Mean Variance Analysis

Mean variance analysis is a mathematical framework used to determine the optimal portfolio by analyzing the trade-off between the expected return and the variance of the portfolio. It assumes that investors want to maximize returns for a given level of risk, measured as variance or standard deviation.

The analysis plots all possible portfolios on a graph to identify the efficient frontier, where the best risk-adjusted returns are located. In the context of options and crypto, this involves calculating the expected returns of various strategies and their associated volatility.

The primary limitation is that it assumes returns follow a normal distribution, which often fails to capture the fat-tailed nature of crypto assets. Despite this, it remains the standard for initial portfolio construction.

By inputting asset returns and the covariance matrix, traders can mathematically derive the ideal weights for their holdings. It is the foundational step before more advanced risk modeling is applied.