Financial risk cover analysis, modeling control and monitoring system

1. A system for financial risk cover analysis, modeling, monitoring and control comprising:

a computer having a processor;

a receiver for receiving a previously designed Financial Risk Cover into a computer readable storage memory device, the Financial Risk Cover comprising at least returns behaviors including probability distribution functions and dynamic statistical matrices connecting statistical behavior of each potential allocation of a Financial Risk Cover submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

a set creator portion of the computer for creating a set of alternative Financial Risk Cover configurations in a computer readable storage, memory by employing one or more genetic optimization processes to produce unpredictable variations of configurations;

a simulator portion of the computer for modeling each of the alternative Financial Risk Cover configurations against a set of potential or expected transient market events representative of a plurality of combinations of transient events;

a set modifier portion of the computer for removing each alternative Financial Risk Cover configuration which fails to meet performance objectives during the modeling from the set of alternative Financial Risk Cover configurations; and

an output portion of the computer for outputting into a computer readable storage memory device each remaining alternative Financial Risk Cover configuration wherein each alternative Financial Risk Cover configuration represents a plurality of investment instruments, each investment instrument being associated with an initial cash position;

an analyzer portion of the computer for analyzing performance data relating to a plurality of Financial Risk Cover submanagers, creating probability distribution functions, and creating dynamic statistical matrices connecting statistical behavior of each potential allocation for each submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

a modeler portion of the computer for receiving the probably distribution functions, and employing quantitative analyses to model returns behavior of each submanager wherein cross relationships and temporal relationships of each submanager and all combinations of submanagers are preserved;

wherein the analyzer analyzes performance data reflecting daily performance statistics relative to each other potential submanager within the plurality of submanagers; and

a monitor/controller portion of the computer for: calculating a plurality of boundary conditions having pairs of upper limits and lower limits, wherein the boundary conditions comprise at least a Bayesian trees process, monitoring performance of a Financial Risk Cover having a configuration according to at least one remaining configuration in the total set of configurations by measuring one or more performance parameters on a periodic basis, and

responsive to one or more performance parameters being outside one or more corresponding boundary conditions, producing an updated set of alternative Financial Risk Cover configurations.

2. The computer-implemented system as set forth in claim 1 wherein the probability distribution functions further comprise one or more additional probability distribution functions selected from the group consisting of submanager portfolio performances relative to each other submanager portfolio, submanager portfolio performances relative to a plurality of major indices, and submanager portfolio performances relative to the client portfolio.

3. The computer-implemented system as set forth in claim 1 wherein the modeler further comprises a Latin-Hypercube sampling process.

4. The system as set forth in claim 1 wherein the modeler comprises an Iman-Connover sampling process.

5. A method for financial risk cover analysis, modeling, monitoring and control comprising:

receiving a previously designed Financial Risk Cover into a computer readable storage memory device by a computer having a processor, the previously designed Financial Risk Cover comprising at least returns behaviors including probability distribution functions and dynamic statistical matrices connecting statistical behavior of each potential allocation of a Financial Risk Cover submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

creating by the computer in a computer readable storage memory device a set of alternative Financial Risk Cover configurations in a computer readable storage memory by employing one or more genetic optimization processes to produce unpredictable variations of configurations;

modeling by the computer each of the alternative Financial Risk Cover configurations against a set of potential or expected transient market events representative of a plurality of combinations of transient events;

removing by the computer each of the alternative Financial Risk Cover configurations which fails to meet performance objectives during the modeling from the set of alternative Financial Risk Cover configurations;

outputting by the computer into a computer readable storage memory device each remaining alternative Financial Risk Cover configuration, wherein each alternative Financial Risk Cover configuration represents a plurality of investment instruments, each investment instrument being associated with an initial cash position;

analyzing by the computer performance data relating to a plurality of Financial Risk Cover submanagers;

creating by the computer probability distribution functions;

creating by the computer dynamic statistical matrices connecting statistical behavior of each potential allocation for each submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

employing by the computer quantitative analyses to model returns behavior of each submanager

