Mean Variance Schätzung (MVE) is a fundamental concept in finance and statistics used to assess the risk and return profile of investment portfolios. Developed by Harry Markowitz in the 1950s, MVE provides a structured way to select assets that maximize expected returns for a given level of risk.
Die Kernidee hinter MVE ist die Analyse des mean (average erwarteter Ertrag) und variance (measure of risk) of different assets. By combining these two metrics, investors can create a diversified portfolio that balances potential gains with acceptable levels of risk.
In practical terms, MVE involves calculating the expected return of individual assets and their correlations with one another. This allows investors to understand how assets might perform together, as some assets may offset risks associated with others. The goal is to construct an ‘efficient frontier’ of optimal portfolios that provide the highest expected return for a given level of risk.
Mathematically, the expected return of a portfolio is calculated as the weighted sum of the expected returns of its individual assets, while the variance is derived from the weights of the assets, their individual variances, and their covariances. This complex interplay forms the basis of Modern Portfolio Theory (MPT).
Obwohl MVE weit verbreitet ist, hat sie Einschränkungen, insbesondere in ihrer Abhängigkeit von historischen Daten zur Vorhersage zukünftiger Renditen und Risiken, was nicht immer zutrifft. Zudem geht sie davon aus, dass Investoren rational sind und Märkte effizient sind, was in der Praxis zu Diskrepanzen führen kann.