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I took daily adjusted close prices (all history) from Yahoo Finance and ran the following code:

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
spy=pd.read_csv("SPY.csv")
spy['Date'] =  pd.to_datetime(spy['Date'], infer_datetime_format=True)
spy["LogRet"]=np.log(spy["Adj Close"]).diff()
pd.plotting.autocorrelation_plot(spy.LogRet[1:],ax= plt.gca(xlim=(1, 10), ylim=(-.1, .1)))

enter image description here

It appears the daily log-returns are autocorrelated past the 99% significance level. Did I mess up? Or if this is true, then why does such a simple stat-arb opportunity exist?

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