Jump (trading) exactly a couple times.

What this dynamic programming coding problem tests

This is a medium-difficulty coding problem that combines array traversal with constrained optimization. It appears regularly in quant and trading interviews because it rewards clean dynamic-programming thinking and efficient state management under real-world constraints.

The core challenge is to maximize accumulated points over a fixed number of moves, where you can either stay put or advance one index at a time. The twist is that you collect points at every step—including when you stay—which means the optimal strategy often involves lingering at high-value positions rather than rushing through the array. Candidates must recognize the state space (current index and remaining moves), design a recurrence relation, and implement it efficiently in either C++ or Python without exceeding time or space budgets.

• State representation: index and step count
• Memoization vs. tabulation trade-offs
• Greedy intuition vs. dynamic-programming correctness
• Handling negative array values and edge-case indices