Forecasting USD/INR Exchange Rates: A Time Series Approach Using ARIMA
DOI:
https://doi.org/10.53983/ijmds.v13n12.002Keywords:
autoregressive, moving average, unit root test, exchange rateAbstract
This study aims to forecast the USD/INR foreign exchange rate employing the Autoregressive Integrated Moving Average model, analyzing its applicability over an extensive historical period from 1970 to 2024. The primary objective is to identify the most suitable model for predicting future exchange rate trends, which is crucial for investors and businesses engaged in international trade. Using 55 years of historical time series data, the ARIMA (2, 2, 0) model was identified as the most appropriate after rigorous testing and evaluation. The analysis revealed that the first and second autoregressive components (AR(1) and AR(2)) significantly enhanced the model’s predictive accuracy, while the moving average components were statistically insignificant. The forecast for 2025 to 2029 indicates an upward trend in the USD/INR exchange rate, suggesting a potential depreciation of the Indian Rupee against the US Dollar. These findings are highly relevant for financial analysts and investors, offering a reliable tool for decision-making and strategic planning in international finance. By applying the ARIMA model over an extended historical period, this study contributes to the literature with a robust forecast that can aid in risk management and future exchange rate assessments.
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