PSO based time series models applied in exchange rate forecasting for business performance management

Jui Fang Chang, Yueh Min Huang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This research used the PSO algorithm to develop three new models, PSOGARCH, PSOEGARCH, and PSOGJR-GARCH, for improving business performance management. The tracking error methods are compared among the models in order to obtain a forecasting model with better performance. The three traditional time series models, GARCH, EGARCH, and GJR-GARCH, are used to undertake foreign exchange forecasting, and the results of these are compared to those of PSOGARCH, PSOEGARCH, and PSOGJR-GARCH models. The PSOGJR-GARCH model had the smallest error and the best forecasting ability, followed by the PSOEGARCH and PSOGARCH models, with the traditional GARCH models having the worst performance.

Original languageEnglish
Pages (from-to)417-434
Number of pages18
JournalElectronic Commerce Research
Volume14
Issue number3
DOIs
Publication statusPublished - 2014 Dec 9

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Economics, Econometrics and Finance (miscellaneous)

Fingerprint Dive into the research topics of 'PSO based time series models applied in exchange rate forecasting for business performance management'. Together they form a unique fingerprint.

  • Cite this