# Efficient Frontier Derivation: why minimize half the portfolio variance instead of just the variance?

In Robert Merton's derivation of the efficient frontier of a portfolio, he minimizes $\frac{1}{2}\sigma^2$ over the investment weights in each asset, where $\sigma^2$ represents portfolio variance. I am confused why the function he minimizes is half the variance, instead of just the variance. It doesn't make a difference in calculations, but I cannot figure out why he (and all other derivations) do this.

$$U(w) = w'\mu - \frac{1}{2} \lambda w' \Sigma w = w'\mu - \frac{1}{2} \lambda \sigma_\omega^2$$

where $\sigma_\omega^2$ denotes the portfolio variance for a portfolio with weights $\omega$.

Dividing by two is purely done for convenience, optimizing this formula requires taking the derivative with respect to $\omega$ and setting it to $0$. When the derivative is taken the factor $\frac{1}{2}$ is canceled by the square.

See this question on more information on setting $\lambda$.

• Clear answer - there is nothing more to it. – Ric Oct 1 '14 at 7:02
• does having 1/2 in the front of the objective function give a different solution for $w$ than when there is no 1/2? If so, how to account for the discrepancy between the two approaches – develarist Jun 28 '19 at 14:34
• @develarist This might be material for a different question. The answer is that it depends: you can change $\lambda$ to compensate. With fixed $\lambda$, yes the result will change and I expect the change to be significant in all cases encountered in practice. – Bob Jansen Jun 28 '19 at 14:37
• so if we forget about the coefficient $\lambda$ and look at the more practical non-utility portfolio optimization,then $\min w'\Sigma w \neq \min (1/2) w'\Sigma w$ – develarist Jun 28 '19 at 14:40
• I don't follow the argument, what happened to $\omega' \mu$ in your equation? – Bob Jansen Jun 28 '19 at 14:42