Method of and system for defining and measuring the real options of a commercial enterprise

• US 20010034686A1
• Filed: 01/19/2001
• Published: 10/25/2001
• Est. Priority Date: 12/10/1997
• Status: Abandoned Application

• Current Assignee: Jeffrey Eder
• Original Assignee: Jeffrey Eder
• Inventors: Eder, Jeff Scott
• Application Number:
  US09/764,068
• Publication Number:
  US 20010034686A1
• Time in Patent Office: Days
• US Class Current: 705/36
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

An automated system (100) and method for defining and measuring the real options of a commercial enterprise on a specified valuation date. The real options are evaluated on the basis of the relative strength of the elements of value of the enterprise. The performance of the elements of value are first summarized using composite variables. The elements of value that cause change in enterprise stock price are then determined. The relative strength of the causal elements of value for the enterprise vis a vis its competitors are then calculated. The relative ranking of the enterprise causal elements of value is then used in determining the discount rate to be used in real option valuation. The real options are then valued using Black Scholes algorithm.

Claims

1. A computer-implemented method for continuously valuing one or more real options of a business enterprise, comprising:

obtaining data related to the real options, elements of value and value of the business enterprise and its competitors,

determining, which elements of value are causing enterprise stock price changes;

calculating for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise,

calculating the appropriate discount rate for use in valuing the real options and contingent liabilities as a function of the relative causal element strength, and

calculating real option values.

2. The computer-implemented method of

claim 1

wherein the value of the business enterprise includes a revenue component, an expense component and a capital component.

3. The computer-implemented method of

claim 1

wherein determining which elements of value are causing stock price changes comprises using output from a causal model.

4. The computer-implemented method of

claim 1

wherein determining the relative ranking of the causal elements of value comprises using output from a data envelopment analysis to determine the relative ranking of the element of value.

5. The computer-implemented method of

claim 1

wherein calculating real option values comprises using a Black Schole'"'"'s algorithm to complete the calculation.

6. The computer-implemented method of

claim 1

wherein calculating real option values comprises using a binomial algorithm to complete the calculation.

7. The computer implemented method of

claim 1

where in processing further comprises identifying the variable that is the best predictor of stock price movement by comparing the clustering accuracy based on different variables on the known clustering of the S&

P 500.

8. A computer readable medium having sequences of instructions stored therein, which when executed cause a processor to perform a method for continuously valuing one or more real options of a business enterprise, comprising:

obtaining data related to the elements of value, real options and value of the business enterprise and its competitors;

determining, which elements of value are causing enterprise stock price changes;

calculating for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise,

calculating the appropriate discount rate for use in valuing the real options and contingent liabilities as a function of the relative causal element strength, and calculating real option values.

9. The computer readable medium of

claim 8

, wherein the value of the business enterprise includes a revenue component, an expense component and a capital component.

10. The computer readable medium of

claim 8

wherein determining which element variables are causing stock price changes comprises using output from a causal model.

11. The computer readable medium of

claim 8

wherein determining the relative ranking of the causal elements of value comprises using output from a data envelopment analysis to determine the relative ranking of each of the causal elements of value.

12. The computer readable medium of

claim 8

wherein calculating real option values comprises using a Black Schole'"'"'s algorithm to complete the calculation.

13. The computer readable medium of

claim 8

wherein calculating real option values comprises using a binomial algorithm to complete the calculation.

14. The computer readable medium of

claim 8

wherein processing further comprises identifying the variable that is the best predictor of stock price movement by comparing the clustering accuracy based on different variables on the known clustering of the S&

P 500.

15. A computer sys tem, comprising:

a processor having circuitry to execute instructions;

a storage device coupled to the processor and having sequences of instructions stored therein, which when executed cause the processor to,

obtain data related to the elements of value, real options and value of the business enterprise and its competitors;

determine, which elements of value are causing enterprise stock price changes;

calculate for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise,

calculate the appropriate discount rate for use in valuing the real options and contingent liabilities as a function of the relative causal element strength, and calculate real option values.

16. The computer system of

claim 15

, wherein the processor is further caused to determine which elements of value are causing stock price changes comprises using output from a causal model.

17. The computer system of

claim 15

wherein determining the relative ranking of the causal elements of value comprises using output from a data envelopment analysis to determine the relative ranking of each of the causal elements of value.

