Modelling exchange rates using regime switching models

Mohd Tahir Ismail, and Zaidi Isa, (2006) Modelling exchange rates using regime switching models. Sains Malaysiana, 35 (2). pp. 55-62. ISSN 0126-6039

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The behaviour of many financial time series cannot be modeled solely by linear time series model. Phenomena such as mean reversion, volatility of stock markets and structural breaks cannot be modelled implicitly using simple linear time series model. Thus, to overcome this problem, nonlinear time series models are typically designed to accommodate these nonlinear features in the data. In this paper, we use portmanteau test and structural change test to detect nonlinear feature in three ASEAN countries exchange rates (Malaysia, Singapore and Thailand). It is found that the null hypothesis of linearity is rejected and there is evidence of structural breaks in the exchange rates series. Therefore, the decision of using regime switching model in this study is justified. Using model selection criteria (AIC, SBC, HQC), we compare the in-sample fitting between two types of regime switching model. The two regime switching models we considered were the Self-Exciting Threshold Autoregressive (SETAR) model and the Markov switching Autoregressive (MS-AR) model where these models can explain the abrupt changes in a time series but differ as how they model the movement between regimes. From the AIC, SBC and HQC values, it is found that the MS -AR model is the best fitted model for all the return series. In addition, the regime switching model also found to perform better than simple autoregressive model in in-sample fitting. This result justified that nonlinear model give better in-sample fitting than linear model.

Item Type:Article
Keywords:exchange rates; regime switching model; nonlinearity; model selection criteria
Journal:Sains Malaysiana
ID Code:3990
Deposited By: Mr Fazli Nafiah -
Deposited On:28 Mar 2012 03:46
Last Modified:28 Mar 2012 03:46

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