Solved – Time series: daily data and daily data without weekends

datasettime series

I've got a daily data set on Bitcoin's price. Trading continues in the weekends, hence there is price data in the weekends as well.

On the other hand, i've got another daily data set. This set does not have data for the weekends.

I want to make a time series regression with the two sets but what should i do with the weekends? Should I replace the empty weekends with the average? Then, missing values will just be replaced by the average.

Edit:
Im going to regress dataset X on the price of BTC. Thus BTC is the dependent variable.
Dataset X: no weekend data, workweeks=daily data
BTC: daily data on the price, also weekends.

Best Answer

Assuming you produce two models, one for predicting Bitcoin (BTC), one for predicting the other while always using both as inputs:

  • For predicting BTC (imputing input only): Fill the last value from the work-week (e.g. Friday) as value for the weekend.
  • For predicting the other (imputing input and output): You can do the same as above (will introduce a slight bias to predict values that appear on Fridays). Or you can consider discarding weekend BTC data and just treat the problem as time series without weekend.
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