Data processing system for global assessment of investment opportunity and cost

• US 5,806,049 A
• Filed: 09/30/1996
• Issued: 09/08/1998
• Est. Priority Date: 04/21/1993
• Status: Expired due to Fees

• Current Assignee: Christopher R. Petruzzi
• Original Assignee: Christopher R. Petruzzi
• Inventors: Petruzzi, Christopher R.
• Primary Examiner(s): Harrity, John E.
• Application Number:
  US08/893,579
• Time in Patent Office: 708 Days
• Field of Search: 705/36, 705/10, 707/2
• US Class Current: 705/36.00R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A data processing system for determining a matrix of optimal investment portfolios based on globally accessed investment return and risk criteria. The system creates a global defined database of investment assets and investors. Asset and investor characteristics are established and applied to provide solutions to the ensuing linear relationships. These solutions are then individually applied to determine an optimal investment portfolio on an individualized basis.

Claims

1. In combination in a data processing system for determining an optimum matrix of investments for a select individual portfolio, said system comprising:

a) means for storing in accessible memory a database on available investment assets and characteristics of said assets relevant to investment therein, said characteristics including current ownership of said assets, anticipated changes in the quantity available of each asset, and anticipated variations in the return of each asset;

b) means for storing in accessible memory a database on a population of investors, further categorized by groups having similar investment criteria, wherein said population of investors are further delineated by attributes comprising tax rates, cost of brokerage, cash flow requirements and aversion to variation in portfolio returns, said database including current portfolios of said investors, anticipated changes in the net worth of each investor group and anticipated changes in the attributes of each of said investors;

c) data processing means for establishing a matrix of relationships describing a relative incremental disutility to each of said investors of said characteristics associated with each of said investment assets, said data processing means comprising linear programming which accepts inputs of said characteristics of each asset group and attributes of each investor group, said linear programming capable of computing risk statistics of the current portfolios and recommended changed portfolios of each investor group based on the inputted characteristics and attributes, said linear programming further determining said matrix of relationships forming a global solution minimizing global disutility of all investor groups; and

d) said data processing means further establishing an optimized individual portfolio based on select investor criteria and said matrix of relationships.

2. The system of claim 1, wherein said optimized individual portfolio avoids corner solutions by forcing a level of diversity in said portfolio through the use of a factor expressing the elimination or reduction of portfolio variance as measured by the change in the sum of the covariances of individual assets with exogenous macroeconomic variables.

3. The system of claim 2, wherein said system utilizes an iterative process, said process is repeated as long as utility is increased and there is either a minimum size to each change, a cost associated with each change, or a minimum incremental utility from each change in order to avoid creating an infinite loop.

4. The system of claim 3, wherein infinitely repeating loops are avoided by not repeating said iterative process of portfolio changes after a portfolio change has failed to decrease dis-utility or increase utility by a fraction of more than one hundred thousandth of a percent (0.0000001) of the original utility.

5. The system of claim 2, wherein said corner solutions are avoided by restricting each incremental portfolio change for determination of individual optimal solutions to less than 0.001 of the total portfolio value.

6. A data processing method for optimizing an individual investor'"'"'s portfolio, said method comprising the steps of:

a) creating a first database of investment assets and investor groups wherein total assets are equal to total combined portfolios for the investor groups both in total and for each individual asset;

b) creating a second database associated with said first database that provides select characteristics for each investment asset and each investment group, said characteristics including cost of brokerage, tax rate, cash flow, monitoring costs, components of variance, anticipated changes in net worth of each investor group, anticipated changes in attributes of each investor, anticipated changes in the quantity available of each asset and anticipated changes in the characteristics of each asset;

c) calculating the relative disutility for each investment asset based on said characteristic;

d) calculating a relative disutility to each investor for each investment asset based on said characteristics, said calculating based on data processing means comprising linear programming which accepts inputs of said characteristics of each asset and attributes of each investor group, said linear programming capable of computing risk statistics of the current portfolios and recommended changed portfolios of each investor group based on the inputted characteristics and attributes, said linear programming further determining a global solution minimizing global disutility of all investor groups;

e) determining with a simultaneous solution an optimal mix of investments for each investor group, based on said calculated disutility for each asset and each investor group; and

f) determining an optimum portfolio for an individual investor based on said disutility calculations and said optimized investor group portfolios.

7. The method of claim 6, wherein said steps (c) and (d) provide a series of disutility functions expressing a relative cost of an investment asset in terms of other investment assets stored in said second database.