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Practical Examples using Eviews

Practical Examples using Eviews. Presented by 顏廣杰 2013/10/24. 2.5 Estimation of an optimal hedge ratio. This section shows how to run a bivariate regression using Eviews . We focus on the relationship between SPOT and FUTURES: Level regression (long run relationship)

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Practical Examples using Eviews

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  1. Practical Examples using Eviews Presented by 顏廣杰 2013/10/24

  2. 2.5 Estimation of an optimal hedge ratio • This section shows how to run a bivariate regression using Eviews. • We focus on the relationship between SPOT and FUTURES: • Level regression (long run relationship) • Return regression (short run relationship) • The appropriate hedge ratio will be the slope estimate, , in a regression where the dependent variable is the spot returns and the independent variable is the futures return. • Test whether or not, we can View  Coeff. Tests  Coeff. Restrictions. Type C(2)=1.

  3. Input Data

  4. Descriptive Statistics • Genr type rfutures=100*dlog(futures) rspot=100*dlog(spot) • Do not forget to Save the workfile.

  5. Run Regression • If 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.

  6. Name  returnreg • In the same way, we also obtain levelreg

  7. Test Coefficients of Regression • Suppose now that we wanted to test the null hypothesis that rather than .

  8. Example for CAPM

  9. Generate New Variables • RSANDP=100*DLOG(SANDP) • RFORD=100*DLOG(FORD) • USTB3M=USTB3M/12 • ERSANDP=RSANDP-USTB3M

  10. CAPM test • To estimate the CAPM equation, click on Equation • Type in the equation window ERFORD C ERSANDP Or DLOG(FORD)-USTB3M C DLOG(SANDP)-USTB3M

  11. APT-style Model • In 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 dspread = baa_aaa_spread – baa_aaa_spread(-1) inflation = 100*dlog(cpi) term = ustb10y – ustb3m ermsoft = rmsoft – mustb3m (excess return of Microsoft) • Stepwise regression

  12. Stepwise regression

  13. Testing for heteroscedasticity • If the residuals of the regression have systematically changing variability over the sample, that is a sign of heteroscedasticity.

  14. To test for heteroscedasticity using White’s test.

  15. Using White’s modified standard error estimates in EViews The heteroscedasticity-consistent s.d. errors are smaller than OLS Durbin-Watson (DW) is a test for first order autocorrelation.

  16. Detecting autocorrelation • Breusch-Godfrey test:

  17. Testing for non-normality • The Bera-Jarque normality tests • View  Residual Tests  Histogram  Normality Test

  18. Multicollinearity • Quick/Group  Statistics/Correlations • In the dialog box that appears: Ersandpdproddcreditdinflationdmoneydspreadrterm

  19. RESET tests • View  Stability tests  Ramsey RESET test

  20. Stability tests • View  Stability Tests  Chow Breakpoint Test

  21. View  Stability Tests  Recursive Estimates (OLS Only)

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