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Portfolio Management: Maximizing Investment Return

Portfolio Management: Maximizing Investment Return. Team 010 Raja Srinivas Elizabeth Wendel Yelizaveta Yermakova. Introduction.

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Portfolio Management: Maximizing Investment Return

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  1. Portfolio Management: Maximizing Investment Return Team 010 Raja Srinivas Elizabeth Wendel Yelizaveta Yermakova

  2. Introduction “October. This is one of the peculiarly dangerous months to speculate in stocks. The others are July, January, September, April, November, May, March, June, December, August, and February.” – Mark Twain • invest $30,000 for one year • analyze 18 technology stocks • select up to 6 stocks • Three-part problem: • selection of stocks • allocation of funds • suggest ways of testing the model

  3. Research and Ranking 40 % - Free Cash Flow (FCF) 35% - Return on Invested Capital (ROIC) 15% - Price to Sales Ratio (P/S ratio) 10% - Price to Earnings Ratio (P/E ratio) Beta, β

  4. Assumptions • market generally rising • no “cooking the books” • no drastic fluctuation on ROIC value based on “fluke” projects

  5. Basis of Comparison Value * All P/E values given were above 18 with an average of 29. On average the overall market P/E ratio has fluctuated between been 15-25 historically. Therefore, we chose 20 as the optimum value for the P/E ratio. A high P/E ratio can represent an over valued company and vice versa. 20 is thus neither too high nor too low.

  6. BCV Basis of Comparison Value (BCV) • FCF and ROIC - the optimum value is large, thus no correcting factor value was needed • P/S - a smaller value is desirable • the inverse of the P/S ratio used to “correct” • P/E - the value as close to 20 as possible

  7. Incorporating Beta

  8. Summative Table of Results Next step: allocation of funds incorporating beta

  9. Normal Curve Distribution for Number of Shares • a normal bell curve • number of shares purchased proportional to the distance of stock beta to target beta (1.2)

  10. Second Equation Normal bell curve (beta values on the x-axis):

  11. Obtaining Results • plug in specific beta values for the top 6 stocks previously determined • f(ß)/∑f(ß) gives distribution of the number of shares of each stock to be purchased by way of percent

  12. Final Allocation

  13. ROIC AND P/E ANALYSIS • recent results suggest that a relatively high ROIC and relatively low (but not too low) P/E are strong indicators of the value of a stock • new information does not change our final choices

  14. Replacing One of the Indicators • problems with P/E • Return on Earnings (ROE) • same values for the ROE and ROIC • difference - ROIC factors in the debt of the company while ROE does not • our stock choices have little or no debt • decided against including a new indicator

  15. Testing the Model • look at a historical data of a market that had general upwards trend (1997-1998) • apply model • pick stocks • compare to actual performance for validation

  16. Results as of 04/16/07

  17. Bibliography • Basic Chart. Market Watch. 3 Mar. 2007 <http://bigcharts.marketwatch.com/>. • Dictionary. Investopedia. 3 Mar. 2007 <http://www.investopedia.com/>. • Hamilton, Adam. “Standard-Deviation Technicals.” Zeal Speculation and Investment . 12 Dec. 2003. 3 Mar. 2007 <http://www.zealllc.com/‌/.htm>. • Key Statistics. Dow Jones & Company. 3 Mar. 2007 <http://www.smartmoney.com>. • “P/Ratio - Price to Earnings.” Value Based Management. 3 Mar. 2007 <http://www.valuebasedmanagement.net/_PEratio.html>. • Return On Equity. Wikipedia. 3 Mar. 2007 <http://en.wikipedia.org//_on_equity>. • “Stock Market Quotes.” Nonstop English. 3 Mar. 2007 <http://www.nonstopenglish.com///_Stock-Market.asp>.

  18. Thank you for your attention. Are there any questions?

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