BOOTSTRAPPING REALIZED VOLATILITY

By Sílvia Gonçalves, Nour Meddahi. 2009

131 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/ae0d4e9caaf9f5bec5fd5044e5fb697e99bd0d15

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Citations in the corpus

Integrated volatility and round-off error (2009, background): “In this setting, a common convergent estimator of the integrated volatility, with rate n−1/2 and feasible asymptotic theory, is given by the realized volatility, that is, for the absolute integrated volatility n∑ i=1 (Xi/n −X(i−1)/n)2 and for the relative integrated volatility n∑ i=1 (log(Xi/n)− log”
Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error (2008, methodology): “Gonçalves and Meddahi (forthcoming) have recently proposed a bootstrap methodology for conducting inference under the assumption of no noise and shown that it has good small sample performance in their model. Zhang et al. (2005b) have developed Edgeworth expansions for the TSRV estimator, and itwoul”
Moving Average-Based Estimators of Integrated Variance (2008, unknown): “refinements are derived in Gonçalves and Meddahi (2005). While RV (m) ∗ is the ideal estimator, it is not a feasible estimator, because p∗ is latent.”
Bootstrap validity for the score test when instruments may be weak (2009, background): “Guggenberger and Smith (2003), Stock and Wright (2000), and Brown and Newey (2004).”
Edgeworth Expansions for Realized Volatility and Related Estimators (2011, unknown): “The latter has been developed in the no-noise case by Gonçalves and Meddahi (2009).”
Bootstrapping realized multivariate volatility measures (2010, background): “We end this section with a discussion of the second order accuracy of the i.i.d. bootstrap in this context.”
Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗ (2008, methodology): “The setting of confidence intervals using bootstrapping has been considered by Goncalves and Meddahi (2005) and Kalnina and Linton (2007).”
High frequency market microstructure noise estimates and liquidity measures (2009, background): “Recently, Goncalves and Meddahi (2005) have developed an Edgeworth expansion for the basic RV estimator when there is no noise.”
Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading (2011, methodology): “land & Zhang (2006), Goncalves & Meddahi (2008) , Mykland & Zhang (2008) and Jacod & Protter”
Exploiting the errors: A simple approach for improved volatility forecasting (2016, unknown): “…arguments that RV follows an ARMA(1,1) model, with AR-parameter equal to φ1 and (invertible) MA-parameter equal to, θ1 = −σ 2u − 1+φ21 σ 2η+ σ 4u +2 1+φ21 σ 2u σ 2 η+ 1−φ21 2 σ 4η 2φ1σ 2η , (7) 6 A formal theoretical justification for this approach is provided byAndersen et al. (2003).”
Box–Cox transforms for realized volatility (2011, background): “Across the models considered in this paper, one of our conclusions is that β = −1 (i.e. relying on the inverse of realized volatility also known as realized precision) is the best choice if we want to control the coverage probability of 95% level confidence intervals for integrated volatility.”
Outlyingness weighted covariation (2011, unknown): “Similar findings for the RCov have been documented in Barndorff-Nielsen and Shephard (2004a, 2005), Dovonon et al. (2011), Gonçalves and Meddahi (2009), Huang and Tauchen (2006), Veraart (2010) and Zhang et al. (2011), among others.”
Robust estimation of intraweek periodicity in volatility and jump detection (2011, background): “A topic of future research is to explore the potential gains in accuracy of using these robust periodicity estimates for forecasting intraday volatility (Taylor and Xu, 1997) or for bootstrapping realized volatility (Gonçalves and Meddahi, 2008).”
Does Realized Skewness Predict the Cross-Section of Equity Returns? (2015, background): “…true price pt: Several studies use Monte Carlo simulations to investigate the properties of realized variance estimators when allowing for market microstructure noise, see for instance Andersen, Bollerslev, and Meddahi (2011), Gonçalves and Meddahi (2009), and Ait-Sahalia and Yu (2009).”
Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment (2017, unknown): “In particular, Gon¸calves and Meddahi (2009) propose the wild bootstrap for realized variance, in a framework where the asset price is observed without error (see also Hounyo, 2019).”
Inference for Continuous Semimartingales Observed at High Frequency: A General Approach (2007, unknown): “As noted, our device is comparable to the use of equivalent martingale measures in options pricing theory (Ross (1976), Harrison and Kreps (1979), Harrison and Pliska (1981), see also Duffie (1996)) in that it affords a convenient probability distribution with which to make computations.”