Portfolio Management - Case Study Example

Portfolio Management al affiliation: To determine how best the investor is performing is considered to be the major challenge faced. For instance it could be better to see that the portfolio is 15% up, but the question remains how you will know that you could have performed better than this (Harvey et al.2003). The major solution to such kind of problem is creating or finding a benchmark against which the portfolio will be evaluated. Theoretically, the bench mark is required to be appropriate for the investment managers. The big challenge in this case is that its very hard to come up with a bench mark meant for all investors (Scherer 2002). The benchmark created is simple and straightforward in case of measuring the relative performance of the manager investing only in one asset class such as US bond or stocks .It is very tricky in measuring the diversified portfolio’s manager (AggarwalR and Wysocki 2005). In most cases, investors benchmark their portfolio against a stock index such as S&P 500 since they believe that index of this kind are the only which they are familiar with or used in the past by their financial advisors (Brentani 2003). Sharpe Ratio The Sharpe Ratio is known to be generated by William Sharpe who is the Nobel prize co-recipient (modern portfolio Theory award) (Treynor 1965).Basing on this, evaluation of relative attractiveness of portfolios and individual asset classes is calculated as below; Risk-free Asset Optimal Risky portfolio Overall portfolio Return 3.01 13.705 8.56 Risk 0 15.547 9.282 Optimal position 0.28 0.4973 Standard deviation portfolio 10.372578 Basing on the above table, Sharpe ratio is calculated as Expected portfolio return=13.705 Risky free rate =3.01 Portfolio standard deviation = 10.372578 = (13-3.01)/0.10372 =0.96317 Sharpe ratio for S &P500 for 15 years is observed to be 0.19 and the Sharpe ratio of our portfolio is seen to be 0.963.This is a clear indication that our investment portfolio might outperform the S & P 500 by about at least 70 percent basing on the adjusted return. Teynor ratio is seen to be similar to Sharpe Ratio since it is risk-adjusted performance figure. The major difference between the two is that standard deviation is used in Sharpe ratio as the measure of the risk while beta is used in Treynor ratio (Epmc 2013). In this case, Treynor ratio =(RI-Rf)/beta Whereby RI represents the return average rate of the investment and Rf is the risk free rate Beta 0.71 Treynor ratio is 0.83 for our portfolio but for S & P is 0.18.This clearly shows that our portfolio can outperform the S & P portfolio. Basing on the portfolio, it is clear that it can be a good choice for one to invest in the company with such portfolio. Treynor ratio just like Sharpe Ratio is applied in measuring the risk. It is relevant only in situation where there is comparison of two investments. Furthermore, beta is seen to has some weaknesses as a volatility measure. The investment could have a low beta because the measure of beta is the correlation of volatility to the market and the beta value can even be zero but it could be highly volatile in terms of price. In this regard, there might not be a correlation between the investments with the existing benchmark (Carmichael and Pomerleano 2002). Concerning the Investment Fund Investment Fund Rebalancing or Asset Allocation Asset Class Target Minimum Maximum Credit/Intermediate Government 40% 35% 45% Small- cap value equity 