This topic has built three design paradigms and shown, concretely, when each one is (and isn't) the right tool: divide-and-conquer for independent subproblems, greedy for problems with a provable exchange-argument-safe local choice, and dynamic programming for overlapping subproblems where greedy's exchange argument fails. This capstone lesson is a decision guide: a short diagnostic checklist, followed by three worked finance-flavoured examples that walk through the actual reasoning process of choosing a paradigm, not just stating the answer.
In this lesson
- Learning objectives
- The diagnostic checklist
- Worked example 1: parallel backtest aggregation
- Worked example 2: capital allocation across discrete deals
- Worked example 3: minimum-cost network connectivity
- The transferable skill
Before you start
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