Methods and systems for valuing investments, budgets and decisions

• US 20070016498A1
• Filed: 07/13/2005
• Published: 01/18/2007
• Est. Priority Date: 07/13/2005
• Status: Active Grant

• Current Assignee: Antony Mott
• Original Assignee: Antony Mott
• Inventors: Mott, Antony
• Granted Patent: US 7,558,755 B2
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/10 Tax strategies

Abstract

A computer implemented method of valuing and modeling an investment comprising the steps of: providing at least one investment for consideration comprised of at least one future cash flow; creating at least one probability distribution for each future cash flow, by a user, each probability distribution to represent uncertainty of magnitude at at least one particular time to provide at least one magnitude distribution; creating at least one probability distribution for each future cash flow, by a user, each probability distribution to represent uncertainty of timing at at least one particular magnitude to provide at least one timing distribution; combining the magnitude distributions and at least one timing distribution into at least one joint-probability distribution function; and converting at least one joint-probability distribution function to generate a two-dimensional net present value probability distribution.

Claims

1. A computer implemented method of valuing and modeling an investment, said method comprising the steps of:

providing at least one investment for consideration, wherein each said investment is comprised of at least one future cash flow;

creating at least one probability distribution for each said future cash flow, by a user, each said probability distribution to represent uncertainty of magnitude at at least one particular time to provide at least one magnitude distribution;

creating at least one probability distribution for each said future cash flow, by said user, each said probability distribution to represent uncertainty of timing at at least one particular magnitude to provide at least one timing distribution;

combining said at least one magnitude distribution and said at least one timing distribution into at least one joint-probability distribution function; and

converting said at least one joint-probability distribution function to generate a two-dimensional net present value probability distribution.

2. A computer implemented method of valuing and modeling an investment as in claim 1, wherein said step of converting said at least one joint-probability distribution function is according to an algorithm.

3. A computer implemented method as in claim 2, wherein said algorithm is performed according to the following steps:

operating on one or more arrays of data by another;

transforming said data into an interim results matrix array;

sorting said interim results matrix array to provide a sorted-interim results matrix;

converting said sorted-interim results matrix array to two new arrays;

combining similar data for each array through internal operations; and

producing two final results arrays; and

plotting the net-present value distribution according to said two final results arrays.

4. A computer implemented method of valuing and modeling an investment as in claim 1, further comprising the step of:

accepting modifications from said user to one or more said joint-probability distributions and re-generating a two-dimensional net present value probability distribution.

5. A computer implemented method of valuing and modeling an investment as in claim 1, further comprising the step of:

accepting information from said user about a relationship between possible future events.

6. A computer implemented method of valuing and modeling an investment as in claim 1, further comprising the step of:

accepting a user modification from said user to said joint-probability distribution function.

7. A computer implemented method of valuing and modeling an investment as in claim 1, further comprising the step of:

providing at least two images from a library of images, said images being pre-calculated probability distributions representative of typical categories of cash flows; and

accepting a selection of one of said at least two images from said user.

8. A computer implemented method of valuing and modeling an investment as in claim 7, wherein said at least two images are images according to category.

9. A method as in claim 7, wherein said library is a library of nine.

10. A computer implemented method of valuing and modeling an investment as in claim 7, wherein at least one of said at least two images is a default curve that looks like a standard bell curve

11. A computer implemented method of valuing and modeling an investment as in claim 1, wherein said future cash flows are comprised of at least one positive cash flow and at least one negative cash flow.

12. A computer implemented method of valuing and modeling an investment as in claim 1, further comprising the steps of:

generating at least two two-dimensional net present value probability distributions; and

comparing said at least two two-dimensional net present value probability distributions.

13. A computer implemented method of making a decision through modeling said decision, said method comprising the steps of:

providing a first decision for consideration, wherein said first decision is comprised of at least one future cash flow;

providing at least one image from a library of images;

selecting an image for each said future cash flow, by a user, to represent uncertainty of magnitude at at least one particular time to provide at least one magnitude distribution;

selecting an image of distribution for each said future cash flow, by said user, to represent uncertainty at at least one particular time to provide at least one timing distribution;

combining said magnitude distribution and said timing distribution into a joint-probability distribution function plotting said joint-probability function on a topography to provide a probability texture;

accepting modifications from said user to said probability texture;

accepting information from said user about a relationship between possible future events;

converting at least two said joint-probability functions to generate a two-dimensional net present value probability distribution;

accepting modifications from said user to said joint-probability functions and re-generating a two-dimensional net present value probability distribution.

14. A method as in claim 13, wherein said step of converting at least two said joint-probability function is according to an algorithm.

