# Patent

## Title
Independent research consensus earnings estimates and methods of determining such

## Abstract

Apparatus and methods are described for correlating business relationships and issuing earnings estimates. According to the present invention, an earnings estimate can be generated for a company as it compares to a consensus estimate, or other rating aggregate, along with an indication of an investment banking relationship or other business relationship that the entity providing the estimate has had with the company. In addition to a consensus estimate that may be based upon current and previous analyst earnings estimates, operating actuals, expected reporting dates, footnotes and company-issued guidelines, indications of investment banking relationships and a consensus estimate is provided that excludes input from banks conducting business with the company. The present invention can also include suggested actions that can be taken based upon data relating to an investment banking relationship, an earnings estimate and/or a consensus earnings estimate that excludes input from banks with substantial business relationships with the company.

## Background
CROSS REFERENCE TO RELATED APPLICATIONS
This application is a continuation of and claims the benefit of and priority to U.S. patent application Ser. No. 10/713,421 filed Nov. 14, 2003 now U.S. Pat. No. 7,702,574, entitled “Independent Research Consensus Earnings Estimates and Methods of Determining Such,” which in turn claims the benefit of and priority to U.S. provisional application Ser. No. 60/426,171 filed Nov. 14, 2002, entitled “Independent Research Consensus Earnings Estimates and Methods of Determining Such.”


BACKGROUND
The present invention relates to a methods and systems for limiting risks associated with a rating supplied by an investment bank relating to a company's earning estimate and/or an investment recommendation (“Risks”).
The capital markets in a country such as the United States may be the most sophisticated and regulated in the world. Research departments of financial institutions analyze and arrive at various estimations of corporate performance, typically for companies whose securities are publicly traded. This type of research, analysis and estimation are an important component to the efficient functioning of such markets. Research analysts develop and utilize specific models to arrive at quarterly earnings estimates for a given company or companies which they cover. Typically such earnings estimates are expressed in terms of earnings per share.
Consensus estimates have been developed which reflect an aggregated view of multiple analysts to arrive at a “consensus” number of range of numbers of expected earnings per share for a particular interval, such as a fiscal quarter. One well known provider of such consensus estimates is, for example, is Thomson “First Call®”.
Recently, however, the integrity of research provide by financial institutions has been called into question where the financial institutions with research departments either have, or hope to, achieve banking relationships with companies covered by their research departments. Presently, regulatory, governmental, legislative and media investigators, class action attorneys and the public are questioning whether analyst reporting may have been unduly influenced by business or banking relationships.
The implications of these questions are beginning to play out in class action litigations, the opinions of commentators and proposed regulations. Arguments have been advanced that analysts provide earnings estimates and other subjective data for reasons that may be influenced by business relationships, such as investment banking activity, with the company. Presently there is no way to determine, based upon a consensus earnings estimate, which estimates have been provided from financial institutions with banking relationships from covered companies and which estimates have not.
Accordingly, what is needed is a method and system for in which a consensus earnings estimate can be provided in such a way to identify and aggregate earnings per share estimates provided by financial institutions with existing or proposed banking or financial relationships with covered companies and those earning per share estimates provided by financial institutions or researchers who do not. Consensus estimates can then be provided in a meaningful manner devoid of any real or imagined influence arising from such relationships.



DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a block diagram of some embodiments of the present invention.
FIG. 2 illustrates a network of computer systems that can embody a Consensus Earnings Reporting server.
FIG. 3 illustrates a flow of exemplary steps that can be executed while implementing some embodiments of the present invention.
FIG. 4 illustrates a flow of exemplary steps that can be executed while implementing other embodiments the present invention.
FIG. 5 illustrates an exemplary graphical user interface that can implement various aspects of the present invention.
FIG. 6 illustrates a device which can be utilized while implementing embodiments of the present invention.



