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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
    as

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    References listed on IDEAS

    as
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