We develop a statistical approach to detect informed trades in options markets.The method is applied to 9.6 million of daily option prices. Empirical results suggest that option informed trades tend to cluster prior to certain events, generate easily large gains exceeding millions, are not contemporaneously reflected in the underlying stock price, and involve liquid options during calm times and cheap options during turbulent times. These findings are not driven by false discoveries in informed trades which are controlled using a multiple hypothesis testing technique. Pricing, policy, and market efficiency implications of these findings are discussed.

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