A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: An Application to High-Frequency Covariance Dynamics
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Publication:6617813
DOI10.1080/07350015.2020.1739530zbMath1547.62642MaRDI QIDQ6617813
Fulvio Corsi, Giacomo Bormetti, Giuseppe Buccheri, Fabrizio Lillo
Publication date: 11 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
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Cites Work
- Unnamed Item
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- The Model Confidence Set
- Accounting for missing values in score-driven time-varying parameter models
- On covariance estimation of non-synchronously observed diffusion processes
- Generalized autoregressive conditional heteroscedasticity
- Econometric analysis of multivariate realised QML: estimation of the covariation of equity prices under asynchronous trading
- Dynamic Models for Volatility and Heavy Tails
- Conditional Heteroskedasticity in Asset Returns: A New Approach
- Evaluating Volatility and Correlation Forecasts
- Realized kernels in practice: trades and quotes
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
- Filtering With Heavy Tails
- A closed-form formula characterization of the Epps effect
- Information-theoretic optimality of observation-driven time series models for continuous responses
- Analysis of Financial Time Series
- Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads
- Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence
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