wherein cross relationships and temporal relationships of each submanager and all combinations of submanagers are preserved, comprising analyzing performance data reflecting daily performance statistics relative to each other potential submanager within the plurality of submanagers; and

monitoring and controlling the Financial Risk Cover by the computer by: calculating a plurality of boundary conditions having pairs of upper limits and lower limits, wherein the boundary conditions comprise at least a Bayesian trees process, monitoring performance of a Financial Risk Cover having a configuration according to at least one remaining configuration in the total set of configurations by measuring one or more performance parameters on a periodic basis, and

responsive to one or more performance parameters being outside one or more corresponding boundary conditions, producing an updated set of alternative Financial Risk Cover configurations.

6. The method as set forth in claim 5

wherein the probability distribution functions comprise at least one probability distribution function selected from the group consisting of submanager portfolio performances relative to each other submanager portfolio, submanager portfolio performances relative to a plurality of major indices, and submanager portfolio performances relative to the said client portfolio.

7. The method as set forth in claim 5 wherein the modeling comprises a Latin-Hypercube sampling process.

8. The method as set forth in claim 5 wherein the modeling comprises an Iman-Connover sampling process.

9. A computer program product for financial risk cover analysis, modeling, monitoring and control comprising:

at least one computer readable storage memory devices;

first program instructions for receiving into a computer readable storage memory device by a computer having a processor a previously designed Financial Risk Cover comprising at least returns behaviors including probability distribution functions and dynamic statistical matrices connecting statistical behavior of each potential allocation of a Financial Risk Cover submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

second program instructions for creating by the computer in a computer readable storage memory device a set of alternative Financial Risk Cover configurations in a computer readable storage memory by employing one or more genetic optimization processes to produce unpredictable variations of configurations;

third program instructions for modeling by the computer each of the alternative Financial Risk Cover configurations against a set of potential or expected transient market events representative of a plurality of combinations of transient events;

fourth program instructions for removing by the computer each of the alternative Financial Risk Cover configurations which fails to meet performance objectives during the modeling from the set of alternative Financial Risk Cover configurations;

fifth program instructions for outputting by the computer into a computer readable storage memory device each remaining alternative Financial Risk Cover configuration, wherein each alternative Financial Risk Cover configuration represents a plurality of investment instruments, each investment instrument being associated with an initial cash position; analyzing by the computer performance data relating to a plurality of Financial Risk Cover submanagers;

sixth program instructions for creating by the computer probability distribution functions;

seventh program instructions for creating by the computer dynamic statistical matrices connecting statistical behavior of each potential allocation for each submanager to a resultant statistical behavior of a Financial Risk Cover associated with a client portfolio;

eighth program instructions for employing by the computer quantitative analyses to model returns behavior of each submanager wherein cross relationships and temporal relationships of each submanager and all combinations of submanagers are preserved, comprising analyzing performance data reflecting daily performance statistics relative to each other potential submanager within the plurality of submanagers; and

ninth program instructions for monitoring and controlling the Financial Risk Cover by the computer by: calculating a plurality of boundary conditions having pairs of upper limits and lower limits, wherein the boundary conditions comprise at least a Bayesian trees process, monitoring performance of a Financial Risk Cover having a configuration according to at least one remaining configuration in the total set of configurations by measuring one or more performance parameters on a periodic basis, and

responsive to one or more performance parameters being outside one or more corresponding boundary conditions, producing an updated set of alternative Financial Risk Cover configurations;

wherein the first, second, third, fourth, fifth, sixth, seventh, eighth and ninth program instructions are stored by, in or on the computer readable storage memory device.

10. The computer program product as set forth in claim 9 wherein the probability distribution functions comprise at least one submanager portfolio performance selected from the group consisting of submanager portfolio performances relative to each other submanager portfolio, submanager portfolio performances relative to a plurality of major indices, and submanager portfolio performances relative to the said client portfolio.

11. The computer program product as set forth in claim 9 wherein the modeling comprises a Latin-Hypercube sampling process.

12. The computer program product as set forth in claim 9 wherein the modeling comprises an Iman-Connover sampling process.