I am trying to use solve.QP to solve a portfolio optimization problem (quadratic problem)
Total 3 assets
There are 4 constraints:
Dmat is the covariance matrix
Dmat <- matrix(c(356.25808, 12.31581, 261.8830, 212.31581, 27.24840, 18.50515, 261.88302, 18.50515,535.45960), nrow=3, ncol=3)
dvec is each asset's expected return
dvec <- matrix(c(9.33, 3.33, 9.07), nrow=3, ncol=1)
Amat is the constraint matrix
A.Equality <- matrix(c(1,1,1), ncol=1)
Amat <- cbind(A.Equality, dvec, diag(3), -diag(3))
constraint A^T b >= b_0, b vector
bvec <- c(1, 5.2, rep(0, 3), rep(-0.5, 3))
meq=2, since there are two equality constraints, first and second constraints are equality
Then I run the function solve.QP
library(quadprog)
qp <- solve.QP(Dmat, dvec, Amat, bvec, meq=2)
But it gives the error
Error in solve.QP(Dmat, dvec, Amat, bvec, meq = 2) : constraints are inconsistent, no solution!
I am not sure where I did wrong.
There were two issues with the code you posted:
Dmat
is not actually symmetric; you had accidentally included value 212.31581 instead of 12.31581meq=2
option means your first two constraints are held at equality, meaning your weights sum to 1 and your return is exactly 5.2%. The second constraint is apparently the one causing the infeasibility; it seems there are no valid portfolios that have return exactly equal to 5.2% given your other constraints. Indeed, since no more than half the portfolio can have return 3.33% and the rest must have return of at least 9.07%, the return must be 6.2% or greater. Therefore, you should relax this to a >= constraint by setting meq=1
.Here's the working code:
library(quadprog)
Dmat <- matrix(c(356.25808, 12.31581, 261.88302, 12.31581, 27.24840, 18.50515, 261.88302, 18.50515,535.45960), nrow=3, ncol=3)
dvec <- matrix(c(9.33, 3.33, 9.07), nrow=3, ncol=1)
A.Equality <- matrix(c(1,1,1), ncol=1)
Amat <- cbind(A.Equality, dvec, diag(3), -diag(3))
bvec <- c(1, 5.2, rep(0, 3), rep(-0.5, 3))
qp <- solve.QP(Dmat, dvec, Amat, bvec, meq=1)
qp$solution
# [1] 0.3808733 0.5000000 0.1191267
The optimal solution is actually associated with a 6.3% return.