Risk and Uncertainty in Decision Making Flashcards
It involves situations or events that may or may not occur, whose probability can be calculated statistically, and whose frequency of occurrence can be predicted from records.
Risk
Pertains to situations or events whose outcome cannot be predicted with statistical confidence.
Uncertainty
It exists when several outcomes are possible and past events are available to estimate the probability of occurrence.
Risk
A decision-maker interested in obtaining the best returns regardless of risk.
Risk Seeker
A decision-maker who assumes that the worst outcome will occur.
Risk-averse
A decision-maker concerned with all possible outcomes and chooses the strategy with the highest Expected Value.
Risk Neutral
It is the financial forecast of the outcome of a course of action multiplied by the probability of achieving that outcome.
Expected Value
Expected value is expressed as a value ranging from what?
0-1
Which expected value should be selected when choosing among several options?
Highest Expected Value
What can be determined when deciding over several options and each option has a range of possible outcomes?
Varying possibilities
Are there situations where possibilities are not available?
Yes
When do situations where probabilities are not available exist?
- When there’s lack of historical information
- When a company faces uncertainty rather than risk
What techniques could be used where uncertainty is incorporated into decision-making?
- Maximin
- Maximax
- Minimax Regret
Its objective is to maximize the minimum return that the company can get.
Maximin
Its objective is to maximize the maximum return that the company can get.
Maximax
Which can be calculated from opportunity cost?
Regret
Which decision-makers choose Maximin?
Risk-averse
Which decision-makers choose Maximax?
Risk Seekers
Decisions are made to minimize what?
The maximum opportunity cost or regret of making the wrong decision.
It is the information that is guaranteed to predict the future with certainty.
Perfect Information
When do perfect information is available?
When there’s market research
What is one drawback of perfect information?
It takes resources
How do you get the value of perfect information?
Value of perfect information (VOPI) = EV (with perfect information) - EV (no perfect information)
Is perfect information perfect?
While market research can yield reasonably accurate information, perfect information is never perfect
When is the gap between perfect information and actual results determined?
After making decisions
It is the gap between perfect information and actual results.
Imperfect information
Is this imperfect information better than no information?
Yes
What should be prepared to quantify the risks to be assessed if two variables are risky?
A joint probability table
What table can allow management to analyze possible outcomes?
Joint Probability Table
These tables do not provide a clear decision to the administration but are useful to show the effects of two variables on the risk being taken.
Joint Probability Table
These are excellent decision-making tools that provide a structure to lay out the options and outcomes of choosing these options.
Decision Trees
It presents a clear picture of the risks and rewards of each option, allowing management to choose between several courses of action.
Decision Trees
How do you evaluate decision trees?
- Calculate the expected values at outcome points
- Choose the highest profits at decision points
Limitations of Decision Tree
- Since it is based on EVs, it has the same disadvantages as all EV techniques
- HIghly dependent on the use of probabilities, which are also based on estimates.
- It tends to oversimplify reality and ignore other factors affecting success or failure.
Standard Deviations can measure what?
Risk
It is calculating how far the outcomes deviate from the mean.
Standard Deviation
What do higher standard deviations indicate?
More dispersion and higher risk
It measures the standard deviation as a percentage of the mean.
Coefficient of variation
It is useful in comparing the dispersion of two sets of data.
Coefficient of variation
What does a higher percentage mean in coefficient of variation?
Higher dispersion
What techniques can the management use to quantify and assess risk when dealing with uncertainties?
Quantitative Techniques
It is a quantitative technique that allows for an alternative risk assessment method.
Sensitivity Analysis
This analysis allows management to focus on the key variables that would change the decision for review.
Sensitivity Analysis
What are the two approaches when making a sensitivity analysis?
- Compute the maximum percentage change in a variable before the decision would change.
- Assess if the decision would change given the change in the variable.
Sensitivity Analysis is used by management to depict a “What if” analysis by examining what?
How the profit would change when the budgeted amounts are not achieved or an underlying assumption changes
Sensitivity analysis allows the management to look at the results by changing what?
Key variables or estimates
The sensitivity analysis should provide management with a better understanding of what?
- Profit/Loss of the Company
- What factors are more sensitive to the profit/loss
What are the what-if questions when a model profit/loss is constructed?
- What if the actual sales are only 60% of the targeted sales? How will it impact my bottom-line profit/loss?
- What if the cost of materials increased by 20% of the budgeted cost? How will it impact my bottom-line profit/loss?
It is one of the limitations of a sensitivity analysis.
It can only be used to assess changes in one variable at a time.
Many variables may be uncertain in what?
Real-life scenarios
What can be generated using computers and random numbers to simulate real-life events?
Simulation Models
It can be used to estimate a variable that management believes to be relevant.
Simulation
It is a model used to predict the probability of different outcomes when random variables may intervene.
Monte Carlo Simulation
What technique can understand the impact of risk and uncertainty in prediction and forecasting models.
Monte Carlo Simulation
