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We investigate whether and how the complexity of derivatives influences analysts' earnings forecast properties. Using a difference-in-differences design, we find that, relative to a matched control sample of non-users, analysts' earnings forecasts for new derivatives users are less accurate and more dispersed after derivatives initiation. These results do not appear to be driven by the economic complexity of derivatives, but rather the financial reporting of such economic complexity. Overall, despite their financial expertise, analysts routinely misjudge the earnings implications of firms' derivatives activity. However, we find evidence that a series of derivatives accounting standards has helped analysts improve their forecasts over time.

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