DETAILED DESCRIPTION
The present invention includes methods and systems for correlating business relationships and issuing earnings estimates. In particular, embodiments of the present invention include methods and systems for presenting an earnings estimate for a company as it compares to a consensus estimate, or other rating aggregate, along with an indication of an investment banking relationship that the entity providing the estimate has had with the company. For example, in addition to a consensus estimate that may be based upon current and previous analyst earnings estimates, operating actuals, expected reporting dates, footnotes and company-issued guidelines, the present invention provides indications of investment banking relationships and a consensus, estimate that excludes input from banks with substantial business relationships with the company. In some embodiments, the present invention can also include recommended actions to take based upon data relating to an investment banking relationship, an earnings estimate and/or a consensus earnings estimate that excludes input from banks with substantial business relationships with the company.
For the purposes of this application, earnings estimates will be considered to be generated by any entity whose estimate may be included in an estimate consensus, however such entities may collectively be referred to as a “bank” without limiting the type of entity, institution or organization that may generate the earnings estimate.
Overview
Referring now to FIG. 1 a block diagram of one embodiment of the present invention is illustrated. Earnings estimates 101-103 can be generated from various banks or other financial institutions or entities. An earnings consensus can be generated for all listed estimates 104. The consensus can be calculated by any means suitable. For example, the consensus may include an average of estimates 101-103 received, using a weighted algorithm, a mean of estimates 101-103, an algorithm that eliminates a highest estimate and a lowest estimate or any other algorithm or means suitable. The present invention can also include an earnings consensus that excludes estimates from banks with substantial business relationships with the company concerned 105, such as an investment banking relationship. A comparison can be made between each consensus estimate, and, if desired with individual bank's estimates.
Business relationships can be ascertained utilizing various data gathering techniques. For example, in some embodiments, a Risk Management Clearinghouse can aggregate data indicative of a significant business relationship, such as an investment banking relationship. The data can be gathered, for example, from filings with the Securities and Exchange Commission (SEC), such as registration statements, prospectuses, statements regarding underwriting. Other sources can include news releases, or other public disclosures. In addition, data can be collected from private investigation firms or other sources.
In some embodiments, a source of a particular earning estimate 101-103 can be permitted to defend or otherwise explain the reasoning utilized to generate a particular earnings estimate and the reason for any discrepancy between the particular estimate 101-103 and a consensus estimate.
Embodiments of the present invention can also include generating a suggested action based upon the compiled data, including, for example, individual earnings estimates, the consensus with multiple estimates 104 and/or consensus with estimates from banks involved in investment banking and/or other business relationships excluded 105. A suggested action can be presented to a user via a GUI, an e-mail message, other electronic message, or any other means of conveying information. (Exemplary suggested actions are discussed at step 316 of the Methods Section below.)
It is also within the scope of this invention to include aggregating historical data indicating a history of earnings estimates, investment banking relationships, other business relationships between a provider of an earnings estimate, and actual earnings reports. The historical data can be useful to extrapolate a company's earnings and/or generate a suggested action.
Systems
Referring now to FIG. 2, a network diagram illustrating some embodiments of the present invention is shown 200. An automated Earnings Reporting server 200 can include a computerized Earnings Reporting server 203 accessible via a distributed network 201 such as the Internet, or a private network. An automated RMC system 202 can include a computerized RMC system also accessible via the distributed network 201. A user, can use an access device 206-207, such as a computerized system or wireless handheld device to receive, input, transmit or view information processed in the Earnings Reporting server 203, RMC system 202, a peer access device, or other network device. A protocol, such as, for example, the transmission control protocol internet protocol (TCP/1P) can be utilized to provide consistency and reliability.
A system access device 206-207 used to access the Earnings Reporting server 203, RMC system 202, or other device can include a processor, memory and a user input device, such as a keyboard and/or mouse, and a user output device, such as a display screen and/or printer, as further detailed in FIG. 6. The system access devices 206-207 can communicate with the Earnings Reporting server 203 or RMC system 202 to access data and programs stored at the respective servers. A system access device 206-207 may interact with the Earnings Reporting server 203 or RMC system 202 as if the servers were a single entity in the network 200. However, the Earnings Reporting server 203 and RMC system 202 may include multiple processing and database sub-systems, such as cooperative or redundant processing and/or database servers that can be geographically dispersed throughout the network 200.
The RMC system 202 and Earnings Reporting server 203 can include one or more databases 204 storing data relating to earnings estimates, earnings reports, investment banking relationships, other business relationships, risk management, or other pertinent information. Information relating to and included in earnings estimates and reports can be aggregated into a searchable data storage structure. Gathering data into an aggregate data structure 204, such as a data warehouse, allows a server to have the data readily available for processing a risk management search associated with a company's earnings. Aggregated data 204 can also be scrubbed or otherwise enhanced to aid in searching.
Typically an access device 206-207 will access the RMC system 202 using client software executed at the system access device 206-207. The client software may include a generic hypertext markup language (HTML) browser, such as Netscape Navigator or Microsoft Internet Explorer, (a “WEB browser”). The client software may also be a proprietary browser, and/or other host access software. In some cases, an executable program, such as a JavaTM program, may be downloaded from a server to the system access device 206-207 and executed at the system access device 206-207 as part of earnings estimates risk management software. Other implementations include proprietary software installed from a computer readable medium, such as a CD ROM. The invention may therefore be implemented in digital electronic circuitry, computer hardware, firmware, software, or in combinations of the above. Apparatus of the invention may be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a programmable processor; and method steps of the invention may be performed by a programmable processor executing a program of instructions to perform functions of the invention by operating on input data and generating output.
