OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning

Xin Sheng (), Rangan Gupta, Afees Salisu and Elie Bouri ()
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Xin Sheng: Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, CM1 1SQ, United Kingdom

No 202101, Working Papers from University of Pretoria, Department of Economics

Abstract: 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.

Keywords: OPEC News; Exchange Rate Forecasting; Bayesian Dynamic Learning (search for similar items in EconPapers)
JEL-codes: C32 C53 Q41 (search for similar items in EconPapers)
Pages: 14 pages
Date: 2021-01
New Economics Papers: this item is included in nep-for and nep-ore
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Citations: View citations in EconPapers (1)

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