  The main outcomes of the paper are divided into two parts. First, we present
a new dual for quadratic programs, in which, the dual variables are affine
functions, and we prove strong duality. Since the new dual is intractable, we
consider a modified version by restricting the feasible set. This leads to a
new bound for quadratic programs. We demonstrate that the dual of the bound is
a semi-definite relaxation of quadratic programs. In addition, we probe the
relationship between this bound and the well-known bounds. In the second part,
thanks to the new bound, we propose a branch and cut algorithm for concave
quadratic programs. We establish that the algorithm enjoys global convergence.
The effectiveness of the method is illustrated for numerical problem instances.
