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Fractional Dynamics in Japanese Financial Time Series

Author

Listed:
  • John Barkoulas

    () (Boston College)

  • Christopher F. Baum

    () (Boston College)

Abstract

Using the spectral regression and Gaussian semiparametric methods of estimating the long-memory parameter, we test for fractional dynamic behavior in a number of important Japanese financial time series: spot exchange rates, forward exchange rates, stock prices, currency forward premia, Euroyen deposit rates, and the Euroyen term premium. Stochastic long memory is established as a feature of the currency forward premia, Euroyen deposit rates, and Euroyen term premium series. The martingale model cannot be rejected for the spot, forward, and stock price series.

Suggested Citation

  • John Barkoulas & Christopher F. Baum, 1996. "Fractional Dynamics in Japanese Financial Time Series," Boston College Working Papers in Economics 334., Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:334
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    References listed on IDEAS

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    Cited by:

    1. Jamdee, Sutthisit & Los, Cornelis A., 2007. "Long memory options: LM evidence and simulations," Research in International Business and Finance, Elsevier, vol. 21(2), pages 260-280, June.
    2. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    3. Chaker Aloui & Duc Khuong Nguyen, 2014. "On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach," Applied Economics, Taylor & Francis Journals, vol. 46(22), pages 2611-2622, August.
    4. Assaf, A., 2006. "Dependence and mean reversion in stock prices: The case of the MENA region," Research in International Business and Finance, Elsevier, vol. 20(3), pages 286-304, September.
    5. Sutthisit Jamdee & Cornelis A. Los, 2005. "Multifractal Modeling of the US Treasury Term Structure and Fed Funds Rate," Finance 0502021, EconWPA.
    6. Guangxi Cao, 2012. "Time-Varying Effects of Changes in the Interest Rate and the RMB Exchange Rate on the Stock Market of China: Evidence from the Long-Memory TVP-VAR Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(0), pages 230-248, July.
    7. Ellis, Craig & Wilson, Patrick, 2004. "Another look at the forecast performance of ARFIMA models," International Review of Financial Analysis, Elsevier, vol. 13(1), pages 63-81.
    8. Cajueiro, Daniel O. & Tabak, Benjamin M., 2010. "Fluctuation dynamics in US interest rates and the role of monetary policy," Finance Research Letters, Elsevier, vol. 7(3), pages 163-169, September.
    9. Guangxi Cao, 2012. "Time-Varying Effects of Changes in the Interest Rate and the RMB Exchange Rate on the Stock Market of China: Evidence from the Long-Memory TVP-VAR Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(0), pages 230-248, July.
    10. Choudhry, Taufiq, 2001. "Inflation and rates of return on stocks: evidence from high inflation countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 11(1), pages 75-96, March.

    More about this item

    Keywords

    Time series; long memory; spectral regression; Gaussian semiparametric method;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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