Practical Examples using Eviews

Presented by 2013/10/24Practical Examples using EviewsP.40-P.43File: SandPhedge.xlsEstimation of an optimal hedge ratioInput Data

Descriptive StatisticsGenr type rfutures=100*dlog(futures) rspot=100*dlog(spot)Do not forget to Save the workfile.

Run RegressionIf you want to save the summary statistics, you must name them by clicking Name and then choose a name, e.g. Descstats. We can now proceed to estimate the regression.

Name returnreg

In the same way, we also obtain levelreg

Test Coefficients of Regression

P.77-P.80File: capm.xlsExample for CAPM

Generate New VariablesRSANDP=100*DLOG(SANDP)RFORD=100*DLOG(FORD)USTB3M=USTB3M/12ERSANDP=RSANDP-USTB3M

CAPM test

P.99-P.104File: macro.xlsPeriod: 1986/03~2007/04APT-style ModelIn the spirit of APT, the following example will examine regressions that seek to determine whether the monthly returns on Microsoft stock an be explained by reference to unexpected changes in a set of macroeconomic and financial variables.Press Genr or type in the Command windowGenr dspread = d(baa_aaa_spread)Genr dprod = d(industrial_production)Genr dcredit = d(consumer_credit)Genr rmsoft = 100*dlog(microsoft)Genr rsandp = 100*dlog(sandp)Genr dmoney = d(m1money_supply)Genr inflation = 100*dlog(cpi)Genr term = ustb10y ustb3m

Stepwise regression

P.136-P.139File: macro.wflPeriod: 1986/03~2007/04Testing for heteroscedasticityIf the residuals of the regression have systematically changing variability over the sample, that is a sign of heteroscedasticity.

It is hard to see any clear pattern, so we need to run the formal statistical test. (Whites test)

To test for heteroscedasticity using Whites test.

VV ambiguous!!XUsing Whites modified standard error estimates in EViews

The heteroscedasticity-consistent s.d. errors are smaller than OLSDurbin-Watson (DW) is a test for first order autocorrelation.Detecting autocorrelation

Testing for non-normalityThe Bera-Jarque normality testsView Residual Tests Histogram Normality Test

MulticollinearityQuick/Group Statistics/CorrelationsIn the dialog box that appears:Ersandp dprod dcredit dinflation dmoney dspread rterm

RESET tests (p.177)View Stability tests Ramsey RESET test

It would be concluded that the linear model for the Microsoft returnsis appropriate.Stability tests (p.188)View Stability Tests Chow Breakpoint Test

P.234-P.238File: UKHP.wflPeriod: 1991/03~2007/05Constructing ARMA models in EviewsWe use the monthly UK house price series in the chapter one to build an ARMA model for the house price changes.Autocorrelation Partial autocorrelationDouble click DHP View/Correlation Lag 12 OK

Estimating the autocorrelation coefficients for up to 12 lagsUsing information criteria to decide on model ordersQuick Estimate Equation

This specify an ARMA(1,1). The output is given in the table below.

One more example: dhp c ar(1) ar(2) ar(3) ar(4) ar(5) ma(1) ma(2) ma(3) ma(4) ma(5)Using AIC to decide which one model is good.Smaller AIC imlies better model.

AIC

Forecasting using ARMA models in EviewsSuppose that the AR(2) model selected for the house price percentage changes series were estimated using observations Feb. 1991-Dec. 2004, leaving 29 remaining observations to construct forecasts.Quick Equation Estimation

Forecast dynamic/static

Simultaneous equations modelling using EViewsWhat is the relationship between inflation and stock returns?In EViews, to do this we need to specify a list of instruments, which would be all of the variables from the reduced form equation. The reduced form equations:

Quick Estimation Equation

P.308File: currencies.wflPeriod: 1991/03~2007/05Vector autoregressive modelsThe simplest case:

Open currencies.wfl Quick Estimate VAR

How to decide the length of lagged term?View Lag Structure Lag Length Criteria 10Conclusion: choose VAR(1).Granger causality test very little evidence of lead-lag interactions between the series.