6% 3% 9% Emerging market equity 5% 2% 8% Total US equity 30% 25% 35% PORTFOLIO ASSET WEIGHT RETURN CONTRIBUTION Credit/Intermediate Government 0.30 4.2 1.26 Small- cap value equity 0.20 3.7 0.74 Emerging market equity 0.30 6.2 1.86 Total: 3.86 Benchmark -- WEIGHT RETURN CONTRIBUTION OVERWEIGHT PERFORMANCE Credit/Intermediate Government 0.20 6.2 1.240 0.10 -2.0 Small- cap value equity 0.30 3.5 1.050 -0.10 0.2 Emerging market equity 0.20 3.7 0.740 0.10 2.5 Total: 3.550 Total: 0.7 ATTRIBUTION -- SELECTION ALLOCATION INTERACTION Credit/Intermediate Government -0.4 0.62 -0.20 Small- cap value equity 0.06 -0.35 -0.02 Emerging market equity 0.5 0.37 0.25 Total: 0.41 0.46 -- ACTIVE MANAGEMENT EFFECT 0.880 ERROR -0.055 OVER PERFORMANCE 0.825 The above results are seen to be useful in determining if the performance by the manager is through security selection or asset allocation. The analysis results above are required to be compared with the process of the fund manager as well as with the stated mandate of the funds. The above results could also give a clue on the manager’s skills and this could promote the process of portfolio construction of the investor. Sharpe Ratio Basing on this, evaluation of relative attractiveness of portfolios and individual asset classes is calculated as below; Risk-free Asset Optimal Risky portfolio Overall portfolio Return 4.01 11.75 7.46 Risk 3 12.57 8.262 Optimal position 0.31 0.343 Basing on the above table, Sharpe ratio is calculated as Expected portfolio return=11.75 Risky free rate =4.01 Portfolio standard deviation = 8.372578 = (13-3.01)/0.10372 =0.66317 Sharpe ratio for S &P500 for 15 years is observed to be 0.19 and the Sharpe ratio of our portfolio is seen to be 0.663.This is a clear indication that our investment portfolio might outperform the S & P 500 by about at least 50 percent basing on the adjusted return Treynor ratio =(RI-Rf)/beta Whereby RI represents the return average rate of the investment and Rf is the risk free rate Beta 0.61 Treynor ratio is 0.76 for our portfolio but for S & P is 0.18.This clearly shows that our portfolio can outperform the S & P portfolio. Basing on the portfolio, it is clear that it can be a good choice for one to invest in the company with such portfolio. 3 Bond Portfolio Mean Annual Total Returns Date GOOG FORD BAC YHOO AAPL TWTR FB MSFT SIRI PFE Portfolio* 30.06.2014 7.6 14.7 47 2.2 2.5 42.6 40 65.8 64 72.0 35.5 30.12.2014 11.5 57.2 9.4 114 7.7 217 17 6.7 18 202 73.7 30.06.2015 39.3 52 32 59.4 53.7 75.2 22 86.8 63. 71.1 44.9 30.12.2015 28.8 24.5 5.9 28.8 0.1 18.3 15 20.2 11 22.9 4.0 30.06.2016 17.4 1.5 10 4.8 39.3 5.0 26 15.2 10 31 7.7 30.12.2016 10.6 41.8 2.5 67.0 11.8 2.6 3.6 22.0 4.3 151 22.2 30.06.2017 59.1 9.0 34 22.9 32.3 40.1 36 11.4 48 38.4 10.3 ANNUAL RETURN(AVERAGE 24.9 13.4 11 23.1 14.7 17.7 1.0 1.5 10 37.4 15.5 Std Dev 45.4 32.4 23 48.8 24.4 88.1 25.9 43.3 38.4 98.0 33.2% 46.8% CORRELATION MATRIX   GOOG FORD BAC YHOO AAPL TWTR FB MSFT SIRI PFE GOOG 1.0000 FORD 0.8357 1.0000 BAC 0.7284 0.7304 1.0000 YHOO 0.8727 0.9371 0.7274 1.0000 AAPL 0.0598 (0.3921) 0.0434 (0.0968) 1.0000 TWTR 0.8155 0.8299 0.5234 0.7946 (0.2941) 1.0000 FB 0.5725 0.6371 0.7796 0.6661 0.0184 0.6635 1.0000 MSFT 0.6137 0.6483 0.9421 0.5663 (0.0827) 0.4882 0.7857 1.0000 SIRI 0.4409 0.5695 0.7488 0.3698 (0.4099) 0.4400 0.5169 0.7937 1.0000 PFE 0.6607 0.8702 0.5515 0.8533 (0.4202) 0.8670 0.6226 0.4344 0.4690 1.0000 CORRELATION MATRIX   GOOG FORD BAC YHOO AAPL TWTR FB MSFT SIRI PFE GOOG 