[Numpy-discussion] Is there a function to calculate ecnomic beta coefficient in numpy given two time series data.

[Vineet Jain (gmail)]

Currently my code handles market returns and stocks as 1d arrays. While the
function below expects a matrix. Is there an equivalent of the function
below which works with numpy arrays?

I'd like to do:

beta, resids, rank, s = mp.linalg.lstsq(mrkt_1d_array, stock_1d_array)

If not, how do:

1. create an empty matrix object and then keep adding arrays objects to it
in a loop?

Thanks,

Vineet

>> import numpy.matlib as mp
>> mrkt = mp.randn(250,1)  # <----- 250 days of returns
>> stocks = mp.randn(250, 4)  # <---- 4 stocks
>> beta, resids, rank, s = mp.linalg.lstsq(mrkt, stocks)
>> matrix([[-0.01701467,  0.11242168,  0.00207398,  0.03920687]])