IDEAS home Printed from https://ideas.repec.org/a/sae/globus/v25y2024i3p585-605.html
   My bibliography  Save this article

Short-term Forecasting Ability of Hybrid Models for BRIC Currencies

Author

Listed:
  • Latha Sreeram
  • Samie Ahmed Sayed

Abstract

This article proposes a new framework to improve short-term forecasting accuracy of exchange rates of BRIC nations, that is, Brazil (USD/BRL), Russia (USD/RUB), India (USD/INR) and China (USD/CNY). The study employs three methodologies for a 42-day forecast: hybrid models based on least square support vector machine, residual hybrid model and automatic hybrid model forecasting using R software. The results show that the proposed residual hybrid model framework, including autoregressive integrated moving average-artificial neural network (ARIMA–ANN)-TBATS, outperformed other models with Brazil and China return series reflecting the best accuracy in ANN model and India and Russia demonstrating the best accuracy in trigonometric seasonal, box-cox transformation, ARIMA residuals, trend and seasonality (TBATS) model. Further, the results indicate that Brazil and China return series follow a non-linear pattern, while India and Russia follow a non-linear complex seasonal pattern. The highest level of forecast accuracy has been observed in China followed by Brazil, India and Russia.

Suggested Citation

  • Latha Sreeram & Samie Ahmed Sayed, 2024. "Short-term Forecasting Ability of Hybrid Models for BRIC Currencies," Global Business Review, International Management Institute, vol. 25(3), pages 585-605, June.
    • Handle: RePEc:sae:globus:v:25:y:2024:i:3:p:585-605
    DOI: 10.1177/0972150920954615
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972150920954615
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0972150920954615?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Gioqinang & Hu, Michael Y., 1998. "Neural network forecasting of the British Pound/US Dollar exchange rate," Omega, Elsevier, vol. 26(4), pages 495-506, August.
    2. Martin D. D. Evans & Richard K. Lyons, 2017. "Meese-Rogoff Redux: Micro-Based Exchange-Rate Forecasting," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 11, pages 457-475, World Scientific Publishing Co. Pte. Ltd..
    3. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    4. Kocaarslan, Baris & Sari, Ramazan & Gormus, Alper & Soytas, Ugur, 2017. "Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 41-56.
    5. Lin, Chiun-Sin & Chiu, Sheng-Hsiung & Lin, Tzu-Yu, 2012. "Empirical mode decomposition–based least squares support vector regression for foreign exchange rate forecasting," Economic Modelling, Elsevier, vol. 29(6), pages 2583-2590.
    6. Paul Newbold & Toni Rayner & Neil Kellard & Christine Ennew, 1998. "Is the dollar/ECU exchange rate a random walk?," Applied Financial Economics, Taylor & Francis Journals, vol. 8(6), pages 553-558.
    7. Koray, Faik & Lastrapes, William D, 1989. "Real Exchange Rate Volatility and U.S. Bilateral Trade: A VAR Approach," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 708-712, November.
    8. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    9. Frankel, Jeffrey A & Froot, Kenneth A, 1990. "Chartists, Fundamentalists, and Trading in the Foreign Exchange Market," American Economic Review, American Economic Association, vol. 80(2), pages 181-185, May.
    10. Rakesh K. Bissoondeeal & Jane M. Binner & Muddun Bhuruth & Alicia Gazely & Veemadevi P. Mootanah, 2008. "Forecasting exchange rates with linear and nonlinear models," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 414-429.
    11. Bailey, Martin J. & Tavlas, George S. & Ulan, Michael, 1987. "The impact of exchange-rate volatility on export growth: Some theoretical considerations and empirical results," Journal of Policy Modeling, Elsevier, vol. 9(1), pages 225-243.
    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. Alejandro Parot & Kevin Michell & Werner D. Kristjanpoller, 2019. "Using Artificial Neural Networks to forecast Exchange Rate, including VAR‐VECM residual analysis and prediction linear combination," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 3-15, January.
    2. F. Pancotto & G. Pignataro & D. Raggi, 2014. "Higher order beliefs and the dynamics of exchange rates," Working Papers wp957, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. Nikola Gradojević & Vladimir Djaković & Goran Andjelić, 2010. "Random Walk Theory and Exchange Rate Dynamics in Transition Economies," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 57(3), pages 303-320, September.
    4. Kelly Burns & Imad Moosa, 2017. "Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?," Applied Economics, Taylor & Francis Journals, vol. 49(48), pages 4897-4910, October.
    5. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    6. Marcos Álvarez-Díaz & Alberto Álvarez, 2002. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0205, Universidade de Vigo, Departamento de Economía Aplicada.
    7. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    8. Peter Rowland & Hugo OLiveros C., 2003. "Colombian Purchasing Power Parity Analysed Using a Framework of Multivariate Cointegration," Borradores de Economia 252, Banco de la Republica de Colombia.
    9. Kaijian He & Rui Zha & Jun Wu & Kin Keung Lai, 2016. "Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price," Sustainability, MDPI, vol. 8(4), pages 1-11, April.
    10. Kun Xing & Honggang Li, 2024. "The profitability of interacting trading strategies from an ecological perspective," Annals of Finance, Springer, vol. 20(3), pages 377-394, September.
    11. Arie Preminger & Uri Ben-zion & David Wettstein, 2007. "The extended switching regression model: allowing for multiple latent state variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 457-473.
    12. Firouzi, Shahrokh & Wang, Xiangning, 2019. "A comparative study of exchange rates and order flow based on wavelet transform coherence and cross wavelet transform," Economic Modelling, Elsevier, vol. 82(C), pages 42-56.
    13. Sun, Shaolong & Wang, Shouyang & Wei, Yunjie, 2019. "A new multiscale decomposition ensemble approach for forecasting exchange rates," Economic Modelling, Elsevier, vol. 81(C), pages 49-58.
    14. Cerrato, Mario & Kim, Hyunsok & MacDonald, Ronald, 2015. "Microstructure order flow: statistical and economic evaluation of nonlinear forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 40-52.
    15. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    16. Audretsch, David B. & Stadtmann, Georg, 2005. "Biases in FX-forecasts: Evidence from panel data," Global Finance Journal, Elsevier, vol. 16(1), pages 99-111, August.
    17. Josh Stillwagon & Peter Sullivan, 2020. "Markov switching in exchange rate models: will more regimes help?," Empirical Economics, Springer, vol. 59(1), pages 413-436, July.
    18. repec:lan:wpaper:470 is not listed on IDEAS
    19. Dick, Christian D. & MacDonald, Ronald & Menkhoff, Lukas, 2015. "Exchange rate forecasts and expected fundamentals," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 235-256.
    20. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    21. Ericsson, Neil R., 1992. "Parameter constancy, mean square forecast errors, and measuring forecast performance: An exposition, extensions, and illustration," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 465-495, August.

    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:sae:globus:v:25:y:2024:i:3:p:585-605. 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: SAGE Publications (email available below). General contact details of provider: http://www.imi.edu/ .

    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.