A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data

DOI10.1016/j.jeconom.2014.01.008zbMath1293.91196OpenAlexW2035342544MaRDI QIDQ2451774

Cheng Yong Tang, Cheng Liu

Publication date: 4 June 2014

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2014.01.008

zbMATH Keywords

quasi-maximum likelihoodhigh-frequency dataintegrated covariance matrixmicrostructure noises

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items (8)

Econometric analysis of multivariate realised QML: estimation of the covariation of equity prices under asynchronous trading ⋮ Sparse Kalman filtering approaches to realized covariance estimation from high frequency financial data ⋮ Optimal covariance matrix estimation for high-dimensional noise in high-frequency data ⋮ Estimating the quadratic covariation matrix from noisy observations: local method of moments and efficiency ⋮ Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading ⋮ Time endogeneity and an optimal weight function in pre-averaging covariance estimation ⋮ A rank test for the number of factors with high-frequency data ⋮ Asymptotics for the systematic and idiosyncratic volatility with large dimensional high-frequency data

Cites Work

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• Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors
• Discretization of processes.
• Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data
• Quasi-maximum likelihood estimation of volatility with high frequency data
• Estimating covariation: Epps effect, microstructure noise
• Ultra high frequency volatility estimation with dependent microstructure noise
• Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading
• Time series: theory and methods.
• Fourier series method for measurement of multivariate volatilities
• Vast volatility matrix estimation for high-frequency financial data
• A Fourier transform method for nonparametric estimation of multivariate volatility
• Microstructure noise in the continuous case: the pre-averaging approach
• Econometric analysis of multivariate realised QML: estimation of the covariation of equity prices under asynchronous trading
• Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach
• Large Volatility Matrix Inference via Combining Low-Frequency and High-Frequency Approaches
• Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise
• Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps
• Multi-Scale Jump and Volatility Analysis for High-Frequency Financial Data
• Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• Diffusions with measurement errors. I. Local Asymptotic Normality
• High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data
• A Tale of Two Time Scales

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