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Problem 4.15 A stock market investor has $500 to spend and is considering purchasing an option contract on 1000 shares of Apricot Computer. The shares themselves are currently selling for $28.50 per share. Apricot is involved in a lawsuit, the outcome of which will be known within a month. If the outcome is in Apricot’s favor, analysts expect Apricot’s stock price to increase by $5 per share. If the outcome is unfavorable, then the price is expected to drop by $2.75 per share. The option costs $500, and owning the option would allow the investor to purchase 1000 shares of Apricot stock for $30 per share. Thus, the investor buys the option and Apricot prevails in the lawsuit, the investor would make an immediate profit. Asides from purchasing the option, the investor could (1) do nothing and earn about 8% on his money, or (2) purchase $500 worth of Apricot shares.
Construct cumulative risk profiles for the three alternatives, assuming Apricot has a 25% chance of winning the lawsuit. Can you draw any conclusions? To construct risk profiles (cumulative or not cumulative), we have to first draw the decision tree Assumptions: 1) 8% is the monthly interest rate; 2) the investor can only purchase an integer number of shares and put the remaining money to savings (0.25) Favorable $3,000 1000*($33.50-$30.00) =$3,500 Purchase Option -$500 (0.75) Unfavorable Lawsuit Outcome -$500 $0 Do Nothing $40 $500*8%=$40 (0.25) Favorable $86.24 17*$33.50 + $15.5*8% =$570.74 Buy Stock -17*$28.5= -$484.5 (0.75) Unfavorable Lawsuit Outcome -$45.51 17*$25.75 + $15.5*8% =$438.99
Favorable (0.25) Probabilities 0.75 0.25 Probabilities 1 Probabilities 0.75 0.75 $3,000 Payoffs $40 Payoffs -$45.51 $86.24 Payoffs -$500 $3,000 Purchase Option (0.75) Unfavorable -$500 Do Nothing $40 (0.25) Favorable $86.24 Buy Stock (0.75) Unfavorable -$45.51 Decision Strategies: 1) Purchase option 2) Do nothing 3) Buy stock
-45.51 86.24 40 Return on Investment
86.24 -45.51 40 Therefore, no immediate conclusions can be drawn since no one alternative dominates another
b. If the investor believes that Apricot stands a 25% chance of winning the lawsuit, should he purchase the option? What if he believes the chance is only 10%? How large does the probability have to be for the option to be worthwhile? Assuming 8% is the monthly interest rate and let p be the probability that Apricot will win the lawsuit 1) The expected monetary value associated with purchasing the option is: EMV(Purchase Option) = 3,000p – 500(1 – p) = 3,500p – 500 2) The expected monetary value associated with doing nothing is: EMV(Do Nothing) = 40 3) The expected monetary value associated with purchasing the stock is: EMV(Buy Stock) = 86.24p – 45.51(1 – p) = 131.75p – 45.51. When p=0.25, EMV(Purchase Option) = $375, EMV(Do Nothing)=$40, EMV(Purchase Stock) = $-12.57 When p=0.1, EMV(Purchase Option) = -$150, EMV(Do Nothing)=$40, EMV(Purchase Stock) = $-32.33 EMV(Purchase Option) > EMV(Do Nothing) 3500p-500>40 p>0.154 EMV(Purchase Option) > EMV(Buy Stock) 3500p-500>131.75p-45.51 p>0.135 p>0.154
Job Offers Robin Pinelli is considering three jobs. In trying to decide which to accept, Robin has concluded that three objectives are important to this decision. First, of course, is to maximize disposable income – the amount left after paying for housing, utilities, taxes, and other necessities. Second, Robin likes cold weather and enjoys winter sports. The third objective relates to the quality of the community. Being single, Robin would like to live in a city with a lot of activities and a large population of single professionals. Developing attributes for these three objectives turn out to be relatively straightforward. Disposable income can be measured directly by calculating monthly take-home pay minus average monthly rent (being careful to include utilities) for appropriate apartment. The second attribute is annual snowfall. For the third attribute, Robin has located a magazine survey of large cities that scores those cities as places for single professionals to live. Although the survey is not perfect from Robin’s point of view, it does capture the main elements of her concern about the quality of the singles community and available activities. Also, all three of the cities under consideration are included in the survey.
