testing for unit roots in eviews open ‘ukhp.wfl’. we test whether the series of ‘hp’ is unit...
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Testing for unit roots in Eviews
• Open ‘ukhp.wfl’. We test whether the series of ‘hp’ is unit root.
• Repeat the above steps to test whether the series of ‘dhp’ is unit root.
Testing for cointegration and modelling cointegrated systems using Eviews
• To overcome the problems of the spurious regression, we use the difference of series to analysis. However, this methodology will diminish the long-run relationship between the two original series.
• The S&P500 spot and futures are cointegrated, this means that the spot and futures prices have a long-term relationship.
The Engle-Granger 2-step method
• Step 1:• Open ‘sandphedge.wfl’• Generate a new equation object:
LSPOT C LFUTURES• Generate a new series:STATRESIDS=RESID• Perform the ADF test on the residual series.
• Since the test statistic (-8.05), the null hypothesis of a unit root in the test regression residuals is strongly rejected.
The two series are cointegrated.An error correction model (ECM) can be
estimated, as there is a linear combination of the spot and futures prices that would be stationary.
• STEP 2:We estimate an error correlation model (ECM) by running the regression:
rspot c rfutures statresids(-1)
ARCH
• Open ‘currencies.wf1’
GARCH
• The GARCH model was developed independently by Bollerslev (1986) and Taylor (1986).
• is known as the conditional variance.
GARCH
• Quick/Estimate Equation. • Select ARCH from the ‘Estimation Settings’
GJR
• The GJR (Glosten, Jagannathan, and Runkle, 1993) model is a simple extension of GARCH with an additional term added to account for possible asymmetries.
GJR
EGARCH
• The exponential GARCH model was proposed by Nelson (1991).
EGARCH
Forecasting from GARCH models
• We stopped the estimation of the GARCH(1,1) model for the Japanese yen returns on 6 July 2005 so as to keep the last two years of data for forecasting.
Forecasting from GARCH models
Dynamic forecast
Static forecast