Full investment
1' w = 1. All capital is allocated. This is an affine equality constraint.
Common portfolio rules translated into solver-ready mathematical constraints.
1' w = 1. All capital is allocated. This is an affine equality constraint.
w >= 0. No short positions. This is an elementwise linear inequality.
l <= w <= u. Each asset has lower and upper weight limits.
||w||_1 <= L. Gross exposure cannot exceed a limit. This is convex.
||w - w0||_1 <= tau. The new portfolio cannot move too far from current holdings.
l <= F' w <= u. Portfolio exposures to sectors, styles, or risk factors stay in allowed ranges.
number of nonzero weights <= k. This is usually nonconvex and often needs mixed-integer optimization or an approximation.
The set of all portfolios satisfying every constraint. Optimization only chooses from this set.
For each constraint, ask: + What real-world rule does it encode? + Is it equality or inequality? + Is it affine, convex, or nonconvex? + Could it make the problem infeasible? + Does it preserve the intended economic meaning?
Use this page while reading Lesson 0003.