Forecasting SGD-INR Exchange Return: An application of Autoregressive Integrated Moving Average

Abstract

Predicting currency has always been open to doubt because in financial as well as in managerial decisions making process it plays a crucial role and it is not easy to forecast foreign rates with higher accuracy than a naive random walk model. The main goal of this paper is to use the Arima model to forecast the yearly exchange rate, here we use real foreign exchange data to check the suitable level of the Arima model for forecasting and it also shows how suitable the Arima model is to estimate foreign exchange. There has been considerable improvement in profitability of MNC which conducts substantial currency transfer in
business courses and forecasts exchange rate accurately. The time series Arima model is applied to forecast the exchange return of SND to INR. To better understand how the Arima model applies within the period 1st February 2011 - 1st February 2021. In this report monthly or daily exchange returns are used for variable inputs. This model is based on a few observations on the Arima model to help predict and solve financial forecasting problems for the best and worst possible situations which results in demonstrating the predictive strength and potential but is still a problematic task.