FORECASTING EXCHANGE RATE VOLATILITY IN INDIA UNDER UNIVARIATE AND MULTIVARIATE ANALYSIS

Sushil Kumar Rai () and Akhilesh Kumar Sharma ()
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Sushil Kumar Rai: University of Petroleum and Energy Studies, Dehradun, India
Akhilesh Kumar Sharma: Institute for Studies in Industrial Development, New Delhi, India

Bulletin of Monetary Economics and Banking, 2023, vol. 26, issue 1, 175-190

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.

Keywords: Exchange rate; Time series analysis; ARIMA; VAR; India (search for similar items in EconPapers)
JEL-codes: C22 C52 F31 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:idn:journl:v:26:y:2023:i:1g:p:175-190

DOI: 10.59091/1410-8046.2050

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