Comparing the performance of time series models for forecasting exchange rate

In this paper an attempt has been made to compare different time series models to forecast exchange rate. A survey of literature shows that continuous debate is going on whether exchange rate follows a random walk or it can be modeled; there is also a debate whether one should use structural models...

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Библиографические подробности
Главный автор:	Newaz, M.K.
Формат:	Статья
Язык:	English
Опубликовано:	BRAC University 2010
Предметы:	Exchange rate forecasting ARIMA Expotential smoothing Naive 1 Naive 2
Online-ссылка:	http://hdl.handle.net/10361/438

id	10361-438
record_format	dspace
spelling	10361-4382019-09-29T05:47:25Z Comparing the performance of time series models for forecasting exchange rate Newaz, M.K. Exchange rate forecasting ARIMA Expotential smoothing Naive 1 Naive 2 In this paper an attempt has been made to compare different time series models to forecast exchange rate. A survey of literature shows that continuous debate is going on whether exchange rate follows a random walk or it can be modeled; there is also a debate whether one should use structural models or time series models to forecast exchange rate. Paper uses Box-Jenkins methodology for building ARIMA model, exponential smoothing, naïve 1 and naïve 2 models. Sample data for the paper were taken from September 1985 to June 2006, out of which data till December 2002 were used to build the model while remaining data points were used to do out of sample forecasting and check the forecasting ability of the model. All the data were collected from various issues of International Financial Statistics published by International Monetary Fund. Result of this study shows that ARIMA models provides a better forecasting of exchange rates than exponential smoothing and Naïve models do. Comparison of the MAE, MEAE, MAPE, MSE and RMSE shows that the proposed ARIMA model is the best among all these models. 2010-10-10T10:46:23Z 2010-10-10T10:46:23Z 2008 Article http://hdl.handle.net/10361/438 en BRAC University Journal, BRAC University;Vol.5, No.2,pp. 55-65 application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Exchange rate forecasting ARIMA Expotential smoothing Naive 1 Naive 2
spellingShingle	Exchange rate forecasting ARIMA Expotential smoothing Naive 1 Naive 2 Newaz, M.K. Comparing the performance of time series models for forecasting exchange rate
description	In this paper an attempt has been made to compare different time series models to forecast exchange rate. A survey of literature shows that continuous debate is going on whether exchange rate follows a random walk or it can be modeled; there is also a debate whether one should use structural models or time series models to forecast exchange rate. Paper uses Box-Jenkins methodology for building ARIMA model, exponential smoothing, naïve 1 and naïve 2 models. Sample data for the paper were taken from September 1985 to June 2006, out of which data till December 2002 were used to build the model while remaining data points were used to do out of sample forecasting and check the forecasting ability of the model. All the data were collected from various issues of International Financial Statistics published by International Monetary Fund. Result of this study shows that ARIMA models provides a better forecasting of exchange rates than exponential smoothing and Naïve models do. Comparison of the MAE, MEAE, MAPE, MSE and RMSE shows that the proposed ARIMA model is the best among all these models.
format	Article
author	Newaz, M.K.
author_facet	Newaz, M.K.
author_sort	Newaz, M.K.
title	Comparing the performance of time series models for forecasting exchange rate
title_short	Comparing the performance of time series models for forecasting exchange rate
title_full	Comparing the performance of time series models for forecasting exchange rate
title_fullStr	Comparing the performance of time series models for forecasting exchange rate
title_full_unstemmed	Comparing the performance of time series models for forecasting exchange rate
title_sort	comparing the performance of time series models for forecasting exchange rate
publisher	BRAC University
publishDate	2010
url	http://hdl.handle.net/10361/438
work_keys_str_mv	AT newazmk comparingtheperformanceoftimeseriesmodelsforforecastingexchangerate
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Comparing the performance of time series models for forecasting exchange rate

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