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RWP 25-03, May 2025

This paper investigates the utility of daily data in measuring high-frequency monetary policy surprises, comparing various announcement-day asset price changes with their intradaily (30-minute) counterparts. We find that both frequencies are similarly distributed and often highly correlated, particularly for longer-horizon measures. Testing daily surprises for systematic contamination from non-monetary policy news, we find no evidence to suggest that contemporaneous news releases bias their measurement. Empirical applications, including high-frequency passthrough to Treasury yields and proxy SVAR models, suggest that daily surprises produce results comparable to those obtained with intradaily data. Our findings suggest that while intradaily data remains invaluable for certain applications, daily data offers a practical and robust alternative for assessing monetary policy surprises, particularly when the event, or the reaction to it, extends beyond a narrow window, or when intradaily data is unavailable.

JEL Classifications: E43, E44, E52, E58, G14

Article Citation

  • An, Phillip, Karlye Dilts Stedman, and Amaze Lusompa. “How High Does High Frequency Need to Be? A Comparison of Daily and Intradaily Monetary Policy Surprises.” Federal Reserve Bank of Kansas City, Research Working Paper no. 25-03, May. Available at External Linkhttps://doi.org/10.18651/RWP2025-03

Authors

Phillip An

Research Associate

Phillip An is a Research Associate at the Federal Reserve Bank of Kansas City. He joined the Economic Research Department in June 2023 after graduating from the University of Te…

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Karlye Dilts Stedman

Senior Economist

Karlye Dilts Stedman is a Senior Economist in the Macroeconomics and Monetary Policy Division at the Federal Reserve Bank of Kansas City. Ms. Dilts Stedman joined the Bank in 20…

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Amaze Lusompa

Economist

Amaze Lusompa is an Economist in the Economic Research Department of the Federal Reserve Bank of Kansas City. Prior to joining the department in 2020, Amaze received a Ph.D. in …

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