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Forecasting Exchange Rate Volatility In India Under Univariate And Multivariate Analysis

Author

Listed:
  • Sushil Kumar Rai

    (University of Petroleum and Energy Studies, Dehradun, India)

  • Akhilesh Kumar Sharma

    (Institute for Studies in Industrial Development, New Delhi, India)

Abstract

This paper addresses the issue of variation in the exchange rate of the Indian Rupee (IR) against the US Dollar (USD) under a flexible exchange rate regime using monthly data spanning January 2005 to December 2020. We find that exchange rate volatility is largely affected by its lag value rather than the inflation rate and the interest rate differential. The results of forecast accuracy suggest that the prediction performance of the ARIMA model is better than the VAR model. We also find that apart from other factors, the sharp changes in the exchange rate should be controlled by the economy because its effect will be reflected in the next period and thus creating a chain event to bring further instability in the exchange rate.

Suggested Citation

  • Sushil Kumar Rai & Akhilesh Kumar Sharma, 2023. "Forecasting Exchange Rate Volatility In India Under Univariate And Multivariate Analysis," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 26(1), pages 175-190, March.
    • Handle: RePEc:idn:journl:v:26:y:2023:i:1g:p:175-190
    DOI: https://doi.org/10.59091/1410-8046.2050
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    More about this item

    Keywords

    Exchange rate; Time series analysis; ARIMA; VAR; India;
    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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