Forecast the Foreign Exchange Rate between Rupiah and US Dollar by Applying Grey Method

  • Tien-Chin Wang
  • Su-Hui Kuo
  • Truong Ngoc Anh
  • Li Li
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 156)


Indonesia is the largest archipelago in the world and also the largest nation in South East Asia. As a big country which is rich of natural resources, there have been many foreign investors from Asia and Europe taking the opportunities to invest in this country. This study applied the GM (1,1) model [6,9,10,11] to predict the exchange rate between Rupiah and US Dollar from 2010/01/01 to 2010/10/18. The results presented that the average accuracy of the forecasting model exceeds 99.65%.


Exchange Rate Grey Relational Analysis Grey Model Grey System Foreign Exchange Rate 
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  1. 1.
    Yao, A.W.L., Chen, J.H.: The optimal parameters design for Grey forecasting of electric demand control. In: Proc. of the 2001 Conference on Control Systems, pp. 137–143. IEEE Control Systems Society, Taipei (2001)Google Scholar
  2. 2.
    Alessandro, P., Schinasi, G.J.: EMU and International Capitals Market: Structural Implications and Risks, IMF Working Paper (1997)Google Scholar
  3. 3.
    Chiang, J.S., Wu, P.L., Chiang, S.D., Chang, T.J., Chang, S.T., Wen, K.L.: Introduction of Grey System Theory. Gao-Li Publication, Taiwan (1998)Google Scholar
  4. 4.
    Deng, J.L.: Control problems of Grey systems. Systems and Control Letters 5, 288–294 (1982)Google Scholar
  5. 5.
    Deng, J.L.: Grey system fundamental method. Huazhong University of Science and Technology Wuhan, China (1982)Google Scholar
  6. 6.
    Deng, J.L.: Grey prediction and decision. Huazhong University of Science and Technology, Wuhan, China (1986)Google Scholar
  7. 7.
    Deng, J.L.: Introduction to Grey system theory. The Journal of Grey System 1(1), 1–24 (1989)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Deng, J.L.: he Course on Grey System Theory, p. 91. Huazhong University of Science & Technology Publish House, Wuhan (1990)Google Scholar
  9. 9.
    Deng, J.L.: The Essential Methods of Grey Systems. Huazhong University of Science and Technology Press, Wuhan (1992)Google Scholar
  10. 10.
    Hsu, C.I., Wen, Y.U.: Improved Grey prediction models for trans-Pacific air passenger market. Transp. Plann. Technol. 22, 87–107 (1998)CrossRefGoogle Scholar
  11. 11.
    Hsu, L.C.: The comparison of three residual modification model. J. Grey System, Assoc. 4(2), 97–110 (2001)Google Scholar
  12. 12.
    Lin, C.-T., Hsu, P.-F.: Forecast of non-alcoholic beverage sales in Taiwan using the Grey theory. Asia Pacific Journal of Marketing and Logistics 4(14), 3–12 (2002)CrossRefGoogle Scholar
  13. 13.
    Lin, C.-T., Yang, S.-Y.: Forecast of the output value of Taiwan’s opto-electronics industry using the Grey forecasting model. Technological Forecasting & Social Change, 177–186 (2003)Google Scholar
  14. 14.
    Renn, J.C., Chen, W.J.: Control of a servo hydraulic positioning system using state space controller with Grey forecasting. JSMEGoogle Scholar
  15. 15.
    Tseng, F.M., Yu, H.C., Tzeng, G.H.: Applied hybrid Grey model to forecast seasonal time series. Technol. Forecast. So. 67, 291–302 (2001)CrossRefGoogle Scholar
  16. 16.
    Wen, J.C., Huang, K.H., Wen, K.L.: The study of a in GM(1,1) model. J. Chin. Inst. Eng. 23(5), 583–589 (2000)CrossRefGoogle Scholar
  17. 17.
    Whyman, P.: The impact of Economic and Monetary Union on British business. European Business Journal 13(1) (Quarterly 2001)Google Scholar
  18. 18.
    Wu, J.H., Lauh, C.R.: A study to improve GM(1,1) via Heuristic method. J. Grey System 10(3), 183–192 (1998)Google Scholar
  19. 19.
    Yeh, M.F., Lu, H.C.: A new modified Grey model. J. Grey System 1(8), 209–216 (1996)Google Scholar
  20. 20.
    Cheng, S.-R., Chen, J.-C., Wu, W.-H., Liu, Y.-T.: Forecasting Equity Fund Performance via GA. International Journal of Innovative Computing, Information and Control 4(2), 333–339 (2010)Google Scholar
  21. 21.
    Mussa, M.: The exchange rate, the balance of payments, and monetary and fiscal policy under a regime of controlled floating. Scandinavian. Journal of Economics 78, 229–248 (1976)Google Scholar
  22. 22.
    Rapach, D., Wohar, M.: In-sample vs. out-of-sample tests of stock return predictability in the context of data mining. Journal of Empirical Finance 13, 231–247 (2006)CrossRefGoogle Scholar
  23. 23.
    Sweeney, R.: Mean reversion in G-10 nominal exchange rates. Journal of Financial and Quantitative Analysis (2006)Google Scholar
  24. 24.
    Faust, J., Rogers, J., Wright, J.: Exchange rate forecasting: The errors we’ve really made. Journal of International Economics 60, 35–59 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  • Tien-Chin Wang
    • 1
  • Su-Hui Kuo
    • 1
  • Truong Ngoc Anh
    • 1
  • Li Li
    • 2
  1. 1.Department of International BusinessNational Kaoshiung University of Applied SciencesKaohsiungTaiwan
  2. 2.Department of Urban Planning & Economic ManagementHarbin Institute of TechnologyHarbinChina

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