IDEAS home Printed from https://ideas.repec.org/p/cns/cnscwp/199914.html
   My bibliography  Save this paper

Modelli non lineari per i tassi di cambio: un confronto previsivo

Author

Listed:
  • G. Boero
  • E. Marrocu

Abstract

In recent years there has been a considerable development in time seriesanalysis, represented mainly by alternative linear models able to describe more adequately the short and long term dynamics and by the renewed interest in modelling nonlinearities and asymmetries in economic and financial variables. Given the relevance of such variables in devising economic and monetary policy, it is of theoretical, as well as practical, importance to propose statistical methods appropriate to represent their dynamic behaviour. The aim of this work is to compare the forecasting performance of different models for the returns of some of the most traded exchange rates, namely the French Franc (FF/$), the German Mark (DM/$) and the Japanese Yen (Y/$). We compare the relative performance of some nonlinear models and contrast them with their simpler linear counterparts. Although we find evidence of noticeable forecasting gains from nonlinear models, the results are sensitive to the metric adopted to measure the forecasting accuracy.e.

Suggested Citation

  • G. Boero & E. Marrocu, 1999. "Modelli non lineari per i tassi di cambio: un confronto previsivo," Working Paper CRENoS 199914, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  • Handle: RePEc:cns:cnscwp:199914
    as

    Download full text from publisher

    File URL: https://crenos.unica.it/crenos/node/141
    Download Restriction: no

    File URL: https://crenos.unica.it/crenos/sites/default/files/wp/99-14.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. B. Priestley, 1980. "State‐Dependent Models: A General Approach To Non‐Linear Time Series Analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 47-71, January.
    2. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    3. Richard A. Meese & Andrew K. Rose, 1991. "An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 603-619.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. David Peel & Alan Speight, 1994. "Testing for non-linear dependence in inter-war exchange rates," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 130(2), pages 391-417, June.
    6. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    7. Clements, M.P. & Hendry, D.F., 1992. "Forecasting in Cointegrated Systems," Economics Series Working Papers 99139, University of Oxford, Department of Economics.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    9. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    10. Clements, M.P. & Smith, J., 1998. "Non-Linearities in Exchange Rates," The Warwick Economics Research Paper Series (TWERPS) 504, University of Warwick, Department of Economics.
    11. A. I. McLeod & W. K. Li, 1983. "Diagnostic Checking Arma Time Series Models Using Squared‐Residual Autocorrelations," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 269-273, July.
    12. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    13. Krager, Horst & Kugler, Peter, 1993. "Non-linearities in foreign exchange markets: a different perspective," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 195-208, April.
    14. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
    15. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Musumeci, 2000. "Innovazione tecnologica e beni culturali. Uno studio sulla situazione della Sicilia," Working Paper CRENoS 200008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. G. Boero & E. Marrocu, 2001. "Evaluating non-linear models on point and interval forecasts: an application with exchange rate returns," Working Paper CRENoS 200110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    3. R. Naylor, 2001. "Firm profits and the number of firms under unionised oligopoly," Working Paper CRENoS 200109, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    4. C. Antonelli & R. Marchionatti & S. Usai, 2000. "Productivity and External Knowledge: The Italian Case," Working Paper CRENoS 200009, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. LR. Keller & E. Strazzera, 2000. "Examining predictive models among discounting models," Working Paper CRENoS 200005, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
    7. R. Naylor, 2001. "Industry profits and market size under bilateral oligopoly," Working Paper CRENoS 200108, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    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. G. Boero & E. Marrocu, 2000. "La performance di modelli non lineari per i tassi di cambio: un'applicazione con dati a diversa frequenza," Working Paper CRENoS 200014, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    3. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    4. G. Boero & E. Marrocu, 2001. "Evaluating non-linear models on point and interval forecasts: an application with exchange rate returns," Working Paper CRENoS 200110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
    6. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-141, March-Apr.
    7. Theodore Panagiotidis, 2010. "Market efficiency and the Euro: the case of the Athens stock exchange," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(3), pages 237-251, July.
    8. Chen, Cathy W.S. & Yang, Ming Jing & Gerlach, Richard & Jim Lo, H., 2006. "The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 401-418.
    9. Martinez Oscar & Olmo Jose, 2012. "A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-39, September.
    10. Ntebogang Dinah Moroke, 2015. "An Optimal Generalized Autoregressive Conditional Heteroscedasticity Model for Forecasting the South African Inflation Volatility," Journal of Economics and Behavioral Studies, AMH International, vol. 7(4), pages 134-149.
    11. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    12. Francesco Audrino & Fabio Trojani, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369, April.
    13. Syed Kamran Ali Haider & Shujahat Haider Hashmi & Ishtiaq Ahmed, 2017. "Systematic Risk Factors And Stock Return Volatility," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 11(1-2), September.
    14. David Peel & Alan Speight, 1994. "Testing for non-linear dependence in inter-war exchange rates," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 130(2), pages 391-417, June.
    15. Ahmad Zubaidi Baharumshah & Liew Khim Sen & Lim Kian Ping, 2003. "Exchange Rates Forecasting Model: An Alternative Estimation Procedure," International Finance 0307005, University Library of Munich, Germany.
    16. LUBRANO, Michel, 1998. "Smooth transition GARCH models: a Bayesian perspective," LIDAM Discussion Papers CORE 1998066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Clements, Michael P. & Smith, Jeremy, 2001. "Evaluating forecasts from SETAR models of exchange rates," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 133-148, February.
    18. Kumari, Jyoti, 2019. "Investor sentiment and stock market liquidity: Evidence from an emerging economy," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 166-180.
    19. Beg, A.B.M. Rabiul Alam & Anwar, Sajid, 2012. "Sources of volatility persistence: A case study of the U.K. pound/U.S. dollar exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 165-184.
    20. Wu, Yih-Jiuan, 1998. "Exchange rate forecasting: an application of radial basis function neural networks," ISU General Staff Papers 1998010108000013540, Iowa State University, Department of Economics.

    More about this item

    Statistics

    Access and download statistics

    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:cns:cnscwp:199914. 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: CRENoS (email available below). General contact details of provider: https://edirc.repec.org/data/crenoit.html .

    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.