Robust Power Calculations with Tests for Serial Correlation in Stock Returns
AbstractThis paper provides an asymptotically most powerful test for a particular class of statistics which test the hypothesis of no serial correlation. This class includes many of the statistics employed in the recent finance and macroeconomics literature. Furthermore, with respect to a popular mean reversion alternative model, we show that the asymptotically most powerful test is quite robust to distributional specifications.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
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.
Bibliographic InfoPaper provided by Wharton School Rodney L. White Center for Financial Research in its series Rodney L. White Center for Financial Research Working Papers with number 12-91.
Date of creation:
Date of revision:
Contact details of provider:
Postal: 3254 Steinberg Hall-Dietrich Hall, Philadelphia, PA 19104-6367
Phone: (215) 898-7616
Fax: (215) 573-8084
Web page: http://finance.wharton.upenn.edu/~rlwctr/
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Campbell, John Y., 2001.
"Why long horizons? A study of power against persistent alternatives,"
Journal of Empirical Finance,
Elsevier, vol. 8(5), pages 459-491, December.
- Campbell, John, 2001. "Why Long Horizons? A Study of Power Against Persistent Alternatives," Scholarly Articles 3196341, Harvard University Department of Economics.
- John Y. Campbell, 1993. "Why Long Horizons: A Study of Power Against Persistent Alternatives," NBER Technical Working Papers 0142, National Bureau of Economic Research, Inc.
- Perron, Pierre & Vodounou, Cosme, 2004. "Tests of return predictability: an analysis of their properties based on a continuous time asymptotic framework," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 203-230, March.
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.