Rise of alternative data could be a boon, not a bust, for hedge funds, says study
Whether it's satellite images or social media activity, alternative data has become hot property as hedge funds and other large asset managers hunt for new ways to gain a competitive edge in their trading strategies.
Unlike traditional data such as regulatory filings or company reports, alternative data draws from an eclectic mix of sources, including smartphones and meteorology reports. Those who buy it from a growing number of sellers do so in hopes that the data set contains clues to the future that others haven't yet found. Activity on a company's private jet could signal a pending merger deal. An increasing number of negative online reviews for a product might mean impending trouble for a company's shares.
Despite concerns that alternative data could spell the demise of those funds unable to keep up with the diverse skills required to interpret it, new research suggests the opposite scenario is more likely, with funds and alternative data sellers growing together.
"The idea that alternative data could be a threat to the hedge fund industry may overlook the complementary roles between the alternative data vendors and alternative data buyers, where hedge funds play a dominant role," says Liyan Yang, a finance professor and the Peter L. Mitchelson/SIT Investment Associates Foundation Chair in Investment Strategy at the University of Toronto's Rotman School of Management and one of the study's three co-authors.
"In our paper, the population of skilled investors and the data sellers' profit always move in the same direction in response to changes in related external factors such as costs and skill volatility, which suggests the two industries foster each other."
Using a theoretical model of the interaction between data sellers, buyers and the skills to process the data, the researchers show that alternative data encourages firms to bring in more highly skilled people to extract unique insights from the data, leading to stronger performance for the fund and for the market. That can be expensive in the short-term, but the model shows that data sellers respond by providing bigger data samples. Larger samples allow buyers to draw more accurate information, which in turn improves how informative or predictive a stock's price is of a company's future earnings, which benefits everyone participating in the market.
Once funds have made the initial costly investments into skills acquisition, they have ready capacity to process more alternative data more cheaply over time, leading them to seek out more alternative data. Eventually, what was once considered "alternative" could become more of a standard source of information.
Skills acquisition is embedded in the model because data alone does not provide an advantage. It needs to be processed, with the useful bits identified, extracted and interpreted, leading to the production of information, which is where the real value lies.
"Even if you have a lot of oil, to make it usable, you have to refine it," says Prof. Yang. "Data is similar."
The study was co-authored with Shiyang Huang of The University of Hong Kong and Yan Xiong of Hong Kong University of Science and Technology.
More information: Shiyang Huang et al, Skill Acquisition and Data Sales, Management Science (2021). DOI: 10.1287/mnsc.2021.4117
Journal information: Management Science
Provided by University of Toronto