Exchange Rate Forecasting using ARIMA, Neural Network and Fuzzy Neuron

Babu AS Reddy SK

54 citations0/0 files storedJournal of Stock & Forex Trading

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

Abstract

Prediction of Exchange rates has been a challenging task for traders and practitioners in modern financial markets. Statistical and econometric models are extensively used in the analysis and prediction of foreign exchange rates. This paper investigates the behavior of daily exchange rates of the Indian Rupee (INR) against the United States Dollar (USD), British Pound (GBP), Euro (EUR) and Japanese Yen (JPY). This paper attempts to examine the performance of ARIMA, Neural Network and Fuzzy neuron models in forecasting the currencies traded in Indian foreign exchange markets. Daily RBI reference exchange rates from January 2010-April 2015 were used for the analysis.

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References

2008Introductory Econometrics for Finance 2000A case study on using neural networks to perform technical forecasting of forex 2008Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs)2012Stock Price Prediction using Neural Network with Hybridized Market Indicators 2013Forecasting of currency exchange rates using an adaptive ARMA model with differential evolution based training 2004ANN-Based Forecasting of Foreign Currency Exchange Rates

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