Abstract
The proposed project analyses and forecasts the exchange rates on the Indian rupee by using time series data concepts from the year 2020 to 2022, using the most popular Box-Jenkins ARIMA model technique. Based on the research study presented, the ARIMA model’s test results depict that the proposed model is very accurate in showing the results and hence works well for forecasting the USD exchange rates. Forecasting the exchange rates plays a significant role in minimizing risks and maximizing profits for the people working in the financial markets, trading as well as general public across the world. ARIMA uses the stationary time series dataset for providing accurate predictions. The real time series data used in this study has been obtained from Yahoo Finance, calculated and analyzed dollar exchange rate for the following day, subsequent 15 days, 30 days, 60 days respectively from the current date. In addition to that, we were able to achieve a small MAPE score/forecast accuracy i.e. 0.923 which indicates that the model gives better accuracy. The Daily exchange rates from 5th June 2020 to the current date were used for the prediction.
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Bharati, A.U., Janakiram, C.S., Pattanayak, R.M., Jose, D., Mohanty, S.N. (2023). Dollar Price Prediction Using ARIMA. In: Balas, V.E., Semwal, V.B., Khandare, A. (eds) Intelligent Computing and Networking. IC-ICN 2023. Lecture Notes in Networks and Systems, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-99-3177-4_2
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DOI: https://doi.org/10.1007/978-981-99-3177-4_2
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