IDEAS home Printed from https://ideas.repec.org/a/gam/jforec/v1y2018i1p2-25d144239.html
   My bibliography  Save this article

Effects of the Swiss Franc/Euro Exchange Rate Floor on the Calibration of Probability Forecasts

Author

Listed:
  • Brian D. Deaton

    (Walter F. and Virginia Johnson School of Business, McMurry University, Abilene 79697, TX, USA)

Abstract

Probability forecasts of the Swiss franc/euro (CHF/EUR) exchange rate are generated before, surrounding and after the placement of a floor on the CHF/EUR by the Swiss National Bank (SNB). The goal is to determine whether the exchange rate floor has a positive, negative or insignificant effect on the calibration of the probability forecasts from three time-series models: a vector autoregression (VAR) model, a VAR model augmented with the LiNGAM causal learning algorithm, and a univariate autoregressive model built on the independent components (ICs) of an independent component analysis (ICA). Score metric rankings of forecasts and plots of calibration functions are used in an attempt to identify the preferred time-series model based on forecast performance. The study not only finds evidence that the floor on the CHF/EUR has a negative impact on the forecasting performance of all three time-series models but also that the policy change by the SNB altered the causal structure underlying the six major currencies.

Suggested Citation

  • Brian D. Deaton, 2018. "Effects of the Swiss Franc/Euro Exchange Rate Floor on the Calibration of Probability Forecasts," Forecasting, MDPI, vol. 1(1), pages 1-23, May.
    • Handle: RePEc:gam:jforec:v:1:y:2018:i:1:p:2-25:d:144239
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-9394/1/1/2/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-9394/1/1/2/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carriero, A. & Kapetanios, G. & Marcellino, M., 2009. "Forecasting exchange rates with a large Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 25(2), pages 400-417.
    2. Grisse, Christian & Nitschka, Thomas, 2015. "On financial risk and the safe haven characteristics of Swiss franc exchange rates," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 153-164.
    3. Lean Yu & Shouyang Wang & Kin Keung Lai, 2007. "Foreign-Exchange-Rate Forecasting With Artificial Neural Networks," International Series in Operations Research and Management Science, Springer, number 978-0-387-71720-3, January.
    4. Jesús Crespo Cuaresma & Jaroslava Hlouskova, 2005. "Beating the random walk in Central and Eastern Europe," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 189-201.
    5. Kling, John L & Bessler, David A, 1989. "Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output," The Journal of Business, University of Chicago Press, vol. 62(4), pages 477-499, October.
    6. Liu, Te-Ru & Gerlow, Mary E. & Irwin, Scott H., 1994. "The performance of alternative VAR models in forecasting exchange rates," International Journal of Forecasting, Elsevier, vol. 10(3), pages 419-433, November.
    7. Bo Qian & Khaled Rasheed, 2010. "Foreign exchange market prediction with multiple classifiers," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 271-284.
    8. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    9. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    2. Tasadduq Imam, 2021. "Model selection for one‐day‐ahead AUD/USD, AUD/EUR forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1808-1824, April.
    3. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
    4. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    5. Frederico Belo & Chen Xue & Lu Zhang, 2010. "Cross-sectional Tobin's Q," NBER Working Papers 16336, National Bureau of Economic Research, Inc.
    6. Hwang, Chiun-Lin, 1989. "Optimal monetary policy in an open macroeconomic model with rational expectation," ISU General Staff Papers 1989010108000010197, Iowa State University, Department of Economics.
    7. Yariv, Leeat & Jackson, Matthew O., 2018. "The Non-Existence of Representative Agents," CEPR Discussion Papers 13397, C.E.P.R. Discussion Papers.
    8. KAMKOUM, Arnaud Cedric, 2023. "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs," Thesis Commons d7pvg, Center for Open Science.
    9. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    10. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 802, University Library of Munich, Germany.
    11. Stefan Laséen & Andrea Pescatori, 2020. "Financial stability and interest‐rate policy: A quantitative assessment of costs and benefit," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(3), pages 1246-1273, August.
    12. Zsolt Darvas, 2013. "Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(2), pages 363-390, May.
    13. Luca Benati & Paolo Surico, 2009. "VAR Analysis and the Great Moderation," American Economic Review, American Economic Association, vol. 99(4), pages 1636-1652, September.
    14. Marçal, Emerson Fernandes & Cunha, Ronan & Merlin, Giovanni Tondin & Simões, Oscar, 2017. "The aftermath of 2008 turmoil on Brazilian economy: Tsunami or “Marolinha”?," Textos para discussão 459, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    15. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    16. G. Menzies & R. Bird & P. Dixon & M. Rimmer, 2010. "Asset Price Regulators, Unite: you have Macroeconomic Stability to Win and the Microeconomic Losses are Second-order," Centre of Policy Studies/IMPACT Centre Working Papers g-205, Victoria University, Centre of Policy Studies/IMPACT Centre.
    17. Takamitsu Kurita, 2007. "A dynamic econometric system for the real yen–dollar rate," Empirical Economics, Springer, vol. 33(1), pages 115-149, July.
    18. Donald L. Kohn, 2008. "Lessons for central bankers from a Phillips curve framework," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    19. Ariane Szafarz, 2015. "Market Efficiency and Crises:Don’t Throw the Baby out with the Bathwater," Bankers, Markets & Investors, ESKA Publishing, issue 139, pages 20-26, November-.
    20. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jforec:v:1:y:2018:i:1:p:2-25:d:144239. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.