Part V

2. Part V Prepared by: Nir Yehuda With contributions by Stephen H. Penman – Columbia University Peter D. Easton and Gregory A. Sommers - Ohio State University Luis Palencia – University of Navarra, IESE Business School

3. Chapter 18 Prepared by: Nir Yehuda With contributions by Stephen H. Penman – Columbia University Peter D. Easton and Gregory A. Sommers - Ohio State University Luis Palencia – University of Navarra, IESE Business School

4. What you will learn from 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

5. What you will learn from this chapter (cont.) • 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 betas

6. 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 payoff (or return) distribution

7. Models of the Distribution of Returns: The Normal Distribution

8. Best and Worst Performers, 1998: Wall Street Journal Shareholder Scorecard

9. The Actual Distribution of Annual Stock Returns

10. Diversification and Risk: the Effect on Standard Deviation from Adding More Securities to a Portfolio

11. The Normal Distribution for the S&P 500 Portfolio Mean annual return = 13% Standard deviation of returns = 20%

12. Number of Times Observed -50% -40% -30% -20% -10% 1% 10% 20% 30% 40% 50% The Actual Distribution of S&P 500 Portfolio Annual Returns, 1926-98 Source: Based on data from the Center for Research in Security Prices, University of Chicago

13. The Problems with “Asset Pricing Models” • Risk factors are hard to identify • Risk premiums on risk factors are very hard to measure • Models often assume normal distributions of returns

14. 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 9½%? • 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

15. Fundamental Risk • Risk is determined by a firm’s business • activities and so is understood by analyzing • those activities • A basic distinction: operating and financing risk

16. A Framework for Analysis of Fundamental Risk Risk is the chance of earning poor residual earnings

17. Profitability Risk: The Chance of Getting Poor ROCE

18. The Analysis of Fundamental Risk

19. Expense Risk Operating Leverage Risk The Analysis of Operating Risk RNOA = PM x ATO The Drivers of Operating Risk • PM Risk • ATO Risk • OLLEV Risk

20. The Analysis of Financing Risk The drivers of the financing premium: • Financial Leverage (FLEV) Risk • Borrowing Cost Risk

21. The Analysis of Growth Risk Sales Risk Sales risk is the primary business risk

22. Compounding Risk Factors Produce 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

23. Value-at-Risk Profiles • Value-at-Risk profiles are prepared by developing 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 • Forecast residual operating income for each scenario and, from these forecasts, calculate the set of values from the scenarios

24. Value-at-Risk Profile: Firm A

25. Value-at-Risk Profile: Firm B

26. Value-at-Risk Profiles: Firm A and B

27. Historical Betas

28. Betas revert towards their average of 1.0 Investors are interested in the future beta over the period they hold the investment. High and low historical betas tend to move closer to 1.0 over time. A rough rule for forecasting future betas from historical betas: This adjustment pulls betas towards 1.0.

29. Fundamental Betas: Forecasting Future Betas from Fundamentals Two steps: • Estimate relationship between historical betas and fundamental attributes (say, FLEV and OLEV) in the cross section • Use estimates of b0, b1, and b2 to predict future beta for a firm using the most recent measures of the fundamentals for that firm:

30. Some Fundamental Measures that have been Used to Predict Betas • Earnings variability • Cash flow variability • Size • Growth in earnings or sales • Growth in assets • P/E ratio • P/B ratio • Dividend yield

31. Scenario Planning and Pro Forma Analysis Pro forma analysis can be used to model outcomes for different planning scenarios. Investigate, for example, • Adaptation Options • Growth Options • Strategic Risk Management Options Different future paths can be articulated with pro forma analysis. The value of each path can then be calculated.

32. Price Risk and Fundamental Risk • Fundamental Risk is the risk of value not being realized because of fundamental factors that affect the firm’s activities • Price Risk is the risk of value not being realized in prices because of factors other than fundamentals

33. Price Risk Market Inefficiency Risk The market price may not reflect the “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

34. P C T V C T P V = 0 0 Price Risk:Scenario A and Scenario B Scenario A: Price gravitates to fundamental value Cum-dividend Value P = V C C T T Normal return, Actual return, V 0 Abnormal return, P 0 Time 0 1 2 3 4 T Scenario B: Price deviates from fundamental value Cum-dividend Value Abnormal return, Actual return, Normal return, Time 0 1 2 3 4 T

35. 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 • Brokers • Market makers • Investment banks (“deal makers”) The fees of these specialists are the costs of reducing the liquidity discount

36. Inferring Cost of Capital from Market Prices Given an estimate of growth (g), the cost of capital can be estimated from prices and forecasts of earnings

37. Relative Value Analysis: Evaluating firms within a Risk Class Relative value ratios for firms in same risk class: A relative value ratio of 1.0 implies no arbitrage

38. Perceived Risk

39. Building in a Margin of Safety • Use a high discount rate in evaluating a BUY; use a low discount rate in evaluating a SELL • Be conservative (for a BUY) or optimistic (for a SELL) in forecasting