Mean-variance analysis

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Mean-variance analysis

Evaluation of risky prospects based on the expected value and variance of possible outcomes.

Mean-Variance Analysis

The process of portfolio selection that assumes that every rational investor, at a given level of risk, will accept only the largest expected return. More specifically, mean-variance analysis attempts to account for risk and expected return mathematically to help the investor find a portfolio with the maximum return for the minimum about of risk. A Markowitz efficient porfolio represents just that: the most expected return at a given amount of risk (sometimes excluding zero risk). Harry Markowitz first began developing this form of analysis in an article published in 1952 and received the Nobel prize for economics for his work in 1990. See also: Homogenous expectations assumption, Markowitz efficient set of portfolios.
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SPIAS employs Modern Portfolio Theory techniques such as mean variance analysis to structure and re-balance each model.