Question

我正在尝试为随机生成的投资组合计算投资组合值，例如收益，标准差。但是，在计算标准偏差时出现错误

试图将numpy数组转换为矩阵，但仍然无法正常工作。

for i in range(no_of_portfolios):
            #Select random weights and normalize to set the sum to 1
            weights = np.array(np.random.random(no_of_assets))
            weights /= np.sum(weights)
            print("Weights are before reshaping",weights,np.shape(weights))
            np.reshape(weights,(3,1))
            print("Weights are after reshaping",weights,np.shape(weights))
            #Calculate the return and standard deviation for every step
            portfolio_return = np.sum(mean_returns * weights)            
            portfolio_std_dev = np.sqrt(np.dot(weights.T,np.dot(v_cov, weights)))

            #Store all the results in a defined array
            v_simulation_res[0,i] = portfolio_return
            v_simulation_res[1,i] = portfolio_std_dev

v_cov is [[ 0.04   -0.009  -0.01  ]
 [-0.009   0.0225 -0.009 ]
 [-0.01   -0.009   0.01  ]]
no_of_portfolios = 10
    no_of_assets = 3
    mean_returns = np.matrix([[0.3],[0.2],[0.1]])
    vol_arr = np.matrix([[0.2],[.15],[0.1]])
    rho_arr = np.matrix([[1,-0.3,-0.5],[-0.3,1,-0.6],[-0.5,-0.6,1]])

对于资产权重的每种组合，我都希望为Portfolio_std_dev获得一个数字，即10个值（每行一个）

我遇到错误：

ValueError: shapes (3,) and (1,3) not aligned: 3 (dim 0) != 1 (dim 0)

可能是因为weights数组的形状为（3,0），但不确定如何修复它。

Answer 1

np.reshape（weights，（3,1））
print（“重量在重塑之后”，weights，np.shape（weights））

np.reshape返回整形数组。它没有改变。所以，我不确定您在这里做什么，但我猜您错过了形状变化吗？如果要更改形状，请分配权重。

尝试使用numpy计算投资组合标准差，出现错误

1 个答案: