Modelling and forecasting stock volatility and return: a new approach based on quantile Rogers-Satchell volatility measure with asymmetric bilinear CARR model
Document Type
Article
Publication Date
6-30-2022
Abstract
This paper proposes quantile Rogers-Satchell (QRS) measure to ensure robustness to intraday extreme prices. We add an efficient term to correct the downward bias of Rogers-Satchell (RS) measure and provide scaling factors for different interquantile range levels to ensure unbiasedness of QRS. Simulation studies confirm the efficiency of QRS measure relative to the intraday squared returns and RS measures in the presence of extreme prices. To smooth out noises, QRS measures are fitted to the CARR model with different asymmetric mean functions and error distributions. By comparing to two realised volatility measures as proxies for the unobserved true volatility, results from Standard and Poor 500 and Dow Jones Industrial Average indices show that QRS estimates using asymmetric bilinear mean function provide the best in-sample model fit based on two robust loss functions with heavier penalty for under-prediction. These fitted volatilities are then incorporated into return models to capture the heteroskedasticity of returns. Model with a constant mean, Student-t errors and QRS estimates gives the best in-sample fit. Different value-at-risk (VaR) and conditional VaR forecasts are provided based on this best return model. Performance measures including Kupiec test for VaRs are evaluated to confirm the accuracy of the VaR forecasts.
Keywords
CARR model, Quantile rogers-satchell, Range-based, Value-at-risk, Volatility
Divisions
MathematicalSciences
Funders
Ministry of Higher Education (MoHE), Malaysia [Grant No:FP041-2017A],Ministry of Higher Education (MoHE), Malaysia [Grant No:FRGS/1/2017/STG06/UM/2019],Universiti Malaya [Grant No:PG037-2016A]
Publication Title
Studies In Nonlinear Dynamics and Econometrics
Volume
26
Issue
3
Publisher
Walter De Gruyter GMBH
Publisher Location
GENTHINER STRASSE 13, D-10785 BERLIN, GERMANY