IDEAS home Printed from https://ideas.repec.org/a/hyp/journl/v3y2015i4p12-22.html

Applied SCGM(1,1)c Model and Weighted Markov Chain for Exchange Rate Ratios

Author

Listed:
  • Shaghayegh KORDNOORI

    (Research Institute for ICT, Tehran, Iran)

  • Hamidreza MOSTAFAEI

    (Islamic Azad University, Tehran, Iran, Institute for International Energy Studies)

  • Shirin KORDNOORI

    (Islamic Azad University,Tehran,Iran)

Abstract

The importance of predicting the fluctuations of exchange rate ratios is noticeable. In relation to markov model and grey system theory, using a single gene system cloud grey SCGM(1,1)c model to adjust the development trend of time series, its error index is randomly fluctuated. Markov chain model is appropriate to forecasting of a random dynamic system, choosing weighted markov chain to predict the error index. We applied a weighted markov SCGM(1,1)c model for predicting the U.S. Dollar /Euro, U.S. Dollar/Japan Yen, U.S. Dollar/Swiss franc and U.S. Dollar/Trade –Weighted Index. The forecasting results are reliable and show that the weighted markov SCGM(1,1)c model has high prediction precision.

Suggested Citation

  • Shaghayegh KORDNOORI & Hamidreza MOSTAFAEI & Shirin KORDNOORI, 2015. "Applied SCGM(1,1)c Model and Weighted Markov Chain for Exchange Rate Ratios," Hyperion Economic Journal, Faculty of Economic Sciences, Hyperion University of Bucharest, Romania, vol. 3(4), pages 12-22, December.
  • Handle: RePEc:hyp:journl:v:3:y:2015:i:4:p:12-22
    as

    Download full text from publisher

    File URL: https://hej.hyperion.ro/articles/4(3)_2015/HEJ%20nr4(3)_2015_A2Kordnoori.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
    2. Li, Der-Chiang & Chang, Che-Jung & Chen, Chien-Chih & Chen, Wen-Chih, 2012. "Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case," Omega, Elsevier, vol. 40(6), pages 767-773.
    3. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
    4. Yuan, Chunming, 2011. "Forecasting exchange rates: The multi-state Markov-switching model with smoothing," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 342-362, April.
    5. Ryan Greenaway-McGrevy & Nelson C. Mark & Donggyu Sul & Jyh-Lin Wu, 2012. "Exchange Rates as Exchange Rate Common Factors," Working Papers 212012, Hong Kong Institute for Monetary Research.
    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. Clements, Kenneth W. & Lan, Yihui, 2010. "A new approach to forecasting exchange rates," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1424-1437, November.
    8. Gerhard Fenz & Martin Schneider, 2004. "Macroeconomic Models and Forecasts for Austria," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 73-76.
    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. Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "On the directional accuracy of forecasts of emerging market exchange rates," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 369-376.
    2. Amat, Christophe & Michalski, Tomasz & Stoltz, Gilles, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 1-24.
    3. Martin McCarthy & Stephen Snudden, 2025. "Forecasts of Period-average Exchange Rates: Insights from Real-time Daily Data," RBA Research Discussion Papers rdp2025-09, Reserve Bank of Australia.
    4. Samuel W. Malone & Robert B. Gramacy & Enrique Ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
    5. Hongcheng Ding & Xuanze Zhao & Ruiting Deng & Shamsul Nahar Abdullah & Deshinta Arrova Dewi, 2024. "EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods," Papers 2408.13214, arXiv.org, revised Jun 2025.
    6. Baillie, Richard T. & Cho, Dooyeon, 2016. "Assessing Euro crises from a time varying international CAPM approach," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 197-208.
    7. 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.
    8. Ye, Li & Yang, Deling & Dang, Yaoguo & Wang, Junjie, 2022. "An enhanced multivariable dynamic time-delay discrete grey forecasting model for predicting China's carbon emissions," Energy, Elsevier, vol. 249(C).
    9. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "The impact of Euro through time: Exchange rate dynamics under different regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1375-1408, January.
    10. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    11. Haryo Kuncoro & Caroline Geetha & Fafurida Fafurida, 2024. "Central Bank Intervention and Exchange Rate Volatility in the Inflation-Targeting Regime," Economic Research Guardian, Mutascu Publishing, vol. 14(1), pages 2-15, June.
    12. P. Geoffrey Allen & Robert Fildes, 2005. "Levels, Differences and ECMs – Principles for Improved Econometric Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 881-904, December.
    13. Samet G nay, 2015. "Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 979-985.
    14. 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.
    15. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
    16. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
    17. Tuncay Özcan, 2017. "Application of Seasonal and Multivariable Grey Prediction Models for Short-Term Load Forecasting," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 5(2), pages 329-338, December.
    18. Wei Zhou & Demei Zhang, 2016. "An Improved Metabolism Grey Model for Predicting Small Samples with a Singular Datum and Its Application to Sulfur Dioxide Emissions in China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-11, February.
    19. Pastorek, Daniel, 2023. "Euro area uncertainty and Euro exchange rate volatility: Exploring the role of transnational economic policy," Finance Research Letters, Elsevier, vol. 58(PA).
    20. Alain Hecq & Marie Ternes & Ines Wilms, 2025. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(6), pages 1946-1968, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:hyp:journl:v:3:y:2015:i:4:p:12-22. 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: Iulian Panait The email address of this maintainer does not seem to be valid anymore. Please ask Iulian Panait to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/fehypro.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.