Two-Asset Maximum-Sharpe Weights with Equal Volatility
Summary
The document derives the portfolio weights that maximize the Sharpe ratio for two risky assets with equal variances and a shared correlation, alongside a risk-free rate. It defines each asset’s excess return as its expected return minus the risk-free rate, constrains the risky-asset weights to sum to one, and writes portfolio return and variance in terms of one weight. Applying a first-order condition yields the weight in asset one; the other weight is the remainder.
The resulting expression depends on both excess returns and the correlation, with a denominator involving their sum and one minus the correlation. The answers also point out that an alternate expression in the question appears to contain a sign error. This is a special case under equal asset variances and unconstrained weights: the thread does not address short-sale limits, estimation error, or unequal volatilities, and gives no empirical portfolio test.
Key ideas
- Excess return is defined as an asset’s return above the risk-free rate.
- With equal asset variances, portfolio variance depends on the weights and the assets’ correlation.
- The maximum-Sharpe allocation can be derived by substituting the sum-to-one constraint into the objective.
- The expression in the question appears to have a denominator sign error; the derivation gives a sum of excess returns.
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Full text
# Finding Expression for Optimal Markowitz Weights
# Finding Expression for Optimal Markowitz Weights
So there are two assets with return rates $r_1$ and $r_2$ which have identical variances and a correlation coefficient $p$. The risk free rate is $r_f$.
I need to find an expression for the optimal Markowitz weights for the two assets.
The books says that the answer is ($s_1 - p s_2$)/[($s_1-s_2$)*($1-p$)], but I'm not sure how this makes any sense as I don't know what the s's mean.
Thank you
## Answer by Gordon (score 2, accepted)
https://quant.stackexchange.com/a/18507
Let $s_1 = r_1 -r_f$ and $s_2 =r_2-r_f$. Then, this is the maximization problem: \begin{align*} & \ \max_{w_1, w_2} SR = \frac{\mu_p}{\sigma_p}, \, \mbox{ subject to}\\ \mu_p = & \ w_1 s_1 + w_2 s_2,\\ \sigma_p^2 = & \ \sigma^2\big(w_1^2 + w_2^2 + 2 w_1 w_2 \rho\big),\\ 1 = & \ w_1+w_2. \end{align*} By certain substitution, we convert the problem to the following \begin{align*} \max_{w_1} \frac{w_1(s_1-s_2)+s_2}{\sqrt{w_1^2 + (1-w_1)^2+2 w_1(1-w_1)\rho}} = \max_{w_1} \frac{w_1(s_1-s_2)+s_2}{\sqrt{2\big(w_1-w_1^2\big)(\rho-1) +1}}. \end{align*} From the first order condition, \begin{align*} (s_1-s_2)\big[2(w_1-w_1^2)(\rho-1)+1\big] -\big[w_1(s_1-s_2) + s_2\big](1-2w_1)(\rho-1)=0, \end{align*} we obtain that \begin{align*} (s_1-s_2) + w_1 (s_1-s_2) (\rho-1) - s_2(1-2w_1)(\rho-1)=0, \end{align*} and, consequently, \begin{align*} w_1 &= \frac{s_1-\rho s_2}{(s_1+s_2)(1-\rho)},\\ w_2 &= 1- w_1. \end{align*}
## Answer by Pontus Hultkrantz (score 1)
https://quant.stackexchange.com/a/15919
I'm sorry for the late answer. I hope you passed the exam anyway!
TO answer your question, $s_2 = r_2-r_f$, that is the excess return over the risk free rate/asset.
However, there seems to be a typo in your formula, I believe it should be
$w_1 = \frac{s_1-ps_2}{(s_1+s_2)(1-p)}$, i.e. plus in the denominator.
$w_1$ is the weight for asset 1 and $w_2 = 1-w_1$ the weight for asset 2 that maximize the Sharpe ratio.
Ohh, and Hi Mark Joshi! :) (in the comments)
## Answer by emcor (score 1)
https://quant.stackexchange.com/a/15936
This is the general solution (where $C$ is the covariance matrix of returns):Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.