@karun_r wrote:
I have a time series data set where the target variable has data ranging from -3000000 to somewhere around 120000000 with lots of 0 values in between and with no proper pattern (or atleast not so obvious pattern). Because of this crazy range, the scaling/normalization methods are also not working properly and require me to predict the variable with upto 7 floating point accuracy.
My question is, is it suggested to use an ARIMA model for this data set ? This paper below doesn’t recommend ARIMA models for high volatile data.
Paper Name -
“Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”How do we proceed with cases like this ? Any guidance regarding this would be really helpful.
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