RESULTS OF INTERBANK EXCHANGE RATES FORECASTING USING STATE SPACE MODEL

Results of Interbank Exchange Rates Forecasting using State Space Model

This study evaluates the performance of three alternative models for forecasting daily interbank exchange rate of U.S. dollar measured in Pak rupees. The simple ARIMA models and complex models such as GARCH-type models and a state space model are discussed and compared. Four different measures are used to evaluate the forecasting accuracy. The main result is the state space model provides the b...

Nonlinearity In Exchange Rates and Forecasting

Forecasting Exchange Rates using Artificial Neural Networks

In the dynamic global economy, the accuracy in forecasting the foreign currency exchange rates is of crucial importance for any future investment. The use of computational intelligence based techniques for forecasting has been proved extremely successful in recent times. The aim of this study is to identify a neural network model which has ability to predict the US Dollar against Sri Lankan Rup...

Forecasting Disconnected Exchange Rates

Catalyzed by the work of Meese and Rogoff (1983), a large literature has documented the inability of empirical models to accurately forecast exchange rates out-of-sample. This paper extends the literature by introducing an empirical strategy that endogenously builds forecast models from a broad set of conventional exchange rate signals. The method is extremely flexible, allowing for potentially...

Forecasting foreign exchange rates with

(2013) Forecasting foreign exchange rates with adaptive neural networks using radial basis functions and particle swarm optimization. The content must not be changed in any way or reproduced in any format or medium without the formal permission of the copyright holder(s) Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and particle swarm optimization...