I am trying to predict demand of Automobiles at dealer and Variant level. I have 2 year, 2 months daily sales data. I need to predict demand at monthly level based on daily data for Enquiry.Dummy data for forecasting

Just to make it more clear, if I am on 5th of March 2017 so based on enquiries so far, earlier sales data etc. I need to predict total sales of March. Again, if I am on 15th of March so based on total enquiries till 15th, sales so far in month (in last 30 days etc.), I need to predict total sales for the month of March.

I have tried regression using lagged variables like total sales in last 30 days, total enquiries in last 30 days etc, but results are very poor. I have tried auto.arima with exogenous variable but results are not very good.

Sales are high on weekends and on March and October (Festival season in India).
I have few questions:

  1. What should be my approach?
  2. What are the other techniques I can use?
  3. I had built ARIMA at day of month level but it gives me only 26 data points. (12*2+) 31 models in total and it does not take care of weekend effect. Can this be improved?
  4. Can some state space model be used here?

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.