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Tracing the Source of Long Memory in Volatility

Author

Listed:
  • Rohit Deo

    (New York University)

  • Mengchen Hsieh

    (New York University)

  • Clifford Hurvich

    (New York University)

Abstract

We study the effects of trade duration properties on dependence in counts (number of transactions) and thus on dependence in volatility of returns. A return model is established to link counts and volatility. We present theorems as well as a conjecture relating properties of durations to long memory in counts and thus in volatility. We then apply several parametric duration models to empirical trade durations and discuss our findings in the light of the theorems and conjecture.

Suggested Citation

  • Rohit Deo & Mengchen Hsieh & Clifford Hurvich, 2005. "Tracing the Source of Long Memory in Volatility," Econometrics 0501005, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0501005
    Note: Type of Document - pdf; pages: 38
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    References listed on IDEAS

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    Cited by:

    1. Rohit Deo & Meng-Chen Hsieh & Clifford M. Hurvich & Philippe Soulier, 2007. "Long Memory in Nonlinear Processes," Papers 0706.1836, arXiv.org.
    2. Rohit Deo & Clifford Hurvich & Philippe Soulier & Yi Wang, 2005. "Propagation of Memory Parameter from Durations to Counts," Econometrics 0511010, University Library of Munich, Germany.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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