1 / 11

LEARNING NOTE 11.4

LN11.4. LEARNING NOTE 11.4. Incorporating uncertainty into the d ecision- m aking process. LN11.4 (1). RISK AND UNCERTAINTY 1. Probabilities are used to measure the likelihood that an event or state of nature will occur.

kasa
Download Presentation

LEARNING NOTE 11.4

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. LN11.4 LEARNING NOTE 11.4 Incorporating uncertainty into the decision-making process

  2. LN11.4 (1) RISK AND UNCERTAINTY 1. Probabilities are used to measure the likelihood that an event or state of nature will occur. 2. A probability distribution lists all possible outcomes for anevent and the probability that each will occur: Student A Student B probability probability Outcome: Pass examination 0.9 0.6 Do not pass 0.10.4 1.01.0 3. Probability distributions provide more meaningful information than stating the most likely outcome (i.e. bothstudents will pass).

  3. LN11.4 (2a) • Instead of presenting probability distributions for eachalternative, two summary measures are often used: • (i) expected value. • (ii) standard deviation. • 2. The expected value is the weighted average of the possibleoutcomes. It represents the long-run average outcome ifthe decision were to berepeated many times.

  4. LN11.4 2b) Example Product A probability distribution (1) (2) (3) Estimated Weighted amount Outcome probability (col.1× col. 2) £ Profits of £6 000 0.10 600 Profits of £7 000 0.20 1 400 Profits of £8 000 0.40 3 200 Profits of £9 000 0.20 1 800 Profits of £10 000 0.101 000 1.008 000Expected value

  5. LN11.4 (3) Product B probability distribution (1) (2) (3) Estimated Weighted amount Outcome probability (col. × col. 2) £ Profits of £4 000 0.05 200 Profits of £6 000 0.10 600 Profits of £8 000 0.40 3 200 Profits of £10 000 0.25 2 500 Profits of £12 000 0.202 400 1.008 900Expected value Which product should the company make?

  6. LN11.4 (4a) • Product C probability distribution • Estimated Expected • Outcome probability value (EV) £ • Loss of £4 000 0.5 (2 000) • Profit of £22 000 0.5 11 000 • 9 000 • Product C has a higher EV than either products B or C, but it issubject to greater uncertainty.

  7. LN11.4 (4b) • The standard deviation is often used to measure thedispersion of the possible outcomes: • SD of A = £1 096 • SD of B = £2 142 • SD of C = £13 000 • 4. The standard deviation measures dispersion around the expected value, but does not measure downside risk (i.e. measuring the possibility of deviations below the expected value).

  8. LN11.4 (4c) 5. The coefficient of variation V is a relative measure of risk: V = Standard deviation Expected value For example, a SD of 200 with an EV of 2 000 has the same relative variation as a SD of 2 000 with an EV of 20 000. 6. Where possible, it is preferable to focus on probability distributions rather than summary measures of EV and SD.

  9. LN11.4 (5a) Decision trees Decision trees are useful for clarifying alternative courses of action and their potential outcomes.

  10. LN11.4 (5b) Example A company is considering whether to develop and market a new product. Development costs are estimated to be £180 000, and there is a 0.75 probability that the development effort will be successful and a 0.25 probability that the development effort will be unsuccessful. If the development is successful, the product will be marketed, and it is estimated that: (i) If the product is very successful, profits will be £540 000. (ii) If the product is moderately successful, profits will be £100 000. (iii) If the product is a failure, there will be a loss of £400 000. Each of the above profit and loss calculations is after taking into account the development costs of £180 000. The estimated probabilities of each of the above events are as follows: (i) Very successful 0.4 (ii) Moderately successful 0.3 (iii) Failure 0.3

  11. LN11.4 (6) Decision tree for example on previous slide

More Related