Big money investors have always sought an edge. Everything from star traders to fast computers to unique analysis can give a big hedge fund an advantage over competitors. The latest battleground is data.
Investors are vying for new data sets that their competitors don’t have, or haven’t thought of using. These can range from the basic credit-card sales information to satellite data that tracks shipping routes, and parsing this kind of data for trading signals has been called “the future of investing.”
The industry providing this to the funds has sprung up amid an explosion in obtainable data over the past decade. The bad news for the regular investor: the cost of data, and the complexity associated with turning it into investment insights, means it will probably only be available to the biggest and most sophisticated funds.
At JPMorgan’s macro quantitative and derivatives conference on May 19, the bank surveyed 237 investors, and asked them about Big Data and Machine Learning. It found that 70% thought that the importance of these tools will gradually grow for all investors. A further 23% said they expected a revolution, with rapid changes to the investment landscape.
“There was widespread agreement that Big Data and Machine Learning is transforming the investment landscape across different trading frequencies, with more than 80% of participants expecting a reduction in relevance of traditional data sources,” JPMorgan said in a note.
To be specific, 52% of investors felt big data was already rendering traditional data sources (like financial statements and economic releases) ineffective. In other words, the quarterly reports that many regular investors rely on are already becoming less relevant.
The rise of so-called alternative data has created a cottage industry of firms that source, process and consult on various data sources. The market for this data is expected to double in the next five years in the US, from $200 million today to $400 million, according to a recent TABB Group report.
More than half (51%) of investors surveyed said they expected to buy semi-processed data, while 29% said they wanted to fully process in-house by consuming raw data.
Respondents to the survey were particularly interested in credit card and transactional data. Investors are able to use anonymous data gleaned from credit card statements, and the rise of online shopping, and the digital receipts we get in our email, is a also boon. That’s because emailed receipts are usually itemized, giving investors greater detail into what people are buying.
The biggest impediment? Cost. While a lack of expertise and management buy-in were cited by respondents as challenges, the most frequently cited impediment was high-fixed costs.
That finding is striking, given JPMorgan’s event attracted big money investors like BlackRock and AQR, with sizeable budgets to spend on the data, expertise and processing power.
If they find it expensive, the regular investor has no chance.