Can a Neural Network Property Portfolio Selection Process Outperform the Property Market?

Abstract

Executive Summary. Evidence of the superior performance of portfolios comprised of ‘value’ stocks over ‘growth’ stocks is wide and varied. Despite this burgeoning literature, relatively little is known about the comparative performance of property sector value stocks and the performance of neural network techniques in relation to this market sector. This study addresses both of these issues by applying neural network modeling techniques to the Australian property sector stocks to construct a variety of value portfolios. Risk-adjusted performance measures show that the value portfolios outperform the market by as much as 7.14%.