Integrated Covariance Estimation using High-frequency Data in the Presence of Noise

By Valeri Voev, Asger Lunde. 2006

148 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/056a9b780599cfa9e8df2bced6ad14f7012a305b

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Citations in the corpus

Econometric Analysis of Vast Covariance Matrices Using Composite Realized Kernels and Their Application to Portfolio Choice (2016, result): “…recent studies, it has been confirmed that realized covariances computed over shorter fixed time periods underestimate the degree of dependence between assets (see, e.g., Renò 2003; Hayashi and Yoshida 2005; Voev and Lunde 2007; Griffin and Oomen 2011; Zhang 2011b; Barndorff-Nielsen et al. 2011).”
High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data (2010, unknown): “Voev and Lunde (2007) provided a bias correction procedure for the HY estimator to correct for the effect of the noise, but the estimator does not achieve consistency.”
Estimating Covariation: Epps Effect, Microstructure Noise (2011, background): “Other work investigating the combination of asynchronicity and microstructure noise includes Lunde and Voev (2007) and Griffin and Oomen (2007).”
REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOLATILITY (2012, unknown): “Estimators that are robust to noise and/or asynchronous observations have been proposed by Hayashi and Yoshida (2005), Voev and Lunde (2007), Griffin and Oomen (2011), Christensen et al. (2010), and Barndorff-Nielsen et al. (2011).”
Realized Volatility: A Review (2008, methodology): “His correction is in line with those proposed by Zhou (1996) and Hansen and Lunde (2006b).”
A Fourier transform method for nonparametric estimation of multivariate volatility (2009, background): “[39] prove that the estimator of [20] is biased in the presence of microstructure noise and its variance diverges as the number of observations increases.”
HAR Modeling for Realized Volatility Forecasting (2012, unknown): “…proposed in the literature: incorporate lead and lag cross returns in the estimator ([70], [32],[22], [9]), avoid any synchronization by directly using tick-by-tick data ([42],[54],[53],[67],[71],[72],[35]), multivariate realized kernel ([11]), and the mul-15 tivariate Fourier method ([68, 64]).”
Covariance measurement in the presence of non-synchronous trading and market microstructure noise (2011, unknown): “ing covariance structure, while Voev and Lunde (2005) use simulations to study the properties of the RC and”
Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading (2011, background): “Some recent econometric work on this topic includes Malliavin & Mancino (2002), Reno(2003), Martens (2003), Hayashi & Yoshida (2005), Bandi & Russell (2005), Voev & Lunde (2007), Griffin &Oomen (2009) and Large (2007).”
The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency (2011, background): “…(2005) have proposed a modification of the realized covariance which corrects for this effect; see also Large (2007), Griffin and Oomen (2008), Voev and Lunde (2007), Zhang (2011), Barndorff-Nielsen et al. (2008b), Kinnebrock and Podolskij (2008) and Aı̈t-Sahalia et al. (2010). volatility…”
VOLATILITY AND COVARIATION ESTIMATION WHEN MICROSTRUCTURE NOISE AND TRADING TIMES ARE ENDOGENOUS (2012, background): “Both lead to a highly biased behavior of na ve high frequency covariation measures, see [21], [ 33 ], [36].”
Pre-Averaging Estimators of the Ex-Post Covariance Matrix in Noisy Diffusion Models with Non-Synchronous Data (2010, unknown): “Additional work in this growing line of research includes Malliavin and Mancino (2002), Martens (2003), Ren`o (2003), Bandi and Russell (2005), Griﬃn and Oomen (2006), Large (2007), Voev and Lunde (2007), and Boudt, Croux, and Laurent (2008), among others.”
A blocking and regularization approach to high dimensional realized covariance estimation (2012, unknown): “Bandi, Russell, and Zhu (2008), Griffin and Oomen (2009), Martens (2006), Sheppard (2006), and Voev and Lunde (2007) study numerous alternative estimators in a bi-variate setting via optimal sampling or lead-lag estimation to obtain substantial efficiency gains.”