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Distinguishing short and long memory volatility specifications

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  • Shiuyan Pong
  • Mark B. Shackleton
  • Stephen J. Taylor

Abstract

Asset price volatility appears to be more persistent than can be captured by individual, short memory, autoregressive or moving average components. Fractional integration offers a very parsimonious and tempting formulation of this long memory property of volatility but other explanations such as structural models (aggregates of several autoregressive components) are possible. Given the ability of the latter to mimic the former, we investigate the extent to which it is possible to distinguish short from long memory volatility specifications. For a likelihood ratio test in the spectral domain, we investigate size and power characteristics by Monte Carlo simulation. Finally applying the same test to Sterling/Dollar returns, we draw conclusions about the minimum number of structural factors that must be present to mimic the long memory volatility properties that are empirically observed. Copyright The Author(s). Journal compilation Royal Economic Society 2008

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Bibliographic Info

Article provided by Royal Economic Society in its journal Econometrics Journal.

Volume (Year): 11 (2008)
Issue (Month): 3 (November)
Pages: 617-637

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Handle: RePEc:ect:emjrnl:v:11:y:2008:i:3:p:617-637

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Cited by:
  1. Julien Chevallier & Benoît Sévi, 2009. "On the Realized Volatility of the ECX CO2 Emissions 2008 Futures Contract: Distribution, Dynamics and Forecasting," Working Papers 2009.113, Fondazione Eni Enrico Mattei.
  2. Julien Chevallier & Benoît Sévi, 2011. "On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting," Annals of Finance, Springer, vol. 7(1), pages 1-29, February.

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