simplelife is a project template to build an annual projection model of basic traditional life policies.
A simplelife model projects life insurance cashflows and reserves for policies represented by model points. Projection items include:
Required capital and investment assets are not modeled. Input data, such as:
are read from an Excel file.
Create a project folder as explained in First Project section.
To build the model, simply run simplelife,
then move to the interactive mode. In Spyder, you can do so by opening the
simplelife and simply run it.
After the script is run, the model is accessible
as model global variable
in the IPython console in Spyder.
You want to make sure the Python session will not terminate after the script is run, in order for you to do manipulate the model.
The model is accessible through the global variable named model.
It is a Model object. Some components of the model are also accessible through global variables.
These are Space objcets. Model and Space are classes defined in modelx package.
For the complete list of model componets available as global variables,
see simplelife page.
See simplelife page for further details on the building process,
There is no explicit ‘Run’ command to run the model. The model calculates its values on the fly, when requested.
The diagram below shows the spaces contained in a simplelife model.
Note that the subspaces under Input space are not drawn in the diagram,
as they are quite a few. For details on the Input subspaces, see simplelife.build_input page.
There are three types of relationships between spaces, namely composition, inheritance, and dependency. The diagram above only depicts composition and inheritance relationships, but does not show dependency relationships. Spaces that each module depends on are listed in the ref section on the page of each source module.
Composition
Lines with the filled diamond arrowheads denote that the spaces on the arrowhead ends contain(and owns) the spaces on the other ends of the lines. In the example diagram below, Space A contains Space B, i.e. Space A is the parent of the Space B, and in tern Space B is a child of Space A. Note that spaces can be directly under their model, in which case the parent of the spaces is the model.
Inheritance
Lines with the hollow triangle arrowheads denote that the spaces on the ends without the arrowheads are derived from the spaces pointed by the arrowheads. In the example diagram below, Space B is derived from Space A, which means copies of all the cells, spaces and refs in Space A are included in Space B.
The Space B above is drawn as a dotted rectangular to indicate that the space acts solely as a base space of others, and it’s not meant to be directly accessed by the user.
Dependency
When Space B is dependent on Space A, then cells in Space B refer to members of Space A to calculate their values by their formulas. Dependency is not necessarily the relationship between spaces, but it could be the cells
Dynamic Spaces
Dynamic spaces are drawn as a stacked rectangular shape.
Dynamic spaces are, in fact, a ‘normal’ space with its child spaces dynamically
created when accessed via subscription([]) or call(()) operator.
In the example diagram below, Spaces A[x] are dynamic spaces.
Space A is a normal space and it has a x parameter.
If A is accessed by, for example A[1], then a dynamic child space is created under
Space A, and in the dynamic child space A[1],
Variable x is available in the child space and it is set to 1.
simplelife |
The main module to build a simplelife model. |
build_input |
Module to create Input space and its child spaces from input data. |
lifetable |
Source module to create LifeTable space from. |
policy |
Source module to create Policy space from. |
assumption |
Source module to create Assumption space from. |
economic |
Source module to create Economic space from. |
projection |
Source module to create Projection space from. |
present_value |
Present Value mix-in modules |