Can't find solutions with lower bound in constraints using cvxpy

Question

My optimization problem is to minimize risk but risk has to be lower than 0.2. It seems whenever I add the lower bound into the constraints, it would show error like below. Are there ways to get around this? Below are my codes.

*** cvxpy.error.DCPError: Problem does not follow DCP rules. Specifically:
The following constraints are not DCP:

risk = cp.quad_form(w-w_bch, Omega)
obj = cp.Minimize(risk)
constraints = [risk >= 0.2]
prob1 = cp.Problem( obj, constraints)
prob1.solve(verbose=verbose, solver=cp.ECOS)