SYSTEMS AND METHODS FOR IMPLEMENTING AN INTEREST-BEARING INSTRUMENT

• US 20100299244A1
• Filed: 04/27/2010
• Published: 11/25/2010
• Est. Priority Date: 02/12/2004
• Status: Active Grant

• Current Assignee: Roger Howard Iii Williams
• Original Assignee: Roger Howard Iii Williams
• Inventors: Williams, Roger Howard III
• Granted Patent: US 8,452,700 B2
• Time in Patent Office: Days
• US Class Current: 705/38
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

Systems and methods are provided that allow a financial instrument to be structured so that the underlying borrowed principal is callable, putable, or both. In a preferred embodiment, a Range Accrual Mortgage is structured so that the underlying borrowed principal is a mortgage that is callable, putable, or both by embedding into the loan structure a rate put option. Systems and methods according to the invention lend symmetry to the interest rate behavior of certain borrowings by making explicit the pricing and market value of options that were previously only implicit in the borrowing structure. For example, a mortgage in accordance with the invention should provide incentives for either the homeowner or the bank to refinance the mortgage and should do so whether interest rates rise or fall, and no matter what path interest rates follow from the inception of the instrument until the maturity of the instrument. The invention achieves the desired advantages, in part, by extending the characteristics of a borrowing via the addition of a rate put option on an interest rate and, in part, by permitting correlative adjustments to the outstanding loan principal.

Claims

1. A computer-implemented apparatus for facilitating issuance of an interest-bearing instrument, comprising:

a memory;

a computer processor in communication with the memory, the computer processor executing functions comprising;

(a) receiving data corresponding to market factors;

(b) storing the received market factors data in a database;

(c) selecting an option model and related parameters;

(d) receiving data corresponding to regression model parameters;

(e) receiving data corresponding to prepayment model parameters;

(f) receiving data corresponding to interest rate term structure model parameters;

(g) receiving data corresponding to default term structure parameters;

(h) receiving data corresponding to transaction indicative details;

(i) normalizing received and stored data;

(j) calculating prepayment probabilities;

(k) calculating a forward term structure;

(l) calculating discount factors;

(m) calculating a default term structure;

(n) calculating an option value from the option model using the prepayment probabilities, the forward term structure, the discount factors, and the default term structure; and

(o) calculating a principal modification value based on the option value.

2. The apparatus of claim 1, further comprising allowing user modification of the calculated option value, or the calculated principal modification value, or both.

3. The apparatus of claim 1, further comprising calculating a risk capital savings using the following equation:

4. The apparatus of claim 1, further comprising allowing real-time analysis of any calculation.

5. The apparatus of claim 1, wherein the market factors data is received from user input, or a networked data feed, or both.

6. The apparatus of claim 1, wherein calculating the forward term structure is done using a Monte Carlo simulation.

7. The apparatus of claim 1, wherein the option model is a Heath-Jarrow-Morton model.

8. The apparatus of claim 1, wherein the option model is a Brace-Gatarek-Musiela model.

9. The apparatus of claim 1, wherein the regression model parameters are based on a Tobit model.

10. The apparatus of claim 1, wherein the regression model parameters are based on a logit model.

11. The apparatus of claim 1, wherein the regression model parameters are based on a probit model.

12. The apparatus of claim 1, wherein the prepayment model parameters are based on an Andy Davidson model.

13. The apparatus of claim 1, wherein the prepayment model parameters are based on an Advanced Financial Technologies model.

22. The method of claim 13, wherein the regression model parameters are based on a Tobit model.

14. A method for facilitating issuance of an interest-bearing instrument, comprising:

(a) receiving data corresponding to market factors;

(b) storing the received market factors data in a database;

(c) selecting an option model and related parameters;

(d) receiving data corresponding to regression model parameters;

(e) receiving data corresponding to prepayment model parameters;

(f) receiving data corresponding to interest rate term structure model parameters;

(g) receiving data corresponding to default term structure parameters;

(h) receiving data corresponding to transaction indicative details;

(i) normalizing received and stored data;

(j) calculating prepayment probabilities;

(k) calculating a forward term structure;

(l) calculating discount factors;

(m) calculating a default term structure;

(n) calculating an option value from the option model using the prepayment probabilities, the forward term structure, and the discount factors, and the default term structures; and

(o) calculating a principal modification value based on the option value.

15. The method of claim 14, further comprising allowing user modification of the calculated option value, the calculated principal modification value, or both.

16. The method of claim 14, further comprising calculating a risk capital savings using the following equation:

17. The method of claim 14, further comprising allowing real-time analysis of any calculation.

18. The method of claim 14, wherein the market factors data is received from user input, or a networked data feed, or both.

19. The method of claim 14, wherein calculating the forward term structure is done using a Monte Carlo simulation.

20. The method of claim 14, wherein the option model is a Heath-Jarrow-Morton model.

21. The method of claim 14, wherein the option model is a Brace-Gatarek-Musiela model.

23. The method of claim 14, wherein the regression model parameters are based on a logit model.

24. The method of claim 14, wherein the regression model parameters are based on a probit model.

25. The method of claim 14, wherein the prepayment model parameters are based on an Andy Davidson model.

26. The method of claim 14, wherein the prepayment model parameters are based on an Advanced Financial Technologies model.

27. A memory storing instructions adapted to be executed by a computer processor to perform a method for facilitating issuance of an interest-bearing instrument, comprising:

(a) receiving data corresponding to market factors;

(b) storing the received market factors data in a database;

(c) selecting an option model and related parameters;

(d) receiving data corresponding to regression model parameters;

(e) receiving data corresponding to prepayment model parameters;

(f) receiving data corresponding to interest rate term structure model parameters;

(g) receiving data corresponding to default term structure parameters;

(h) receiving data corresponding to transaction indicative details;

(i) normalizing received and stored data;

(j) calculating prepayment probabilities;

(k) calculating a forward term structure;

(l) calculating discount factors;

(m) calculating a default term structure;

(n) calculating an option value from the option model using the prepayment probabilities, the forward term structure, the discount factors, and the default teem structure; and

(o) calculating a principal modification value based on the option value.

28. The memory of claim 27, further comprising allowing user modification of the calculated option value, the calculated principal modification value, or both.

29. The memory of claim 27, further comprising calculating a risk capital savings using the following equation:

30. The memory of claim 27, further comprising allowing real-time analysis of any calculation.

31. The memory of claim 27, wherein the market factors data is received from user input, or a networked data feed, or both.

32. The memory of claim 27, wherein calculating the forward term structure is done using a Monte Carlo simulation.

33. The memory of claim 27, wherein the option model is a Heath-Jarrow-Morton model.

34. The memory of claim 27, wherein the option model is a Brace-Gatarek-Musiela model.

35. The memory of claim 27, wherein the regression model parameters are based on a Tobit model.

36. The memory of claim 27, wherein the regression model parameters are based on a logit model.

37. The memory of claim 27, wherein the regression model parameters are based on a probit model.

38. The memory of claim 27, wherein the prepayment model parameters are based on an Andy Davidson model.

39. The memory of claim 27, wherein the prepayment model parameters are based on an Advanced Financial Technologies model.