References—375

estimated by Bollerslev, Engle, and Nelson (1994, equation 9.1, page 3015) for different data.

•EGARCH with generalized error distributed errors (egarch1.prg): estimates Nelson’s (1991) exponential GARCH with generalized error distribution. The specification and likelihood are described in Hamilton (1994a, p. 668–669). Note that this model may more easily be estimated using the standard ARCH estimation tools provided in EViews (Chapter 24. “ARCH and GARCH Estimation,” on page 195).

•Multivariate GARCH (bv_garch.prg and tv_garch.prg): estimates the bior the trivariate version of the BEKK GARCH specification (Engle and Kroner, 1995). Note that this specification may be estimated using the built-in procedures available in the system object (“System Estimation,” on page 419).

References

Bollerslev, Tim, Robert F. Engle and Daniel B. Nelson (1994). “ARCH Models,” Chapter 49 in Robert F. Engle and Daniel L. McFadden (eds.), Handbook of Econometrics, Volume 4, Amsterdam: Elsevier Science B.V.

Engle, Robert F. and K. F. Kroner (1995). “Multivariate Simultaneous Generalized ARCH,” Econometric Theory, 11, 122-150.

Greene, William H. (2008). Econometric Analysis, 6th Edition, Upper Saddle River, NJ: Prentice-Hall.

Hamilton, James D. (1994a). Time Series Analysis, Princeton University Press.

Judge, George G., W. E. Griffiths, R. Carter Hill, Helmut Lütkepohl, and Tsoung-Chao Lee (1985). The Theory and Practice of Econometrics, 2nd edition, New York: John Wiley & Sons.

Nelson, Daniel B. (1991). “Conditional Heteroskedasticity in Asset Returns: A New Approach,” Econometrica, 59, 347–370.

Quandt, Richard E. (1988). The Econometrics of Disequilibrium, Oxford: Blackwell Publishing Co.

Vuong, Q. H. (1989). “Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses,” Econometrica, 57(2), 307–333.

376—Chapter 29. The Log Likelihood (LogL) Object