Magazine Rating Income Rating Snowfall Rating Disposable Income Magazine Snowfall 100 (0.15) 56 75 25 $1,500 200 (0.70) 50 56 75 50 400 (0.15) (0.6) 56 75 100 Madison Publishing 100 (0.15) 56 25 25 $1,300 200 (0.70) 56 25 50 (0.4) 400 (0.15) 56 25 100 150 (0.15) 0 100 37.5 MPR Manufacturing 230 (0.70) $1,600 75 0 100 57.5 320 (0.15) 80 0 100 Pandemonium Pizza $1,200 0 100 0 0 95 * The gray numbers are not in the original decision tree shown in the textbook
1. Verify the ratings in the consequence matrix are proportional scores To do a tradeoff analysis, we have to first make sure different attributes have comparable measures Convert the measures of three attributes – income, snowfall, and magazine score – to the scale of 0-100. Income: Set $1600 = 100, $1200 = 0. For an intermediate value x , its converted score = (x-min)/(max-min) = (x-1200)/(1600-1200) When x =$1300, (1300-1200)/(1600-1200)=25%, so its converted score is 25. When x =$1500, (1500-1200)/(1600-1200)=75%, so its converted score is 75. Snowfall: set 400 =100, 0=0. For an intermediate value x , its converted score = (x-0)/(400-0) When x = 100, (100-0)/(400-0)=25%, so its converted score is 25. When x = 150, (150-0)/(400-0)=37.5%, so its converted score is 37.5. When x = 200, (200-0)/(400-0)=50%, so its converted score is 50. When x = 230, (230-0)/(400-0)=57.5%, so its converted score is 57.5. When x = 320, (320-0)/(400-0)=80%, so its converted score is 80.
Magazine Score: Set 95=100, 50=0 For an intermediate value x , its converted score = (x-50)/(95-50) When x = 75, (75-50)/(95-50)≈56%, so its converted score is about 56.
3. After considering the situation, Robin concludes that the quality of he city is most important, the amount of snow is next, and third is income. Furthermore, Robin concludes that the weight for the magazine rating in consequence matrix should be 1.5 times the weight for the snowfall rating and three times as much as the weight for the income rating. Use this information to calculate the weight for the three attributes and do calculate overall scores for all of the end of branches in the decision tree. Denote the weights of income, snowfall or magazine as Ki, Ks, and Km, respectively. Km= 1.5Ks,Km = 3Ki, and Km+ Ks + Ki= 1. Solving the equations, we can get Km= 1/2, Ks= 1/3, and Ki = 1/6
Original Income Income Rating $1,500 75 (0.6) Madison Publishing $1,300 25 (0.4) MPR Manufacturing $1,600 100 Pandemonium Pizza $1,200 0 4. Analyze the decision tree using expected values. Calculate expected values for the three measures as well as for the overall score There is an expected value (EV) for each attribute in each job Income: • For Madison EV(Income) = $1500*0.6+$1300*0.4=$1,420 Or at the converted scale, EV(Income) = 75*0.6+25*0.4=55 • For MPR EV(Income) = $1,600 (Constant) Or at the converted scale, EV(Income) = 100 • For Pandemonium EV(Income) = $1,200 (Constant) Or at the converted scale, EV(Income) = 0
Snowfall Rating Snowfall 100 (0.15) 25 200 (0.70) 50 400 (0.15) 100 (0.6) Madison Publishing 100 (0.15) 25 50 200 (0.70) (0.4) 400 (0.15) 100 100*0.15+200*0.7+400*0.15 E(U2)= 150 (0.15) 37.5 MPR Manufacturing 230 (0.70) 57.5 320 (0.15) 80 Pandemonium Pizza 0 0 Snowfall: • For Madison EV(Snowfall) = (100*0.15+200*0.7+400*0.15)*0.6 + (100*0.15+200*0.7+400*0.15)*0.4 =215 100*0.15+200*0.7+400*0.15 E(U1)= U1 E(U)=0.6*E(U1)+0.4*E(U2) U Or at the converted scale, EV(Snowfall) = (25*0.15+50*0.7+100*0.15)*0.6 + (25*0.15+50*0.7+100*0.15)*0.4 =53.75 U2 • For MPR EV(Snowfall) =150*0.15+230*0.7+320*0.15=231.5 Or at the converted scale, EV(Snowfall) =37.5*0.15+57.5*0.7+80*0.15=57.875 • For Pandemonium EV(Snowfall) = 0 (Constant) Or at the converted scale, EV(Snowfall) = 0
