiment. While hedge funds are the first movers in this space, traditional long-only investment managers also are augmenting their investment decisions using alternative data sets. Different classes of investment managers and information vendors (from hedge funds, family offices and proprietary trading desks to fintech firms and data support vendors) have leveraged alternative data in a number of ways, based on their unique decision-making processes, analytical capabilities and risk-return objectives. These include:

  • A hedge fund monitors private corporate flight records for travel patterns of CEOs and other key executives to predict M&A activity.2
  • An alternative data vendor partners with an auto insurance firm to predict car sales based on insurance policies sold.
  • A family office combines alternative data sets—including credit card transactions, geo-location, and mobile app downloads—to analyze the performance of a global burger chain.3

Collective Intelligence Investing: Alpha generation via alternative data brings new risks

Read the full report

Considerations when adopting alternative data

As alternative data becomes mainstream, investment managers can consider a few points while beginning the adoption process. These include:

  1. Identifying the right alternative data type and developing a quick access method for integration within the investment decision-making process. Regular efficacy testing of the data set signals could also be required to test for alpha decay.
  2. Using an integrated data analytics platform to undertake different analytics to promote idea-sharing and greater efficiency. Combining this with a traditional financial data platform can generate differentiated market insights.
  3. Establishing a fluid data architecture to manage vastly different technology, storage, and computing requirements. A system that can handle multiple data feeds via application programming interface (API) along with scalable processing power could be a prerequisite to manage alternative data sets.
  4. Creating a collaborative insights team comprising data scientists, engineers, and financial analysts to derive new insights. Conducting cross-functional training also prepares the insights team to handle new data sets quickly.

Maintaining the alpha-generation edge is difficult, as some of these data sets are susceptible to proliferation decay. To retain the alpha-generation capability of alternative data sets, investment managers and alternative data vendors could either preserve the exclusivity factor or relentlessly innovate with both new alternative data sets and creative analytics methods.

Exclusivity or innovation?

If your firm’s goal is to preserve the exclusivity factor, consider one approach many data vendors are using: limit access to the alternative data set. By charging investment managers tens of thousands of dollars to access the alternative data set, vendors ensure the data and subsequent insights remains in the hands of only a few customers.4 Some vendors are even limiting licensing of data to preserve value, based on its predicted value. Some investment management (IM) firms are cultivating or developing unique data sets of their own. Others are developing unique insights through crowdsourcing (also called collective intelligence investing or CII), which may be less subject to proliferation decay.

If your firm’s goal is to relentlessly innovate, you must remain at the cutting-edge of innovation in alternative data sets to maintain their alpha-generation capabilities. Innovation could be focused on two areas.

  1. Investment managers should continuously evaluate different and new types of alternative data sets for insight generation. Consider assigning specific members of the investment team to explore such data sets to fulfill this objective. 
  2. Employ new analytical methods and approaches to generate market insights from data that has been easily available but until now unable to be analyzed due to its high volume. Through on-demand computing, investment managers can easily scale their data-processing capabilities to generate insights from these high-volume data sets.

In the race to generate alpha through alternative data, investment managers must make sure they do not cross a line that could lead to regulatory or compliance hurdles. Accessing and analyzing alternative data poses a number of risks for investment managers, including data, model, and talent risk. For more details, please refer to Deloitte’s Alternative data for investment decisions report, and our recent report on Collective Intelligence Investing.

What is your take on alternative data?

Are there other factors that investment managers could keep in mind during the adoption phase? What different approaches would enable investment managers to retain their edge in alternative data analytics? Join the conversation on Twittter at @DeloitteFinSvcs.

“How to pick a quantitative hedge fund,” Man FRM, September 15, 2017.
Nick Wells, “Making millions from the data hidden in plain sight,” CNBC, November 28, 2017.
“Alternative Data – Use Cases Edition 3,” Eagle Alpha, November 29, 2017.
Nick Wells, “Making millions from the data hidden in plain sight,” CNBC, November 28, 2017.

QuickLook is a weekly blog from the Deloitte Center for Financial Services about technology, innovation, growth, regulation, and other challenges facing the industry. The views expressed in this blog are those of the blogger and not official statements by Deloitte or any of its affiliates or member firms.

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