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Exchange rate volatility: A forecasting approach of using the ARCH family along with ARIMA SARIMA and semi-structural-SVAR in Turkey

Author

Listed:
  • Ganbold, Batzorig
  • Akram, Iqra
  • Fahrozi Lubis, Raisal

Abstract

The ability to predict the volatility of Exchange rate is an enormous challenge when it comes to economic and financial considerations. In this context, it is important to be able to predict the exchange rate volatility in financial markets and the world economy. This paper proposes a heightened approach to modeling and forecasting of exchange rate volatility in Turkey. For past recent years, Turkey experienced political turbulence that the possibility of effecting exchange rate, thus create uncertainty volatility of exchange rate. Therefore daily exchange rate data have been taken from 2005-2017 and applied autoregressive conditional heteroskedasticity ARCH and GARCH families (EGARCH, IGARCH, and PARCH) to forecast exchange rate volatility. The proposed methodology able to calculate the breakpoint by including dummy variables. The result is more confined after including dummy that EGARCH (1,1) is best performing to forecast exchange rate volatility and successfully overcome the leverage effect on the exchange rate. Moreover, this paper also investigates the monthly data forecasting by applying ARIMA SARIMA along with SVAR technique for next few months. And Exchange rate pass-through also encounter it, which indicates the pass-through is more pronounced in PPI than CPI. The forecast result of SARIMA and SVAR distribute the same direction of fluctuation in the exchange rate that is declining of the current exchange rate in the future. However, ARIMA’s forecast tends to increase and different with two models.

Suggested Citation

  • Ganbold, Batzorig & Akram, Iqra & Fahrozi Lubis, Raisal, 2017. "Exchange rate volatility: A forecasting approach of using the ARCH family along with ARIMA SARIMA and semi-structural-SVAR in Turkey," MPRA Paper 84447, University Library of Munich, Germany, revised 2017.
    • Handle: RePEc:pra:mprapa:84447
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    Cited by:

    1. Nyoni, Thabani, 2019. "An ARIMA analysis of the Indian Rupee/USD exchange rate in India," MPRA Paper 96908, University Library of Munich, Germany.
    2. M’bakob Gilles Brice & Mandeng ma Ntamack Jules, 2024. "Influence of psychological exchange rates (PER) on forex price formation: theory, empirical, and experimental evidence," SN Business & Economics, Springer, vol. 4(9), pages 1-53, September.

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    More about this item

    Keywords

    Exchange rate; Volatility; Forecast; SVAR;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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