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Take this example python code:
from bidask import edge
o = np.array([29.926592, 28.242779, 27.170715, 27.953915, 26.39432, 26.888105,
26.966768, 27.62503, 27.7497, 28.776056, 29.558401, 29.762136,
30.09086, 29.762465, 29.762665, 30.051258, 29.926998, 29.847376,
27.624899, 27.624887, 30.505402, 30.419634, 30.709461, 30.670303,
31.242111, 32.847298, 35.681507, 41.43737 , 49.987385, 52.289425],
dtype=np.float32)
h = np.array([32.886364, 28.282244, 28.94, 28.69716, 27.584791, 27.295898,
27.913893, 28.243303, 28.571865, 29.59823, 30.051699, 30.54483 ,
30.255291, 30.012405, 30.216503, 30.215687, 30.420301, 29.847376,
27.828798, 31.5713, 30.992119, 30.87346, 30.709461, 31.282,
32.886433, 34.98494, 40.45, 52.00061 , 52.618298, 52.578827],
dtype=np.float32)
l = np.array([26.309092, 26.184095, 26.348557, 26.474, 26.308815, 26.802599,
26.67737, 26.927826, 27.545805, 28.407722, 29.144032, 29.722672,
29.14374, 29.473063, 29.762665, 29.433, 29.190334, 27.663742,
26.967163, 27.624887, 29.887136, 30.340708, 30.255629, 30.459827,
31.202648, 32.597363, 35.47761, 41.397907, 48.836357, 50.151806],
dtype=np.float32)
c = np.array([28.94, 26.559, 28.94, 26.474, 27.006, 27.092, 27.71, 27.75 ,
28.243, 29.026, 29.269, 30.091, 29.762, 29.723, 30.131, 29.433,
29.927, 28.282, 27.421, 31.078, 30.216, 30.834, 30.67, 31.282,
32.722, 34.735, 40.45, 47.357, 52.125, 50.849], dtype=np.float32)
spread = edge(o, h, l, c)
print(spread)
assert spread != 0The spread here is estimated at zero, which seems unlikely. This is real stock data for 30 days of a random stock I pulled (split adjusted prices for ticker A with last entry being on 1999-12-31).
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