Methods
Referring now to FIG. 3, steps that can be performed while practicing the present invention are illustrated. From the perspective of an earnings estimate provider, risk management clearinghouse, or other service provider, at 310 earnings estimates can be received, such as, for example, via an electronic communication, facsimile, hardcopy, or voice call. In any case, the earnings estimates can be input into an electronic storage. At 311, a consensus earnings estimate can be generated. At 312 information relating to business relationships between an entity providing an estimate and a company can be aggregated.
At 313 a consensus earnings estimate can be generated that excludes estimates from entities with a business relationship, and in some embodiments, as a material business relationship or other predetermined threshold of business, with a company concerned. At 314, in some embodiments, an indication can be made to identify those entities that have been excluded from a related business earnings estimate consensus. For example, in order to be excluded, an entity may need to be involved with a threshold amount of business, or over a threshold amount of time. At 315, embodiments can also include an indication of a particular business relationship.
At 316, a suggest action can be generated based upon the earnings estimates and the aggregated data indicating business relationships. A suggested action can include, for example: an indication to buy or sell a security of a company: a indication to buy or sell a derivative indicating value of a company will increase/decrease within a predetermined period of time, such as for example, within 30 days following issuance of an earnings report or with 90 days of the earnings estimate consensus. In some embodiments, a suggested action may include notifying an appropriate authority.
Embodiments can also include allowing a user to select those entities whose estimates should be excluded from an earnings estimate consensus. Selection can allow additional options relating to the selected entity such as including an estimate from the excluded entity or providing details as to why the entity was excluded. Accordingly, embodiments can include presenting data relating to business relationships between an entity providing an earnings estimate and the company concerned. In some embodiments, the data can be presented, for example as a result of a Risk Management Clearinghouse search or query.
Some embodiments can also include a verification step which can allow any of the entities or companies involved such as, for example, an excluded entity, to independently indicate the veracity of information put forth in a statement of a business relationship. Other embodiments can convey any information put forth with no value judgment, research or other indication relating to the veracity or completeness of any information conveyed.
Accordingly, embodiments can also include notifying an entity that its earnings estimate will be excluded from a consensus estimate and the reason for the exclusion and allow the entity to address the situation.
Referring now to FIG. 4, additional steps that can be performed while implementing some embodiments of the present invention are illustrated. At 410, historical information can be aggregated relating to earnings estimates, such as, for example, information that relates to business relationships between an entity providing an earnings estimate and a company. At 411 historical relationships can be analyzed as compared to actual earnings. At 412, the historical perspective can be extrapolated with current data so that at 413, a suggested action can be generated.
Graphical Interface
Referring now to FIG. 5, an exemplary GUI 500 that can be utilized while practicing the present invention is illustrated. A portion of a display 501 can display information that relates to a company, such as a publicly traded company. Another portion of the display 502 can include information descriptive of an earnings estimate 101-103 as well as the entity responsible for generating the earnings estimate. At 503 a consensus generated with some estimates excluded according to a predetermined criteria, or in some embodiments, a user identified criteria. A portion 504 can also display instructions relating to a suggested action 107 based upon the earnings estimate 101-103 and the business relationships associated with the earnings estimate 101-103.
Communication Controller
FIG. 6 illustrates an exemplary Earnings Reporting controller 203 that is descriptive of the devices shown, for example, in FIG. 2 according to some embodiments of the present invention. The Earnings Reporting controller 203 comprises a processor 610, such as one or more Intel® or AMD® processors, coupled to a communication device 620 configured to communicate via a communication network (not shown in FIG. 6). The communication device 620 may be used to communicate, for example, with one or more network access devices 206-25 207.
The processor 610 is also in communication with a storage device 204, 630. The storage device 204, 630 may comprise any appropriate information storage device, including combinations of magnetic storage devices (e.g., magnetic tape and hard disk drives), optical storage devices, and/or semiconductor memory devices such as Random Access Memory (RAM) devices and Read Only Memory (ROM) devices.
In some embodiments, the storage device 209, 630 can store a program 615 for controlling the processor 610. The processor 610 performs instructions of the program 615, and thereby operates in accordance with the present invention. For example, the processor 610 may receive an indication data relating to earnings reports and one or more business relationships and generate a consensus earnings reports and/or a suggested action based upon the data. The processor 610 may also transmit information comprising the Earnings Reporting and/or one or more suggested actions to appropriate destinations.
The storage device 630 can store for example, an Earnings Reporting information database 700 and a RMC database 800. The illustrations and accompanying descriptions of the databases presented herein are exemplary, and any number of other database arrangements could be employed besides those suggested by the figures.
A number of embodiments of the present invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. For example, certified hard copy documents can be gathered and scanned into a system such that the scanned image, and/or the data contained therein can be utilized or forwarded to a user as appropriate. Accordingly, other embodiments are within the scope of the following claims.

