meanvarianceramverket

Mean-variance optimization is a fundamental concept in modern portfolio theory, developed by Harry Markowitz. It provides a framework for selecting the optimal portfolio of assets by considering both their expected returns and their variances (or standard deviations), which are measures of risk. The core idea is to maximize expected return for a given level of risk, or equivalently, minimize risk for a given level of expected return.

The framework involves plotting portfolios on a graph with expected return on the vertical axis and risk (variance or standard deviation) on the horizontal axis. A set of possible portfolios forms a region. The upper boundary of this region is known as the efficient frontier. Any portfolio lying on the efficient frontier is considered optimal because no other portfolio offers a higher expected return for the same level of risk, nor a lower level of risk for the same expected return.

Investors can then choose a portfolio from the efficient frontier based on their individual risk tolerance. For example, a risk-averse investor would choose a portfolio with lower risk and consequently lower expected return, while a risk-seeking investor would opt for a portfolio with higher risk and higher expected return.

The mean-variance framework relies on estimates of expected returns, variances, and covariances of the assets. The accuracy of these estimates significantly impacts the resulting optimal portfolio. Practical implementation can be complex due to the large number of potential asset combinations and the sensitivity of the results to input data. Despite these challenges, mean-variance optimization remains a cornerstone of investment management and financial planning.