METHODS AND SYSTEMS FOR ASSESSING UNDERWRITING AND DISTRIBUTION RISKS ASSOCIATED WITH SUBORDINATE DEBT

• US 20090307146A1
• Filed: 06/09/2008
• Published: 12/10/2009
• Est. Priority Date: 06/09/2008
• Status: Active Grant

• Current Assignee: GE Corporate Financial Services, Inc. (General Electric Company)
• Original Assignee: GE Corporate Financial Services, Inc. (General Electric Company)
• Inventors: Allred, Charles, Keenan, Sean Coleman, Keyes, Tim Kerry
• Granted Patent: US 9,892,461 B2
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

A method for assessing underwriting and distribution risks associated with a portfolio of subordinate debt is provided. The method is performed using a computer system coupled to a database. The method includes storing in the database historical bond issue data for a period of time preceding and proceeding at least one historical liquidity event and generating a plurality of simulated subordinate debt warehouses using the computer and the historical bond issue data stored in the database. The method also includes calculating a historical loss distribution based on the plurality of simulated subordinate debt warehouses generated. The method also includes determining a value at risk for a portfolio of subordinate debt resulting from a potential liquidity event by applying the historical loss distribution to the portfolio of subordinate debt.

Claims

1. A method for assessing underwriting and distribution risks associated with a portfolio of subordinate debt, said method performed using a computer system coupled to a database, said method comprising:

storing in the database historical bond issue data for a period of time preceding and proceeding at least one historical liquidity event;

generating a plurality of simulated subordinate debt warehouses using the computer and the historical bond issue data stored in the database;

calculating a historical loss distribution based on the plurality of simulated subordinate debt warehouses generated, the historical loss distribution representing reduction in value of the bonds stored in the database from the at least one historical liquidity event; and

determining a value at risk for a portfolio of subordinate debt resulting from a potential liquidity event by applying the historical loss distribution to the portfolio of subordinate debt, the value at risk representing a value that based on the historical loss distribution has a predetermined probability of eroding.

2. A method in accordance with claim 1, wherein storing in the database historical bond issue data comprises storing at least one of a historical bond price on a first day of the event, a historical bond price on a last day of the event, and historical bond prices at predetermined, or intermittent, intervals during the event.

3. A method in accordance with claim 1, wherein storing in the database historical bond issue data comprises storing a historical bond price from six months preceding the at least one historical liquidity event and a historical bond price from six months proceeding the at least one historical liquidity event, wherein the at least one historical liquidity event comprises a period of time wherein a decline in a bond market index was greater than any other time period being considered.

4. A method in accordance with claim 1, wherein generating the plurality of simulated subordinate debt warehouses and calculating the historical loss distribution further comprises performing Monte Carlo trials on the historical bond issue data.

5. A method in accordance with claim 1, wherein calculating the historical loss distribution further comprises generating a baseline warehouse loss distribution and generating an adjusted warehouse loss distribution by adjusting the baseline warehouse loss distribution to account for at least one of assumed underwriting fees and assumed demand coupon values.

6. A method in accordance with claim 5, wherein determining a value at risk for a portfolio of subordinate debt comprises applying the adjusted warehouse loss distribution to the portfolio of subordinate debt.

7. A method in accordance with claim 6, wherein determining a value at risk for a portfolio further comprises:

calculating an effective deal size of each potential bond deal included in the portfolio of subordinate debt;

calculating a base value at risk of each potential bond deal; and

adjusting the base value at risk of each potential bond deal to determine a final value at risk of each of the potential bond deals.

8. A method in accordance with claim 7, wherein calculating the effective deal size further comprises increasing a deal commitment value to account for differences between at least one of actual underwriting fees and the assumed underwriting fees and actual demand coupon values and the assumed demand coupon values.

9. A method in accordance with claim 7, wherein adjusting the base value at risk further comprises calculating underwriting fees that exceed the assumed value and reducing the base value at risk to account for the excess underwriting fees.

10. A system for assessing underwriting and distribution risks associated with a portfolio of subordinate debt, said system comprising a computer coupled to a database, said computer configured to:

store in said database historical bond issue data for a period of time preceding and proceeding at least one historical liquidity event;

generate a plurality of simulated subordinate debt warehouses using the historical bond issue data stored in said database;

calculate a historical loss distribution based on the plurality of simulated subordinate debt warehouses generated, the historical loss distribution representing reduction in value of the bonds stored in said database from the at least one historical liquidity event; and

determine a value at risk for a portfolio of subordinate debt resulting from a potential liquidity event by applying the historical loss distribution to the portfolio of subordinate debt.

11. A system in accordance with claim 10, wherein said computer is further configured to store at least one of a historical bond price from six months preceding the at least one historical liquidity event, a historical bond price on a first day of the event, a historical bond price on a last day of the event, and a historical bond price on from six months proceeding the at least one historical liquidity event, wherein the at least one historical liquidity event comprises a period of time wherein a decline in a bond market index was greater than any other time period being considered.

12. A system in accordance with claim 10, wherein said computer is further configured to perform Monte Carlo trials on the historical bond issue data to generate the plurality of simulated subordinate debt warehouses and calculate the historical loss distribution.

13. A system in accordance with claim 10, wherein said computer is further configured to generate a baseline warehouse loss distribution and an adjusted warehouse loss distribution, said computer configured to generate the adjusted warehouse loss distribution by adjusting the baseline warehouse loss distribution to account for at least one of assumed underwriting fees and assumed demand coupon values.

