Forecasting Exchange Rates: a Comparative Analysis

Nonlinearity In Exchange Rates and Forecasting

Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...

A Comparative Study of Two Technical Analysis Tools: Moving Average Convergence and Divergence V/S Relative Strength Index: A Case Study of HDFC Bank ltd listed in National Stock Exchange of India (NSE)

Technical analysis is the forecasting of future price movement based on an examination of past prices. Some scientist found that the study of historical prices cannot predict future prices. In this research we intend to study which technical analysis tool is better for prediction of future price movement, for this purpose we are studying two the most strongest technical analysis tools is called...

A hybrid computational intelligence model for foreign exchange rate forecasting

Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...

The Comparison among ARIMA and hybrid ARIMA-GARCH Models in Forecasting the Exchange Rate of Iran

This paper attempts to compare the forecasting performance of the ARIMA model and hybrid ARMA-GARCH Models by using daily data of the Iran’s exchange rate against the U.S. Dollar (IRR/USD) for the period of 20 March 2014 to 20 June 2015. The period of 20 March 2014 to 19 April 2015 was used to build the model while remaining data were used to do out of sample forecasting and check the forecasti...