Computer-based method for teaming research analysts to generate improved securities investment recommendations

1. A computer-based method for processing and combining investment recommendations from research providers such as stock analysts, comprising:

providing a server running a research team management module on a digital communications network;

providing identifiers for a set of research providers to a client node linked to the communications network;

with the research team management module, generating a research team comprising two or more of the research providers based on selections received from the client node;

assigning team rules with the research team management module to the research team defining an algorithm for aggregating recommendations of research providers on the research team;

accessing recommendations of the research providers on the research team for a security;

generating a team recommendation for the security by processing the accessed recommendations using the algorithm defined by the team rules, wherein the algorithm comprises combining the accessed recommendations after applying weights to the accessed recommendations that are defined in the team rules for both positive and negative recommendations for each of the research providers on the research team; and

reporting the team recommendation to the client node.

2. The method of claim 1 , wherein the weights are user-selected based on input received from the client node and wherein the weights for the positive recommendations differ from the weights for the positive recommendations of at least one of the research providers.

3. The method of claim 1 , wherein the algorithm comprises determining whether more than half of the research providers agree on a positive or a negative recommendation and if so, choosing the agreed upon positive or negative recommendation as the team recommendation.

4. The method of claim 1 , wherein the algorithm comprises determining from the accessed recommendations whether all of the research providers on the research team have provided a positive or a negative recommendation for the security and if so, providing the positive or negative recommendation as the team recommendation.

5. The method of claim 1 , wherein the algorithm comprises determining from the accessed recommendations whether all of the research providers on the research team have provided a positive recommendation for the security and if so, providing the positive recommendation as the team recommendation.

6. The method of claim 5 , wherein the algorithm further comprises determining if any of the accessed recommendations is a negative recommendation, and if so, providing the negative recommendation as the team recommendation.

7. The method of claim 1 , further comprising running a performance analytics module to determine historic performance of the set of research providers for recommending securities and delivering at least a portion of the determined historic performance to the client node prior to the generating of the research team.

8. The method of claim 7 , further comprising running the performance analytics module to determine historic performance of the research team including accessing prior recommendations of the research providers on the research team over a time period, applying the team rules to the prior recommendations to generate historic team recommendations, and processing security pricing information with the historic team recommendations and the method further comprising reporting the historic performance of the research team to the client node with a comparison to the historic performance of the set of research providers.

9. The method of claim 7 , wherein the historic performance of the set of research providers is determined based on a performance analysis methodology user-selected from a set of methodologies and wherein the selections for the two or more research providers for the research team comprise at least one request for a highest performer based on one of the methodologies.

10. The method of claim 1 , further comprising repeating the accessing, the generating, and the reporting for a set of securities and yet further comprising monitoring for modifications of the recommendations of the research providers and when detected generating an alert to the client node with a new recommendation created by repeating the team recommendation generating.

11. A computer-based method for processing and combining investment recommendations from research providers such as stock analysts, comprising:

providing a server running a research team management module on a digital communications network;

providing identifiers for a set of research providers to a client node linked to the communications network;

with the research team management module, generating a research team comprising two or more of the research providers based on selections received from he client node;

assigning weights for recommendations provided by the research providers on the research team:

accessing recommendations of the research providers on the research team for a security; and

generating a team recommendation for the security by processing the accessed recommendations based on the assigned weights,

wherein the generating of the team recommendation further includes one of:

determining whether more than half of the research providers agree on a positive or a negative recommendation and if so, choosing the agreed upon positive or negative recommendation as the team recommendation;

determining from the accessed recommendations whether all of the research providers on the research team have provided a positive or a negative recommendation for the security and if so, providing the positive or negative recommendation as the team recommendation; and

determining from the accessed recommendations whether all of the research providers on the research team have provided a positive recommendation for the security and if so, providing the positive recommendation as the team recommendation.

12. The method of claim 11 , wherein the assigned weights are assigned for both positive and negative recommendations for each of the research providers on the research team.

13. The method of claim 12 , wherein the weights for the positive recommendations differ from the weights for the positive recommendations of at least one of the research providers.

14. The method of claim 11 , wherein the algorithm further comprises determining if any of the accessed recommendations is a negative recommendation, and if so, providing the negative recommendation as the team recommendation.

15. The method of claim 11 , further comprising running a performance analytics module to determine historic performance of the set of research providers for recommending securities and delivering at least a portion of the determined historic performance to the client node prior to the generating of the research team.

16. The method of claim 15 , further comprising running the performance analytics module to determine historic performance of the research team including accessing prior recommendations of the research providers on the research team over a time period, applying the team rules to the prior recommendations to generate historic team recommendations, and processing security pricing information with the historic team recommendations and the method further comprising reporting the historic performance of the research team to the client node with a comparison to the historic performance of the set of research providers.

17. The method of claim 15 , wherein the historic performance of the set of research providers is determined based on a performance analysis methodology user-selected from a set of methodologies and wherein the selections for the two or more research providers for the research team comprise at least one request for a highest performer based on one of the methodologies.