Asset managers are always looking for new sources of alpha. The data revolution is impacting many different industries and it is finally here to change the investment industry as well.
Users generating data with sensors are not likely to represent the population. Social media users are usually young and tech savvy representing rather a specific demographic group. Search data, on the other hand, can be used in econometric modelling more straightforwardly.
Data is all around us, and is growing in volume every day. The amount of data created every 2 days is as much as was created from the beginning of time until 2003. If we were to put 1 year’s worth of data on DVDs, the stack would go from Earth to the moon and back.
80% of respondents who participated in BrightLocal’s 2015 Local Consumer Review Survey admitted they would trust online reviews as much as personal recommendations. Lee, Park and Han’s study showed that purchase intention increases with the perceived credibility of consumer reviews.
Over 7,000 articles have been written on the subject of sentiment analysis, primarily in the last decade. The asset management community has been experimenting with the use of sentiment analysis, specifically in analyzing the polarity of sentiment expressed in social media and news media.
The rapid uptake of alternative data research by both fundamental and quantitative institutional investors is shifting the investment landscape and creating innovative sources of alpha generation.
Asset managers use information derived from alternative data companies that specialize in analysing satellite imagery to assist in their estimation of revenues of companies in different sectors, including retail, oil and gas and construction.
This article outlines the big data concept and questions its practical implications for investment managers. We set the parameters for assessing asset management systems and technology to prepare and prosper as big data takes hold.
In October 2014, Gene Ekster delivered a talk to the NY Open Statistical Programming Group explaining how unstructured and alternative data could be used to generate returns.
