1. A computer-implemented method for determining a bid price for at least one tranche of a portfolio of financial instruments using a computer coupled to a database, the computer configured to calculate for the at least one tranche at least one of an internal rate of return (IRR), a net present value (NPV) and a time to profit probability, said method comprising the steps of:
dividing the portfolio into separately marketable sub-portfolios or tranches;
giving each tranche a trial bid price;
combining the tranches with historical asset performance data of at least one of a buying or selling party, other market and underwriting;
utilizing the computer to perform at least one of a NPV, an IRR and a time to profit analysis on the tranches; and
determining an actual bid price for each tranche based on the at least one of the NPV, the IRR and the time to profit analysis performed on the tranches.
2. A method according to claim 1 wherein said step of dividing the portfolio into separately marketable sub-portfolios or tranches further comprises the step of forecasting a cash flow probability distribution and time duration from prior analysis.
3. A method according to claim 2 wherein said step of forecasting a cash flow probability distribution further comprises the step of expressing a tranche probabilistic evaluation as at least one of a minimum high evaluation, a most probable evaluation, a low evaluation and other suitable probability distribution.
4. A method according to claim 1 wherein said step of combining the tranches with historical asset performance data further comprises the step of using an iterated sampling technique to produce a distribution.
5. A method according to claim 4 wherein said step of using an iterated sampling technique further comprises the step of using a Monte Carlo analysis.
6. A method according to claim 1 further comprising the step of selecting tranches not to buy.
7. A method according to claim 6 further comprising the step of recognizing a pattern of the best selection of tranches to purchase and at what price, subject to constraints.
8. A method according to claim 7 wherein said step of recognizing a pattern of the best selection of tranches to purchase is determined by stochastic optimization.
9. A method according to claim 6 wherein said step of selecting tranches not to buy further comprises the step of selecting tranches having a mean internal rate of return (IRR) that is below a defined threshold.
10. A method according to claim 6 wherein said step of selecting tranches not to buy further comprises the step of selecting tranches having a negative net present value (NPV) or a certain time to profit that is greater than a defined threshold.
11. A system for determining a bid price for at least one tranche of a portfolio of financial instruments that satisfies at least one of an internal rate of return (IRR), a net present value (NPV) and a time to profit probability requirements, said system comprising:
a computer configured as a server and further configured with a database of asset portfolios; and
at least one client system connected to said server through a network, said server configured to divide the portfolio into separately marketable sub-portfolios or tranches, assign each tranche a trial bid price, combine the tranches with historical asset performance data of at least one of a buying or selling party, other market and underwriting, and perform at least one of a NPV, an IRR and a time to profit analysis on the tranches, and determine an actual bid price for each tranche based on the at least one of the NPV, the IRR and the time to profit analysis performed on the tranches.
12. A system according to claim 11 wherein said server is configured to forecast a cash flow probability distribution and time duration using a prior analysis.
13. A system according to claim 11 wherein said server is configured to express a tranche probabilistic evaluation as at least one of a minimum high evaluation, a most probable evaluation, a low evaluation and other suitable probability distribution.
14. A system according to claim 11 wherein said server is configured to use an iterated sampling technique to produce a distribution.
15. A system according to claim 14 wherein said server is configured to use a Monte Carlo analysis.
16. A system according to claim 11 wherein said server is configured to select tranches not to buy.
17. A system according to claim 16 wherein said server is configured to recognize a pattern of the best selection of tranches to purchase and at what price, subject to constraints.
18. A system according to claim 17 wherein said server is configured to use stochastic optimization to recognize a pattern of the best selection of tranches to purchase.
19. A system according to claim 16 wherein said server is configured to select tranches having a mean internal rate of return (IRR) that is below a defined threshold.
20. A system according to claim 16 wherein said server is configured to select tranches having a negative net present value (NPV) or a certain time to profit that is greater than a defined threshold.
21. A computer for determining a bid price for at least one tranche of a portfolio of financial instruments that satisfies at least one of an internal rate of return (IRR), a net present value (NPV) and a time to profit probability requirements, said computer including a database of asset portfolios, said computer programmed to:
divide the portfolio into separately marketable sub-portfolios or tranches;
assign each tranche a trial bid price;
combine the tranches with historical asset performance data of at least one of a buying or selling party, other market and underwriting;
perform at least one of a NPV, an IRR and a time to profit analysis on the tranches determine an actual bid price for each trance based on the at least one of the NPV, the IRR and the time to profit analysis performed on the tranches.
22. A computer according to claim 21 programmed to forecast a cash flow probability distribution and time duration using a prior analysis.
23. A computer according to claim 21 programmed to express a tranche probabilistic evaluation as at least one of a minimum high evaluation, a most probable evaluation, a low evaluation and other suitable probability distribution.
24. A computer according to claim 21 programmed to use an iterated sampling technique to produce a distribution.
25. A computer according to claim 24 programmed to use a Monte Carlo analysis.
26. A computer according to claim 21 programmed to select tranches not to buy.
27. A computer according to claim 26 programmed to recognize a pattern of the best selection of tranches to purchase and at what price, subject to constraints.
28. A computer according to claim 27 programmed to use stochastic optimization to recognize a pattern of the best selection of tranches to purchase.
29. A computer according to claim 26 programmed to select tranches having a mean internal rate of return (IRR) that is below a defined threshold.
30. A computer according to claim 26 programmed to select tranches having a negative net present value (NPV) or a certain time to profit that is greater than a defined threshold.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An image processor for a camera module having an image sensor that captures an image, said image processor comprising:
a central processing unit;
program memory, associated with said central processing unit, said program memory, storing program steps for execution by said central processing unit to operate said camera module to capture said image;
one or more interface units communicating with components of said camera module;
image storage memory storing said image;
an image capture unit in communication with said image storage memory, said central processing unit, and said image sensor, said image capture unit capturing said image from said image sensor and storing said image in said image storage memory; and
image processing units, being application specific integrated circuits, in communication with said image storage memory, to transform said image into a CIE L*a*b* color space; and
a serial bus interface communicating said transformed image with a Serial Bus of a compact printer module interconnected with the camera module, the camera module receiving operational power only from the printer module via the Serial Bus.
2. The image processor of claim 1 further comprising scratch memory associated with said central processing unit for variable storage.
3. The image processor of claim 2 wherein said scratch memory is no greater than 2 Kbytes.
4. The image processor of claim 1 wherein said serial bus interface is in communication with one or more further modules, said Serial Bus communicating power and data between said camera module and said one or more further modules.
5. The image processor of claim 4 wherein said data includes image data transformed by said image processing units.
6. The image processor of claim 1 wherein said central processing unit is a micro-controller running at about 1 Mhz.
7. The image processor of claim 1 wherein at least one of said one or more interface units is a parallel interface unit communicating with a take button for initiating capture of an image by said image capture unit.
8. The image processor of claim 1 wherein said image storage memory is less than 1 Mbytes.
9. The image processor of claim 8 wherein said image storage memory is approximately 0.5 Mbytes.
10. The image processor of claim 1 wherein said program memory is no greater than 8 Kbytes.
11. The image processor of claim 1 wherein said image processing units include an image histogram unit and an image enhancement unit.
12. The image processor of claim 11 wherein said image enhancement unit includes a white balance and range expansion unit, resample unit, color conversion unit and a sharpen unit.