Thursday, March 8, 2012
Top 10 reasons for a modeler to learn PROC FCMP
10. New financial functions
34 pre-compiled financial functions were shipped with SAS for free, which can be called in DATA step.
9. A management GUI
There is a nice-looking Java-powered GUI to manage the user-defined functions: SAS FCmp function editor.
8. Dynamic parameters
Parameters from other statistical procedures in SAS can be passed to a function. We can use a macro to wrap PROC FCMP to create tons of data-driven functions (temporary or permanent).
7. Migration from VBA
Excel dominates every desktop. However, using VBA to process large data is just a pain, such as calculating a transition matrix for probability of default. PROC FCMP is built on the logic of VBA -- easy to port any Excel macro/functions to SAS.
PROC FCMP loads data into memory. For backtesting task, it is much more efficient than hard-disk based DATA step.
5. Function/subroutine compiler
A lot of functions/subroutines SAS doesn’t have can be built, such as Binomial tree function or an asset price simulation subroutine.
To combine a lot of macros/nested macros for a complicated system, encapsulating the macro variables is a serious concern – PROC FCMP may be a rescue.
3. Monte Carlo simulation
The MCMC procedure, the designated procedure for Monte Carlo simulation in SAS, fully supports the syntax of PROC FCMP with its BEGINCNST and ENDCNST statements.
2. Deal with matrix
As part of SAS/BASE, PROC FCMP, allows all kinds of matrix operations everywhere with a SAS system.
1. Low level computation
The combination of PROC FCMP and PROC PROTO together wraps C functions in SAS. It is interesting to compare the efficiency between a C function and a SAS function.
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