In this paper, the author has tried to build a univariate model to forecast the exchange
rate of the Indian rupee in terms of different currencies like SDR, USD, GBP, Euro and
JPY. This paper uses the Box-Jenkins Methodology of building the ARIMA model.
Sample data for the paper was taken from March 1992 to June 2004, out of which data
till December 2002 were used to build the model, while the remaining data was used to
conduct out-of-sample forecasting and check the forecasting ability of the model. The data
was collected from the Indiastat database. The paper shows that the ARIMA models
provide a better forecasting of exchange rates than the simple autoregressive models or
moving average models. The author was able to build a model for all the currencies
except USD, which shows the relative efficiency of the USD currency market.
This paper is an attempt to forecast the exchange rate of the Indian Rupee (INR) in terms of five
different currencies: SDR, USD, GBP, Euro and JPY. This paper tries to make short horizon forecasts
based on univariate time series analysis. A survey of literature shows that a continuous debate is on as
to whether exchange rate follows a random walk or provides room to be modeled, and whether one
should use structural models or time series models to forecast exchange rate.
Forecasting exchange rate is important not only for firms having their business spread over different
countries or firms planning to raise long or short-term funds from international markets, but also for
firms confined to their entire business in the domestic market only, because a change in foreign
exchange rate can change the business and the competition scenario for firms. Firms having exposure
to foreign currencies are subject to two types of risk: Accounting Exposure1—which does not involve
any cash flow but still can influence the profitability of a firm, and Cash Flow Exposure—which has a
direct impact on the profitability of a firm by affecting its cash flow. Forecasting exchange rate is an
important input in various corporate decisions like currency for invoicing, pricing decision, borrowing
and lending decisions; and management of exposures and hedging strategies. The demise of the
Bretton Woods system in 1973 gave rise to both the difficulty and desirability of obtaining reliableforecasts of exchange rates to earn income from speculative activities, in order to determine optimal
government policies as well as to make business decisions.