1. Risk and uncertainty By 刘明 周凯亮 李名扬
Chapter 7
Risk and uncertainty
By 刘明
周凯亮
李名扬

2. Risk and uncertainty The concept of risk and uncertainty
The meaning of risk and uncertainty analysis

3. Risk involves situations or events which may or may not occure,but whose probability of occurrence can be estimated statistically
Uncertain events are events where the outcome cannot be estimated wish a statistical probability

4. The difference between the uncertainty and risk in the following four aspects:
(1) can be quantified.
(2) can the insurance.
(3) the probability and availability.
(4) influence the size

5. The meaning of risk and uncertainty analysis
The nature of the uncertainty and risk
Objectivity
variability
periodically
variety
relativity
diversity

6. The method of uncertainty analysis
Methods: mainly includes break-even analysis and sensitivity analysis

7. The process of risk analysis, methods
Methods: mainly including sensitivity analysis and probability analysis 风险 识别 风险 估计 风险 评价 风险 对策

8. The investment risk and uncertainty is objective existence
Risk and uncertainty analysis of investment decisions has a special important role.

9. Risk impact (loss) The serious influence Great influence
Secondary effects
Small effect
Negligible effect

10. The risk probability High: 81% ~ 100% Higher: 61% - 80%
Medium: 41% ~ 60%
Lower: 21% - 40%
Low: 0% - 20%

11. 4 Decision rules Maximin decision rule: maximise the minimum profit
Maximax decision rule:
maximise the maximum profit
Minimax regret rule:
aims to minimise the regret from making the wrong decision

12. Example Project choice Pay-off table $000 D E F Ⅰ 100 80 60Ⅰ
Scenarios Ⅱ
Ⅲ (20)
Maximin: (20)
Maximax:

13. The regret for each decision option project option D E F Ⅰ 0 20 40
Pay-off table $000
Project choice
D E F Ⅰ
Scenarios Ⅱ
Ⅲ (20)
The regret for each decision option
project option
D E F Ⅰ
Scenarios Ⅱ Ⅲ
Maximum regret Ⅰ

14. Criticiisms of the maximin rule
It is defensive and conservative,being a safety first principle of avoiding the worst outcomes without taking into accout opportunities for maximising profit.
It ignores the probability of each different outcome kaking place.
Criticiisms of the maximax rule
It ignores the probability of different outcomes.
It ignores the outcomes that are less than the best possible.For some decision options,the worst possible may be more than the organization can afford.It is a decision rule for the risk-seeker.

15. 5 Decision trees
Decision tress are diagrams which illustrate the choices and possible ouecomes of a decision.The possible outcomes are usually given associated probabilities of occurrence.
Rollback analysis evaluates the EV of each decision option.You have to work from right to left and calculate EVs each outcome point.

16. Constructing a decision tree
Be drawn from left to right
The square is the decision point
The circle will be used as the symbol for an outcome point.
The decision tree can be drawn as a two-stage tree if a decision taken now will lead to other decisions to be taken in the futrue.

17. Example

18. At ouecome point E At decision point C At decision point D
Profit probability
x p px
$' $'000
High ,
Medium
Low (200) (40) EV
At decision point C
market,EV=+360
Abandon,value=+50
Choice would to be market,and so the EV at decision point C is +360.
At decision point D
market,value=-600
Choice would be to abandon,and so the EV at decision point D is +50.

19. Calculate the EV at outcome point B
0.6 *360
* 50 =
Compare the optiond at point A
Test:EV=EV at B - test cost = =136
Abandon:Value=50
So,the choice would be to test market the product.

20. The value of perfect information
Perfect information is guarateed to predict the future with 100% accuracy.Imperfect information is better than no information at all but could be wrong in its prediction of the future.
The value of perfect information is the difference between the EV of profit with perfect information and the EV of profit without perfect information.

21. With perfect information, the best decision option will always be selected .The choice will be the outcome that gives the highest profit (or lowest cost)in the circumstances that we know will occur.

23. Perfect information and decision trees
When the option exists to obtion information,the decision can be shown ,like any other decision,in the form of a decision tree.We will suppose,for illustration,that the cost of obtaining perfect information is $400.

24. The value of impefect information
There is one serious drawback to the 'pefect information'technique we have just looked at.In practice,information is never perfect.Market research findings or information from pliot tests and so on are likely to be reasonably accurate,but they can still be wrong:they provide imperfect information.

25. That there is a 60% probablity that the economy will be weak and a 40% probability that the economy will be strong.
Option A Option B
Weak economy $ $20000
Strong economy $ $100000

26. There is an 80% probability that reasearch would predict this correctly.There is an 90% probability that the research would predict this correctly.
Option A:(0.6x$50000)+(0.4x$60000)$54000
Option B:(0.6x$20000)+(0.4x$100000)$52000

27. Actual Predict Decision Profit Probability EV of profit
Weak Weak Op A $ (0.6X0.8)
Weak Strong Op B $ (0.6x0.2)
Strong Weak Op B $ (0.4x0.9)
Strong Strong Op A $ (0.4x0.1)
64800
The value of the imperfect information = $64800-$54000=$10800

28. Thank you