Here is the interview question prompt, presented for reference.

This is a classic technical interview question that I've seen a number of times in real life interviews. Let's say you're given an array of stock prices, with each element being an integer that represents a price in dollars.

[ 10, 7, 6, 2, 9, 4 ]

Each index of the array represents a single day, and the the element at that index is the stock price for that given day. This means that the array below represents:

prices = [ 10, 7, 6, 2, 9, 4 ]
# Day 0 - a price of `$10`
# Day 1 - `$7`
# Day 2 - `$6` (and so on...)

int[] prices = {10, 7, 6, 2, 9, 4};
// Day 0 - a price of `$10`
// Day 1 - `$7`
// Day 2 - `$6` (and so on...)

let prices = [10, 7, 6, 2, 9, 4];
// Day 0 - a price of `$10`
// Day 1 - `$7`
// Day 2 - `$6` (and so on...)

int prices[]{ 10, 7, 6, 2, 9, 4 };
// Day 0 - a price of `$10`
// Day 1 - `$7`
// Day 2 - `$6` (and so on...)

int[] prices = {10, 7, 6, 2, 9, 4};
// Day 0 - a price of `$10`
// Day 1 - `$7`
// Day 2 - `$6` (and so on...)

var prices = []int{10, 7, 6, 2, 9, 4}
/* Day 0 - a price of `$10`
Day 1 - `$7`
Day 2 - `$6` (and so on...) */

Given the ability to only buy once and sell once, our goal is to maximize the amount of profit (selling price - purchase price) that we can attain and return that value. Note the only caveat is that that we cannot sell a stock before we buy it, which is important in identifying a solution.

Can you write a stock optimizer method called stockOptimizer? See the following examples for further clarification:

stockOptimizer([ 10, 7, 6, 2, 9, 4 ])
# 7

stockOptimizer(new int[] {10, 7, 6, 2, 9, 4});
// 7

stockOptimizer([10, 7, 6, 2, 9, 4]);
// 7

stockOptimizer({10, 7, 6, 2, 9, 4});
// 7

StockOptimizer(new int[]{10, 7, 6, 2, 9, 4});
// 7

stockOptimizer([]int{10, 7, 6, 2, 9, 4})
// 7

For the above example, the max profit is made when we buy on day/index 3 (when the price is 2) and sell on day/index 4 (when the price is 9). 9 - 2 gives us 7, which is returned by the function. Let's do another example.

stockOptimizer([9, 8, 6, 5, 3])
# 0

stockOptimizer(new int[]{9, 8, 6, 5, 3});
// 0

stockOptimizer([9, 8, 6, 5, 3]);
// 0

stockOptimizer({9, 8, 6, 5, 3});
// 0

stockOptimizer(new int[]{9, 8, 6, 5, 3});
// 0

stockOptimizer([]int{9, 8, 6, 5, 3})
// 0

From a quick glance, it seems like there's enough price differences to generate a profit. However, notice that the price drops every day, and thus we can't have a profit since we're required to buy before selling.

Constraints

• Length of the given array <= 100000
• The array will always consist of non zero integer (including 0)
• The maximum price would be <= 2147483647
• Expected time complexity : O(n)
• Expected space complexity : O(1)
• The array would always contain more than 1 element

You can see the full challenge with visuals at this link.