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OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning

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  • Sheng, Xin
  • Gupta, Rangan
  • Salisu, Afees A.
  • Bouri, Elie

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.

Suggested Citation

  • Sheng, Xin & Gupta, Rangan & Salisu, Afees A. & Bouri, Elie, 2022. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Finance Research Letters, Elsevier, vol. 45(C).
    • Handle: RePEc:eee:finlet:v:45:y:2022:i:c:s1544612321002063
    DOI: 10.1016/j.frl.2021.102125
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    More about this item

    Keywords

    Opec news; Exchange rate forecasting; Bayesian Dynamic Learning;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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