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Michael Giberson July 9th, 2007

A number of issues arise at the intersection of the two broad categories “insider trading” and “prediction markets.” Managers of public prediction markets may wonder what policy toward insider trading would be best for their markets. Participants in prediction markets wonder whether they will be exploited by insiders, and whether they can protect themselves against exploitation. Academics may wonder which policy toward insider participation in public prediction markets would provide optimum outcomes.

In this paper, Robin Hanson is not concerned with the effects of insider trading on prediction markets. Instead, he addresses the role current U.S. insider trading regulation plays in hampering the spread of prediction markets within companies. It takes Hanson nearly nine pages of somewhat meandering prose, but finally, at the end of page nine, he states the problem clearly:

Insider trading rules are one of the reasons that managers have given for not applying prediction markets to the highest value corporate topics. Simple cost benefit analysis suggests we apply prediction markets to the highest value topics we can find. In a corporation, those high value topics are the key corporate decisions, such as choosing to merge, to introduce products, setting price points, moving into new geographic regions, or even changing the CEO. It would be straightforward to directly ask decision markets whether such choices would be good for the firm stock.

Since one of the main advantages of prediction markets is not needing to know who to include, one could reasonably want to open participation in such markets to a large group, such as all employees. But allowing all employees access to key corporate information could create an insider trading nightmare.

Hanson then suggests a number of ways to run high level prediction markets without running afoul of insider trading restrictions, each of which would require some changes to insider trading laws.

The most direct approach would return to the company the discretion to limit insider trading. The company would then make the necessary trade-offs, if any, between restrictive insider trading rules and running high level prediction markets. Another approach would be to replace today’s insider trading rules with a simpler and more general requirement that insiders preannounce sales of stock in their company. A more elaborate version of this approach would designate one or more levels of “Well Informed Traders,” (WITs), and require WITs to preannounce trades before trading with ordinary traders (or lower level WITs).

In fact, Hanson concludes:

There seem to be a number of approaches that could allow the wide use of prediction markets within firms, and yet keep ordinary people from suffering inefficient adverse selection in stock trades. But the status quo insider trading rules do not seem to consist of one of these approaches.

I suspect many readers of Midas Oracle would be more interested in other issues at the intersection of “insider trading” and “prediction markets.”* Nonetheless, to the extent that existing insider trading regulations interfere with the use of prediction markets within publicly-traded companies, it is important for both developers of such markets and the broader prediction market community to understand the issues and articulate possible solutions.

(*Readers interested in “other issues” may want to read Stephen Bainbridge’s comments on insider trading in prediction markets in this blog post. Bainbridge points to the Wolfers and Zitzewitz paper, “Five Open Questions About Prediction Markets” as spurring some of his thinking on the topic.)

Robin Hanson, “Insider Trading and Prediction Markets,” a paper presented at the Journal of Law, Economics and Policy Symposium on Insider Trading, George Mason University School of Law, January 2007; the paper will be published in a special edition of the Journal of Law, Economics and Policy. (I reviewed the March 2007 version of the paper, available online at Hanson’s website.)

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