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Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market

Author

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  • Su, EnDer
  • Fen, Yu-Gin

Abstract

The present study uses the structural equation model (SEM) to analyze the correlations between various economic indices pertaining to latent variables, such as the New Taiwan Dollar (NTD) value, the United States Dollar (USD) value, and USD index. In addition, a risk factor of volatility of currency returns is considered to develop a risk-controllable fuzzy inference system. The rational and linguistic knowledge-based fuzzy rules are established based on the SEM model and then optimized using the genetic algorithm. The empirical results reveal that the fuzzy logic trading system using the SEM indeed outperforms the buy-and-hold strategy. Moreover, when considering the risk factor of currency volatility, the performance appears significantly better. Remarkably, the trading strategy is apparently affected when the USD value or the volatility of currency returns shifts into either a higher or lower state.

Suggested Citation

  • Su, EnDer & Fen, Yu-Gin, 2011. "Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market," MPRA Paper 35474, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:35474
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    References listed on IDEAS

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    1. Branson, William H. & Henderson, Dale W., 1985. "The specification and influence of asset markets," Handbook of International Economics, in: R. W. Jones & P. B. Kenen (ed.), Handbook of International Economics, edition 1, volume 2, chapter 15, pages 749-805, Elsevier.
    2. Doidge, Craig & Griffin, John & Williamson, Rohan, 2006. "Measuring the economic importance of exchange rate exposure," Journal of Empirical Finance, Elsevier, vol. 13(4-5), pages 550-576, October.
    3. Koedijk, Kees G. & Kool, Clemens J. M. & Schotman, Peter C. & van Dijk, Mathijs A., 2002. "The cost of capital in international financial markets: local or global?," Journal of International Money and Finance, Elsevier, vol. 21(6), pages 905-929, November.
    4. Arun Kuppam & Ram Pendyala, 2001. "A structural equations analysis of commuters' activity and travel patterns," Transportation, Springer, vol. 28(1), pages 33-54, February.
    5. Branson, William H. & Halttunen, Hannu & Masson, Paul, 1977. "Exchange rates in the short run: The dollar-dentschemark rate," European Economic Review, Elsevier, vol. 10(3), pages 303-324.
    6. Bilson, John F O, 1981. "The "Speculative Efficiency" Hypothesis," The Journal of Business, University of Chicago Press, vol. 54(3), pages 435-451, July.
    7. Christopher J. Neely, 2005. "An analysis of recent studies of the effect of foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 685-718.
    8. Williamson, Rohan, 2001. "Exchange rate exposure and competition: evidence from the automotive industry," Journal of Financial Economics, Elsevier, vol. 59(3), pages 441-475, March.
    9. Gordon M. Bodnar & M.H. Franco Wong, 2003. "Estimating Exchange Rate Exposures: Issues in Model Structure," Financial Management, Financial Management Association, vol. 32(1), Spring.
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    More about this item

    Keywords

    Knowledge-based Systems; Fuzzy Sets; Structural Equation Model (SEM); Genetic Algorithm (GA); Currency Volatility;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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