[Solved] You are given an array representing daily stock prices. You want to maximize profit by making as many buy-sell transactions as you... Which algorithmic approach guarantees the optimal total profit? | Greedy Algorithms

Greedy Algorithms - Best Time to Buy and Sell Stock II

You are given an array representing daily stock prices. You want to maximize profit by making as many buy-sell transactions as you like, but you must sell before you buy again. Which algorithmic approach guarantees the optimal total profit?

AGreedy approach summing all positive price differences between consecutive days

BDynamic Programming with memoization to explore all buy-sell pairs

CSingle pass to find the maximum single buy-sell pair profit

DDivide and conquer to split the array and combine profits

Step-by-Step Solution

Solution:

Step 1: Understand the problem constraints
The problem allows unlimited transactions but requires selling before buying again, so multiple buy-sell pairs can be combined.
Step 2: Identify the approach that captures all profitable segments
Summing all positive consecutive day price differences captures every profitable transaction, ensuring maximum total profit.
Final Answer:
Option A -> Option A
Quick Check:
Summing positive differences matches the optimal profit for all test cases [OK]

Quick Trick: Sum all positive consecutive price differences [OK]

Common Mistakes:

MISTAKES

Trying to find only one best buy-sell pair
Using complex DP when greedy suffices
Ignoring multiple transactions allowed

Trap Explanation:

PITFALL

Many think only one transaction is allowed, so they pick max single pair profit, but multiple transactions yield more profit.

Interviewer Note:

CONTEXT

Tests if candidate recognizes greedy pattern for multiple transactions profit maximization.

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More Greedy Algorithms Quizzes

Which algorithmic approach guarantees the optimal total profit?

Step 1: Understand the problem constraints

Step 2: Identify the approach that captures all profitable segments

Final Answer:

Quick Check:

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