Title

Efficient modelling and forecasting with range based volatility models and its application

Document Type

Journal Article

Publisher

Elsevier Inc.

Place of Publication

United Kingdom

School

School of Business and Law

Comments

Originally published as: Ng, K. H., Peiris, S., So-kuen-Chan, J., Allen, D., & Ng, K. H. (2017). Efficient Modelling & Forecasting with range based volatility models and application. 42(November 2017), 448-460. Article available here

Abstract

This paper considers an alternative method for fitting CARR models using the combined estimating functions (CEF) by showing its usefulness in applications in economics and quantitative finance. The associated information matrix for corresponding new estimates is derived to calculate the standard errors. Extensive simulation study is carried out to demonstrate its superiority relative to two other competitors: the linear estimating functions (LEF) and the maximum likelihood (ML). Results show that the CEF method is more efficient than the LEF and ML methods when the error distribution is mis-specified. Applying a real data set from financial market, we illustrate the applicability of the CEF method in practice and report some reliable forecast values for minimizing the risk in decision making process.

DOI

10.1016/j.najef.2017.08.009

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