In Python-End-to-end-Data-Analysis/Module2/Python_Data_Analysis_code/Chapter 7/random_walk.ipynb
according to the formula given in the book
ratiosratios == [][]
for symbol in ch7util.STOCKS:
ohlc = dl.data.OHLC()
P = ohlc.get(symbol)['Adj Close'].values
N = len(P)
mu = (np.log(P[-1]) - np.log(P[0]))/N
var_a = 0
var_b = 0
for k in range(1, N):
var_a = (np.log(P[k]) - np.log(P[k - 1]) - mu) ** 2
var_a = var_a / N
for k in range(1, N//2):
var_b = (np.log(P[2 * k]) - np.log(P[2 * k - 2]) - 2 * mu) ** 2
var_b = var_b / N
ratios.append(np.sqrt(N) * (var_b/var_a - 1))
should be
for k in range(1, N):
var_a += (np.log(P[k]) - np.log(P[k - 1]) - mu) ** 2
var_a = var_a / N
for k in range(1, N//2):
var_b += (np.log(P[2 * k]) - np.log(P[2 * k - 2]) - 2 * mu) ** 2
var_b = var_b / N
In Python-End-to-end-Data-Analysis/Module2/Python_Data_Analysis_code/Chapter 7/random_walk.ipynb
according to the formula given in the book
should be