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Let's Get "Real"" about Using Economic Data"

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  • Peter Christoffersen
  • Eric Ghysels
  • Norman R. Swanson

Abstract

Breeden, Gibbons and Litzenberger (1989), and Lamont (1999), use "economic tracking portfolios" to forecast macroeconomic data. Tracking portfolios are constructed to reflect market expectations and reveal the impact of news. However, these papers, as well as many related studies which examine the market impact of macroeconomic news, use "currently available" macroeconomic data. The combination of various different "vintages" of economic data has several important and undesirable consequences, particularly when the timing of information and its impact on financial markets is the focus of investigation. We therefore use a real-time macroeconomic data set to accurately mimic the accumulation of macroeconomic information in real time. We attempt to shed new light on the methodology used to construct tracking portfolios, as well as on the impact of macroeconomic news on financial markets. In addition, we address a number of related questions, including: Does the data revision process itself have an impact on financial markets? Do market participants: (i) care about "final" releases of macroeconomic variables; or (ii) form their decisions based on preliminary data; or (iii) instead form their decisions by using vintages of data which they assume correspond to those vintages used by public policy decision-makers?
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  • Peter Christoffersen & Eric Ghysels & Norman R. Swanson, 2001. "Let's Get "Real"" about Using Economic Data"," CIRANO Working Papers 2001s-44, CIRANO.
    • Handle: RePEc:cir:cirwor:2001s-44
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    2. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Richard G. Anderson, 2006. "Replicability, real-time data, and the science of economic research: FRED, ALFRED, and VDC," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 81-93.
    4. Eric Ghysels & Casidhe Horan & Emanuel Moench, 2018. "Forecasting through the Rearview Mirror: Data Revisions and Bond Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 678-714.
    5. Faust, Jon & Rogers, John H. & H. Wright, Jonathan, 2003. "Exchange rate forecasting: the errors we've really made," Journal of International Economics, Elsevier, vol. 60(1), pages 35-59, May.
    6. Bernard Sinclair-Desgagné, 2001. "Incentives in Common Agency," Cahiers de recherche 01-08, HEC Montréal, Institut d'économie appliquée.
    7. Vázquez, Jesús & María-Dolores, Ramón & Londoño, Juan M., 2012. "The Effect of Data Revisions on the Basic New Keynesian Model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 235-249.
    8. Richard Lajeunesse & Paul Lanoie & Michel Patry, 2001. "Environmental Regulation and Productivity: New Findings on the Porter Analysis," CIRANO Working Papers 2001s-53, CIRANO.
    9. Christodoulakis, George & Mamatzakis, Emmanuel, 2013. "Behavioural asymmetries in the G7 foreign exchange market," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 261-270.
    10. Vrugt, Evert B., 2009. "U.S. and Japanese macroeconomic news and stock market volatility in Asia-Pacific," Pacific-Basin Finance Journal, Elsevier, vol. 17(5), pages 611-627, November.
    11. Michael Pedersen, 2013. "Extracting GDP signals from the monthly indicator of economic activity: Evidence from Chilean real-time data," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(1), pages 1-16.
    12. Lamont, Owen A., 2001. "Economic tracking portfolios," Journal of Econometrics, Elsevier, vol. 105(1), pages 161-184, November.
    13. Kizys, Renatas & Pierdzioch, Christian, 2011. "The changing sensitivity of realized portfolio betas to U.S. output growth: An analysis based on real-time data," Journal of Economics and Business, Elsevier, vol. 63(3), pages 168-186, May.
    14. Julie Doonan & Paul Lanoie & Benoit Laplante, 2002. "Environmental Performance of Canadian Pulp and Paper Plants: Why Some Do Well and Others Do Not ?," CIRANO Working Papers 2002s-24, CIRANO.
    15. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    16. John W. Galbraith & Serguei Zernov & Victoria Zinde-Walsh, 2001. "Conditional Quantiles of Volatility in Equity Index and Foreign Exchange Data," CIRANO Working Papers 2001s-61, CIRANO.
    17. Ronney Ncwadi, 2016. "Assessing Efficiency of GDP Revisions in South Africa," Journal of Education and e-Learning Research, Asian Online Journal Publishing Group, vol. 3(2), pages 72-77.
    18. Christoffersen, Peter & Errunza, Vihang, 2000. "Towards a global financial architecture: capital mobility and risk management issues," Emerging Markets Review, Elsevier, vol. 1(1), pages 3-20, May.
    19. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
    20. Junttila, Juha & Kinnunen, Heli, 2004. "The performance of economic tracking portfolios in an IT-intensive stock market," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(4), pages 601-623, September.
    21. Padrón, Yaiza García & Boza, Juan García, 2006. "Which are the Risk Factors in the Pricing of Personal Pension in Spain?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 60(2), November.

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    More about this item

    Keywords

    Market efficiency; expectations; news; data revision process; Efficacité des marchés; attentes; nouvelles; processus de révision des données;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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