Optimal Portfolio Allocation

Problem Statement:

You work for a prestigious investment firm that manages a large number of clients' portfolios.

Your task is to develop a program that determines the optimal allocation of assets in a given

investment portfolio.

The portfolio consists of $N$ different assets, each with an associated expected return and

risk level. Your program should take as input the expected return and risk of each asset, along

with the total investment amount available. The goal is to find the allocation of assets that

maximizes the portfolio's expected return while keeping the risk within a specified tolerance

level.

Your program should solve this problem using two different algorithm paradigms: Brute

Force and Dynamic Programming.

Project Part $1$: Brute Force Approach

Implement a brute force algorithm to exhaustively search all possible asset allocations within

the given investment amount. Evaluate the return and risk of each allocation and find the one

that maximizes the expected return while keeping the risk within the specified tolerance level.ID$-$of$-$asset : Expected$-$return : Risk$-$level : Quantity$($units$)$

Example.txt:

Example $1$:

AAPL : $0\mathrm{.}05$:$0\mathrm{.}02$:$1000$

GOOGL : $0\mathrm{.}08$:$0\mathrm{.}03$:$500$

MSFT : $0\mathrm{.}04$:$0\mathrm{.}015$:$800$

Total investment is $1000$ units

Risk tolerance level is $0\mathrm{.}024$

Example $2$:

AMZN : $0\mathrm{.}07$:$0\mathrm{.}04$:$600$

TSLA : $0\mathrm{.}1$:$0\mathrm{.}05$:$400$

FB : $0\mathrm{.}06$:$0\mathrm{.}025$:$700$

Total Investment is $900$ units

Risk Tolerance Level is $0\mathrm{.}038$

Output Sample:

Example $1$: Optimal Allocation:

AAPL: $200$ units

GOOGL: $300$ units

MSFT: $500$ units

Expected Portfolio Return: $0\mathrm{.}064$

Portfolio Risk Level: $0\mathrm{.}024$

Example $2$:

Optimal Allocation:

AMZN: $100$ units

TSLA: $300$ units

FB: $500$ units

Expected Portfolio Return: $0\mathrm{.}079$