ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: ABSTRACT: We propose a general methodology for using digit-distributions as an approach to examine arbitrary datasets. Using the Newcomb-Benford-Law as a starting point we develop a more general framework for digital analysis. We propose two measures based on this framework, namely the Digital-Fit-Factor (DFF) and the Mantissae-Distortion-Factor (MDF). Using these approaches we demonstrate the use for index comparison on the S&P 500, the Dow Jones Industrial Average and the Nikkei 225 index. To demonstrate the use of these measures we construct portfolios and measure the performance compared to the index itself. Our measures exceed the index by more than 10 percentage points per year. Furthermore these measures require only a very small proportion of the available information and are thus very efficient
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Reference Type: Journal Article
Subject Area(s): Economics