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Is the Intrinsic Value of Macroeconomic News Announcements Related to Their Asset Price Impact?

Author

Listed:
  • Thomas Gilbert

    (University of Washington)

  • Chiara Scotti

    (Federal Reserve System, Board of Governors)

  • Georg H. Strasser

    (Department of Economics, Boston College)

  • Clara Vega

    (Federal Reserve System, Board of Governors)

Abstract
The literature documents a heterogeneous asset price response to macroeconomic news announcements: Some announcements have a strong impact on asset prices and others do not. In order to explain these differences, we estimate a novel measure of the intrinsic value of a macroeconomic announcement, which we define as the announcement's ability to nowcast GDP growth, inflation, and the Federal Funds Target Rate. Using the same nowcasting framework, we then decompose this intrinsic value into the announcement's characteristics: its relation to fundamentals, timing, and revision noise. We find that in the 1998-2013 period, a significant fraction of the variation in the announcements' price impact on the Treasury bond futures market can be explained by differences in intrinsic value. Furthermore, our novel measure of timing explains significantly more of this variation than the announcements' relation to fundamentals, reporting lag (which previous studies have used as a measure of timing), or revision noise.

Suggested Citation

  • Thomas Gilbert & Chiara Scotti & Georg H. Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to Their Asset Price Impact?," Boston College Working Papers in Economics 874, Boston College Department of Economics, revised 23 Apr 2015.
  • Handle: RePEc:boc:bocoec:874
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    References listed on IDEAS

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    Cited by:

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    3. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    4. Kočenda, Evžen & Moravcová, Michala, 2018. "Intraday effect of news on emerging European forex markets: An event study analysis," Economic Systems, Elsevier, vol. 42(4), pages 597-615.
    5. Yang-Ho Park, 2019. "Information in Yield Spread Trades," Finance and Economics Discussion Series 2019-025, Board of Governors of the Federal Reserve System (U.S.).
    6. Paul Alagidede & Tseke Maserumule, 2018. "Impact of macroeconomic announcements on foreign exchange volatility: Evidence from South Africa," Working Papers 751, Economic Research Southern Africa.
    7. Frankel, Jeffrey & Saiki, Ayako, 2016. "Does It Matter If Statistical Agencies Frame the Month's CPI Report on a 1-Month or 12-Month Basis?," Working Paper Series 16-011, Harvard University, John F. Kennedy School of Government.
    8. Kurov, Alexander & Sancetta, Alessio & Strasser, Georg & Wolfe, Marketa Halova, 2019. "Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(1), pages 449-479, February.
    9. Andreas Neuhierl & Michael Weber & Michael Weber, 2016. "Monetary Policy and the Stock Market: Time-Series Evidence," CESifo Working Paper Series 6199, CESifo.
    10. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    11. Altavilla, Carlo & Giannone, Domenico & Modugno, Michele, 2017. "Low frequency effects of macroeconomic news on government bond yields," Journal of Monetary Economics, Elsevier, vol. 92(C), pages 31-46.
    12. Tseke Maserumule & Paul Alagidede, 2017. "Impact of Macroeconomic Announcements on Foreign Exchange Volatility: Evidence from South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 85(3), pages 405-429, September.
    13. Andreas Neuhierl & Michael Weber, 2016. "Monetary Policy and the Stock Market: Time-Series Evidence," NBER Working Papers 22831, National Bureau of Economic Research, Inc.
    14. Scotti, Chiara, 2016. "Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.
    15. Adrian Cantemir CĂLIN & Radu LUPU, 2016. "The Effects Of Labor Market News On International Financial Markets," Romanian Economic Business Review, Romanian-American University, vol. 11(2), pages 207-215, June.
    16. John B. Broughton & Bento J. Lobo, 2018. "Herding and anchoring in macroeconomic forecasts: the case of the PMI," Empirical Economics, Springer, vol. 55(3), pages 1337-1355, November.
    17. Ehrmann, Michael & Talmi, Jonathan, 2020. "Starting from a blank page? Semantic similarity in central bank communication and market volatility," Journal of Monetary Economics, Elsevier, vol. 111(C), pages 48-62.
    18. Strasser, Georg, 2017. "What determines the impact of macroeconomic news on asset markets?," Research Bulletin, European Central Bank, vol. 37.
    19. Francis, Bill B. & Hunter, Delroy M. & Kelly, Patrick J., 2020. "Do foreign investors insulate firms from local shocks? Evidence from the response of investable firms to monetary policy," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 386-411.
    20. Gau, Yin-Feng & Wu, Zhen-Xing, 2017. "Macroeconomic announcements and price discovery in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 232-254.
    21. Ben Omrane, Walid & Savaşer, Tanseli, 2017. "Exchange rate volatility response to macroeconomic news during the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 130-143.

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    More about this item

    Keywords

    Macroeconomic announcements; price discovery; public information; macroeconomic forecasting; learning; coordination role of public information; central bank policy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • G1 - Financial Economics - - General Financial Markets

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