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We build a framework to forecast out-of-sample any asset price movement in a tight window around the release of any macroeconomic indicator. As a case study, we examine the predictability of the EUR/USD exchange rate conditional on the market-based surprise in the first 60 min after the release of the United States Non-Farm Payrolls and ISM manufacturing index. We empirically investigate whether the findings of the literature obtained using an in-sample approach also hold in a real-time out-of-sample exercise. We demonstrate that the main econometric models lose accuracy in an out-of-sample application and cannot outperform a naive model. Additionally, we highlight that the main reason is the counterintuitive direction of a large number of small asset price movements around the release. Finally, we show that clustering the responses to the market-based surprises by their size improves the predictability, reconciling the role given by the literature to nonlinearities.