Abstract

This paper analysed the performance of selected property companies (PCs) stocks returns observed over the time period from Jan 2007 to June 2012. The analysis is based on the Markowitz Model and the Single Index Model (SIM). This paper focused on the results from the Markowitz Model in particular, as the SIM is a simplified approach. The selection of the assets for either portfolio was exhaustive relying on various reputable data sources reporting financial characteristics of each stock. The specific criteria for selecting an asset in all portfolios are volume, P/E ratio, return on equity, positive returns and data sufficiency. Thus, the current study considered PCs stocks with large trading volume to avoid daily swings in security prices. The study compared the return on equity (ROE) of each stock with the ROE of its real estate sector, selecting only those stocks that historically outperformed the sector. PCs with unusually high P/E ratios and those with missing P/E data were excluded. Monthly returns were used for the calculations. The analysis of the results clearly indicated the significance of selecting an appropriate time span for the historical stocks returns used for calculating the efficient frontier. It was shown in this paper that the estimated parameters of the models differ considerably when different time frames are chosen for the analysis. In addition the number of observations used for the calculations has great ramifications on the accuracy of the estimates. As long time spans do not reflect the current character of stocks it becomes important to keep the intervals between observations as narrow as possible. The efficient frontiers for both models were analysed and justifications for the inclusion and exclusion of certain stocks were discussed. Certainly, it is important to note that the outcome of this paper is specific to the PCs stocks that were included in each portfolio and during the period in which this paper was conducted. Also this study concluded that as Real Estate market becomes more volatile, such results may not hold due to greater imbalances and global market inefficiency.

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