Estimating Conditional Expectations When Volatility Fluctuates
Asymptotic variances of estimated parameters in models of conditional expectations are calculated analytically assuming a GARCH process for conditional volatility. Under such heteroskedasticity, OLS estimators of parameters in single-period models can possess substantially larger asymptotic variances than GMM estimators employing additional multiperiod moment conditions - an approach yielding no efficiency gain under homoskedasticity. In estimating models of long-horizon expectations the VAR approach provides an efficiency advantage over long-horizon regressions under homoskedasticity, but that ordering can reverse under heteroskedasticity, especially when the conditional mean and variance are both persistent. In such cases, the VAR approach maintains a slight efficiency advantage if the OLS estimator is replaced by an alternative GMM estimator. Heteroskedasticity can increase dramatically the apparent asymptotic power advantages of long-horizon regressions to reject constant expectations against persistent alternatives.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (215) 898-7616
Fax: (215) 573-8084
Web page: http://finance.wharton.upenn.edu/~rlwctr/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Baillie, R.T. & Bollerslev, R.T., 1990.
"Prediction In Dynamic Models With Time Dependent Conditional Variances,"
8815, Michigan State - Econometrics and Economic Theory.
- Baillie, Richard T. & Bollerslev, Tim, 1992. "Prediction in dynamic models with time-dependent conditional variances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 91-113.
- Geweke, John, 1981. "The Approximate Slopes of Econometric Tests," Econometrica, Econometric Society, vol. 49(6), pages 1427-42, November.
- Hansen, Lars Peter & Singleton, Kenneth J, 1996.
"Efficient Estimation of Linear Asset-Pricing Models with Moving Average Errors,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 14(1), pages 53-68, January.
- Lars Peter Hansen & Kenneth J. Singleton, 1997. "Efficient Estimation of Linear Asset Pricing Models with Moving-Average Errors," NBER Technical Working Papers 0086, National Bureau of Economic Research, Inc.
- Shmuel Kandel & Robert F. Stambaugh, . "Modeling Expected Stock Returns for Long and Short Horizons," Rodney L. White Center for Financial Research Working Papers 42-88, Wharton School Rodney L. White Center for Financial Research.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Donald B. Keim & Robert F. Stambaugh, .
"Predicting Returns in the Stock and Bond Markets,"
Rodney L. White Center for Financial Research Working Papers
15-85, Wharton School Rodney L. White Center for Financial Research.
- Frederic S. Mishkin, 1991.
"Does Correcting for Heteroskedasticity Help?,"
NBER Technical Working Papers
0088, National Bureau of Economic Research, Inc.
- Richardson, Matthew & Smith, Tom, 1991. "Tests of Financial Models in the Presence of Overlapping Observations," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 227-54.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Campbell, John, 1991.
"A Variance Decomposition for Stock Returns,"
3207695, Harvard University Department of Economics.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Hodrick, Robert J, 1992.
"Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement,"
Review of Financial Studies,
Society for Financial Studies, vol. 5(3), pages 357-86.
- Tom Doan, . "OLSHODRICK: RATS procedure to compute Hodrick standard errors," Statistical Software Components RTS00147, Boston College Department of Economics.
- Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
- Cragg, John G, 1983. "More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form," Econometrica, Econometric Society, vol. 51(3), pages 751-63, May.
When requesting a correction, please mention this item's handle: RePEc:fth:pennfi:17-93. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.