OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning

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.

The Relationship between Oil Prices and Exchange Rate: A Systematic Literature Review

“…The author linked the relationship with some macroeconomic events and further found the Volatility spillover from the developed markets to the Indian market. Sheng (2021) explored the linkage between the exchange rate of G10 countries with the newspaper count index of the petroleum exporting countries(OPEC) organization by applying a Bayesian inference methodology and various vector autoregressive models on monthly data from 1996 to 2020. Chuvakhina et al (2021) studied the exchange rate movement concerning the dollar in OPEC countries.…”