Overall Score 49*0.15+57*0.7+74*0.15 E(U1)= 49 (0.15) (0.70) 57 (0.15) (0.6) 74 41*0.15+49*0.7+66*0.15 E(U2)= Madison Publishing (0.15) 41 (0.70) 49 (0.15) (0.4) 66 (0.15) 29 (0.70) 36 MPR Manufacturing (0.15) 43 Pandemonium Pizza 50 Magazine Score: • For Madison EV(magazine) = 50 (Constant) Or at the converted scale, EV(magazine) = 56 • For MPR EV(magazine) = 75 (Constant) Or at the converted scale, EV(magazine) = 0 • For Pandemonium EV(magazine) = 95 (Constant) Or at the converted scale, EV(magazine) =100 Overall Score: • For Madison EV(Overall) = (49*0.15+57*0.7+74*0.15)*0.6 + (41*0.15+49*0.7+66*0.15)*0.4 =55 U1 E(U)=0.6*E(U1)+0.4*E(U2) U • For MPR U2 EV(Overall) =29*0.15+36*0.7+43*0.15=36 • For Pandemonium EV(Overall) = 50 (Constant)
Income: Decision Strategies: 1) Madison Publishing $1,500 Probabilities 0.4 0.6 Income $1,300 $1,500 (0.6) Madison Publishing $1,300 Probabilities 1 Probabilities 1 Income $1,200 Income $1,600 (0.4) 2) MPR 3) Pandemonium 5. Do a risk-profile analysis of the three cities. Create risk profiles for each of three attributes as well as the overall score. Does any additional insight arise from this analysis?
Pandemonium MPR Madison Publishing Risk Profiles of Income
Cumulative Risk Profiles of Income Madison Publishing MPR Pandemonium MPR stochastically dominates Madison which stochastically dominates Pandemonium
100 (0.15) 200 (0.70) 400 (0.15) (0.6) Probabilities 0.15 0.70 0.15 Snowfall 150 230 320 Madison Publishing 100 (0.15) 200 (0.70) (0.4) 400 (0.15) 150 (0.15) Probabilities 1 Snowfall 0 MPR Manufacturing 230 (0.70) 320 (0.15) Snowfall: Decision Strategies: 1) Madison Publishing Probabilities 0.6*0.15+0.4*0.15=0.15 0.6*0.70+0.4*0.70=0.70 0.6*0.15+0.4*0.15=0.15 Snowfall 100 200 400 2) MPR 3) Pandemonium
Risk Profiles of Snowfall Madison Publishing MPR Pandemonium
Cumulative Risk Profiles of Snowfall Madison Publishing MPR Pandemonium Both MPR and Madison stochastically dominates Pandemonium but no domination relation between MPR and Madison
Probabilities 1 Probabilities 1 Probabilities 1 Magazine 50 Magazine 75 Magazine 95 Magazine Score: Decision Strategies: 1) Madison Publishing 2) MPR 3) Pandemonium
Risk Profiles of Magazine Score Madison Publishing MPR Pandemonium
Cumulative Risk Profiles of Magazine Score Madison Publishing MPR Pandemonium Pandemonium stochastically dominates MPR which stochastically dominates Madison
49 (0.15) Probabilities 1 (0.70) 57 Magazine 50 (0.15) (0.6) 74 Probabilities 0.15 0.70 0.15 Probabilities 0.4*0.15=0.06 0.6*0.15+0.4*0.70=0.37 0.6*0.7=0.42 0.4*0.15=0.06 0.6*0.15=0.09 Overall 29 36 43 Overall 41 49 57 66 74 Madison Publishing (0.15) 41 (0.70) 49 (0.15) (0.4) 66 (0.15) 29 MPR Manufacturing (0.70) 36 (0.15) 43 Overall Score: Decision Strategies: 1) Madison Publishing 2) MPR 3) Pandemonium
Risk Profiles of Overall Score Madison Publishing MPR Pandemonium
Cumulative Risk Profiles of Overall Score Madison Publishing MPR Pandemonium Madison and Pandemonium stochastically dominates MPR, but there is obvious domination relationship between Madison and Pandemonium