I’ve written before about Big Data and the democratic factor of financial markets. But in the face of a recent Business Insider article that predicts Big Data insights will be too costly for average investors, I feel it’s necessary to point out a few truths that say otherwise.
1. Financial products like exchange-traded funds (ETFs) make technology and data-driven insights more accessible to more investors.
2. Advancements in data processing capabilities, and the wide deployment of graphics processing units (GPUs), are bringing high-performance computing to the masses. Data-crunching costs are coming down and will continue to do so over time. Artificial intelligence (AI) is transforming almost every industry and business vertical through broader access to system automation and data analytics.
AI technologies can power smarter, faster business processes at lower costs, which will usher in a wave of market disruption by newcomers. Now that fewer people can do more with less, it’s conceivable for a small startup to take on a Fortune 500 market leader.
Companies are using technology to improve report writing, job listings, customer relationship management, and numerous other functions. There are many examples out there, including the pharmaceutical industry, which is using AI to find new drugs and speed up clinical trials to bring down hefty R&D costs. Also, hiring managers and human resources professionals are starting to use AI to find the right talent at a fraction of the time and cost of traditional recruiting tools.
3. Sourcing insights from alternative data sets requires expertise and technological skill—the average person simply cannot build such models themselves. We will continue to rely on specialist firms to do this work (see sidebar) and competition will regulate the cost of obtaining such information.
Hedge funds and other asset managers will likely attempt to charge high fees and justify them due to the cost and complexity of gaining insights from alternative data. But this is a red herring to protect their interests. Investors should do their due diligence around management fees and choose investments wisely.
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Alternative data 101
Traditional data sources that influence stock prices—news articles, historic market performance, financial statements, quarterly reports, regulatory filings—are now augmented by what’s become known in the financial industry as “alternative data”.
Alternative data is raw and unstructured. It can be anything from mobile phone usage to satellite imagery of parking lots to weather patterns to web traffic. Over the past decade, the growth of Big Data has created an ideal environment for turning obscure data sets into tradable information.
A specialized data tech industry has mushroomed to support demand from trading firms looking for an edge. Mining investment insights from raw and unstructured data is going mainstream.
Which begs the question, how much longer will alternative data still be considered alternative?