Modelling and forecasting stock volatility and return: a new approach based on quantile Rogers-Satchell volatility measure with asymmetric bilinear CARR model

DOI10.1515/snde-2019-0101OpenAlexW3166732506MaRDI QIDQ2700553

Shay Kee Tan, Kok-Haur Ng, Jennifer So-Kuen Chan

Publication date: 27 April 2023

Published in: Studies in Nonlinear Dynamics and Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/snde-2019-0101

zbMATH Keywords

value-at-riskvolatilityrange-basedCARR modelquantile Rogers-Satchell

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Cites Work

• Measuring volatility with the realized range
• Realized range-based estimation of integrated variance
• Asymmetric GARCH processes featuring both threshold effect and bilinear structure
• The economic value of volatility timing using a range-based volatility model
• Volatility forecast comparison using imperfect volatility proxies
• Volatility forecasting using threshold heteroskedastic models of the intra-day range
• Estimating variance from high, low and closing prices
• BL-GARCH models and asymmetries in volatility
• Generalized autoregressive conditional heteroscedasticity
• A Bayesian conditional autoregressive geometric process model for range data
• Efficient estimation of financial risk by regressing the quantiles of parametric distributions: an application to CARR models
• Coherent Measures of Risk
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Regression Quantiles
• The Distribution of Realized Exchange Rate Volatility

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