Singular Conditional Autoregressive Wishart Model for Realized Covariance Matrices
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Publication:6190695
DOI10.1080/07350015.2022.2075370OpenAlexW3209673146WikidataQ114100315 ScholiaQ114100315MaRDI QIDQ6190695
Taras Bodnar, Farrukh Javed, Gustav Alfelt, Joanna Tyrcha
Publication date: 6 March 2024
Published in: Journal of Business & Economic Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07350015.2022.2075370
high-dimensional datarealized covariance matrixcovariance targetingstock co-volatilitytime series matrix-variate model
Cites Work
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- Estimation of the global minimum variance portfolio in high dimensions
- The Model Confidence Set
- The Wishart autoregressive process of multivariate stochastic volatility
- Estimating the quadratic covariation matrix from noisy observations: local method of moments and efficiency
- Dominating estimators for minimum-variance portfolios
- Ultra high frequency volatility estimation with dependent microstructure noise
- The conditional autoregressive Wishart model for multivariate stock market volatility
- Properties of the singular, inverse and generalized inverse partitioned Wishart distributions
- High frequency market microstructure noise estimates and liquidity measures
- Singular Wishart and multivariate beta distributions
- Recent advances in shrinkage-based high-dimensional inference
- High-dimensional minimum variance portfolio estimation based on high-frequency data
- Econometric analysis of multivariate realised QML: estimation of the covariation of equity prices under asynchronous trading
- A test for the rank of the volatility process: the random perturbation approach
- Multivariate rotated ARCH models
- High dimensional minimum variance portfolio estimation under statistical factor models
- Distribution of the product of a singular Wishart matrix and a normal vector
- Statistical Inference for High-Dimensional Global Minimum Variance Portfolios
- Microstructure Noise, Realized Variance, and Optimal Sampling
- EXcess Idle Time
- The Econometrics of Ultra-high-frequency Data
- Modeling and forecasting realized covariance matrices with accounting for leverage
- Goodness-of-fit tests for centralized Wishart processes
- Multivariate variance targeting in the BEKK-GARCH model
- Statistical Inference for the Expected Utility Portfolio in High Dimensions
- Tests for the Weights of the Global Minimum Variance Portfolio in a High-Dimensional Setting
- Modeling and Forecasting Realized Volatility
- Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
- Multivariate Stochastic Volatility: A Review
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