Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI

Kho Chia Chen, Arifah Bahar, Ibrahim Lawal Kane, Chee Ming Ting, Haliza Abd Rahman

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

4 Citations (Scopus)

Abstract

In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.

Original languageEnglish
Title of host publication2nd ISM International Statistical Conference 2014, ISM 2014
Subtitle of host publicationEmpowering the Applications of Statistical and Mathematical Sciences
EditorsNor Aida Zuraimi Md Noar, Roslinazairimah Zakaria, Wan Nur Syahidah Wan Yusoff, Mohd Sham Mohamad, Mohd Rashid Ab Hamid
PublisherAmerican Institute of Physics
Pages73-79
Number of pages7
ISBN (Electronic)9780735412811
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventISM International Statistical Conference 2014 - Kuantan, Pahang, Malaysia
Duration: 12 Aug 201414 Aug 2014
Conference number: 2nd
https://aip.scitation.org/toc/apc/1643/1 (Proceedings)

Publication series

NameAIP Conference Proceedings
Volume1643
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceISM International Statistical Conference 2014
Abbreviated titleISM 2014
CountryMalaysia
CityKuantan, Pahang
Period12/08/1414/08/14
Internet address

Keywords

  • Fractional Ornstein-Uhlenbeck model
  • Hurst exponent
  • Least square estimator
  • Long memory stochastic volatility
  • OLS-based CUSUM test
  • Quadratic generalized variations

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