Forecast Modeling with different time period datas

I want to model electricity price forecasting. However I have different time period datas. For example; I have hourly and daily datas for different variables. I do not know how to combine them in a model? Do you have any idea?

Answer 1

[Roger Wohlwend]

If you want to forecast hourly price movements then you have to ignore the daily data and work with the hourly data only. However, if you intend to forecast prices on a daily basis, use the whole dataset. For the hourly data use the latest data point of each day only. If you have the Financial toolbox, create a fints object for each time series and merge them with the function merge. In such a way it is quite easy to combine data with different frequencies.

[Adam]

Hi Roger. Thank you for your reply at first. I wish to ignore all daily variables however hourly data and daily data are related each other. I have to know what is the effect each other to the model. Morever I have approx. 12 different data type and I am thinking to group them but I do not how to do it. For example I have x,y,z,t datas. I have to analysis firstly z,t data because I know its results effect to x more relaible. Than make analysis with others.

I am thinkinh of state space form of equation. For example x,y and z are the hourly datas however t is daily data. I can build a model with x,y,z and put the daily t data into the equation as a trend function in state-space form but I am really confused how to do it.