Sub-Additive Recursive ‘Matching’ Noise and Biases in Risk-Weighted Index Calculation Methods in Incomplete Markets with Partially Observable Multi-Attribute Preferences

31 Pages Posted: 23 Jun 2010 Last revised: 11 Jun 2012

Date Written: March 10, 2012

Abstract

While Indices, Index tracking funds and ETFs have grown in popularity during then last ten years, there are many structural problems inherent in Index calculation methodologies and the legal/economic structure of ETFs. These problems raise actionable issues of “Suitability” and “fraud” under US securities laws, because most Indices and ETFs are mis-leading, have substantial tracking errors and don’t reflect what they are supposed to track. This article contributes to the existing literature by: a) introducing new critiques of Index calculation methods, b) introducing and characterizing the Biases inherent in risk-weighted methods and the associated adverse effects; c) showing how these biases/effects inherent in Index calculation methods reduce social welfare, and can form the basis for harmful arbitrage activities.

Keywords: Indices, asset allocation, risk management, complexity, decision analysis, ICAPM

Suggested Citation

Nwogugu, Michael C. I., Sub-Additive Recursive ‘Matching’ Noise and Biases in Risk-Weighted Index Calculation Methods in Incomplete Markets with Partially Observable Multi-Attribute Preferences (March 10, 2012). Available at SSRN: https://ssrn.com/abstract=1628907 or http://dx.doi.org/10.2139/ssrn.1628907

Michael C. I. Nwogugu (Contact Author)

Independent ( email )

P. O. 996
Newark, NJ 07101
United States

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