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Foreign exchange, fractional cointegration and the implied-realized volatility relation

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  • Kellard, Neil
  • Dunis, Christian
  • Sarantis, Nicholas
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    Abstract

    Almost all relevant literature has characterized implied volatility as a biased predictor of realized volatility. In this paper we provide new time series techniques to investigate the validity of this finding in several foreign exchange options markets, including the Euro market. First, we develop a new fractional cointegration test that is shown to be robust to both stationary and non-stationary regions. Second, we employ both intra-day and daily data to measure realized volatility in order to assess the relevance of data frequency in resolving the bias. Third, we use data on implied volatility traded on the market. In contrast to previous studies, we show that the frequency of data used for measuring realized volatility within a fractionally cointegrating framework is important for the results of unbiasedness tests. Significantly, for many popular exchange rates, the use of intra-day rather than daily data affects the emergence of a different bias, as the possibility of a fractionally integrated risk premium admits itself!

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Banking & Finance.

    Volume (Year): 34 (2010)
    Issue (Month): 4 (April)
    Pages: 882-891

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    Handle: RePEc:eee:jbfina:v:34:y:2010:i:4:p:882-891

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    Web page: http://www.elsevier.com/locate/jbf

    Related research

    Keywords: Market efficiency Options markets Fractional cointegration Narrow band least squares Bootstrap Traded volatility Intra-day data;

    References

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    Cited by:
    1. Chiu, Mei Choi & Wong, Hoi Ying, 2011. "Mean-variance portfolio selection of cointegrated assets," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1369-1385, August.
    2. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    3. Evarist Stoja & Richard D. F. Harris & Fatih Yilmaz, 2010. "A Cyclical Model of Exchange Rate Volatility," Bristol Economics Discussion Papers 10/618, Department of Economics, University of Bristol, UK.
    4. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    5. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    6. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2013. "Volatility co-movements: a time scale decomposition analysis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13111, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".

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