Could selling data end in an insider trading lawsuit on Wall Street?

Could selling data end in an insider trading lawsuit on Wall Street?

The investment landscape is changing rapidly and asset managers are finding themselves in an arms race for new forms of alternative data. Everything from mobile phone location data to internet of things (IoT) data about crop yields, are being scraped, sanitized, packaged and sold on to investment managers looking for an edge when making decisions.

But the brave new world of big data-driven investing is something of a regulatory grey area. At what point does some exclusive, real-time look through into a company’s performance constitute insider trading? In legal terms this means trading on material, non-public information received in violation of a duty to keep it confidential.

Highly respected Wall Street lawyer Jonathan Streeter has said a legal case involving the purchase of data for trading purposes could be brought soon. Streeter, a New York-based partner at the law firm Dechert, was the federal prosecutor who led the insider trading case against Raj Rajaratnam, co-founder of Galleon Group.

Streeter says the ways and means of using alternative data is becoming a hot topic among the hedge fund clients he advises. “My clients are often calling me up and saying, I have this vendor who wants to sell me this data set; do you see any problems with that?

“Oftentimes the way it works is, there’s the original kind of creator of the data or owner of the data, the cell phone company or the company that takes the satellite images or whatever, and then there’s a vendor in between who buys the data from them, massages it in various ways and turns around and sells it to investors.”

There are two lines of legal analysis here: one is the securities law angle which concerns the risk of insider trading on material, non-public information. Secondly, there’s the question of internet laws and data privacy rules.

The hedge funds and asset managers who scope out alternative data are generally interested in aggregates; not only don’t they require personal details within the data, they don’t want it.

Regarding the risk of insider trading, it’s perhaps useful to differentiate along the lines of public and non-public data. I can stand in Walmart’s car park and count cars all day, so using satellite imagery to do this may give me an unfair advantage, but doesn’t change the fact that it’s public data.

However, imagine a very big retailer, for instance, selling transaction data pinpointing how many Panasonic televisions it sold this quarter versus last quarter.

Streeter said an example like that may catch the eye of regulators. “There is stuff that’s happening, or is about to start happening that I think the SEC, the FCA and other regulators are going to be interested in,” he said. “There are some of these data sets that start to look like, wow, someone is really going to have a huge advantage if they have this data set.

“If you’re a hedge fund you may be able to buy this data set and ordinary investors don’t have access to that information. And that is material, non-public information about product sales that a public company is going to announce at its next quarterly earnings.

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