Risk appetite - maximax, maximin and minimax regret - part 2
Taught by Nick Drape · AI tutor support included
You'll learn three decision-making approaches under uncertainty: maximax (choosing the best possible outcome), maximin (protecting against the worst case), and minimax regret (minimising what you wish you'd done differently).
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In this lesson
- 0:00 Decision-making under uncertainty introduction
- 1:05 Maximax approach for optimists
- 2:02 Maximin approach for pessimists
- 2:51 Minimax regret and regret tables
- 4:46 Building and interpreting regret calculations
- 6:32 Choosing the minimax regret option
About this lesson
This video uses a practical lemonade ordering example to show how risk appetite shapes strategic choices—essential for P1, P2, and P3 papers where you'll need to recommend decisions based on an organisation's attitude to risk. The maximax approach suits optimists: you identify the highest payoff across all scenarios and choose the decision that delivers it, regardless of how unlikely. The maximin approach suits pessimists: you identify the worst outcome for each decision option, then choose the option with the least damaging worst case. Both are straightforward once you understand the logic. Minimax regret is more complex but important to master. You build a regret table by calculating the difference between the best possible outcome in each scenario and what you'd actually earn if you made the wrong choice. Then you find the maximum regret attached to each decision and choose the option that minimises it. This approach appeals to decision-makers who fear missed opportunities more than losses. Understanding these three frameworks helps you analyse case study scenarios and justify recommendations that align with the organisation's stated risk appetite and strategic priorities.
Duration: 8m
Transcript
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