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Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships

Author

Listed:
  • Anna Pajor

    (Cracow University of Economics
    Jagiellonian University in Kraków)

  • Justyna Wróblewska

    (Cracow University of Economics)

Abstract

The paper is focused on comparing the forecasting performance of two relatively new types of Vector Error Correction - Multiplicative Stochastic Factor (VEC-MSF) specifications: VEC-MSF with constant conditional correlations, and VEC-MSF-SBEKK with time-varying conditional correlations. For the sake of comparison, random walks, vector autoregressions (VAR) with constant conditional covariance matrix, and VAR-SBEKK models are also considered. Based on daily quotations on three exchange rates: PLN/EUR, PLN/USD, and EUR/USD, where the cointegrating vector may be assumed to be known a priori, we show that in econometric models it can be more important to allow for cointegration relationships than for time-varying conditional covariance matrix.

Suggested Citation

  • Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    • Handle: RePEc:spr:eurase:v:12:y:2022:i:3:d:10.1007_s40822-022-00203-x
    DOI: 10.1007/s40822-022-00203-x
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    More about this item

    Keywords

    Multivariate time series; Cointegration; Stochastic volatility; Predictive Bayes factor; Exchange rate;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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