1 / 18

ENGM 661

ENGM 661. Risk Analysis with @ Risk. A 1 A 2 A 3. 3. ,. 000. p. . 1. /. 4. . . A i. . 4. ,. 000. p. . 1. /. 2. . 1 2 3. . 5. ,. 000. p. . 1. /. 4. . 10,000. Class Problem.

river
Download Presentation

ENGM 661

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ENGM 661 Risk Analysis with @ Risk

  2. A1 A2 A3 3 , 000 p  1 / 4   Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Class Problem Suppose we have the following cash flow diagram (MARR = 15%). Determine if the project is worthwhile.

  3. A1 A2 A3 3 , 000 p  1 / 4   Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Central Limit Theorem Preliminary

  4. A1 A2 A3 3 , 000 p  1 / 4   Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Central Limit Theorem Distribution of NPW

  5. A1 A2 A3 3 , 000 p  1 / 4   - = 867 E [ NPW ] Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Central Limit Theorem Distribution of NPW

  6. A1 A2 A3 3 , 000 p  1 / 4  N(-867, 938)  - = 867 E [ NPW ] Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 -3,681 -867 1,947 Central Limit Theorem Distribution of NPW σ = 938

  7. A1 A2 A3 N(-867, 938) 1 2 3 10,000 -3,681 -867 1,947 Central Limit Theorem Distribution of NPW P {NPW>0 = P {(NPW-u)/σ > (0- (-867))/938 = P{Z>.92} = 1- P{Z<.92} = .178

  8. P{NPW >0} = .031 .063 .031 .016 .031 .016 .188

  9. Analytic P{NPW > 0} = 0.188 C.L.T. P{NPW > 0} = 0.178

  10. A1 A2 A3 3 , 000 p  1 / 4   Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Simulation

  11. A1 A2 A3 3 , 000 p  1 / 4   Ai  4 , 000 p  1 / 2  1 2 3  5 , 000 p  1 / 4  10,000 Simulation

  12. Simulation

  13. Simulation

  14. Simulation P{NPW > 0} = 5/20 = 0.25

  15. Simulation Analytic P{NPW > 0} = 0.188 C.L.T. P{NPW > 0} = 0.178 Simulation P{NPW > 0} = 0.25

  16. @Risk

  17. @Risk Analytic P{NPW > 0} = 0.188 C.L.T. P{NPW > 0} = 0.178 Simulation P{NPW > 0} = 0.25 @Risk P{NPW > 0} = 0.20 Next WEEK

More Related