What's the difference between pandas ACF and statsmodel ACF?

Question

I\'m calculating the Autocorrelation Function for a stock\'s returns. To do so I tested two functions, the autocorr function built into Pandas, and the acf

Answer 1

As suggested in comments, the problem can be decreased, but not completely resolved, by supplying unbiased=True to the statsmodels function. Using a random input:

import statistics

import numpy as np
import pandas as pd
from statsmodels.tsa.stattools import acf

DATA_LEN = 100
N_TESTS = 100
N_LAGS = 32

def test(unbiased):
  data = pd.Series(np.random.random(DATA_LEN))
  data_acf_1 = acf(data, unbiased=unbiased, nlags=N_LAGS)
  data_acf_2 = [data.autocorr(i) for i in range(N_LAGS+1)]
  # return difference between results
  return sum(abs(data_acf_1 - data_acf_2))

for value in (False, True):
  diffs = [test(value) for _ in range(N_TESTS)]
  print(value, statistics.mean(diffs))

Output:

False 0.464562410987
True 0.0820847168593