We will use the `hanning()`

function to smooth arrays of stock returns, as shown in the following steps:

- Call the
`hanning()`

function to compute weights for a certain length window (in this example 8) as follows:N = 8 weights = np.hanning(N) print("Weights", weights)

The weights are as follows:

**Weights [ 0. 0.1882551 0.61126047 0.95048443 0.95048443 0.61126047****0.1882551 0. ]** - Calculate the stock returns for the BHP and VALE quotes using
`convolve()`

with normalized weights:bhp = np.loadtxt('BHP.csv', delimiter=',', usecols=(6,), unpack=True) bhp_returns = np.diff(bhp) / bhp[ : -1] smooth_bhp = np.convolve(weights/weights.sum(), bhp_returns)[N-1:-N+1] vale = np.loadtxt('VALE.csv', delimiter=',', ...

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