Chapter 12 - Risk and Uncertainty Flashcards
Risk vs Uncertainty
Risk: quantifiable, associated probability (ie risk of not finding oil when drilling in an explored area)
Uncertainty: unquantifiable, cannot be mathematically modeled (a number of possible outcomes, but not probability can be assigned - ie digging for oil in an unexplored area)
Expected value
chance weighted outcomes (revenues)
Risk -
Neutral
Seeker
Averse
-Behaviour
Neutral: selects maximum expected value
Seeker: selects highest pay off (maximax)
Averse: trades off lower revenue for higher likelihood (maximin)
Utility Theory
Risk appetite changes with the level of investment amount.
Standard deviation
std dev = ROOT((SUM(x-MEAN)^2/n
Measure of distribution around a mean
Coefficient of variation
In order to be able to compare std deviations by dividing by its expected value allows to compare std deviations.
Expected Values (EV’s)
PRO
CON
PRO
considers risk
easy rule (one number)
simple to calc
CON subjective not useful for one-offs ignores attitude to risk no answer possible
Pay off tables and decision criteria
A quantification of all possible outcomes
Maximax
Maximin
Minimax
Maximax (optimist)
maximise payout
Maximin (pessimist)
Maximise minimum payout
Minimax (lost opportunity minimiser)
Minimise maximum regret
Perfect and Imperfect Information
Perfect: 100% accurate
Imperfect: usually correct
Decision trees
Square = decision point Circle = chance outcome
Build EV’s following the tree lines
Decision Trees further considerations
Time value of money: incorporate dCF
Assume risk neutrality: decision maker selects option with the highest EV
Sensitivity analysis: show chances of possible outcomes
Oversimplification: decision models are an approximation of the reality, hence do not encompass all possible scenarios
Conditional probabilities
Contingency tables
Probability of an event based on the knowledge of the occurrence of a second event
table showing all chance weighted outcomes
