A Streamlined Process for Alternative Data The new WorldQuant Data Exchange makes the submission and review process more efficient for companies interested in licensing their data to asset management firms like WorldQuant.

The world of investment management is built around the ability to make decisions. In today’s digital economy, investment firms must sift through an overwhelming amount of information — spanning everything from news and social media to satellite data, in order to be able to reach better conclusions — and the growth in available information shows no sign of slowing down. Research firm IDC projects that new data created annually will reach 163 zettabytes in 2025 (up from 16.1 zettabytes in 2016), powered in part by the growth in alternative data sources. (One zettabyte is the equivalent of 1 trillion gigabytes.)

Consulting firm Deloitte asserts that alternative data has the power to transform active investment management over the next five years — in large part because of advances in technology. “Advanced technologies enable processing of large, heterogeneous, and unstructured data sets at an extremely fast rate,” according to a recent report by the Deloitte Center for Financial Services. The report further notes that “[t]he adoption of alternative data, to a large extent, was driven by the development of sophisticated programs that can analyze” data from myriad sources.

The demand for data continues to expand. Burton-Taylor International Consulting calculates that the total global spend on financial market data and analysis set an all-time high last year, topping $28 billion, and is growing at the highest rate since 2011. Research by Opimas suggests that spending on alternative data will exceed $7 billion annually by 2020. Ten years ago, many quant firms simply followed the newest fad in alternative data. Satellite imagery was very popular, followed by social media sentiment. After that, location data gleaned from smartphones was all the rage. “Frequently, the new data was not designed for investing, but rather for marketing, agricultural and industrial production, security and other purposes,” Opimas co-founder and CEO Octavio Marenzi wrote last year.

Scouring the Planet

At WorldQuant, we believe it is critical to identify unique alternative datasets. Because we are a quantitative asset management firm, data is a key ingredient in our development of trading signals, which we call alphas. We spend significant time searching for, analyzing and back-testing datasets. Data is integral to our research process; we are constantly scouring the planet for new and better sources of it. That’s why we are excited to announce the launch of the WorldQuant Data Exchange. The Data Exchange is a tool that will help us connect with data providers large and small, all over the world. Although emerging markets like India and Singapore are saturated with interesting data, finding ways to engage with companies in those markets isn’t always easy. Through this new web portal, WorldQuant will be able to initiate dialogue with companies that have data that could be useful for financial research.

The Data Exchange website provides organizations with a simple, streamlined way to recommend and potentially submit data products for evaluation. The process enables WorldQuant to quickly review and respond to submissions, and may lead us to trial and later purchase ongoing updates to the particular datasets for use in our investment research process (after conducting due diligence and relevant procurement steps). By expanding our reach, we hope to establish new long-term partnerships that are mutually beneficial to the data providers and WorldQuant. 


Not all data is “good.” Here are some of the questions we consider when evaluating a dataset:

How hard is it to cut through the noise? This is arguably the most important issue facing investors when it comes to data. “Concerns that data will prove unreliable or will produce an inaccurate trading signal may nullify the value of alternative datasets,” writes Deloitte. “Since each alternative dataset may be unique or scarce, investment teams may have difficulty finding a way to verify the accuracy of a dataset.” 

Does the data have a consistent history? History is extremely important in the world of quantitative investing. Having a historical time series helps investors to back-test against different market conditions.

Does the data pertain to capital markets? We invest in capital markets, so we’re specifically looking for information that can be used to establish an investment thesis.  

Are there any biases in the data? “Good” data is consistent. Having biases isn’t necessarily a bad thing, but we have to know what they are. We can adjust for any biases as long as they are consistent and can be accounted for.

Is the data in a format that is workable for quantitative research? Whether it’s in an API or some other form, we need data that can be uploaded and evaluated reliably and in an accessible format.

Is the data compliant with regulatory requirements? We conduct diligence to ensure we meet the relevant requirements with regard to applicable laws, rules and regulations.

While the pursuit of alternative data has shone a spotlight on what quantitative investors do, there are still challenges remaining for firms like WorldQuant in the area of data procurement. On the whole, we believe that the WorldQuant Data Exchange will help companies better realize that they may be sitting on a pipeline of data that can potentially be useful for investment research — and potentially be lucrative for them as well!


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