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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We investigate how firms' use of derivatives impacts voluntary disclosure and offer four main findings. First, we find that when firms begin using derivative instruments, they increase the frequency of management earnings forecasts. Second, using path analysis, we find a direct link between derivative usage and forecast frequency, as well as an indirect link through reduced earnings volatility. Third, we find that CEOs with more pronounced career concerns increase forecast frequency only when derivatives make earnings easier to forecast and find no evidence that investor demand drives the decision to provide a forecast. These results suggest that the primary mechanism for the association between derivative usage and forecast frequency is a reduction in the manager's costs of providing the forecasts. Finally, we find that the majority of derivative‐induced forecasts are uninformative to capital market participants, especially after FAS 161 provided the necessary underlying data to understand how firms use derivatives. Overall, we provide the first empirical evidence that firms that use derivatives issue more management forecasts, but we also find that these incremental forecasts are largely uninformative and appear driven by managerial career concerns.

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