18. The computer system of

claim 15

wherein calculating the value the real options comprises using a Black Schole'"'"'s algorithm to complete the calculation.

19. The computer system method of

claim 15

wherein calculating the value of the real option comprises using a binomial algorithm to complete the calculation.

20. The computer system method of

claim 15

wherein calculating the value of the real option further comprises identifying the variable that is the best predictor of stock price movement by comparing the clustering accuracy based on different variables on the known clustering of the S&

P 500.

21. A computer-implemented method for continuously valuing the elements of value of a business enterprise, comprising:

obtaining data relative to the value of the enterprise and its competitors,

identifying causal value drivers by element of value,

determining the relative impact of causal value drivers on the current operation cash flow of the enterprise by element of value,

determine the elements of value that are causal to stock price movement,

determining the value impact of causal elements of value on the real options of the enterprise, and

calculating the value of the element of value by adding the impact of the element of value on the real options of the enterprise with the product of the relative impact of the element of value on current operation cash flow and the enterprise current operation cash flow.

22. The computer-implemented method of

claim 21

wherein valuing the elements of value for the enterprise further comprises calculating for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise and calculating the appropriate discount rate for use in valuing the real options as a function of the relative causal element strength using data envelopment analysis.

23. The computer-implemented method of

claim 21

wherein the value drivers identified by predictive models have been determined to be causal drivers by a causal model.

24. The computer-implemented method of

claim 21

wherein determining the percentage of the cash flow, attributable to each causal value driver comprises using output from a predictive model to determine the percentage of the cash flow attributable to the value driver.

25. The computer-implemented method of

claim 21

wherein the value driver comprises one or more item variables, one or more composite variables and/or one or more item performance indicators.

26. A computer readable medium having sequences of instructions stored therein, which when executed cause a processor to perform a method for continuously valuing the elements of value of a business enterprise, comprising:

obtaining data relative to the value of the enterprise and its competitors,

identifying causal value drivers by element of value,

determining the relative impact of causal value drivers on the current operation cash flow of the enterprise by element of value,

identifying causal elements of value for stock price movement,

determining the value impact of causal elements of value on the real options of the enterprise, and

calculating the value of the element of value by adding the product of the relative impact of the element of value on current operation cash flow and the forecast enterprise cash flow with the impact of the element of value on the real options of the enterprise

27. The computer readable medium of

claim 26

wherein valuing the elements of value for the enterprise further comprises calculating for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise and calculating the appropriate discount rate for use in valuing the real options as a function of the relative causal element strength using data envelopment analysis.

28. The computer readable medium of

claim 26

wherein the value drivers identified by predictive models have been determined to be causal drivers by a causal model.

29. The computer readable medium of

claim 26

wherein determining the percentage of the cash flow, attributable to each causal value driver comprises using output from a predictive model to determine the percentage of the cash flow attributable to the value driver.

30. The computer readable medium of

claim 26

wherein the value driver comprises one or more item variables, one or more composite variables and/or one or more item performance indicators.

31. A computer system, comprising:

a processor having circuitry to execute instructions;

a storage device coupled to the processor and having sequences of instructions stored therein, which when executed cause the processor to,

obtain data relative to the value of the enterprise and its competitors,

identify causal value drivers by element of value,

determine the relative impact of causal value drivers on the current operation cash flow of the enterprise by element of value,

identify causal elements of value for stock price movement,

determine the value impact of causal elements of value on the real options of the enterprise, and

calculate the value of the element of value by adding the product of the relative impact of the element of value on current operation cash flow and the forecast enterprise cash flow with the impact of the element of value on the real options of the enterprise

32. The computer system of

claim 31

wherein valuing the elements of value for the enterprise further comprises calculating for each causal element of value the relative ranking of each causal element vis a vis firms competing with the enterprise and calculating the appropriate discount rate for use in valuing the real options as a function of the relative causal element strength using data envelopment analysis.

33. The computer system of

claim 31

wherein the value drivers identified by predictive models have been determined to be causal drivers by a causal model.

34. The computer system of

claim 31

wherein determining the percentage of the cash flow, attributable to each causal value driver comprises using output from a predictive model to determine the percentage of the cash flow attributable to the value driver.

35. The computer system of

claim 31

wherein the value driver comprises one or more item variables, one or more composite variables and/or one or more item performance indicators.