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Exchange Rate Market Expectations and Central Bank Policy: The case of the Mexican Peso-US Dollar from 2005-2009

  • Gustavo Abarca
  • José Gonzalo Rangel
  • Guillermo Benavides

We examine two approaches characterized by different tail features to extract market expectations on the Mexican peso-US dollar exchange rate. Expectations are gauged by risk-neutral densities. The methods used to estimate these densities are the Volatility Function Technique (VFT) and the Generalized Extreme Value (GEV) approach. We compare these methods in the context of monetary policy announcements in Mexico and the US. Once the surprise component of the announcements is considered, our results indicate that, although both VFT and GEV suggest similar dynamics at the center of the distribution, these two methods show significantly different patterns in the tails. Our empirical evidence shows that the GEV model captures better the extreme values.

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File URL: http://www.banxico.org.mx/publicaciones-y-discursos/publicaciones/documentos-de-investigacion/banxico/%7BDFEC9239-3798-C4E6-0792-A67EBF5B345B%7D.pdf
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Paper provided by Banco de México in its series Working Papers with number 2010-17.

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Date of creation: Dec 2010
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Handle: RePEc:bdm:wpaper:2010-17
Contact details of provider: Web page: http://www.banxico.org.mx

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  1. Kenneth N. Kuttner, 2000. "Monetary policy surprises and interest rates: evidence from the Fed funds futures markets," Staff Reports 99, Federal Reserve Bank of New York.
  2. Ben S. Bernanke & Kenneth N. Kuttner, 2005. "What Explains the Stock Market's Reaction to Federal Reserve Policy?," Journal of Finance, American Finance Association, vol. 60(3), pages 1221-1257, 06.
  3. Charles M. Jones & Owen Lamont & Robin Lumsdaine, 1996. "Macroeconomic News and Bond Market Volatility," Home Pages _005, Princeton University, Department of Economics.
  4. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, 02.
  5. Yacine Aït-Sahalia & Andrew W. Lo, . "Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices," CRSP working papers 332, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
  6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
  7. Bates, David S, 1991. " The Crash of '87: Was It Expected? The Evidence from Options Markets," Journal of Finance, American Finance Association, vol. 46(3), pages 1009-44, July.
  8. Guillermo Benavides & Carlos Capistrán, 2009. "Forecasting Exchange Rate Volatility: The Superior Performance of Conditional Combinations of Time Series and Option Implied Forecasts," Working Papers 2009-01, Banco de México.
  9. Mark Rubinstein., 1994. "Implied Binomial Trees," Research Program in Finance Working Papers RPF-232, University of California at Berkeley.
  10. Bhupinder Bahra, 1997. "Implied risk-neutral probability density functions from option prices: theory and application," Bank of England working papers 66, Bank of England.
  11. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
  12. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
  13. James D. Hamilton, 2009. "Daily Changes in Fed Funds Futures Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 567-582, 06.
  14. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
  15. Söderlind, Paul, 1997. "Market Expectations in the UK Before and After the ERM Crisis," SSE/EFI Working Paper Series in Economics and Finance 210, Stockholm School of Economics, revised 01 Sep 1998.
  16. Jens Carsten Jackwerth & George M. Constantinaides & Stylianos Perrakis, 2005. "Option Pricing: Real and Risk-Neutral Distributions," CoFE Discussion Paper 05-06, Center of Finance and Econometrics, University of Konstanz.
  17. Rubinstein, Mark, 1994. " Implied Binomial Trees," Journal of Finance, American Finance Association, vol. 49(3), pages 771-818, July.
  18. Garman, Mark B. & Kohlhagen, Steven W., 1983. "Foreign currency option values," Journal of International Money and Finance, Elsevier, vol. 2(3), pages 231-237, December.
  19. Bomfim, Antulio N., 2003. "Pre-announcement effects, news effects, and volatility: Monetary policy and the stock market," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 133-151, January.
  20. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2005. "The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models," American Economic Review, American Economic Association, vol. 95(1), pages 425-436, March.
  21. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-51, October.
  22. Bliss, Robert R. & Panigirtzoglou, Nikolaos, 2002. "Testing the stability of implied probability density functions," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 381-422, March.
  23. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-54, May-June.
  24. Mc Manus, Des, 1999. "The Information Content of Interest Rate Futures Options," Working Papers 99-15, Bank of Canada.
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