Problem Statement During tough times like these, investment becomes more uncertain with more dangers. To solve it, we might try to train a model to decide when to buy or sell. Therefore, to provide it with correct data, we plan to design an algorithm that answers:what is the perfect moment to buy and when to sell to maximize your profit?Assume you must buyInput:???????: array listing ??????? ?? ??? ??????, where indices represent days; it has at least two valueschanges: array listing changes in the prices, where indices represent days; it has at least two valuesOutput:???????????:index of the change before which we buy:index of the change before which we sell:the profit of this intervali:index of the change before which we buyj:index of the change before which we sellmaxProfit:the profit of this intervalExample:Assume the below table contains the prices of a particular stock over days ??????prices???????changesDayValue 050-163132707340-304551556510660-5772128797968-1110746Therefore, the output of maxProfit([13,7,-30,15,10,-5,12,7,-11,6]) should be (3, 7, 39) . This is because our maximum profit would be 3939 when we buy the stock at day 4, index of 33, and sell after day 8, index of 77. Then, the total profit is 15+10−5+12+7=3915+10−5+12+7=39We will try to solve the problem using various techniques:Brute-ForceDivide-and-Conquer Divide and ConquerNow, we would try to use a divide and conquer paradigm. Hint: try the three steps, and design multiple versions to master these stepsIn [ ]: # write your implementation heredef maxProfit(changes):This is just an interface for it returns the indices of (i,j) indicating the day to buy and sell respectivelyto have the maximum profit in a list of prices per day in .Inputs:- changes: the list holding the changes in prices; the value whose index is k representsthe change between day and day has at least a single change [two days]Output:- i: the index of the change before which we buy- j: the index of the change after which we sell- maxProfit: the value of the maximum profitreturn (0,0,0)In [ ]: maxProfit([13,7,-30,15,10, -5,12,7,-11,6]) Brute ForceAs we in general, try to solve the problem first; we start with a brute force algorithm: design it belowIn [ ]: # write your implementation heredef maxProfitBrute(changes):it returns the indices of (i,j) indicating the day to buy and sell respectivelyto have the maximum profit in a list of prices per day in .Inputs:- changes: the list holding the changes in prices; the value whose index is k representsthe change between day and day has at least a single change [two days]Output:- i: the index of the change before which we buy- j: the index of the change after which we selimaxProfit: the value of the maximum profitExample:changes = [1,2]- that means the price started with ;day 1: it became - day 2: it became In that case: (i,j) = (8,1) as we should buy at the first day, and sell after the third day# return the valuesreturn (e,0,0)In [ ]: # Try your algorithmmaxProfitBrute([13,7,-30,15,1e, -5,12,7,-11,6])

Solution: //C++ language: //1. Approach: Non recursive: //include necessary header files#include…

Problem Statement During tough times like these, investment becomes more uncertain with more dangers. To solve it, we might try to train a model to decide when to buy or sell. Therefore, to provide it with correct data, we plan to design an algorithm that answers: what is the perfect moment to buy and when to sell to maximize your profit? Assume you must buy Input: ???????: array listing ??????? ?? ??? ??????, where indices represent days; it has at least two valueschanges: array listing changes in the prices, where indices represent days; it has at least two values Output: ???????????:index of the change before which we buy:index of the change before which we sell:the profit of this intervali:index of the change before which we buyj:index of the change before which we sellmaxProfit:the profit of this interval Example: Assume the below table contains the prices of a particular stock over days ??????prices ???????changes Day Value 0 50 - 1 63 13 2 70 7 3 40 -30 4 55 15 5 65 10 6 60 -5 7 72 12 8 79 7 9 68 -11 10 74 6 Therefore, the output of maxProfit([13,7,-30,15,10,-5,12,7,-11,6]) should be (3, 7, 39) . This is because our maximum profit would be 3939 when we buy the stock at day 4, index of 33, and sell after day 8, index of 77. Then, the total profit is 15+10−5+12+7=3915+10−5+12+7=39 We will try to solve the problem using various techniques: Brute-Force Divide-and-Conquer

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

See similar textbooks

Problem Statement

During tough times like these, investment becomes more uncertain with more dangers. To solve it, we might try to train a model to decide when to buy or sell. Therefore, to provide it with correct data, we plan to design an algorithm that answers:

what is the perfect moment to buy and when to sell to maximize your profit?
Assume you must buy

Input:

???????: array listing ??????? ?? ??? ??????, where indices represent days; it has at least two valueschanges: array listing changes in the prices, where indices represent days; it has at least two values

Output:

???????????:index of the change before which we buy:index of the change before which we sell:the profit of this intervali:index of the change before which we buyj:index of the change before which we sellmaxProfit:the profit of this interval

Example:
Assume the below table contains the prices of a particular stock over days

??????prices	???????changes
Day	Value
0	50	-
1	63	13
2	70	7
3	40	-30
4	55	15
5	65	10
6	60	-5
7	72	12
8	79	7
9	68	-11
10	74	6

Therefore, the output of maxProfit([13,7,-30,15,10,-5,12,7,-11,6]) should be (3, 7, 39) . This is because our maximum profit would be 3939 when we buy the stock at day 4, index of 33, and sell after day 8, index of 77. Then, the total profit is 15+10−5+12+7=3915+10−5+12+7=39

We will try to solve the problem using various techniques: