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Financial Statement Analysis and Security Valuation Stephen H. Penman

Financial Statement Analysis and Security Valuation Stephen H. Penman. Prepared by Peter D. Easton and Gregory A. Sommers Fisher College of Business The Ohio State University With contributions by Stephen H. Penman – Columbia University

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Financial Statement Analysis and Security Valuation Stephen H. Penman

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  1. Financial Statement Analysisand Security ValuationStephen H. Penman Prepared by Peter D. Easton and Gregory A. Sommers Fisher College of Business The Ohio State University With contributions by Stephen H. Penman – Columbia University Luis Palencia – University of Navarra, IESE Business School

  2. The Analysis of Equity Risk and the Cost of Capital Chapter 20

  3. Chapter 20 Page 685 What You Will Learn in This Chapter • That precise measures of the cost of capital are difficult to calculate • What risk is • How business investment can yield extreme (high and low) returns • How diversification reduces risk • Problems with using the standard Capital Asset Pricing Model and other beta technologies • The difference between fundamental risk and price risk • The determinants of fundamental risk • The determinants of price risk • How fundamental analysis protects against price risk • How pro forma analysis can be adapted to prepare value-at-risk profiles • How fundamentals help to measure predicted betas

  4. Chapter 20 Page 686 The Nature of Risk • Value is determined by expected payoffs discounted for risk • Risk is determined by the likelihood of getting payoffs that are different from the expected payoff • Risk is characterized by the set of possible outcomes that an investor faces and the probabilities of these outcomes: a return distribution

  5. Chapter 20 Page 688 Figure 20.1 Models of the Distribution of Returns: The Normal Distribution With a normal distribution, there is a 68.26% probability that a return will be within one standard deviation of the mean and a 95.44% probability that a return will be within two standard deviations of the mean.

  6. The Wall Street Journal Shareholder Scorecard: Best and Worst Performers, 1998 The Best PerformersThe Worst Performers Amazon.com Inc. +966.4% Sunbeam Corp.  83.7% Network Solutions Inc. +896.8 MedPartners Inc.  76.5 Metromedia Fiber Network Inc. +706.1 Parker Drilling Co.  73.8 CMGI Inc. +604.1 Agco Crop.  73.0 America Online Inc. +585.6 Harnischfeger Industries Inc.  70.4 Yahoo! Inc. +584.3 IKON Office Solutions Inc.  69.2 MindSpring Enterprises Inc. +444.8 Venator Group Inc.  68.1 Infoseek Corp. +359.3 ENSCO International Inc.  67.9 Earthlink Network Inc. +342.7 Rowan Companies Inc.  67.6 Dell Computer Corp. +248.5 Santa Fe International Corp.  64.2 Best Buy Co. +232.9 Case Corp.  63.7 Century Communications Corp. +225.3 Global Marine Inc.  63.4 Apple Computer Inc. +211.9 Weatherford International Inc.  62.6 EMC Corp. +209.8 Union Pacific Resources Group Inc.  62.1 Lagato Systems Inc. +199.7 Thermo Electron Corp.  61.5 At Home Corp. +195.5 Polaroid Corp.  60.9 Level 3 Communications Inc. +191.4 Baker Hughes Inc.  59.0 EchoStar Communications Corp. +188.8 Starwood Hotels & Res. Worldwide  58.8 International Network Services +187.6 Security Capital Group Inc.  58.3 Excite Inc. +180.4 Sensormatic Electronics Corp.  57.8 Lucent Technologies Inc. +175.9 Noble Drilling Corp.  57.8 Lycos Inc. +168.6 Tidewater Inc.  57.4 Ascend Communications Inc. +168.4 Nabors Industries Inc.  57.3 Allegiance Corp. +165.2 Thermo Instrument Systems Inc.  56.3 Lexmark International Corp. +164.5 UCAR International Inc.  55.4 Chapter 20 Page 686 Table 20-1

  7. Chapter 20 Page 688 Figure 20.1 Comparing Actual Returns withthe Normal Model: TheEmpirical Distribution of Returns

  8. Chapter 20 Page 690 Figure 20.2 Diversification of Risk The effect on the standard deviation of return from adding more securities to a portfolio

  9. Chapter 20 Page 689 Figure 20.1 The Normal Distribution of Returns for a Portfolio: The S&P 500 The normal distribution of annual returns on the S&P 500 stock portfolio with a mean of 13% and a standard deviation of 20%

  10. Chapter 20 Page 689 Figure 20.1 The Empirical Distribution ofAnnual Stock Returns forPortfolios: The S&P 500 • The empirical distribution of annual returns for the S&P 500 stock portfolio, 1926-1998 Source: Based on data from the Center for Research in Security Prices, University of Chicago

  11. Chapter 20 Page 691 The Problems with “AssetPricing Models” (see also Chapter 3) • Risk factors are hard to identify • Risk premiums on risk factors are hard to measure • Often assume normal distributions of returns

  12. Chapter 20 Page 691 The CAPM is “Seductively Precise” • Normally distributed stock returns are assumed • The market risk premium is a big guess Is it 3½%, 4½%, 8%, or 9 ½%? • Has the market risk premium declined in the 1990s? • Betas are estimated with error • Estimates of the cost of capital are made from market prices and assume that the market is efficient

  13. Chapter 20 Page 693 Fundamental Risk • Risk is determined by the firm’s business activities and so is understood by analyzing these activities • A basic distinction: operating and financing activities Operating risk Financing risk premium

  14. Chapter 20 Page 693 A Framework for Analysisof Fundamental Risk Profitability Risk Growth Risk Risk is the chance of not getting the forecasted residual earnings

  15. Chapter 20 Page 695 Profitability Risk: The Chance ofNot Getting Forecasted ROCE The Drivers: Operating risk Financing risk

