diff --git a/Chapter6_Priorities/Ch6_Priors_PyMC2.ipynb b/Chapter6_Priorities/Ch6_Priors_PyMC2.ipynb
index b69bed49..e3fc22f0 100644
--- a/Chapter6_Priorities/Ch6_Priors_PyMC2.ipynb
+++ b/Chapter6_Priorities/Ch6_Priors_PyMC2.ipynb
@@ -1378,7 +1378,7 @@
     "\n",
     "With this Bayesian analysis of the stock market, we can throw it into a Mean-Variance optimizer (which I cannot stress enough to not use with frequentist point estimates) and find the minimum. This optimizer balances the tradeoff between a high return and high variance.\n",
     "\n",
-    "$$ w_{opt} = \\min_{w} \\frac{1}{N}\\left( \\sum_{i=0}^N \\mu_i^T w - \\frac{\\lambda}{2}w^T\\Sigma_i w \\right)$$\n",
+    "$$ w_{opt} = \\max_{w} \\frac{1}{N}\\left( \\sum_{i=0}^N \\mu_i^T w - \\frac{\\lambda}{2}w^T\\Sigma_i w \\right)$$\n",
     "\n",
     "where $\\mu_i$ and $\\Sigma_i$ are the $i$th posterior estimate of the mean returns and the covariance matrix. This is another example of loss function optimization."
    ]
diff --git a/Chapter6_Priorities/Ch6_Priors_PyMC3.ipynb b/Chapter6_Priorities/Ch6_Priors_PyMC3.ipynb
index 0e8d4e63..6306a8f8 100644
--- a/Chapter6_Priorities/Ch6_Priors_PyMC3.ipynb
+++ b/Chapter6_Priorities/Ch6_Priors_PyMC3.ipynb
@@ -1378,7 +1378,7 @@
     "\n",
     "With this Bayesian analysis of the stock market, we can throw it into a Mean-Variance optimizer (which I cannot stress enough, do not use with frequentist point estimates) and find the minimum. This optimizer balances the tradeoff between a high return and high variance.\n",
     "\n",
-    "$$ w_{opt} = \\min_{w} \\frac{1}{N}\\left( \\sum_{i=0}^N \\mu_i^T w - \\frac{\\lambda}{2}w^T\\Sigma_i w \\right)$$\n",
+    "$$ w_{opt} = \\max_{w} \\frac{1}{N}\\left( \\sum_{i=0}^N \\mu_i^T w - \\frac{\\lambda}{2}w^T\\Sigma_i w \\right)$$\n",
     "\n",
     "where $\\mu_i$ and $\\Sigma_i$ are the $i$th posterior estimate of the mean returns and the covariance matrix. This is another example of loss function optimization."
    ]