The Scenario Analysis allows the study of
possible future events on the basis of the different performances
of some economic or financial variables (scenarios).
The method of the Scenario Analysis supplements
and integrates simulation techniques since it leads to choose,
among the various future outcomes of interest and in a flexible
way, the trajectory which comes from the scenario that best
corresponds to the set of events which are happening.
Correct use of this technique suggests that:
scenarios correspond to several degrees of trends of the
economic state of interest;
scenarios are defined by a small number of variables with
respect to the number of simulated outputs;
selected independent variables, through their possible
combinations, must be representative in sufficient detail
of the various economic situations that may happen during
the chosen forecast period.
The estimation of future realisations of
variables of interest on the basis of different scenarios
leads to a better understanding of the implications between
the simulated outputs and the scenario variables.
In general, every scenario has its own probability
to occur which reflects the degree of likelihood that the
related hypotheses may happen. The user can choose to utilise
the forecasts related to the scenario more probable and/or
more coherent with his perception of the behaviour of the
GRETA uses this approach in making its monthly reports MEFIM, MEFIM Plusand GAM.
In this case, the levels of bank and inter-bank rates, interest
rate term structure and banks' volumes are forecasted on the
basis of three scenarios, defined from the refinancing rate
of the central banks, market indexes, industrial production
indexes and consumer price indexes. These variables are a
useful guideline to define various possible trends of the
GRETA applies the scenario analysis to the GREM (GRETA Regional Macroeconometric Model) that
is a quarterly product dedicated to the Italian regions. GREM is a macroeconometric model based on annual data and provides
forecasts of some variables judged relevant in the regional
economic programming process and in the evaluation of the
European Community programs. G.R.E.M. is developed for all
the Italian regions.
GRETA has also taken advantage of this approach with
reference to Asset Allocation models. In particular, approaches to find an efficient way
to optimise the portfolio composition, on the basis of operator's
views on the future behaviour of the economy, have been developed.
The main advantage is to obtain a link between the business
cycle and the expected portfolio performance, thanks to the
specification of several scenarios of asset price realisations.