MARKOWITZ PORTFOLIO OPTIMIZATION USING MONTE CARLO SIMULATION

Description
This spreadsheet has a built in dialogue that allows the user to choose up to 30 stocks, bonds or ETFs or a combination of these. The simulation is a Monte Carlo program that is iterated 500 000 times to attach weights to the selected financial tickers.  In one instance it attempts to provide an optimized portfolio based on Sharpe's ratio, and in another instance, it provides an optimized simulation based on minimized volatility. The application is an integrated environment using the Python programming language and several dependencies together with a front-end built using Lazarus Free Pascal plus VBA.  The Python program is divided into two sections.  The first part uses YFinance, a package for Python to download the required items.  The second part of the program uses the information from these items to do a Monte Carlo simulation that strives to provide a more or less optimized portfolio.  Several stock tickers are provided in the spreadsheet for the user to use to test the software.  An entire spreadsheet is also provided with about 6000 tickers for a diverse range of businesses traded on the New York stock exchange. This can assist in building a diversified portfolio. Users can contact me at any time if there are additional questions, problems or suggestions to integrate the software better, or to improve.