Anglia Ruskin Research Online (ARRO)
Browse

OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning

Download (897.26 kB)
journal contribution
posted on 2023-08-30, 19:42 authored by Xin Sheng, Rangan Gupta, Afees A. Salisu, Elie Bouri
We consider whether a newspaper article count index related to the organization of the petroleum exporting countries (OPEC), which rises in response to important OPEC meetings and events connected with OPEC production levels, contains predictive power for the foreign exchange rates of G10 countries. The applied Bayesian inference methodology synthesizes a wide array of established approaches to modelling exchange rate dynamics, whereby various vector-autoregressive models are considered. Monthly data from 1996:01 to 2020:08 (given an in-sample of 1986:02 to 1995:12), shows that incorporating the OPEC news-related index into the proposed methodology leads to statistical gains in out-of-sample forecasts.

History

Refereed

  • Yes

Volume

45

Page range

102125

Publication title

Finance Research Letters

ISSN

1544-6123

Publisher

Elsevier

File version

  • Accepted version

Language

  • eng

Legacy posted date

2022-03-10

Legacy creation date

2022-03-10

Legacy Faculty/School/Department

Faculty of Business & Law

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC