SciELO - Scientific Electronic Library Online

 
vol.25 número3A farm site development method: Creating a roadmap towards site saturationPrioritising maintenance improvement opportunities in Physical Asset Management índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Em processo de indexaçãoSimilares em Google

Compartilhar


South African Journal of Industrial Engineering

versão On-line ISSN 2224-7890
versão impressa ISSN 1012-277X

Resumo

EBRAHIMI, S.B.  e  OLYAEE, F.R.. A new multivariate nonlinear model to handle the volatility transmission. S. Afr. J. Ind. Eng. [online]. 2014, vol.25, n.3, pp.140-153. ISSN 2224-7890.

Price volatility of stocks is an important issue in stock markets. It should also be taken into account that the stochastic nature of volatility affects decision-makers' minds to a great extent. Therefore, predicting price volatility could help them make proper decisions. In this paper, a new multivariate fractionally integrated generalised autoregressive conditional heteroscedasticity (MFIGARCH) model is proposed to handle the price volatility in stocks. In this model, a long-term parameter is considered and estimated along with other parameters. In estimating the parameters of this nonlinear model, the maximum likelihood estimation method, which could be solved by standard econometric packages, is applied. However, these packages are no longer efficient when the size of the model increases. Thus meta-heuristic approaches, which stochastically seek optimal or near-optimal solutions, were used. In this paper, the well-known Particle Swarm Optimisation (PSO) meta-heuristic method is used for solving the suggested multivariate FIGARCH model. Hence the main objective of this paper is to introduce a new model for addressing the stock price volatility (i.e., the development of FIGARCH to create the MFIGARCH model) and to apply an efficient estimation method (i.e. PSO) for finding the parameters of the problem.

        · resumo em Africaner     · texto em Inglês

 

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons