Modelling and Forecasting Stock Volatility and Return: A New Approach Based on Quantile Rogers-Satchell Volatility Measure With Asymmetric Bilinear CARR Model

41 Pages Posted: 18 Feb 2020

See all articles by Shay Kee Tan

Shay Kee Tan

University of Malaya (UM) - Institute of Mathematical Sciences

Jennifer Chan

The University of Sydney - School of Mathematics and Statistics

Kok Haur Ng

University of Malaya

Date Written: January 22, 2020

Abstract

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to ensure robustness and correct the downward bias of RS measure with an additive term. Moreover scaling factors are provided for different interquantile ranges to ensure unbiasedness. Simulation studies confirm the efficiency of QRS measure relative to the intraday (open-to-close) squared returns and RS measures in the presence of intraday extreme prices. To smooth out the noises, QRS measures are fitted to the conditional autoregressive range (CARR) model with different asymmetric mean functions and error distributions. These fitted volatilities are then incorporated into return models to capture the heteroskedasticity of returns. Different value-at-risk (VaR) and conditional VaR return forecasts are provided and tested. Results based on Standard and Poor 500 and Dow Jones Industrial Average indices show that volatility estimates using QRS measures, asymmetric bilinear mean function and generalised beta type II distribution provide the best in-sample model-fit and out-of-sample forecast. For return models, the constant mean structure with Student-t errors and QRS volatility estimates provides the best in-sample fit. Different performance measures including Kupiec test for VaRs based on the best return model are evaluated to confirm the accuracy of the VaR forecasts.

Keywords: Volatility, Range-based, Quantile Rogers-Satchell, CARR Model, Value-at-Risk

JEL Classification: C13, C22, C53, C55, G17

Suggested Citation

Tan, Shay Kee and Chan, Jennifer and Ng, Kok Haur, Modelling and Forecasting Stock Volatility and Return: A New Approach Based on Quantile Rogers-Satchell Volatility Measure With Asymmetric Bilinear CARR Model (January 22, 2020). Available at SSRN: https://ssrn.com/abstract=3523783 or http://dx.doi.org/10.2139/ssrn.3523783

Shay Kee Tan

University of Malaya (UM) - Institute of Mathematical Sciences ( email )

Kuala Lumpur, Kuala Lumpur 50603
Malaysia

Jennifer Chan

The University of Sydney - School of Mathematics and Statistics ( email )

Sydney, New South Wales 2006
Australia

Kok Haur Ng (Contact Author)

University of Malaya ( email )

Kuala Lumpur, Kuala Lumpur 50603
Malaysia
+60379674338 (Phone)
+60379674143 (Fax)

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