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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
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    References listed on IDEAS

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    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. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

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