Defection of Traditional Standard Deviation Scaling of Capital Asset Returns
AbstractIn this paper, we investigate the adequacy of scaling, a method frequently used in estimation of standard deviation of stock returns. Scaling is based on the assumption that standard deviation is proportional to the square root of the length of the time interval of the sample (for example daily, monthly or annual data). We analyze the cases when this assumption is justified, and emphasize possible weaknesses of this procedure. As an example, we test the assumptions of scaling on three market indices: Slovak SAX, Czech PX-50 and the S&P 500 index. We conclude that in case of Czech and Slovak index we find significant deviations from stated assumptions. Hence, contrary to the common practice, time-series scaling cannot be used on all time series and requires prior careful examination of the analyzed data.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.
Volume (Year): 54 (2004)
Issue (Month): 7-8 (July)
asset returns; normal distribution; white-noise process; random walk;
Find related papers by JEL classification:
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Lenka Herrmannova).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.