Capturing measurement error bias in volatility forecasting by realized GARCH models

DOI10.1007/978-3-031-15885-8_10MaRDI QIDQ6613594

Giuseppe Storti, Richard H. Gerlach, Antonio Naimoli

Publication date: 2 October 2024

zbMATH Keywords

jumpsrealized volatilityheteroskedasticityrealized GARCHattenuation biasrealized quarticity

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• The Model Confidence Set
• Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White
• Financial econometric analysis at ultra-high frequency: Data handling concerns
• Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes
• Jump-robust volatility estimation using nearest neighbor truncation
• Volatility forecast comparison using imperfect volatility proxies
• Microstructure noise in the continuous case: the pre-averaging approach
• Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• A Tale of Two Time Scales
• Exploiting the errors: a simple approach for improved volatility forecasting

This page was built for publication: Capturing measurement error bias in volatility forecasting by realized GARCH models