This is the final project for CS50 Introduction to Python. The project implements a classical portfolio optimization methodology called Efficient Frontier using Python. It provides a simple yet effective approach to constructing optimal portfolios.
Video Demo: here
In the world of investments, achieving the best results often involves finding the optimal portfolio. This isn't just about picking investments with the highest returns. It's about creating a balance between risk and reward that aligns with your financial goals and risk tolerance. It can either include high-potential investments with controlled risk or lower-risk options with a guaranteed minimum return.
Developed in 1952 by Harry Markowitz, the efficient frontier is a core principle of modern portfolio theory. It helps you find investment combinations that balance risk and reward. It highlights portfolios with the best return for a specific risk level, or the lowest risk for a desired return.
The visualization of Efficient Frontier is as follows:
For more information, you can read in here.
This final project includes 2 main files:
project.py contains all functions which are used to gernerate an optimal portfolio based on user's input.
check_budget_input: check if the budget is a valid number (no text or special characters),check_number_of_stocks: verify that the user provided a valid integer for the number of stock symbols,is_valid_date_format: make sure the date is formatted correctly (YYYY-MM-DD),check_valid_start_end_date: the calculation start date should be before you buy,check_symbol_existence: ensure the provided stock symbol exists in the financial data source,input_each_stock_symbol: input the stock symbol,extract_stock_price: look up past prices for a stock within a specific timeframe,optimal_portfolio: calculate the optimal investment amounts for a diversified portfolio and report the leftover cash,validation: calculate the total profit or loss on an investment held for a specific time frame.
test_project.py contains all test functions that collectively test my implementation of project.py thoroughly, prepended with test_.
test_check_budget_inputtest_check_number_of_stockstest_is_valid_date_formattest_check_valid_start_end_datetest_check_symbol_existence
You need to install the following packages to run this program:
$ pip install yfinance
$ pip install PyPortfolioOpt
These are following steps of you must do to help the program run smoothly:
- 1st: Input your budget amount,
- 2nd: Input the number of stock symbols,
- 3rd: Input the start date (YYYY-MM-DD),
- 4th: Input the deadline for your purchases (YYYY-MM-DD),
- 5th: Input the date you want to validate data (YYYY-MM-DD),
- 6th: Input stock symbols
Input Example:
Output Example:
Comment: The constructed portfolio clearly has a higher return compared to the portfolio with an equally distributed budget across all assets.
Feel free to contact me on my email.