Stationary and non stationary determination
When we execute the DF test to check the stationarity for market value data sts.adfuller(df.market_value) we can not reject the null hypothesis due to the p value is .33 (higher than all signifince level),
But we reject the null hypothesis with the returns data even if we got a higher p value (7.2) than the p value of FTSE prices
Isn't there a contradiction in applying that method?
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Pay attention to the scientific notation behind it.
market_value: 0.33010893277028264
returns: 7.798058336040906e-24 -> which basically means 0 (zero)
therefore we reject null hypothesis.
and remember p-value range is between 0 and 1.
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