Applying A New Portfolio Risk/Return Measurement mannerological analysis Based on Recent Advances in Quantifying constant Paretian alter Tailed Distributions and Investor Loss Aversion Preferences August 5, 2006 Version 1.0 procure 2006 LifeCycle Returns 1 By Rawley Thomas 2 President and Co-Founder of LifeCycle Returns
Rawley@LCRT.com
630-377-0761 plagiarise Based on recent work by Kevin Dowd on investor loss aversion preferences and work by Benoit Mandelbrot on Stable Paretian distributions with Huston McCullochs parameter estimation procedures, this paper recommends the practical practise of new portfolio risk/ output measurements to achieved and back tested convey portfolio performance. This new risk measurement process addresses the issue of sempiternal sectionalizations empiric in ally observed in most stock return distributions. Introduction To statistically justify portfolio diversification, Harry Markowitz wrote the classic halt 3 on portfolio selection. Markowitz employed a mean variance framework, but recognized the variance risk measure does not fully recognize investor wishes to avoid losses. Benoit Mandelbrots 4 empirical analysis strongly suggested actual stock returns follow racy tailed Stable Paretian distributions with infinite variances. J.
Huston McCulloch 5 recommended a quantile method for estimating the four parameters of the Stable distribution with significance statistics to measure how extreme from Gaussian Normal they lie. Kevin Dowd suggested a utility function to glint observed investor loss aversion over the entire distribution of anticipated returns. 6 To the
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