  16. Chapter 20 Page 694 Figure 20.3 Analysis of Fundamental Risk

  17. Chapter 20 Page 695 Analysis of Operating Risk The Drivers of Operating Risk: • PM Risk • ATO Risk • OLLEV Risk

  18. Chapter 20 Page 695 Financing Risk Drivers of Financing Premium: • Financial leverage (FLEV) risk • Borrowing cost risk

  19. Chapter 20 Page 696 Growth Risk Sales risk • Sales risk is the primary business risk

  20. Chapter 20 Pages 696-698 Compounding Risk FactorsProduce Extreme Returns A drop in sales is compounded by PM risk, ATO risk, FLEV risk and NBC risk • The effect of a drop in sales is magnified by expense risk • The effect of a drop in sales is magnified by operating leverage risk • The effect of a drop in sales is magnified by asset turnover risk • The effect of a drop in sales is magnified by OLLEV risk • The effect of a drop in sales is magnified by FLEV risk • The effect of a drop in sales is magnified by borrowing cost risk

  21. Chapter 20 Page 697 Getting a Feel for the Distributionof Returns: Value-at-Risk Profiles • Value-at-Risk Profiles are prepared using pro formas for different scenarios. The outcomes in these pro formas are determined by the risk factors • Steps to prepare Value-at-Risk Profiles • Identify economic factors that affect the risk drivers • Identify risk protection mechanisms in place within the firm • Identify the effect of economic factors on the fundamental risk drivers • Prepare pro forma financial statements under alternative scenarios for the fundamental risk drivers in the future • Calculate projected residual operating income for each scenario and, from these projections, calculate the set of values from the scenarios

  22. Chapter 20 Page 699 Table 20-2 Value-at-Risk Profile for Two Firms Firm A Scenario 1 2 3 4 5 6 7 Factor: GDP growth 1% 0% 1% 2% 3% 4% 5% Probability of scenario 0.1 0.1 0.2 0.2 0.2 0.1 0.1 Fundamentals affected Sales ($ million) 25 50 75 100 125 150 175 Operating expenses ($ mil) Fixed costs 20 20 20 20 20 20 20 Variable costs 18 36 54 72 90 108 126 Total expenses 38 56 74 92 110 128 146 Operating income ($ million) 13 6 1 8 15 22 29 Profit margin 52% 12% 1.3% 8.0% 12% 14.7% 16.6% Asset turnover 0.63 1.03 1.30 1.50 1.65 1.77 1.87 RNOA 32.7% 12.3% 1.7% 12.0% 19.8% 26.0% 30.9% Beginning NOA ($ million) 39.7 48.7 57.7 66.7 75.7 84.7 93.7 ReOI (R=1.06) 15.4 8.9 2.5 4.0 10.5 16.9 23.4 Value with limited liability 40 49 16 133 251 366 484 PM risk driver: Operating expense = 20 + 72% of sales ATO risk driver: Net operating assets = 30.7 + 36% of sales

  23. Chapter 20 Page 699 Table 20-2 Value-at-Risk Profile for Two Firms Firm B Scenario 1 2 3 4 5 6 7 Factor: GDP growth 1% 0% 1% 2% 3% 4% 5% Probability of scenario 0.1 0.1 0.2 0.2 0.2 0.1 0.1 Fundamentals affected Sales ($ million) 25 50 75 100 125 150 175 Operating expenses ($ mil) Fixed costs 4 4 4 4 4 4 4 Variable costs 22 44 66 88 110 132 154 Total expenses 26 48 70 92 114 136 158 Operating income ($ million) 1 2 5 8 11 14 17 Profit margin 4% 4% 6.7% 8.0% 8.8% 9.3% 9.7% Asset turnover 0.81 1.17 1.37 1.50 1.59 1.65 1.70 RNOA 3.3% 4.7% 9.1% 12.0% 14.0% 15.4% 16.6% Beginning NOA ($ million) 30.7 42.7 54.7 66.7 78.7 90.7 102.7 ReOI (R=1.06) 2.8 0.6 1.7 4.0 6.3 8.6 10.8 Value with limited liability 31 33 83 133 184 234 283 PM risk driver: Operating expense = 4 + 88% of sales ATO risk driver: Net operating assets = 18.7 + 48% of sales

  24. Chapter 20 Page 701 Adaptive Pro Forma Analysis • Adaptation Options • Growth Options • Strategic Risk Management • Scenario Planning

  25. Chapter 20 Page 705 Price Risk and Fundamental Risk • Fundamental Risk is the risk of value not being realized because of fundamental factors that affect the firms activities • Price Risk is the risk of value not being realized in prices because of factors other than fundamentals

  26. Chapter 20 Page 705 Price Risk • Market Inefficiency Risk The market price may not reflect “fundamental value” • Scenario A risk • Scenario B risk Fundamental analysis reduces Scenario A risk, but Scenario B risk can still affect a diligent fundamental investor

  27. Chapter 20 Page 706 Liquidity Risk Liquidity risk is the risk of not finding a buyer or seller at the fundamental price • Liquidity discounts • Mechanisms to reduce liquidity risk

  28. Chapter 20 Page 707 Inferring Risk from Market Prices Required return can be inferred if growth rate, g, is forecasted Review: J. Claus and J. Thomas, “The Equity Risk Premium is Much Lower than You Think It Is: Empirical Estimates from a New Approach,” Working paper, Columbia University, 1998. W. Gebhardt, C. Lee and B. Swaminathan, “Towards an Ex Ante Cost-of-Capital,” Working paper, Cornell University, 1999. P. Easton, G. Taylor, P. Shroff, and T. Sougiannis, “Estimating Cost of Capital and Growth Using Forecasts of Profitability,” Working paper, The Ohio State University, 1999.

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