## Claims

1. A processor-implemented method for managing risk associated with earnings estimates for an institution, comprising:
receiving earning estimates for an institution from a plurality of entities;
generating via a processor an earnings consensus estimate based on the average of the received earning estimates;
aggregating via the processor information relating to business relationship between each entity providing an estimate and the institution;
identifying based on the aggregated information one or more entities engaging in a business relationship with the institution over a predefined period of time;
excluding the earning estimates provided by the identified entities from the earning consensus estimate to generate an updated earnings consensus estimate; and
generating a suggested action based on the updated earnings consensus estimate.

2. The method of claim 1, further comprising generating a suggested action based on the earnings consensus estimate based on the earning estimates received from the plurality of entities.

3. The method of claim 1, further comprising notifying the entities providing the excluded earning estimates.

4. The method of claim 1, wherein the identified entities engage in a threshold amount of business activities with the institution.

5. The method of claim 1 further comprising:
aggregating historical data related to business relationship between the entities and the institution;
aggregating corresponding historical data related to earnings estimate;
aggregating data related to actual earnings; and
analyzing the aggregated historical data and the actual earnings data to determine expected earnings.

6. The method of claim 5 further comprising generating a suggested action based on the aggregated historical data related to business relationship and earnings estimate.

7. The method of claim 1, wherein the information related to business relationship between the entities and the institution is derived from sources including a Risk Management Clearinghouse, Securities and Exchange Commission and public disclosures.

8. The method of claim 1, wherein the suggested action is to buy or sell a security of the institution.

9. The method of claim 1, wherein the suggested action is to engage III a derivative transaction which will be profitable if value of the institution increases within a predetermined period of time.

10. The method of claim 1, wherein the suggested action is to engage in a derivative transaction which will be profitable if value of the institution decreases within a predetermined period of time.

11. A system for managing risk associated with earnings estimates for an institution, comprising:
a memory;
a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to:
receive earning estimates for an institution from a plurality of entities;
generate an earnings consensus estimate based on the average of the received earning estimates;
aggregate information relating to business relationship between each entity providing an estimate and the institution;
identify based on the aggregated information one or more entities engaging in a business relationship with the institution over a predefined period of time;
exclude the earning estimates provided by the identified entities from the earning consensus estimate to generate an updated earnings consensus estimate; and
generate a suggested action based on the updated earnings consensus estimate.

12. The system of claim 11, wherein the processor issues further instructions to:
generate a suggested action based on the earnings consensus estimate based on the earning estimates received from the plurality of entities.

13. The system of claim 11, wherein the processor issues further instructions to notify the entities providing the excluded earning estimates.

14. The system of claim 11, wherein the identified entities engage in a threshold amount of business activities with the institution.

15. The system of claim 11, wherein the processor issues further instructions to:
aggregate historical data related to business relationship between the entities and the institution;
aggregate corresponding historical data related to earnings estimate;
aggregate data related to actual earnings; and
analyze the aggregated historical data and the actual earnings data to determine expected earnings.

16. The system of claim 15 further comprising generating a suggested action based on the aggregated historical data related to business relationship and earnings estimate.

17. The system of claim 11, wherein the information related to business relationship between the entities and the institution is derived from sources including a Risk Management Clearinghouse, Securities and Exchange Commission and public disclosures.

18. The system of claim 11, wherein the suggested action is to buy or sell a security of the institution.

19. A non-transitory processor-readable medium storing processor issuable instructions to:
receive earning estimates for an institution from a plurality of entities;
generate an earnings consensus estimate based on the average of the received earning estimates;
aggregate information relating to business relationship between each entity providing an estimate and the institution;
identify based on the aggregated information one or more entities engaging in a business relationship with the institution over a predefined period of time;
exclude the earning estimates provided by the identified entities from the earning consensus estimate to generate an updated earnings consensus estimate; and
generate a suggested action based on the updated earnings consensus estimate.

20. The non-transitory processor-readable medium of claim 19, wherein the processor issues further instructions to:
generate a suggested action based on the earnings consensus estimate based on the earning estimates received from the plurality of entities.