Forecast Modeling with different time period datas

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Adam
Adam am 20 Okt. 2014
Kommentiert: Adam am 21 Okt. 2014
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?

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Roger Wohlwend
Roger Wohlwend am 21 Okt. 2014
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.
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Adam
Adam am 21 Okt. 2014
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.

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