Alhagyan, Mohammed and Misiran, Masnita and Omar, Zurni (2020) Efficient estimators for geometric fractional brownian motion perturbed by fractional Ornstein-Uhlenbeck process. Advances and Applications in Statistics, 62 (2). pp. 203-226. ISSN 09723617

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Abstract

This paper discusses an enhanced model of geometric fractional Brownian motion where its volatility is assumed to be stochastic volatility model obey fractional Ornstein-Uhlenbeck process. The method of estimation for all parameters in this model are derived. After, simulation experiments are conducted to examine the performance of the proposed estimators. The result shows that the proposed method provides efficient estimates for the parameters. Thus, the proposed model is promising and can apply in real financial environments.

Item Type:	Article
Uncontrolled Keywords:	geometric fractional Brownian motion, fractional Ornstein-Uhlenbeck process, long memory stochastic volatility, innovation algorithm, constraint transcription method, segmentation.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Quantitative Sciences
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	25 Nov 2020 00:59
Last Modified:	25 Nov 2020 00:59
URI:	https://repo.uum.edu.my/id/eprint/27914

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