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High Frequency Deutsche Mark-US Dollar Returns: FIGARCH Representations and Non Linearities

Author

Listed:
  • Richard T. Baillie

    (Michigan State University, U.S.A.)

  • Aydin A. Cecen

    (Central Michigan University, U.S.A.)

  • Young-Wook Han

    (Michigan State University, U.S.A.)

Abstract

This article considers the use of the long memory volatility process, FIGARCH, in representing Deutschemark - US dollar spot exchange rate returns for both high and low frequency returns data. The FIGARCH model is found to be the preferred specification for both high frequency and daily returns data, with similar values of the long memory volatility parameter across frequencies, which is indicative of returns being generated by a self similar process. The BDS test for non-linearity is applied to the residuals of the model for the high frequency returns. No evidence is found to suggest that the procedure for filtering the high frequency returns to remove the intraday periodicity has induced any non-linearities in the residuals; and the FIGARCH specification is found to be adequate.

Suggested Citation

  • Richard T. Baillie & Aydin A. Cecen & Young-Wook Han, 2000. "High Frequency Deutsche Mark-US Dollar Returns: FIGARCH Representations and Non Linearities," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 247-267, September.
    • Handle: RePEc:mfj:journl:v:4:y:2000:i:3-4:p:247-267
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    References listed on IDEAS

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    Cited by:

    1. Richard T. Baillie & Young Wook Han, 2019. "Long Memory Volatility, Central Bank Intervention and Uncovered Interest Rate Parity in the 1920s Exchange Markets," Korean Economic Review, Korean Economic Association, vol. 35, pages 183-203.
    2. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    3. Uctum, Remzi & Renou-Maissant, Patricia & Prat, Georges & Lecarpentier-Moyal, Sylvie, 2017. "Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data," Review of Financial Economics, Elsevier, vol. 35(C), pages 43-56.
    4. Clifford M. Hurvich & Eric Moulines & Philippe Soulier, 2005. "Estimating Long Memory in Volatility," Econometrica, Econometric Society, vol. 73(4), pages 1283-1328, July.
    5. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    6. repec:ipg:wpaper:27 is not listed on IDEAS
    7. Morten Ørregaard Nielsen & Antoine L. Noël, 2020. "To infinity and beyond: Efficient computation of ARCH(\infty) models," Working Paper 1425, Economics Department, Queen's University.
    8. Carlos P. Barros & Luis A. Gil-Alana & Zhongfei Chen, 2016. "Exchange rate persistence of the Chinese yuan against the US dollar in the NDF market," Empirical Economics, Springer, vol. 51(4), pages 1399-1414, December.
    9. Ying Jiang & Shamim Ahmed & Xiaoquan Liu, 2017. "Volatility forecasting in the Chinese commodity futures market with intraday data," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 1123-1173, May.
    10. Gil-Alana, Luis A. & Carcel, Hector, 2020. "A fractional cointegration var analysis of exchange rate dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. Zhenjie Liang & Futian Weng & Yuanting Ma & Yan Xu & Miao Zhu & Cai Yang, 2022. "Measurement and Analysis of High Frequency Assert Volatility Based on Functional Data Analysis," Mathematics, MDPI, vol. 10(7), pages 1-11, April.
    12. Morten Ørregaard Nielsen & Antoine L. Noël, 2020. "To infinity and beyond: Efficient computation of ARCH(1) models," CREATES Research Papers 2020-13, Department of Economics and Business Economics, Aarhus University.
    13. repec:ipg:wpaper:2013-027 is not listed on IDEAS
    14. Guglielmo Maria Caporale & Luis Gil-Alana, 2012. "Long Memory and Volatility Dynamics in the US Dollar Exchange Rate," Multinational Finance Journal, Multinational Finance Journal, vol. 16(1-2), pages 105-136, March - J.
    15. Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
    16. Maheu John, 2005. "Can GARCH Models Capture Long-Range Dependence?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-43, December.
    17. Anagnostidis, Panagiotis & Emmanouilides, Christos J., 2015. "Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 473-487.

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    More about this item

    Keywords

    BDS test; correlation dimension; FIGARCH; high frequency data; intra day periodicity; volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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