Hello, I have had an error that I have been trying to solve for a couple days with no luck. If anyone could help, I would really appreciate it.
This is the error:
(It is way over my head in terms of my programming knowledge)
site-packages/cvxopt/coneprog.py", line 2067, in coneqp
raise ValueError(“Rank(A) < p or Rank([P; A; G]) < n”)
ValueError: Rank(A) < p or Rank([P; A; G]) < n
The issue arises from the ‘optimal_portfolio’ function. I actually copy and pasted someone elses completed code, and it still wouldn’t work. Could it just be my computer?
Here is the function:
n = returns.shape
returns = np.transpose(returns.to_numpy()) # originally as_matrix changed to values
N = 100 mus = [10**(5.0 * t/N - 1.0) for t in range(N)] # Convert to cvxopt matrices S = opt.matrix(np.cov(returns)) pbar = opt.matrix(np.mean(returns, axis=1)) # Create constraint matrices G = -opt.matrix(np.eye(n)) # negative n x n identity matrix h = opt.matrix(0.0, (n ,1)) A = opt.matrix(1.0, (1, n)) b = opt.matrix(1.0) # Calculate efficient frontier weights using quadratic programming portfolios = [solvers.qp(mu*S, -pbar, G, h, A, b)['x'] for mu in mus] ## CALCULATE RISKS AND RETURNS FOR FRONTIER returns = [blas.dot(pbar, x) for x in portfolios] risks = [np.sqrt(blas.dot(x, S*x)) for x in portfolios] ## CALCULATE THE 2ND DEGREE POLYNOMIAL OF THE FRONTIER CURVE m1 = np.polyfit(returns, risks, 2) x1 = np.sqrt(m1 / m1) # CALCULATE THE OPTIMAL PORTFOLIO wt = solvers.qp(opt.matrix(x1 * S), -pbar, G, h, A, b)['x'] return np.asarray(wt), returns, risks
Please let me know if you can help in anyway