Risk Analysis, Real Options, and Capital Budgeting MBAC 6060 Chapter 7 Risk Analysis, Real Options, and Capital Budgeting

Chapter Overview: 7.1 Sensitivity Analysis, Scenario Analysis, and Break-Even Analysis We will cover this section in detail 7.2 Monte Carlo Simulation Just some description 7.3 Real Options 7.4 Decision Trees A simple example

Sensitivity Analysis How sensitive are the calculated values to our estimates? How wrong can we be and still make money? Definition of Sensitivity Analysis Change one variable See how it changes a calculated value OCF, Total CF, NPV, IRR, Working Capital needs…

Scenario Analysis If one thing changes, lots of thing might change Change multiple variables See how this changes a calculated value OCF, Total CF, NPV, IRR, Working Capital needs…

Sensitivity Analysis Example: A machine costs $1,000 It will last 5 years Depreciated straight-line to $0 over its life Sales will be 150 units at $30 per unit Variable costs will be $25 per unit Fixed costs will be $400 per year Tax rate is 30% Required return is 10% Calculate the NPV 

Sensitivity Analysis Example: Cost = $1,000 Years = 5 Dep Exp = 1,000/5 = $200 Units = 150 Price = $30 VC = $25 FC = $400 T = 30% R = 10% OCF = (Sales – Costs)(1 – T) + Dep x T = (30 x 150 – 25 x 150 – 400)(1 - .3) + 200 x .30 = $305 NPV = -PV(rate, nper, pmt, [fv], [type]) - Cost = -PV(0.1,5,305) - 1000 = $156.19 Go to the Simple Sensitivity Analysis Spreadsheet 

Sensitivity Analysis Example Continued: How sensitive is the OCF and NPV to our estimates? How good are the individual forecasts? How important are the forecasts to the success of the project? Things to Consider when looking at the forecasts: What are we forecasting? Revenue: Sales Price per Unit x Units Sold Must consider our sales price, competitors’ sales price… Must consider market size, market share… Costs: fixed, variable, labor, materials… Is it our decisions, competitors’ decisions, government’s decisions… How far in the future are we forecasting? Today? One Year? Ten Years?

Accounting Break-Even First consider the units estimate of 150 per year How many units sold for a positive NI? NI = (Units x Price – Units x VC – FC – Dep)(1 – T) So set NI equal to zero and solve for Units… [Units x (Price – VC) – FC – Dep](1 – T) = 0 Units x (Price – VC) – FC – Dep = 0 Units = (FC + Dep)/(Price – VC) = (400 + 200)/(30 – 25) = 600/5 = 120 Back to the spreadsheet 

Financial (or NPV) Break-Even How many units for a positive NPV? First Estimate (and then use Solver or Goal Seek) NPV at 150 units  $156.19 Re-calc NPV at 151 units  $169.46 ΔNPV/ΔUnits = (169.46 – 156.19)/1 = $13.27 For NPV to change by $13.27, Units change by 1 For NPV to change by $156.19, Units change by 156.19/13.27 = 11.77 If Units = 150 – 11 = 139  NPV > 0 If Units = 150 – 12 = 138  NPV < 0 Back to the spreadsheet 

NPV Break-Even for Each Input Solver and Goal Seek are iterative solvers in Excel   Base Units Price VC FC Cost 1000 Years 5 Dep 200 150 138 30 29.61 25 25.39 400 458.86 Tax 30% R 10% OCF 305 263.80 NPV $156.19 $0.00 %Δ -7.85% -1.31% 1.57% 14.72%

More about Break-Even The text shows how to calculate the break-even point using EAC and algebra I don’t like this method because it only works for simple situations Same sales and costs estimates in each year The Excel-model based methods (Solver or Goal Seek) work for more complex situations We’ll see this in a few minutes with the Baldwin Example…

Scenario Analysis (New Example): 5 Year Project costs $200k Straight-Line to zero with no salvage (Dep = $40k per year) Tax rate is 34%, R = 12% Sales and Cost Estimates (for all 5 years): Unit Sales 6,000 Sale Price per Unit $80 Variable Cost per Unit $60 Fixed Costs $50,000

Scenario Analysis In each year OCF = (Sales – Costs)(1 – T) + Dep x T Sales = 6k x $80 = $480k VC = 6k x $60 = $360k OCF = ($480 – $360 - $50)(1 – 0.34) + $40(0.34) = $59.8

Scenario Analysis Example Continued: CF0 = -$200, CF1 through CF5 = $59.8 NPV @ 12% = $15,566 So how good is our NPV estimate? Forecasting: Units, Sale Price, Unit Cost, Fixed Costs What if we are wrong? We can do sensitivity analysis like before But also try a Scenario Analysis: Best guess for all variables is called the Base Case First forecast Upper Bound and Lower Bound for each variable Second create two new scenarios: Best Case is best of each variable (high revs, low costs) Worst Case is worst of each variable (low revs, high costs)

OCF for the Three Scenarios: First estimate the Upper and Lower Bound for each variable: Next calculate the Best Case (high revs and low costs) and the Worst Case (low revs and high costs):

