Navigating a new investment edge – Examining hedge funds use of alternative data
Published: 18 July 2019
Hedge funds have always been at the cutting edge of investment science. They pioneered the idea that the traits of an investment opportunity can be quantified, and that opportunities with similar traits can be grouped together and targeted. Just like other industries, hedge funds are being disrupted by revolutionary technologies including artificial intelligence and machine learning.
Consider this mind-boggling statistic for a moment – 90% of the world’s data available today was produced in the past two years. Over the next five years, it is estimated that this number is likely to increase by a factor of 10 times more!
In a world where information is readily available to everyone, investment managers, including hedge funds, are turning to alternative data to find new ways of generating alpha. Put simply, alternative data (or as it may also be called, Big Data) is defined as any type of dataset that does not meet the criteria for traditional financial data (e.g. income statement, balance sheet) or financial market data (e.g. pricing, volumes traded, investment factors). This data can be compiled from sources such as financial transactions, mobile devices, satellites, public records and the internet.
The systematic collection and ordering of data are important for hedge funds – whether they are fundamental or systematic in their approach to investing.
If you are a hedge fund, we urge you to take the below short survey; the results of which will help inform a paper that we will publish in Q4 which explores managers’ use of alternative data. All data provided from this survey will be collated and retained by AIMA. Any data used in publications will only be presented or shared in the aggregate, and not be attributed to any specific firm or individual. Thank you for your support.