Analysing digits for portfolio formation and index tracking

Peter N Posch () and Welf A Kreiner
Additional contact information
Peter N Posch: Department of Finance. University of Ulm
Welf A Kreiner: Department of Finance. University of Ulm

Journal of Asset Management, 2006, vol. 7, issue 1, No 8, 69-80

Abstract: Abstract A general methodology is proposed for using digit distributions as an approach to examining arbitrary datasets. With the Newcomb–Benford law as a starting point, a more general framework for digital analysis is developed. A new measure is proposed based on this framework, namely the Digital-Fit Factor (DFF). The use of index comparison on the S&P500 and the Dow Jones Industrial Average is demonstrated. The DFF is then used to construct portfolios and measure their performance compared with that of the index. The average returns using the measure exceed the index composition by 6–14 percentage points per year by being more stable at the same time. Furthermore, these measures require only a very small proportion of the available information and are thus very efficient.

Keywords: stock market index; digital analysis; Newcomb–Benford law (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jam.2240203 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:assmgt:v:7:y:2006:i:1:d:10.1057_palgrave.jam.2240203

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/41260

DOI: 10.1057/palgrave.jam.2240203

Access Statistics for this article

Journal of Asset Management is currently edited by Marielle de Jong and Dan diBartolomeo

More articles in Journal of Asset Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().