I'm using stock price data to model the volatility and forecast volatility using EViews. In forecasting when I use the static forecast, the mean absolute percentage error is high but it is low when I use dynamic forecast. What is the difference between these two methods? and which is more accurate?
The differences are in the forecast origin t and the forecast horizon h. In dynamic forecasting, the forecast origin is moving and the forecast horizon is fixed. In static forecasting, the forecast origin is fixed and the forecast horizon varies. That means that the static forecast at time t + h doesn't make use of the observations at time t + h - 1, ..., t + 1, whereas the dynamic forecast at time t + h can make use of these observations. The information set is thus not the same. Consequently, there is no sense to compare the two kinds of forecasts although, typically, the dynamic forecasts will often appear better. For the concept of information set, see e.g., the book by Clive Granger entitled Forecasting in Business and Economics, 1980.
Dynamic forecast uses the value of the previous forecasted value of the dependent variable to compute the next one.
Static forecast uses values of explanatory variables from the forecast sample.
Choosing the right one depends on your model.
In EViews, a static forecast is a one-step ahead forecast that uses the actual value for each subsequent forecast. A dynamic forecast is a multi-step ahead forecast that uses the previous forecasted value of the dependent variable to compute the next one.
As for which gives the most accurate forecasts, it depends on the data and the model used. In general, dynamic forecasts are more accurate than static forecasts. However, it is always important to evaluate the accuracy of both methods before making any conclusions.
In the dynamic forecast, the lagged residuals are forecasted dynamically. This means that future values of lagged residuals are formed using the forecasted values of the dependent variable. In contrast, the static forecast uses actual lagged residuals and actual values for the dependent variable to produce forecasts.
- Badges
- Science topic
- Similar topics
- Methodology
- Research Methodology
- Research Papers