I was given the following statement:
If matrices $A$ and $B$ are positive definite, then it is impossible for $AB$ to be negative definite.
I'm trying to generate a counter-example. This question was similar (it showed that $AB$ doesn't have to be positive definite) but my question is a step further.
So, how do I construct an example where matrices $A$ and $B$ are both positive definite, so for every real non-zero vector $x$: \begin{gather*} x^T A x > 0\\ x^T B x > 0 \end{gather*} but $AB$ is negative definite, so: \begin{gather*} x^T (AB)x < 0 \end{gather*}
I know how to compute the eigenvalues of a matrix, but I'm not sure how to go about constructing this counterexample.
Let $x$ be an eigenvector of $B$ with corresponding eigenvalue $\lambda$. Since $B$ is positive definite, $\lambda >0$. Then $$ x^T(AB)x = (x^TA)(Bx) = (x^TA)(\lambda x) = \lambda x^T Ax > 0 $$ since $A$ is positive definite. So negative definite will definitely not happen...