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Recent studies have emphasized that survey-based inflation risk measures are informative about future inflation, and thus are useful for monetary authorities. However, these data are typically only available at a quarterly frequency, whereas monetary policy decisions require a more frequent monitoring of such risks. Using the ECB Survey of Professional Forecasters, we show that high-frequency financial market data have predictive power for the low-frequency survey-based inflation risk indicators observed at the end of a quarter. We rely on MIDAS regressions for handling the problem of mixing data with different frequencies that such an analysis implies. We also illustrate that upside and downside risks react differently to financial indicators.