Build a VBA program that calculates efficient portfolios based onModern Portfolios Theory (MPT) by Markowitz

Here's a breakdown of programming a Modern Portfolio Theory (MPT) Markowitz setup in Excel using VBA: Objective: Build a VBA program that calculates efficient portfolios based on user-defined inputs, adhering to MPT principles. Inputs: • Import historic prices from Yahoo Finance. I have a functional code that you can uce. • Expected returns: Leave a field in the main excel sheet that allows for the user to input the expected returns for each asset. • Risk-free rate: Leave a field for the user to input the risk-free rate of return. • Log returns: Calculate the log returns on the historical prices, taking into account the dividends. • covariance matrix: A matrix representing the covariance between each pair of assets. • Target return or risk level: User-defined target return or desired level of risk (e.g., standard deviation). Outputs: • Optimal portfolio weights: An array or range containing the optimal weights for each asset in the efficient portfolio. • Additional outputs like expected return, standard deviation, Sharpe ratio, and efficient frontier visualization. Steps: 1. Data Import: o Utilize functions like [login to view URL] to access historic data for prices and dividends o Validate and handle potential errors in data format or size. 2. Efficient Frontier Calculation: o Calculate covariance matrix using input expected returns and risk-free rate. o Implement the Markowitz optimization algorithm using libraries like Solver or custom optimization functions. o Solve the optimization problem to find the portfolio weights that minimize risk (standard deviation) for a given target return or maximize return for a given risk level. o Consider using constraint handling in Solver to enforce bounds on weights (e.g., non-negative, sum to 1). 3. Output & Visualization: o Display the calculated optimal portfolio weights in a designated range or format. o Calculate and display additional metrics like expected return, standard deviation, Sharpe ratio, and plot the efficient frontier using charting libraries like ChartObjects. 4. Error Handling: o Implement robust error handling mechanisms to address potential issues like invalid data, solver failures, or unexpected calculations. o Provide informative error messages to guide the user. Additional Considerations: • User Interface: Consider building a user-friendly interface with input fields, buttons, and clear output displays using VBA forms or custom dialog boxes. • Flexibility: Allow users to specify different objective functions (e.g., maximize Sharpe ratio) or incorporate transaction costs. • Data Management: Handle large datasets efficiently and provide options for loading data from external sources like text files or databases. Remember, this is a high-level overview, and the specific implementation details will depend on your preferences and chosen libraries.