This project aims to demonstrate the implementation of the Markowitz model for portfolio optimization. The model will be applied to a set of historical asset returns data on VOO(NYSE) and BLV(NYSE) in Google Sheets to construct an efficient frontier of portfolios and identify the optimal portfolio for a given level of expected return and risk.
Once the data is imported, it will need to be cleaned and prepared for analysis. This includes calculating the mean returns, variances, and covariances for each asset. Covariance measures the relationship between the returns of two assets, while correlation measures the strength and direction of that relationship. These values will be used in the next steps of the model.
The Sharpe ratio is a measure of the risk-adjusted return of an investment, and will be used to evaluate the efficiency of the portfolio. To calculate the Sharpe ratio, you will need to determine the expected return and volatility of the portfolio, along with the risk-free rate.
The final step is to graph the results and analyze the outcomes. This includes creating a plot of the efficient frontier and identifying the optimal portfolio, as well as discussing any observations or insights that can be drawn from the analysis.
Google Sheets implementation of the above model for two assets can be found here: Click Here
The image below shows the Mean Return(Reward) vs Standard Deviation(Risk) plot with Efficient Frontier:
