Date of Publication :22nd February 2018

Abstract: This paper focuses on Time Series forecasting techniques to financial time series with an autoregressive integrated moving average (ARIMA) and Seasonal and Trend decomposition using Loess(STL) that estimates nonlinear relationships. The data used are historical currency exchange rates of INR/USD, INR/GBP, INR/EURO and INR/YEN from May 2005 to July 2014 provided by Reserve Bank of India. First, we show the Multivariate Analysis and then perform the forecasting on individual currency. Various plots are used for visualization.

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