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DM-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies

Author

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  • Torben G. Andersen
  • Tim Bollerslev
Abstract
This paper characterizes the volatility in the DM-dollar foreign exchange market using an annual sample of five-minute returns. Our modeling approach explicitly captures the pronounced intraday activity patterns, the strong macroeconomic announcement effects, and the volatility persistence, or ARCH effects, familiar from lower frequency returns. The different features are separately quantified and shown, in conjunction, to account for a substantial fraction of the realized return variability, both at the intradaily and daily levels. Moreover, we demonstrate how the high frequency returns, when properly modeled, constitute an extremely valuable and vastly underutilized resource for better understanding the volatility dynamics at the daily or lower frequencies.

Suggested Citation

  • Torben G. Andersen & Tim Bollerslev, 1996. "DM-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," NBER Working Papers 5783, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:5783
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    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.
    2. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    3. Melvin, Michael & Yin, Xixi, 2000. "Public Information Arrival, Exchange Rate Volatility, and Quote Frequency," Economic Journal, Royal Economic Society, vol. 110(465), pages 644-661, July.
    4. Michael J. Fleming & Eli M. Remolona, 1997. "What moves the bond market?," Economic Policy Review, Federal Reserve Bank of New York, vol. 3(Dec), pages 31-50.
    5. Magdalena E. Sokalska & Ananda Chanda & Robert F. Engle, 2005. "High Frequency Multiplicative Component Garch," Computing in Economics and Finance 2005 409, Society for Computational Economics.
    6. Michael J. Fleming & Eli M. Remolona, 1996. "Price formation and liquidity in the U.S. treasuries market: evidence from intraday patterns around announcements," Research Paper 9633, Federal Reserve Bank of New York.
    7. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    8. David McMillan & Alan Speight, 2006. "Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(13), pages 959-972.
    9. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    10. Neil Beattie & Jean-François Fillion, 1999. "An Intraday Analysis of the Effectiveness of Foreign Exchange Intervention," Staff Working Papers 99-4, Bank of Canada.
    11. M. D. Mckenzie & R. D. Brooks, 2003. "The role of information in Hong Kong individual stock futures trading," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 123-131.

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    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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