A theoretical comparison between integrated and realized volatility

By Nour Meddahi. 2002

303 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/65f480060d3a0be2208e8351f37547dd6484339a

Citations in the corpus

• Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities (2005, unknown): “The exact form of the measurement error will, of course, depend on the assumed model structure (see, e.g., Meddahi, 2002, and Barndorff-Nielsen and Shephard, 2002a), but it will generally result in a downward bias in the estimated degree of predictability obtained through any forecast evaluation…”
• Realized volatility forecasting and market microstructure noise (2011, unknown): “In the absence of any drift, E[r∗(h)t+ih] = 0 and V ar[r ∗(h) t+ih] = a0h (see, e.g., Meddahi, 2002b).”
• A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data (2005, unknown): “The RV is interesting because it can be used as a proxy for theoretical quantities such as the integrated variance (IV), see Andersen & Bollerslev (1998), Barndorff-Nielsen & Shephard (2002a, 2002b), and Meddahi (2002). However, in order to calculate a RV that spans a full day one needs high-frequen”
• Estimating quadratic variation using realized variance (2002, unknown): “See also the recent important contribution by Meddahi (2002).”
• ESTIMATING THE PERSISTENCE AND THE AUTOCORRELATION FUNCTION OF A TIME SERIES THAT IS MEASURED WITH ERROR (2013, unknown): “See also Meddahi (2001), Meddahi (2002), Andersen et al. (2004), and Andersen, Bollerslev, and Meddahi (2011).”
• Realized Volatility: A Review (2008, unknown): “Based on the theoretical results of Barndorff-Nielsen and Shephard (2002), Andersen et al. (2003), and Meddahi (2002), several recent studies have documented the properties of realized volatilities constructed from high frequency data.”
• Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions? (2011, unknown): “…(1998), Andersen, Bollerslev, Diebold, and Labys (2001), Andersen, Bollerslev, Diebold, and Ebens (2001), Barndorff-Nielsen and Shephard (2002), and Meddahi (2002), among others,1 have established the theoretical and empirical properties of the estimation of quadratic variation for a broad class…”
• Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes (2005, unknown): “…process, see for instance Andersen, Bollerslev, Diebold, and Labys (2003), Bandi and Russell (2004a,b), Barndorff-Nielsen and Shephard (2004a) , BarndorffNielsen, Hansen, Lunde, and Shephard (2004), Hansen and Lunde (2004), Meddahi (2002), Zhang (2004), Zhang, Mykland, and Äıt-Sahalia (2004).”
• Properties of Realized Variance Under Alternative Sampling Schemes (2006, unknown): “Barndorff-Nielsen and Shephard, 2004b; Meddahi, 2002 ).”
• Integrated Covariance Estimation using High-frequency Data in the Presence of Noise (2006, unknown): “Specifically, we simulate two univariate price processes p∗A(t) and p∗B(t) by the following stochastic differential equations with leverage effect, see for example, Meddahi (2002):”
• Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility (2003, unknown): “12 Note that while the relative magnitude of the R(2)’s for a given volatility series are directly comparable across the two models, as discussed in Andersen, Bollerslev and Meddahi (2002), the measurement errors in the left-hand-side realized volatility measures result in a systematic downward bias”
• Realized Variance and Market Microstructure Noise (2006, unknown): “A feasible asymptotic distribution heory of realized variance (in relation to integrated variance) is established in Barndorff-Nielsen & Shephard (2002), see also Meddahi (2002) and Gonçalves & Meddahi (2005).”
• Moving Average-Based Estimators of Integrated Variance (2008, unknown): “The realized variance of p∗ is defined by RV (m)∗ ≡ m∑ i=1 y∗2i ,m , and it follows that RV (m)∗ is consistent for the IV as m → ∞, and i ,m → 0; see, e.g., Barndorff-Nielsen and Shephard (2002), see also Meddahi (2002) for the relation between RV (m)∗ and IV.”