OCF for the Three Scenarios: Now calculate the OCF for the Best, Base and Worst case: OCF = (Sales – Costs)(1 – T) + Dep x T Best OCF = ($552.5 - $337 - $45)(0.66) + $40(0.34) = $99.73 Base OCF = ($480 - $360 - $50)(0.66) + $40(0.34) = $59.8 Worst OCF = ($412.5 - $341 - $55)(0.66) + $40(0.34) = $24.49 Note that OCF is the same in each year of the project

NPV for the Three Scenarios: Best: CF0 = -$200, CF1 through CF5 = $99.73, NPV = $159.50 Base: CF0 = -$200, CF1 through CF5 = $59.80, NPV = $15.57 Worst: CF0 = -$200, CF1 through CF5 = $24.49, NPV = -$111.72 These scenarios use the “best” and “worst” of the “upper” and “lower” bounds of the variable estimates That is why they are called the “Best Case” and “Worst Case” Obviously not the best and worst possible outcomes Go to “Scenario Example” tab on spreadsheet 

Baldwin Example (From Chapter 6) Bowling balls will be manufactured for 5 years Use a building with market value of $150,000 Building market value will be $150,00 after this project The cost of the bowling ball machine is $100,000 Market value of machine in five years is $30,000 Units per year: 5,000, 8,000, 12,000, 10,000 and 6,000 Price of bowling is $20 and will increase at 2% per year VC is $10, increase at 10% per year Tax Rate is 34% NWC of $10,000 is required at time zero NWC at year end will equal 10% of sales for that year NWC will decline to $0 at project’s end Cost of Capital (Required Rate) = 10% Lets consider these estimates 

Baldwin Example How important are the assumptions : Market value of the machine in 5 years ($30,000)? Market value of the building in 5 years ($150,000)? Price ($20) and Price Growth (2%)? VC ($10) and VC Growth (10%)? NWC assumptions? The Tax Rate? The Discount Rate? Go to “Baldwin Model” tab 

7.2 Monte Carlo Simulation Program the NPV model and Identify the Variables Market Size, Market Share, Price, VC, FC… Define a Distribution for each variable: One possible Distribution for Market Share: 20% probability of 2% market share 60% probability of 4% market share 20% probability of 5% market share Anther possible Distribution for Market Share: Market share will be Normally Distributed with a 4.0% mean and a 0.5% standard deviation Define the Interactions Between Variables If Market Size and Price are both related to economic growth Set 40% correlation between them

Monte Carlo Simulation Plug all this into Monte Carlo simulation software Crystal Ball, @Risk… The machine “draws” values for each variable It then calculates an NPV using the programed model Then it starts over Draws new values for each variable Calculates a new NPV After 10,000 draws, you have distribution of NPVs (or OCFs, Total CFs,…) From the distribution, calculate an Expected NPV and Distribution Statistics

Monte Carlo Simulation Results Figure 7.4 , Page 218 (Distribution of Total Cash Flows from year 3)

7.3 Real Options Managerial Options: Not just accept or reject: Managers can wait See what competitors do See what government will do If a five-year project is losing money after 2 years If it is the worst case scenario QUIT! Or reduce the scale If it’s making money after 2 years: If it is the best case scenario EXPAND! Or extend the life of the project Options on Real Assets are called “Real Options”

7.4 Decision Trees A decision tree is a graphical representation of alternatives Example: A company has developed a new product If the product is successful (50% chance) the NPV at time of product launch is $22m If the product fails (50% chance) the NPV at time of product launch is $9m The company can delay the launch for one year and spend $1.5m to test market the project Test marketing would increase the probability of a successful product to 80% The discount rate is 11%

Decision Tree 80% prob of NPV = $22 Delay 1 year 20% prob of NPV = $9 Test (Pay $1.5) 50% prob of NPV = $22 If you don’t invest, the NPV = 0, even if you test first, because the cost of testing becomes a sunk cost. If you are so unwise as to invest in the face of a failed test, you incur lots of additional costs, but not much in the way of revenue, so you have a negative NPV as of date 1. Referring back to slide 7 (Decision to Test) may help to clarify the application of decision trees. Not Test (Launch) 50% prob of NPV = $9

Calculate NPV of Each Choice: NPV of going directly to market (Not Test) 50% chance of $22, 50% chance of $9 NPV = 0.50 x $22 + 0.50 x $9 = $15.5 NPV of Test Marketing First Pay $1.5 at time 0 to increase probability of launch-time NPV of $22 to 80% Delay launch date one year So must discount launch-time NPV by 11% NPV = -$1.5 + [(.80 x $22) + (.2 x $9)]/1.11 = -$1.5 + [$19.40]/1.11 = -$1.5 + $17.48 = $15.98

Decision: “Not Test” NPV = $15.5 “Test Market” NPV = $15.98 So better to pay $1.5 and delay launch in order to increase probability of a successful product.

Capital Rationing A firm or division may have limited resources Soft rationing When business units are allocated only a certain amount of capital by management Hard rationing When a firm is unable to raise the capital

Where do we go from here? We have been looking at Capital Budgeting Decisions Using the NPV Framework: We looked at the numerators Now we will look at the denominators What is the correct discount rate? How much does the firm need to earn on its projects? How much do investors require the firm to earn? What does it cost the firm to raise money (its cost of capital)? We’ll start with terminology and pricing models for bonds and stocks Then move to risk and return The calculations and tradeoffs Then we’ll look at the financing mix for a company Sell ownership stakes or borrow?