Refinancing model

1. A computer-implemented method for modeling a current expected prepayment spread for a mortgage-backed security (MBS) as a function of a current refinance activity, the method comprising:

for each of a plurality of historical time values:

computing a historical MBS prepayment spread value; and

determining a historical refinance activity value;

wherein the historical MBS prepayment spread value and the corresponding historical refinance activity value define a data pair;

processing the data pairs corresponding to the plurality of historical time values to determine the current expected prepayment spread in accordance with the current refinance activity.

2. The method of claim 1 , wherein computing a historical MBS prepayment spread value for each of the plurality of historical time values includes:

determining a historical MBS yield value for the corresponding historical date;

computing a historical benchmark yield value for the corresponding historical date; and

computing a spread between the historical MBS yield value and the historical benchmark yield value.

3. The method of claim 2 , wherein computing a historical benchmark yield value includes computing a historical swap value.

4. The method of claim 3 , wherein computing a historical swap value includes computing a historical swap value having a weighted average life equivalent to a weighted average life of the MBS.

5. The method of claim 1 , wherein determining a historical refinance activity value includes determining a historical refinance activity value using a published refinance index.

6. The method of claim 1 , wherein processing the data pairs includes processing the data pairs using statistical methods.

7. The method of claim 6 , wherein processing the data pairs using statistical methods includes processing the data pairs using a linear regression algorithm.

8. A method for determining a current value of a mortgage-backed-security (MBS), the method comprising:

computing a first current prepayment spread value for the MBS;

computing a second current prepayment spread value for the MBS; and

determining the current value of the MBS based upon a comparison of the first current prepayment spread to the second current prepayment spread.

9. The method of claim 8 , wherein computing a first current prepayment spread value for the MBS includes computing an observed current prepayment spread value.

10. The method of claim 8 , wherein computing a second current prepayment spread value for the MBS includes computing a current expected prepayment spread value based on a current refinance activity value.

11. The method of claim 10 , wherein computing a current expected prepayment spread value based on a current refinance activity value includes:

for each of a plurality of historical time values:

computing a historical MBS prepayment spread value; and

determining a historical refinance activity value;

wherein the historical MBS prepayment spread value and the corresponding historical refinance activity value define a data pair;

processing the data pairs corresponding to the plurality of historical time values to determine the current expected prepayment spread in accordance with the current refinance activity value.

12. The method of claim 11 , wherein computing a historical MBS prepayment spread value for each of the plurality of historical time values includes:

determining a historical MBS yield value for the corresponding historical date;

computing a historical benchmark yield value for the corresponding historical date; and

computing a spread between the historical MBS yield value and the historical benchmark yield value.

13. The method of claim 12 , wherein computing a historical benchmark yield value includes computing a historical swap value.

14. The method of claim 13 , wherein computing a historical swap value includes computing a historical swap value having a weighted average life equivalent to a weighted average life of the MBS.

15. The method of claim 11 , wherein determining a historical refinance activity value includes determining a historical refinance activity value using a published refinance index.

16. The method of claim 11 , wherein processing the data pairs includes processing the data pairs using statistical methods.

17. The method of claim 16 , wherein processing the data pairs using statistical methods includes processing the data pairs using a linear regression algorithm.

18. A computer-readable medium comprising computer-executable instructions thereon which, when executed by a processor, cause the processor to:

for each of a plurality of historical time values:

compute a historical MBS prepayment spread value; and

determine a historical refinance activity value;

wherein the historical MBS prepayment spread value and the corresponding historical refinance activity value define a data pair;

process the data pairs corresponding to the plurality of historical time values to determine a current expected prepayment spread in accordance with a current refinance activity.

19. The medium of claim 18 , wherein the instructions cause the processor to process the data pairs using a linear regression algorithm.

20. A computer-implemented system for modeling a current expected prepayment spread for a mortgage-backed security (MBS) as a function of a current refinance activity, the system comprising:

a derivation module, wherein the derivation module is for:

for each of a plurality of historical time values:

computing a historical MBS prepayment spread value; and determining a historical refinance activity value;

wherein the historical MBS prepayment spread value and the corresponding historical refinance activity value define a data pair; and

processing the data pairs corresponding to the plurality of historical time values to determine a model that is used to calculate the current expected prepayment spread, wherein the model includes as a variable the current refinance activity;

a database in communication with the derivation module for storing the model; and

an application module for retrieving the model from the database and for computing the current expected prepayment spread based upon the model and a current refinance activity value;

wherein the application module is stored in a computer-readable medium.