Answered! PYTHON CODE ONLY! Assume: 1. Your semi­annual raise is .07 (7%)…

PYTHON CODE ONLY!

Assume:

1. Your semi­annual raise is .07 (7%)

2. Your investments have an annual return of 0.04 (4%)

3. The down payment is 0.25 (25%) of the cost of the house

4. The cost of the house that you are saving for is $1M.

You are now going to try to find the best rate of savings to achieve a down payment on a $1M house in 36 months. Since hitting this exactly is a challenge, we simply want your savings to be within $100 of the required down payment.

Write a program to calculate the best savings rate, as a function of your starting salary. You should use bisection search​ to help you do this efficiently. You should keep track of the number of steps it takes your bisections search to finish.

Expert Answer

 main.py
def find_best_savings_rate(starting_salary):
    low = 0
    high = 10000
    steps = 0
    # Bisection search for the best savings rate
    while True:
        steps += 1
        best_savings_rate_guess = (high + low) // 2
        current_savings = 0
        annual_salary = starting_salary
        for months in range(36):
            current_savings += annual_salary / 12 * best_savings_rate_guess / 10000 + current_savings * 0.04 / 12
            # Salary is raised for 7% AFTER every 6 months
            if months != 0 and months % 6 == 0:
                annual_salary += annual_salary * 0.07

        # Savings + or - 100$ are OK
        if 249900 <= current_savings <= 250100:
            print("Best savings rate:", best_savings_rate_guess / 10000)
            print("Steps in bisection search:", steps)
            return
        if current_savings < 249900:
            low = best_savings_rate_guess
        elif current_savings > 250100:
            high = best_savings_rate_guess
        if steps > 14:
            print("It is not possible to pay the down payment in three years.")
            return


salary = int(input("Enter the starting salary:"))
find_best_savings_rate(salary)

output:

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