5.9197 11.5160 37.2715 1.6548 (0.1977) 0.5019 0.3856 0.6816 0.5824 0.5038 FORD 11.5160 22.8317 74.0932 3.1536 (0.3751) 0.6361 0.7463 1.2369 1.0415 0.8582 BAC 37.2715 74.0932 241.2552 9.8756 (1.0334) 1.5106 2.3600 3.8614 3.2553 2.0761 YHOO 1.6548 3.1536 9.8756 0.6027 (0.1297) 0.3577 0.1269 0.2383 0.2123 0.4476 AAPL (0.1977) (0.3751) (1.0334) (0.1297) 0.0519 (0.1145) (0.0206) (0.0476) (0.0352) (0.1710) TWTR 0.5019 0.6361 1.5106 0.3577 (0.1145) 0.6798 0.1090 0.1205 0.1065 0.6268 FB 0.3856 0.7463 2.3600 0.1269 (0.0206) 0.1090 0.0589 0.0565 0.0376 0.1025 MSFT 0.6816 1.2369 3.8614 0.2383 (0.0476) 0.1205 0.0565 0.1643 0.1261 0.0894 SIRI 0.5824 1.0415 3.2553 0.2123 (0.0352) 0.1065 0.0376 0.1261 0.1289 0.1121 PFE 0.5038 0.8582 2.0761 0.4476 (0.1710) 0.6268 0.1025 0.0894 0.1121 0.8404 STANDARD DEVIATION OF PORTFOLIO MINIMIZED RISK MAXIMIZED RETURN Equal- Min Long 0% to 25% 5% to 15% -100% to Long 0% to 25% 5% to 15% Weighted Var Only Weights Weights +100% Only Weights Weights Stock Portfolio Stock Portfolio Portfolio Portfolio Portfolio Stock Portfolio Portfolio Portfolio Portfolio GOOG 10.00% GOOG 43 0.0 0.0 5.0 GOOG 100 0.0 25.0 15.0 FORD 10.0 FORD 87.9 16.9 25.0 15.0 FORD 100 0.0 0.0 15.0 BAC 10.0 BAC 7.72 0.0 0.0 15.0 BAC -100 0.0 0.0 5.0 YHOO 10.0 YHOO 14.0 0.0 0.0 5.0 YHOO 100 0.0 25.0 15.0 AAPL 10.0 AAPL 70.7 59.6 25.0 15.0 AAPL -100 0.0 0.0 5.0 TWTR 10.0 TWTR 18.6 0.0 0.0 5.0 TWTR 100 0.0 25.0 15.0 FB 10.0 FB 28 0.0 25.0 15.0 FB -100 0.0 0.0 5.0 MSFT 10.0 MSFT 1.61 0.0 0.0 5.0 MSFT 0.0 0.0 0.0 5.0 SIRI 10.0 SIRI 5.13 23.3 25.0 15.0 SIRI -100 0.0 0.0 5.0 PFE 10.0 PFE 5.83 0.0 0.0 5.0 PFE 100 100 25 15.0 WEIGHTS(SUM) 100 Sum of Weight 100 100 100 100 Sum of Weight 100 100 100 100 EXPECTED RETURN 117 Expected Return 194 48.7 61.8 151 Expected Return -245 37.3 60.4 104 STANDARD DEVIATION OF PORTFOLIO 242 Std Dev 420 82.4 127 327 Std Dev 820 91 100 204 Limitations of the above analysis undertaken for bond portfolio High interest rates could lead to consideration of alternatives to traditional bond funds that include fixed income that is nontraditional or unconstrained. Funds of such kind are free from constrains emerging from benchmark that gives an opportunity in terms of global markets as well as sectors. Furthermore, derivatives are actively transacted than the traditional core-bond (Levine 2005). The size of fund could influence the way managers transact in credit market as well as in global fixed income. In this case, large funds could gain access through derivatives contracts. References Brentani,C.(2003).Portfolio Management in Practice. Burlington, Elsevier. http://www.123library.org/book_details/?id=33945.Business Review. Carmichael J and PomerleanoM(2002), The Development and Regulation of Non-Bank Financial Institutions, World Bank Epmc, Inc. (2013). Project portfolio management a view from the management trenches. Hoboken, N.J., Wiley. http://rbdigital.oneclickdigital.com. Harvey, Campbell R., John C. Liechty, Merrill W. Liechty, and Peter Müller. (2003). “Portfolio Selection with Higher Moments.” Working Paper, October 16. Levine, H. A. (2005). Project portfolio management a practical guide to selecting projects, managing portfolios, and maximizing benefits. San Francisco, Jossey-Bass. http://site.ebrary.com/id/10301234. Scherer, Bernd. (2002). “Portfolio Resampling: Review and Critique.” Financial Analysts Journal, November/December , 98-109. Treynor Jack L., (1965)."How to Rate Management of Investment Funds", Harvard Read More