14. A system in accordance with claim 10, wherein said computer is further configured to:

calculate an effective deal size of each potential bond deal included in the portfolio of subordinate debt;

calculate a base value at risk of each potential bond deal; and

adjust the base value at risk of each potential bond deal to determine a final value at risk of each of the potential bond deals.

15. A system in accordance with claim 14, wherein said computer is further configured to calculate the effective deal size by increasing a deal commitment value to account for differences between at least one of actual underwriting fees and the assumed underwriting fees and actual demand coupon values and the assumed demand coupon values.

16. A system in accordance with claim 14, wherein said computer is further configured to adjust the base value at risk by calculating underwriting fees that exceed the assumed value and reducing the base value at risk to account for the excess underwriting fees.

17. A server system for assessing underwriting and distribution risks associated with a portfolio of subordinate debt, said system comprising:

a client system comprising a browser;

a centralized database for storing information; and

a server system configured to be coupled to said client system and said database, said server further configured to;

store in said database historical bond issue data for a period of time preceding and proceeding at least one historical liquidity event;

generate a plurality of simulated subordinate debt warehouses using the historical bond issue data stored in said database;

calculate a historical loss distribution based on the plurality of simulated subordinate debt warehouses generated, the historical loss distribution representing reduction in value of the bonds stored in said database from the at least one historical liquidity event; and

determine a value at risk for a portfolio of subordinate debt resulting from a potential liquidity event by applying the historical loss distribution to the portfolio of subordinate debt.

18. A system in accordance with claim 17, wherein said server is further configured to store at least one of a historical bond price from six months preceding the at least one historical liquidity event, a historical bond price on a first day of the event, a historical bond price on a last day of the event, and a historical bond price from six months proceeding the at least one historical liquidity event, wherein the at least one historical liquidity event comprises a period of time wherein a decline in a bond market index was greater than any other time period being considered.

19. A system in accordance with claim 17, wherein said server is further configured to perform Monte Carlo trials on the historical bond issue data to generate the plurality of simulated subordinate debt warehouses and calculate the historical loss distribution.

20. A system in accordance with claim 17, wherein said server is further configured to generate a baseline warehouse loss distribution and an adjusted warehouse loss distribution, said server configured to generate the adjusted warehouse loss distribution by adjusting the baseline warehouse loss distribution to account for at least one of assumed underwriting fees and assumed demand coupon values.

21. A system in accordance with claim 20, wherein said server is further configured to:

calculate an effective deal size of each potential bond deal included in the portfolio of subordinate debt;

calculate a base value at risk of each potential bond deal; and

adjust the base value at risk of each potential bond deal to determine a final value at risk of each of the potential bond deals.

22. A system in accordance with claim 21, wherein said server is further configured to calculate the effective deal size by increasing a deal commitment value to account for differences between at least one of actual underwriting fees and the assumed underwriting fees and actual demand coupon values and the assumed demand coupon values.

23. A system in accordance with claim 21, wherein said server is further configured to adjust the base value at risk by reducing the base value at risk to account for underwriting fees that exceed the assumed underwriting fees.

24. A computer program embodied on a computer readable medium for assessing underwriting and distribution risks associated with a portfolio of subordinate debt, said program comprising at least one code segment that:

stores in a database historical bond issue data for a period of time preceding and proceeding at least one historical liquidity event;

generates a plurality of simulated subordinate debt warehouses using the historical bond issue data stored in the database;

calculates a historical loss distribution based on the plurality of simulated subordinate debt warehouses generated, the historical loss distribution representing reduction in value of the bonds stored in the database from the at least one historical liquidity event; and

determines a value at risk for a portfolio of subordinate debt resulting from a potential liquidity event by applying the historical loss distribution to the portfolio of subordinate debt.

25. A computer program in accordance with claim 24 further comprising at least one code segment that stores at least one of a historical bond price from six months preceding the at least one historical liquidity event, a historical bond price on a first day of the event, a historical bond price on a last day of the event, and a historical bond price from six months proceeding the at least one historical liquidity event, wherein the at least one historical liquidity event comprises a period of time wherein a decline in a bond market index was greater than any other time period being considered.

26. A computer program in accordance with claim 24 further comprising at least one code segment that performs Monte Carlo trials on the historical bond issue data to generate the plurality of simulated subordinate debt warehouses and calculate the historical loss distribution.

27. A computer program in accordance with claim 24 further comprising at least one code segment that generates a baseline warehouse loss distribution and an adjusted warehouse loss distribution by adjusting the baseline warehouse loss distribution to account for at least one of assumed underwriting fees and assumed demand coupon values.

28. A computer program in accordance with claim 27 further comprising at least one code segment that:

calculates an effective deal size of each potential bond deal included in the portfolio of subordinate debt;

calculates a base value at risk of each potential bond deal; and

adjusts the base value at risk of each potential bond deal to determine a final value at risk of each of the potential bond deals.

29. A computer program in accordance with claim 28 further comprising at least one code segment that calculates the effective deal size by increasing a deal commitment value to account for differences between at least one of actual underwriting fees and the assumed underwriting fees and actual demand coupon values and the assumed demand coupon values.

30. A computer program in accordance with claim 28 further comprising at least one code segment that adjusts the base value at risk by calculating underwriting fees that exceed the assumed value and reducing the base value at risk to account for the excess underwriting fees.