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Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020

Author

Listed:
  • Astrid Ayala

    (Universidad Francisco Marroquín)

  • Szabolcs Blazsek

    (Universidad Francisco Marroquín)

  • Adrian Licht

    (Universidad Francisco Marroquín)

Abstract

In this paper, score-driven time series models are used, in order to provide robust estimates of the seasonal components of Russian rouble (RUB) currency exchange rates for the period of 1999 to 2020. This paper is the first empirical application of score-driven models to the RUB to US dollar (USD) and RUB to Euro (EUR) currency exchange rates in the literature. The model includes score-driven local level, seasonality, and volatility components for a variety of probability distributions: Student’s t distribution, skewed generalized t (Skew-Gen-t) distribution, exponential generalized beta distribution of the second kind (EGB2), normal-inverse Gaussian (NIG) distribution, and Meixner (MXN) distribution. The use of the MXN distribution is new in the literature of score-driven seasonality models. We show that the score-driven models of this paper are robust to changes in the currency exchange rate regimes of the Bank of Russia. We find that the annual seasonality of the RUB is significant, and it is in the range of $$\pm 4\%$$ ± 4 % . We review the determinants of the RUB seasonality using data on exports, imports, and primary income from the current account of the Russian Federation. The statistical performances of all score-driven models are superior to the statistical performance of the classical multiplicative seasonal autoregressive integrated moving average (ARIMA) model. Our results may motivate the practical use of score-driven models of the RUB exchange rate seasonality for financing, investment, or policy decisions.

Suggested Citation

  • Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    • Handle: RePEc:spr:empeco:v:62:y:2022:i:5:d:10.1007_s00181-021-02103-6
    DOI: 10.1007/s00181-021-02103-6
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    More about this item

    Keywords

    Russian rouble; Current account of Russia; Currency exchange rate regimes of the Bank of Russia; Score-driven local level; seasonality; and volatility; Dynamic conditional score; Generalized autoregressive score;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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