15. A computer implemented method as in claim 14, wherein said algorithm is performed according to the following steps:

operating on one or more arrays of data by another;

transforming said data into an interim results matrix array;

sorting said interim results matrix array to provide a sorted-interim results matrix;

converting said sorted-interim results matrix array to two new arrays;

combining similar data for each array through internal operations; and

producing two final results arrays; and

plotting the net-present value distribution according to said two final results arrays.

16. A method as in claim 13, further comprising the steps of:

providing a second decision for consideration, wherein said second decision is comprised of a series of future cash flows;

providing at least one image from a library of images;

selecting an image for each said future cash flow, by a user, to represent said uncertainty of magnitude to provide a magnitude distribution;

selecting an image of distribution, by said user, to represent said uncertainty in timing to providing a timing distribution;

combining said magnitude distribution and said timing distribution into a joint-probability distribution function plotting said joint-probability function on a topography to provide a probability texture;

accepting modifications from said user to said probability texture;

accepting information from said user about a relationship between possible future events;

converting at least two joint-probability functions with an algorithm to generate a two-dimensional net present value probability distribution;

accepting modifications from said user to said joint-probability functions and re-generating a two-dimensional net present value probability distribution.

17. A computer implemented method of valuing and modeling an investment as in claim 13, further comprising the step of:

providing at least two images from a library of images; and

accepting a selection of one of said at least two images from said user.

18. A computer implemented method of valuing and modeling an investment as in claim 13, wherein said at least two images are images according to category.

19. A method as in claim 13, wherein said library of images is a library of nine.

20. A computer implemented method of valuing and modeling an investment as in claim 13, wherein at least one of said at least two images is a default curve that looks like a standard bell curve

21. A computer implemented method of valuing and modeling an investment as in claim 13, wherein said future cash flows are comprised of at least one positive cash flow and at least one negative cash flow.

22. A computer implemented method of valuing and modeling an investment as in claim 16, further comprising the steps of:

generating at least two two-dimensional net present value probability distributions; and

comparing said at least two two-dimensional net present value probability distributions.

23. A method as in claim 16, wherein said step of selecting an image of distribution is comprised of the steps of:

providing said user with a library of standard distribution images.

24. A computer implemented method of making a decision through modeling said decision, said method comprising the steps of:

providing a first decision for consideration, wherein said decision is comprised of at least one future cash flow;

providing at least one image from a library of images;

selecting an image for each said future cash flow, by a user, to represent uncertainty of magnitude at at least one particular time to provide at least one magnitude distribution;

selecting an image of distribution for each said future cash flow, by said user, to represent uncertainty at at least one particular time to provide at least one timing distribution;

combining said magnitude distribution and said timing distribution into a joint-probability distribution function;

plotting said joint-probability function on a topography to provide a probability texture;

accepting modifications from said user to said probability texture;

accepting information from said user about a relationship between possible future events;

converting at least two said joint-probability functions with an algorithm to generate a two-dimensional net present value probability distribution;

accepting modifications from said user to said joint-probability functions and re-generating a two-dimensional net present value probability distribution;

providing a second decision for consideration, wherein said second decision is comprised of a series of future flows;

providing at least one image from a library of images;

selecting an image for each said future flow, by a user, to represent said uncertainty of magnitude to provide a magnitude distribution;

selecting an image of distribution, by said user, to represent said uncertainty in timing to providing a timing distribution;

combining said magnitude distribution and said timing distribution into a joint-probability distribution function;

plotting said joint-probability function on a topography to provide a probability texture;

accepting modifications from said user to said probability texture;

accepting information from said user about a relationship between possible future events;

converting at least two joint-probability functions with an algorithm to generate a two-dimensional net present value probability distribution;

accepting modifications from said user to said joint-probability functions and re-generating a two-dimensional net present value probability distribution;

generating at least two two-dimensional net present value probability distributions.

25. A computer implemented method of valuing and modeling an investment as in claim 24, wherein said at least two images are images according to category.

26. A method as in claim 24, wherein said library of images is a library of nine.

27. A computer implemented method of valuing and modeling an investment as in claim 24, wherein at least one of said at least two images is a default curve that looks like a standard bell curve

28. A computer implemented method of valuing and modeling an investment as in claim 24, wherein said future cash flows are comprised of at least one positive cash flow and at least one negative cash flow.

29. A computer implemented method of valuing and modeling an investment as in claim 24, further comprising the steps of:

comparing said at least two two-dimensional net present value probability distributions.

30. A computer implemented method as in claim 24, wherein said algorithm is performed according to the following steps:

operating on one or more arrays of data by another;

transforming said data into an interim results matrix array;

sorting said interim results matrix array to provide a sorted-interim results matrix;

converting said sorted-interim results matrix array to two new arrays;

combining similar data for each array through internal operations; and

producing two final results arrays; and

plotting the net-present value distribution according to said two final results arrays.