Systems and methods for implementing an interest-bearing instrument

• US 8,452,700 B2
• Filed: 04/27/2010
• Issued: 05/28/2013
• 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
• Primary Examiner(s): Subramanian, Narayanswamy
• Application Number:
  US12/768,548
• Publication Number:
  US 20100299244A1
• Time in Patent Office: 1,127 Days
• Field of Search: 705 35- 39
• 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 one example, 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, and by permitting correlative adjustments to the outstanding loan principal. The invention lends 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 its maturity.

Claims

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

a memory; and

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;

(d) receiving data corresponding to a regression model;

(e) receiving data corresponding to a prepayment model;

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

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

(h) receiving data corresponding to transaction indicative details associated with the interest bearing instrument to be issued;

(i) normalizing the received and stored data;

(j) calculating prepayment probabilities based on an output of the regression model and an output of the prepayment model;

(k) calculating a forward term structure of at least one benchmark rate based on the interest rate term structure model;

(l) calculating discount factors to be applied to at least one cashflow associated with the interest bearing instrument to be issued;

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

(n) calculating a principal modification value based on the option value, wherein the principal modification value modifies a principal amount associated with the interest bearing instrument to be issued;

(o) calculating a risk capital savings using the following equation;

2. The apparatus of claim 1, wherein the computer processor further executes functions for receiving user input and, based on the user input, changing the calculated option value, or the calculated principal modification value, or both.

3. The apparatus of claim 1, wherein the computer processor further executes at least one function for outputting real-time data related to any of the calculations.

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

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

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

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

8. The apparatus of claim 1, wherein the regression model is based on a Tobit model.

9. The apparatus of claim 1, wherein the regression model is based on a logit model.

10. The apparatus of claim 1, wherein the regression model is based on a probit model.

11. The apparatus of claim 1, wherein the prepayment model is based on an Andy Davidson model.

12. The apparatus of claim 1, wherein the prepayment model is based on an Advanced Financial Technologies model.