1. Risk and Capital Budgeting 13 Chapter Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin

2. 13-2 Chapter Outline Concept of risk in capital budgeting Concept of risk averse Risk and rate of return Risk assessment – simulation models and decision trees Impact of individual risky project on total risk of the firm

3. 13-3 Definition of Risk in Capital Budgeting Risk is defined in terms of variability of possible outcomes from a given investment Risk is measured not only in terms of losses but also in terms of uncertainty

4. 13-4 Variability and Risk Three investment proposals illustrated in the following slide All investments in the illustration have the same expected value Investment “C” is the most risky investment owing to its variability

5. 13-5 Variability and Risk (cont’d)

6. 13-6 The Concept of Risk-Averse Risk avoidance unless adequately compensated for Most investors and managers are risk- averse –They prefer relative certainty as opposed to uncertainty –They expect higher value or return for risky investments

7. 13-7 Actual Measurement of Risk Basic statistical devices used –Expected value: D = ∑ DP –Standard deviation: σ = √∑ (D – D) 2 P –Co-efficient of Variation: (V) = σ D

8. 13-8 Probability Distribution of with Differing Degrees of Risk The larger the standard deviation (or spread of outcomes), the greater is the risk

9. 13-9 Probability Distribution with Differing Degrees of Risk (cont’d) Direct comparison of standard deviations would not be helpful in measuring risk if the expected values of the investments are different A standard deviation of $600 with an expected value of $6,000 may indicate less risk than a standard deviation of $190 with an expected value of only $600

10. 13-10 Coefficient of Variation (V) The size difficulty can be eliminated by introducing “Coefficient of Variation” (V) Formula: –Co-efficient of Variation: (V) = σ ÷ D The larger the coefficient of variation, the greater the risk

11. 13-11 Risk measure — Beta (β) A risk measure widely used with portfolios of common stock Measures the volatility of returns on an individual stock relative to returns on a stock market index

12. 13-12 Betas for Five-Year Period (Ending January 2009)

13. 13-13 Risk and the Capital Budgeting Process An informed investor or a manager would differentiate between: –Investments that produce ‘certain’ returns, and –Investments that produce an expected value of return, but have a high coefficient of variation

14. 13-14 Risk-Adjusted Discount Rate Different capital expenditure proposals with different risk levels would require different discount rates –Project with normal amount of risk discounted at the cost of capital –Project with greater than normal risk discounted at higher rate (as shown in the following slide) Risk is assumed to be measured by the coefficient of variation (V)

15. 13-15 Relationship of Risk to Discount Rate This is an example of being increasingly risk-averse at higher levels of risk and potential return

16. 13-16 Increasing Risk over Time Accurate forecasting becomes more obscure farther out in time Unexpected events: –Create a higher standard deviation in cash flows –Increase risk associated with long-lived projects Use of progressively higher discount rates to compensate for risk tends to penalize later cash flows more than earlier ones

17. 13-17 Qualitative Measures Setting up of risk classes based on qualitative considerations This again equates the discount rate to the perceived risk Example of such risk classes illustrated in the following slide

18. 13-18 Risk Categories and Discount rates

19. 13-19 Capital Budgeting Analysis This following table shows Investment B as a preferred investment based on NPV calculation without considering the risk factor Table 13–4

20. 13-20 Capital Budgeting Decision Adjusted for Risk: Example Assumption (Table 13-4): –Investment A calls for an addition to normal product line and is assigned discount rate of 10% –Investment B represents a new product in foreign market and must carry 20% discount rate to adjust for a large risk component

21. 13-21 Capital Budgeting Decision Adjusted for Risk: Example (cont’d) Investment A is the only acceptable alternative after adjusting the risk factor

22. 13-22 Simulation Models Help in dealing with uncertainties involved in forecasting the outcome of capital budgeting projects or other types of decisions –Computers enable the simulation of various economic and financial outcomes using a number of variables A Monte Carlo simulation model uses random variable for inputs –Rely on repetition of the same random process as many as several hundred times

23. 13-23 Simulation Models (cont’d) –Have the ability to test various combinations of events –Are used to test possible changes in variable conditions included in the process –Allow the planner to ask “what if” questions –Are driven by sales forecasts, with assumptions to derive income statements and balance sheets –Generate probability acceptance curves for capital budgeting decisions

24. 13-24 Simulation Flow Chart

25. 13-25 Decision Trees Help lay out a sequence of decisions that can be made Present a tabular or graphical comparison between investment choices Provide an important analytical process

26. 13-26 Decision Trees (cont’d) Assuming that a firm is considering two choices: –Project A: Expanding the production semiconductors for sale to end users –Project B: Entering the highly competitive personal computer market using the firm’s technology –Cost of both projects is $60 million, with different net present value (NPV) and risk Project A: High likelihood of positive rate of return and the long-run growth is a reasonable expectation Project B: Stiff competition may result in loss of more money or higher profit if sales are high

27. 13-27 Decision Trees (cont’d)

28. 13-28 The Portfolio Effect Considers impact of a given investment proposal on the overall risk of firm –A firm planning to invest in the building products industry carrying a high degree of risk Has a primary business in manufacture of electronic components for industrial use The investing firm could alter cyclical fluctuations inherent in its primary business and reduce overall risk exposure The standard deviation for the entire company could be reduced Thus, overall risk exposure of that firm might diminish

29. 13-29 Portfolio Risk Whether a given investment would change the overall risk of the firm depends on its relationship to other investments –Highly correlated investments - do not diversify away risk –Negatively correlated investments - provide high degree of risk reduction –Uncorrelated investments - provide some overall reduction in risk

30. 13-30 Coefficient of Correlation Represents the extent of correlation among various projects / investments –A measure that may take on values anywhere from -1 to +1 –Real world – a more likely measure between -.2 negative correlation and +.3 positive correlation Risk can be reduced by: –Combining risky assets with low or negatively correlated assets

31. 13-31 Coefficient of Correlation : Case of Conglomerate, Inc., and Two Merger Candidates Merger with Negative Correlation, Inc., appears to be the best decision

32. 13-32 Evaluation of Combinations Two primary objectives in choosing combinations: –Achieve the highest possible return at a given risk level –Provide the lowest possible risk at a given return level Determining position of the firm on the efficient frontier: –Willingness to take larger risks for superior returns –Make a conservative selection

33. 13-33 Risk-Return Trade-Offs All the best opportunities will fall along the leftmost sector of the diagram (line C–F–G) Any point to the right is less desirable

34. 13-34 The Share Price Effect Firm risk impacts share prices When firm takes unnecessary or undesirable risks: –Higher discount rate and a lower valuation may be assigned to the stock in the market Higher profits, could have opposite impact on stock price if such profits result from risky ventures –The overall valuation of a firm could decrease with an increase in coefficient of variation, or beta