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The Scapegoat Theory of Exchange Rates: The First Tests

  • Fratzscher, Marcel
  • Sarno, Lucio
  • Zinna, Gabriele

This paper provides an empirical test of the scapegoat theory of exchange rates (Bacchetta and van Wincoop 2004, 2011), as an attempt to evaluate its potential for explaining the poor empirical performance of traditional exchange rate models. This theory suggests that market participants may at times attach significantly more weight to individual economic fundamentals to rationalize the pricing of currencies, which are partly driven by unobservable shocks. Using novel survey data which directly measure foreign exchange scapegoats for 12 currencies and a decade of proprietary data on order flow, we find empirical evidence that strongly supports the empirical implications of the scapegoat theory of exchange rates, with the resulting models explaining a large fraction of the variation and directional changes in exchange rates. The findings have implications for exchange rate modelling, suggesting that a more accurate understanding of exchange rates requires taking into account the role of scapegoat factors and their time-varying nature.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8812.

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Date of creation: Feb 2012
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Handle: RePEc:cpr:ceprdp:8812
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  1. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not As Bad As You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441 National Bureau of Economic Research, Inc.
  2. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-33, October.
  3. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, EconWPA.
  4. Philippe Bacchetta & Eric van Wincoop, 2009. "On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," NBER Working Papers 15008, National Bureau of Economic Research, Inc.
  5. Philippe Bacchetta & Eric van Wincoop, 2009. "Tacit On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 09.07, Université de Lausanne, Faculté des HEC, DEEP.
  6. David W. Berger & Alain P. Chaboud & Sergey V. Chernenko & Edward Howorka & Jonathan H. Wright, 2006. "Order flow and exchange rate dynamics in electronic brokerage system data," International Finance Discussion Papers 830, Board of Governors of the Federal Reserve System (U.S.).
  7. Garry J. Schinasi & P.A.V.B. Swamy, 1987. "The out-of-sample forecasting performance of exchange rate models when coefficients are allowed to change," Special Studies Papers 212, Board of Governors of the Federal Reserve System (U.S.).
  8. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
  9. Martin D. D. Evans and Richard K. Lyons., 1999. "Order Flow and Exchange Rate Dynamics," Research Program in Finance Working Papers RPF-288, University of California at Berkeley.
  10. Sarno, Lucio & Valente, Giorgio, 2008. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," CEPR Discussion Papers 6638, C.E.P.R. Discussion Papers.
  11. Nelson C. Mark, 2005. "Changing Monetary Policy Rules, Learning, and Real Exchange Rate Dynamics," NBER Working Papers 11061, National Bureau of Economic Research, Inc.
  12. Kevin Hoover & Stephen J. Perez, 2003. "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Working Papers 9727, University of California, Davis, Department of Economics.
  13. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
  14. David F. Hendry & Hans-Martin Krolzig, 1999. "Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 202-219.
  15. Love, Ryan & Payne, Richard, 2008. "Macroeconomic News, Order Flows, and Exchange Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(02), pages 467-488, June.
  16. Yin-Wong Cheung & Menzie D. Chinn, 2000. "Currency Traders and Exchange Rate Dynamics: A Survey of the U.S. Market," CESifo Working Paper Series 251, CESifo Group Munich.
  17. Philippe Bacchetta & Eric van Wincoop & Toni Beutler, 2009. "Can Parameter Instability Explain the Meese-Rogoff Puzzle?," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 09.08, Université de Lausanne, Faculté des HEC, DEEP.
  18. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  19. Lucio Sarno & Elvira Sojli, 2009. "The Feeble Link between Exchange Rates and Fundamentals: Can We Blame the Discount Factor?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 437-442, 03.
  20. Barbara Rossi, 2005. "Testing Long-Horizon Predictive Ability With High Persistence, And The Meese-Rogoff Puzzle," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(1), pages 61-92, 02.
  21. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-18, March.
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