For as long as managed mutual funds have been in existence there has been a desire to accurately assess their relative performance against each other, and also their respective performance in relation to an appropriate stock market index. There has been a specific interest in whether the expensive, professionally managed mutual funds can justify their high cost with respect to low cost, simple index trackers by producing superior, post-cost performance, and this proposition is implicitly tested within this thesis. The aim of this thesis is to undertake an empirical assessment of the managerial performance of mutual funds utilising a three-stage DEA-SFA-DEA methodology which combines linear mathematical programming (DEA) and stochastic frontier analysis (SFA). Specifically, this thesis focuses on evaluating the managerial performance of UK domiciled open-ended investment companies (OEICs) and unit trusts (UTs) over a three year period from 1st January 2008 to 31st December 2010. Various DEA models are utilised including CCR, BCC and SBM DEA models with various orientations, and also versions of these DEA models which make use of the SORM procedure. These are used to carry out an initial evaluation of the managerial performance of the OEICs/UTs, before two of these DEA models are combined with SFA regression analysis in a three-stage DEA-SFA-DEA methodology to purge the influence of environmental factors and statistical noise, thus leading to a more robust evaluation of the true managerial performance of the OEICs/UTs under assessment. The results of this thesis extend support to the premise of the Efficient Market Hypothesis (EMH) that financial markets are information efficient , and thus it is not possible, given the information available when the investment is made, to consistently obtain returns in excess of the average market return on a risk-adjusted basis, and this thesis does so through the use of a novel approach.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:603015 |
Date | January 2013 |
Creators | Burrows, Tim |
Publisher | Loughborough University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://dspace.lboro.ac.uk/2134/14531 |
Page generated in 0.0024 seconds