Alternative Data – The New Frontier in Asset Management

Executive Summary

Asset management is being fundamentally changed by an explosion in the information world that is reshaping its operations and creating a new hierarchy of winners. To stay competitive, traders and portfolio managers increasingly need to incorporate new, alternative data that stretch well beyond the traditional market intelligence that has been the mainstay of investing.

These alternative data come from a bewildering array of sources, including satellite and drone imagery, GPS tracking for cars, trains, and mobile phones, transactional data for credit cards and other payments, sentiment analysis for social media and news feeds, and so on. Frequently, the new data was not designed for investing, but rather for marketing, agricultural and industrial production, security and other purposes.

The explosion of new data presents a particular challenge to hedge funds and other asset managers, as acquiring the necessary skills and infrastructure to leverage these sources of information will require large investments. We expect that alternative data will contribute significantly to a further shrinkage in the hedge fund population, as firms unable to exploit the information needed to compete effectively in the new world of intelligent investing will fall behind.  The sell side will be challenged, too.

Opimas estimates that buy side and sell side investments in the race to master and employ the plethora of data will exceed $US7 billion by 2020. (See Figure 1) While potential returns are currently impossible to pin down, the current 21% annual growth in spending in this space implies that managers believe the alpha generated will at least cover their investments initially, and over time could produce attractive returns. In the case of one hedge fund that is advancing in this race, we estimate that the excess return could ultimately exceed 5%.

Figure 1. Spending on Alternative Data for Trading and Asset Management

Source: Opimas Analysis

This sea change in asset management creates opportunities for providers of the underlying data, but also challenges. We believe that:

  • Buy-side firms will need to develop a wide range of skills in order to adapt to this new environment. These include data management to unearth and apply hundreds of data sources covering thousands of data sets; domain expertise to interpret and contextualise the new data; data science to create quantitative trading models using advanced statistics and artificial intelligence, and information technology to create architectures designed to deploy the investing models based on heterogeneous data.
  • Sell-side institutions are in a position to benefit by providing the necessary infrastructure to their buy-side clients. In addition, broker-dealers that are part of large universal banks are well-placed to package and resell some of the vast quantities of data available within their bank. These data cover payments, loan origination, FX trading patterns, trade finance, loan delinquency information and much more.
  • Market data vendors are naturally positioned to act as aggregators of fragmented data sources and to provide services that directly tie the alternative data to tradable instruments.
  • Exchanges, the primary source of traditional market data, are likely to see muted growth in their more advanced market-data offerings. Vulnerable areas will include ultra-low-latency data feeds and depth-of-book products, as clients’ earlier focus on quantitative trading shifts away from high-frequency strategies to those that are rooted in alternative data. Exchanges are being challenged by the rise of alternative data and we expect a handful of them to respond by making acquisitions that can restore their advantages in the coming years.

In this report, Opimas provides an overview of alternative data now required for trading and asset management. We examine some of the providers of alternative data, analyse best practices, and show how exchanges, market-data aggregators, sell-side institutions and other participants can leverage their existing positions to benefit from this trend. Managing the flow of information and converting it into investment strategies will be one of the biggest challenges facing the asset management industry in the coming years.

Firms mentioned in this report:

7park Data, Airsage, Cardlytics, Dataminr, Descartes Labs, Discern, Envestnet Yodlee, Foursquare, Genscape, Heckyl, INRIX, MasterCard, MKT MediaStat , Orbital Insight, Owlin, Placed, PlaceMeter, Premise, Quandl, Ravenpack, Rezatec, Rsmetrics, Second Measure , Selerity , Sentieo, Spaceknow, Spire, Streetlight Data, Tellus Labs, Ursaspace, Windward, Yipit Data


Table of Contents of Report    

Executive Summary







A Definition



A Sea Change in Quantitative Investing



Vast and Expanding Sources of Data



How Much Alpha?


Sources of Raw Data







Proprietary Sensors






Web Pages



Transactional Data


Alternative Data Providers




Image Processing and Analysis



Other Imagery



GPS Data Analysis



Web Pages Analysis



Transactional Data Analysis


Applications of Alternative Data



Preparing for the Future




Asset Managers



Market Data Vendors



Sell-Side Institutions









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