Modeling Time Series with the Wilkie Model in @RISK

 

All editions of @RISK can model time series using the Wilkie model with parameters you select. With @RISK Industrial, you can also fit parameters to historical data using the Time Series feature.

Example Prototype:

• Two Wilkie models are included: Retail Price Index (RPI) and Share Dividend Yield (SY).

RPI Model:

• Parameters can be set manually (recommended literature values are on the Wilkie Models sheet).

• Alternatively, use @RISK’s Time Series fitting with an AR1 model.

• Historical data (column C of the Data sheet) can be transformed logarithmically and detrended using first-order differencing.

• The resulting parameters (mean, standard deviation, autoregressive parameter) are listed on the Parameters RPI sheet.

• With these parameters, create the RPI time series model on the RPI sheet.

SY Model:

• Constructed directly using recommended literature parameters.

• See the SY sheet for implementation.

This approach allows easy creation and analysis of Wilkie time series models, either by parameter selection or fitting to historical data.

 

 

Attachments:
Wilkie Models.xlsx