June 12, 2018 - Paul Lashmet | Big Data Ecosystem

Alternative Data Strategy: How and Why

An alternative data strategy is a collaborative, iterative, and exploratory process that is driven by domain subject matter expertise. That is our take from the research survey that we commissioned from Greenwich Associates to understand how buy-side portfolio managers, chief investment officers, and fund managers “Put Alternative Data to Use.” Our primary focus was to discover the “how” and “why” of implementing an alternative data strategy, because that is the basis from which to determine which tools and processes would work the best, and to identify the personas who would use them. Even within the buy-side community, we found that asset managers and hedge fund managers are distinct personas, and have differing perspectives on the use of alternative data.

In this part one of a two-part series, we consider buy-side perspectives as they relate to the types of alternative data being used, the measurement of return on investment, and how deep they want to get into the data.


Alternative Data Types: Useful Today versus Useful in the Future

Each participant in the survey was asked two questions about the types of alternative data:

  1. “What type(s) of alternative data do you use?” ranked on a scale of one (used extensively) to three (not used).
  2. “What alternative data would you like to incorporate but don’t have access to (wish list)?” ranked from one (really want it) to three (not so much).

For the overall buy-side community, social media and logistics data are the most used alternative data types today, while the Internet of Things (IoT) and satellite imagery are the biggest items on their wish list. The desirability of geolocation data also had a big jump up the wish list.

Both hedge fund and asset managers agree that satellite imagery would be useful in the future. The difference is the flow of opinion from what is useful today to what could be useful in the future. The pattern we see is that asset managers are more diversified in that decision, while hedge fund managers seem to flow mostly from using “logistics” and “social media and news feeds.”  

It’s important to note that these firms are not leaving one data set and moving on to another, but appending new data insight (satellite imagery in this case) to what they are already using (logistics and social media). The pattern visualized below could reflect a hedge fund manager’s strategy of being more narrowly focused, whereas big asset managers could be looking to enhance returns on a number of long-only strategies.


Data Transparency Is a Substantial Factor in Return on Investment

“Ninety percent of our respondents reported that they received a positive return on their alternative data investment.”

That’s an awesome headline for a data provider’s marketing team, but our “how” and “why” investigation shows that the measure of ROI is more nuanced than gaining alpha and beating the market.

We asked, “Do you demonstrate/explain your trading strategy to your investors?” As a group, eighty-eight percent responded “yes,” with asset managers more so (90%) than hedge fund managers (80%). For those that responded “yes” we asked, “Does alternative data provide additional insight to explain your trading strategy?” Both asset managers and hedge fund managers overwhelmingly affirmed the use of alternative data, 96% to 94% respectively.

As Kevin McPartland, Head of Market Structure & Technology Research at Greenwich Associates points out, “Not only does alternative data help improve returns, it often makes it easier for fund managers to demonstrate their strategy to their clients, ultimately increasing the total assets they manage as well.”

This makes sense for two reasons. Portfolio managers can distinguish themselves from the competition by demonstrating market sophistication that moves past the same quarterly reports and analyst opinions that every other firm has access to.

Another reason is that investors demand transparency. A recent Bank of New York Mellon report shows that nearly half of investors (45%) are dissatisfied with the transparency provided by hedge fund managers. Most of these dissatisfied investors (83%) are looking for more information on the underlying assets in a fund. The BNY Mellon report further states that managers are listening—71% plan to offer greater transparency over the coming 12 months.


It’s Harder to Convince Hedge Fund Managers of Value, but Then They Go for It

Regarding future spending, a slight majority of the buy-side community (58%) plans to increase their spending on alternative data. However, hedge fund managers are more aggressive in this area, as a majority (74%) plan to spend more, while less than half (48%) of asset managers plan to do the same.

An interesting story appears when we correlate the above with perceived roadblocks. Although hedge fund managers plan to spend more, the biggest roadblocks that they point out are high fees and convincing management of value. It appears that it is harder to convince hedge fund management, but once they are in, they are all in.


Details, Details, Details

When it comes to using alternative data, we found that the buy-side community tended to respond to the survey with specifics as opposed to generalities. This tells us that the buy-side industry is past the hype and generalities of alternative data (“generate alpha”, “to provide an edge over peers”) and are using it for specific purposes (“identify anomalies”, “understand patterns at a micro level”).

Tools to Leverage Alternative Data

In this post, we highlighted three key aspects regarding how the buy-side community puts alternative data to use. These are highlighted below, along with the capabilities required by the tools that facilitate that use:

  1. What is considered alternative data will shift over time. Analytic tools need to be able to handle all varieties of data: structured/unstructured, real time/historical, large sets/small sets.
  2. Data transparency is fundamental. Analytical tools should be able to drill down from summaries to very fine-grained detail.
  3. Alternative data is fit for purpose, and is used for specific reasons. Business users need tools that they can use, that are customized for their own purposes, but that may not be fully fleshed out yet.

Watch this video that demonstrates how conventional portfolio analysis can be enriched with two types of alternative data sources: sentiment analysis and location intelligence. Also, watch this webinar to learn how asset managers and hedge fund managers are finding, using, and benefiting from alternative data sources.

In the next blog post, we will continue to explore the “how” and “why” of alternative data as it relates to collaboration, strategies, the decision-making process, and the personas that drive that process.


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