Quandl Launches Corporate Jet Dataset for Predicting M&A Activity

Dubbed the Corporate Aviation Intelligence platform, the new data tracks 26,000 private jets that reveal the travel patterns of executives from 1,300 public companies—representing 70 percent of the S&P 500 index—and 3,100 private companies between 25,000 destinations worldwide.

Quandl CEO Tammer Kamel says the vendor created the dataset by combining data and technologies from five different sources—several of which it licenses on an exclusive basis, including collecting and aggregating data from long-form ownership paperwork, flight licenses, and radio spectrum licenses, among other sources.

In addition, building the dataset required “substantial manual effort” around mapping jet tail numbers to their owners, and to a complex network of ownership relationships between corporations and their subsidiaries, Kamel says.

“This is necessary because deducing corporate ownership of aircraft is inherently complicated. Companies hire other companies to handle administrative work. Companies lease or use aircraft owned or registered by someone else. Shell companies are put to use. Aircraft are registered under lesser-known subsidiaries. And then you have fractional ownership issues—think NetJets—where ownership is subdivided through contracts,” he says.

In fact, companies use these complexities to camouflage activities that might reveal corporate strategies. “Corporations regularly try to conceal their and their executives’ movements, but there is only so much that can legally be done to do so. We use fully legal technology and data sources to piece together this picture, including corporate ownership and connections,” he adds.

Despite the complexity of the data sourcing and mapping, Kamel says Quandl has kept the end product simple, and has developed a visual front-end interface to make it easy for analysts to monitor the companies they are interested in, rather than delivery via datafeed, since the product is not aimed at quantitative analysts and traders. Users can search by company, flight origin and destination, and the front end also includes functionality to help users identify patterns, such as whether a company is frequently flying to the same destination.

Quandl will not provide a definitive statement of what will take place, when, and between whom, or any commentary around the data, leaving it up to clients to draw their own conclusions based on the available information. Instead, the data is designed to provide signals to analysts already monitoring specific companies and potential corporate activity, which they can then investigate further and validate with other data points.

“There are very few, if any, certainties in trading or in M&A, but aviation intelligence can be the tipping signal an analyst needs. For example, Cigna announced the acquisition of Express Scripts on March 8 this year. Our data shows repeated HQ-to-HQ flights, by both fully-owned and fractionally-owned jets, from both parties in advance of this announcement. The acquirer’s travel tends to be more interesting to analysts, but an acquiree’s travel can add confidence to a rumor,” Kamel says, adding that Quandl has included anomaly detection, proximity understanding, and an alerting system to automate the analysis process for users.