Difference between revisions of "Temporal Grid"
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== Definition == | == Definition == | ||
− | + | A '''Temporal Grid''' denotes the specification of how precisely the information that describes the state and processes ongoing within the financial system is captured along the temporal dimension. | |
== Usage == | == Usage == | ||
− | In the simplest case, future cashflows of credit asset and liabilities that are part of the credit network are considered at a set of given ''timepoints'' <math>t_k \in [T_0,T_M]</math>. | + | In the context of a [[Credit Network]] model an in the simplest case, future cashflows of credit asset and liabilities that are part of the credit network are considered at a set of given ''timepoints'' <math>t_k \in [T_0,T_M]</math>. |
The modelling period spans the time interval from the current date (as-off date) <math>T_0</math> till the end of the calculation period (e.g., expected life / longest tenor) <math>T_M</math> of all credit assets and/or liabilities). | The modelling period spans the time interval from the current date (as-off date) <math>T_0</math> till the end of the calculation period (e.g., expected life / longest tenor) <math>T_M</math> of all credit assets and/or liabilities). |
Latest revision as of 17:34, 21 May 2024
Definition
A Temporal Grid denotes the specification of how precisely the information that describes the state and processes ongoing within the financial system is captured along the temporal dimension.
Usage
In the context of a Credit Network model an in the simplest case, future cashflows of credit asset and liabilities that are part of the credit network are considered at a set of given timepoints .
The modelling period spans the time interval from the current date (as-off date) till the end of the calculation period (e.g., expected life / longest tenor) of all credit assets and/or liabilities).
NB: For brevity we may drop the M index and refer to $T$ instead and similarly indicate a timepoint by its index k instead of .
Grid Variables
All variables represented on the grid are either state or flux (flow) variables. State variables are associated (e.g represent state) with a single timepoint whereas flow variables are associated with a period .
Issues and Challenges
- When a temporal grid is selected to be coarse (e.g. annual) all input data must be appropriately mapped to timepoints/periods.