The Dataset is time series data of crypto currency consisting of of 1869 observation and 21 features(each feature showing different crypto currency). Frequency of the observations is 5 min showing from date 18/01/18 to 24/01/18.
As the data belongs to the crypto exchange. Intraday short-term data infers to the short-term speculation objective of the prediction model.
Predicting the 5 min data for particular observations in continuous time format.
Each observation (21) in the dataset is closing value of respective observation along with timestamp. Columns are numerical values.
There were lot many observations missing in the dataset. We built regression model to impute those values.
Plot, examine, and prepare series for modeling
Extract the seasonality component from the time series
Test for stationarity and apply appropriate transformations
Choose the order of an ARIMA model
Forecast the series