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UK stock returns and robust tests of mean variance efficiency
Institution:1. Department of Computer Science, School of Systems and Technology, University of Management and Technology, C-II Johar Town, Lahore, Pakistan;2. Dr Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan;3. Faculty of Computing and Information Technology in Rabigh, King Abdul Aziz University, Jeddah 21577, Saudi Arabia;4. Gordon Life Science Institute, Boston, MA 02478, USA;5. Department of Computer Sciences, Abdul Wali Khan University, Mardan, Pakistan
Abstract:We test both the unconditional and conditional Mean Variance Efficiency of the UK stockmarket, paying particular attention to choosing a suitable set of instruments for the conditional version of the model. By considering more carefully than previous authors the pricing of economic risk within the mean-variance framework we show that certain instruments can enhance the basic model structure. Given the tendency for financial market data to display non-constancy in variance and non-normality we employ the GMM procedure described in Hansen (1982), which requires much weaker distributional assumptions than the more traditional OLS techniques. We discuss forming portfolios of stocks using both size and dividend yield as a criterion to achieve a suitable spread of risk and return, and find that our conclusions are sensitive both to the method of portfolio formation and to the choice of estimator. This is an important finding given the problem of thin trading associated with the size ordering of UK stocks. We find some support for both the unconditional and conditional version of the CAPM, though we are cautious about our conclusions given the instability of the parameter estimates.
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