Sheng, XinGupta, RanganSalisu, Afees A.Bouri, Elie2022-08-162022-08-162022-03Sheng, X., Gupta, R., Salisu, A.A. et al. 2022, 'OPEC news and exchange rate forecasting using dynamic Bayesian learning', Finance Research Letters, vol. 45, art. 102125, pp. 1-7, doi : 10.1016/j.frl.2021.102125.1544-6123 (print)1544-6131 (online)10.1016/j.frl.2021.102125https://repository.up.ac.za/handle/2263/86793We 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.en© 2021 Elsevier Inc. All rights reserved. Notice : this is the author’s version of a work that was submitted for publication in Finance Research Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms are not reflected in this document. A definitive version was subsequently published in Finance Research Letters, vol. 45, art. 102125, pp. 1-7, 2022. doi : 10.1016/j.frl.2021.102125.Organization of the petroleum exporting countries (OPEC)Opec newsExchange rate forecastingBayesian dynamic learningPreprint Article