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ACCY 302 (Chen) Fall 2009, Class 27 1 Objectives for today Using a simple example, understand:  Decision trees what they are drawing them using them to evaluate alternatives Is gathering additional information worth the cost? value of perfect information value of imperfect information efficiency of imperfect information Uncertainty & sensitivity analyses

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ACCY 302 (Chen) Fall 2009, Class 27 2 Decision trees - What they are A roadmap of a decision problem  Provides a  chronological  depiction of: action choices (alternatives) uncertainties states of nature probabilities outcomes "Chronological" is key!
ACCY 302 (Chen) Fall 2009, Class 27 3 Decision trees - Drawing them 1) Draw a tree of the decision alternatives  (squares)  using  available information: possible states of nature  (circles) their probabilities of occurrence the outcomes for those states 2) If you may obtain further information, include other  "limbs"  (or use more trees)  to determine if it's cost-effective  to do so 3) Remember that in some cases, "do nothing" is an  alternative!

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ACCY 302 (Chen) Fall 2009, Class 27 4 Decision trees - Using them to evaluate  alternatives Determine the optimal decision: 1) identify decision criteria usually expected monetary value (EV) 2) apply backwards induction “fold back” and "prune" the tree compute EV at each circle choose the optimal EV branch at each square by trimming the  other EV branches 3) think about "unquantifibles" - e.g., strategy, customers, uncertainty, sensitivity
ACCY 302 (Chen) Fall 2009, Class 27 5 Decision trees - A simple example Donald Frump, a real estate developer, has the opportunity to  purchase land that is currently zoned residential. If the county board  approves  a request to rezone the property  as commercial within the next year, Frump will be able to  lease the land to Schmuck's, a supermarket chain that  wants to open a new store on the property. However, if the zoning change is  not approved , Frump will  have to sell the property at a loss.

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ACCY 302 (Chen) Fall 2009, Class 27 6 Decision trees - A simple example  (continued) Frump's potential profits are shown in the following payoff  table.   Decision alternatives: States of Nature Rezoning approved (s 1 ) Rezoning not approved (s 2 ) Purchase (d 1 ) Don't purchase (d 2 ) If the probability that the rezoning will be approved is 0.50,  what decision would you recommend to Frump, and what is the  expected profit?
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