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Friday, August 9, 2019

Portfolio Management Statistics Project Example | Topics and Well Written Essays - 2250 words

Portfolio Management - Statistics Project Example The stock returns values experience wide variance due to the fluctuation in portfolio weights across the period. From the set of 28 stocks, the time series was filtered on the criteria of performance to retain the 11 stocks shown in the time series as the most efficient portfolio. The process of refining the investment involved ignoring the portfolio with low weights and retaining the high weight portfolio. The selection aimed at picking 3 stocks with the best returns to represent the high efficiency required in the pool decision. The high efficiency stocks were found to be IBM and MMM. The decision was made on the values based on the original currency returns. The time series for the refined investment pool carries the following stock: The major reason for reducing the number of stocks in the refined investment is that many assets have caused a wide variation of the portfolio weights and return on investment (Tobin 1958, p. 65). The analysis sets up individual each of the assets independently to as to classify them as either risky assets or risk free assets using the correlation projections. The refinement judges the investment by their return, hence; it operates with the few selected manageable stocks to reduce the portfolio size by ignoring the low return stocks. The tangent portfolio was constructed using the Matlab program. The program uses the data entries from the covariance matrix with the new weights of portfolios. The mean return values and the optimal portfolio variances are shown with the least variance portfolio return averaging approximately 14.6%. After making the entry of the matrix, the exercise is repeated for the reduction of the variance to show the restricted efficient frontier as shown in figure 6 below. The assumption made in the construction of the frontier is that investment can run on negative portfolio weights, even though the current weights are positive. The

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