This study investigates whether oil prices have enough predictive information to predict the direction of the movement of exchange rate by examining the type of cointegration relationship between exchange rate and oil prices in India between 1991Q1 and 2013Q1. Our findings suggest the existence of cointegration relationship between exchange rate and oil prices using both Engle-Granger two-step cointegration test and Johansen cointegration test. Using a momentum threshold autoregressive consistent model, we find evidence in favour of asymmetric cointegration between the two variables. Nevertheless we find no evidence to support asymmetric cointegration relationship between the two variables when threshold autoregressive, threshold autoregressive consistent, and momentum threshold autoregressive models are used. Thus, the results suggest that for certain time period, the adjustment process between exchange rate and oil price is constant, which makes it conducive for predicting the direction of exchange rate movement. However, evidence of asymmetric cointegration suggests that the stable relationship is likely to be interrupted with intervals of structural change implying correction in the dynamics of influencing factors.
ARTICLE HISTORY
This paper uses the gross domestic product growth rates of Malaysia, Thailand, Indonesia and China in an empirical examination to determine whether an integrated time series should be differenced before it is used for forecasting. The results reveal that Mallows model combination (M.M.A.) of original and differenced series is a better choice than just differencing the series only if the perturbation instability measure is more than 1.25 for autoregressive (A.R.) model, and 1.105 for moving average (M.A.) model and autoregressive fractional integrated moving average (A.R.F.I.M.A.) model. Furthermore, it is found that M.M.A. performs better in forecasting with better model stability for the case of M.A. and A.R.F.I.M.A. than A.R. However, M.M.A. is very sensitive in financial crisis.
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