Computer-based method for teaming research analysts to generate improved securities investment recommendations
A computer-based method for combining investment recommendations of individual research providers such as stock analysts. The method includes providing a server running a research team management module. A list of individual research providers is displayed on a client node linked to the server network. A research team is generated based on user input including a number of the research providers. Team rules are assigned to the team defining an algorithm for processing recommendations from the members of the team. Recommendations for securities are retrieved for the research providers on the team, and team recommendations are generated by applying the team rules to the recommendations. Team recommendations are reported to the client node for guiding investments. Processing of the individual recommendations may include applying differing weights to the positive and negative recommendations and combining the weighted recommendations, with the weights being user-selected differentiating strengths of members of the research team.
1. A method for forming a team of individual research providers to generate stock recommendations, comprising:
running a user interface on a client node linked to a network;
displaying performance information based on analysis of prior stock investment recommendations for a plurality of research providers in the user interface;
receiving a selection of a set of the research providers for a research team;
generating team rules for combining stock investment recommendations from the set of research providers on the research team into team investment recommendations;
running an analytic module on a server to determine investment performance for the research team for a period of time based on the team investment recommendations for the period of time for a set of stocks; and
reporting the investment performance to the client node along with individual performance information for the period of time for the set of research providers on the research team.
2. The method of claim 1 , further operating the analytic module to determine the performance information for the plurality of research providers based on a user-selected performance analysis methodology.
3. The method of claim 1 , wherein the team investment recommendations for the set of stocks comprise positive, neutral, or negative recommendations and the team rules comprise aggregation rules for combining the positive, neutral, or negative recommendations of the set of research providers on the research team.
4. The method of claim 3 , wherein the team rules generating comprises receiving from the client node weights to apply to each positive recommendation and each negative recommendation of each of the research providers on the research team and wherein the aggregation rules comprise combining the recommendations after applying the weights.
5. The method of claim 1 , wherein team rules are selected from the group of methods for combining team member recommendations consisting of an averaging methodology, a majority methodology, a consensus methodology, and a unanimous-to-buy-one-to-sell methodology.
6. A method for forming a team of individual research providers to generate stock recommendations, comprising:
receiving a selection of a set of research providers for a research team;
generating team rules for combining stock investment recommendations from the set of research providers on the research team into team investment recommendations;
running an analytic module on a server to determine investment performance for the research team based for a period of time based on the team investment recommendations for the period of time for a set of stocks; and
reporting the investment performance to a client node along with individual performance information for the period of time for the set of research providers on the research team,
wherein the team investment recommendations for the set of stocks comprise positive, neutral, or negative recommendations and the team rules comprise aggregation rules for combining the positive, neutral, or negative recommendations of the set of research providers on the research team.
7. The method of claim 6 , further comprising prior to the receiving of the selection of the set of the research providers:
running a user interface on the client node linked to a network; and
displaying performance information based on analysis of prior stock investment recommendations for a plurality of research providers in the user interface.
8. The method of claim 6 , further operating the analytic module to determine the performance information for the plurality of research providers based on a user-selected performance analysis methodology.
9. The method of claim 6 , wherein the team rules generating comprises receiving from the client node weights to apply to each positive recommendation and each negative recommendation of each of the research providers on the research team and wherein the aggregation rules comprise combining the recommendations after applying the weights.
10. The method of claim 6 , wherein team rules are selected from the group of methods for combining team member recommendations consisting of an averaging methodology, a majority methodology, a consensus methodology, and a unanimous-to-buy-one-to-sell methodology.
11. A method for forming a team of individual research providers to generate stock recommendations, comprising:
running a user interface on a client node linked to a network;
displaying performance information based on analysis of prior stock investment recommendations for a plurality of research providers in the user interface;
receiving a selection of a set of the research providers for a research team;
generating team rules for combining stock investment recommendations from the set of research providers on the research team into team investment recommendations; and
running an analytic module on a server to determine investment performance for the research team based for a period of time based on the team investment recommendations for the period of time for a set of stocks.
12. The method of claim 11 , further including reporting the investment performance to the client node along with individual performance information for the period of time for the set of research providers on the research team.
13. The method of claim 11 , further operating the analytic module to determine the performance information for the plurality of research providers based on a user-selected performance analysis methodology.
14. The method of claim 11 , wherein the team investment recommendations for the set of stocks comprise positive, neutral, or negative recommendations and the team rules comprise aggregation rules for combining the positive, neutral, or negative recommendations of the set of research providers on the research team.
15. The method of claim 14 , wherein the team rules generating comprises receiving from the client node weights to apply to each positive recommendation and each negative recommendation of each of the research providers on the research team and wherein the aggregation rules comprise combining the recommendations after applying the weights.
16. The method of claim 11 , wherein team rules are selected from the group of methods for combining team member recommendations consisting of an averaging methodology, a majority methodology, a consensus methodology, and a unanimous-to-buy-one-to-sell methodology.
17. A system for providing a virtual security analyst providing a single investment recommendation for each security in a set of securities based on recommendations of a set of research providers, comprising:
means for enabling a user to specify two or more of the research providers to include on a research team;
means for enabling a user to specify a set of rules for combining positive and negative recommendations for securities generated by the research providers on the research team;
means for determining for a set of securities historic performance of individual ones of the research providers on the research team and of the research team based on the set of rules and prior positive and negative recommendations of the research providers; and
means for reporting the historic performances to a user.
18. The system of claim 17 , wherein the set of rules includes separate weight values assigned to negative recommendations and to positive recommendations for each of the research providers on the research team.
19. The system of claim 17 , means for enabling a user to define a plurality of securities for coverage by the research team, means for determining positive and negative recommendations of the research providers on the research team for the plurality of securities, means for generating team recommendations by processing the determined positive and negative recommendations using the set of rules, and means for reporting the team recommendations.
20. The system of claim 19 , means for generating updated team recommendations in response to modifications of one or more of the determined positive and negative recommendations and means for alerting a user to the generated updated team recommendations.
21. The system of claim 17 , wherein the historic performances reported to the user exclude the prior positive and negative recommendations of the research providers, whereby the research team is validated without release of recommendation information of the research providers on the research team.