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ARMA representation of integrated and realized variances

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Author Info
Nour Meddahi
Abstract

This paper derives the ARMA representation of integrated and realized variances when the spot variance depends linearly on two autoregressive factors, i.e. SR-SARV(2) models. This class of processes includes affine, GARCH diffusion, and CEV models, as well as the eigenfunction stochastic volatility and the positive Ornstein--Uhlenbeck models. We also study the leverage effect case, and the relationship between the weak GARCH representation of returns and the ARMA representation of realized variances. Finally, various empirical implications of these ARMA representations are considered. We find that it is possible that some parameters of the ARMA representation are negative. Hence, the positiveness of the expected values of integrated or realized variances is not guaranteed. We also find that for some frequencies of observations, the continuous time model parameters may be weakly or not identified through the ARMA representation of realized variances. Copyright Royal Economic Society, 2003

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

Volume (Year): 6 (2003)
Issue (Month): 2 (December)
Pages: 335-356
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Handle: RePEc:ect:emjrnl:v:6:y:2003:i:2:p:335-356

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  1. Francois-Éric Racicot & Raymond Théoret & Alain Coen, 2006. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," RePAd Working Paper Series UQO-DSA-wp152006, Département des sciences administratives, UQO. [Downloadable!]
    Other versions:
  2. Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  3. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics. [Downloadable!]
  4. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics. [Downloadable!]
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