Autor: Md.
Zahangir Alam
Abstract:
The key motivation of this study is to examine the application of autoregressive model for forecasting and trading the NTD/USD exchange rates from July 03, 2006 to April 30, 2008 as in-sample and May 01, 2008 to July 04, 2009 as out of sample data set. AR and ARMA models are benchmarked with a naïve strategy model. The major findings of this study is that in case of in-sample data set, the ARMA model, whereas in case of out-of-sample data set, both the ARMA and AR models jointly outperform other models for forecasting the NTD/USD exchange rate respectively in the context of statistical performance measures. As per trading performance, both the ARMA and naive strategy models outperform all other models in case of in-sample data set. On the other hand, both the AR and naive strategy models do better than all other models in case of out-of-sample data sets as per trading performance.
The key motivation of this study is to examine the application of autoregressive model for forecasting and trading the NTD/USD exchange rates from July 03, 2006 to April 30, 2008 as in-sample and May 01, 2008 to July 04, 2009 as out of sample data set. AR and ARMA models are benchmarked with a naïve strategy model. The major findings of this study is that in case of in-sample data set, the ARMA model, whereas in case of out-of-sample data set, both the ARMA and AR models jointly outperform other models for forecasting the NTD/USD exchange rate respectively in the context of statistical performance measures. As per trading performance, both the ARMA and naive strategy models outperform all other models in case of in-sample data set. On the other hand, both the AR and naive strategy models do better than all other models in case of out-of-sample data sets as per trading performance.
Keyword:
Forecasting, Autoregressive and
Autoregressive Moving Average Models, and Naïve Strategy.
GJMBR-B Classification : JEL Code : C53
Source: Global
Journal of Management and Business Research Volume 12 Issue 19 Version 1.0 Year
2012
Type: Double
Blind Peer Reviewed International Research Journal
Publisher: Global
Journals Inc. (USA) Online ISSN: 2249-4588 & Print ISSN: 0975-5853
