I am trying to build an ARIMA model for the movements of the returns of a
stock. I have differentiated my data series once to make it stationary.
The autocorrelations and partial autocorrelations do not show any clear
pattern to indicate a model. I have tried all kinds of low-order models,
but they fit the data VERY poorly. However, if I differentiate it three
times or more, the fit gets better. But, what does this mean? The series
is stationary after the first differencing and should require no further
differencing. Is it that further differencing only smoothes the curve out?
Is it possible that a process like this cannot be modelled with ARIMA?
Any help would be greatly appreciated.
Nilufer
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