Systems and methods for determining a significance index
Systems, methods, and computer-readable instructions are configured to calculate an aggregated significance score for consumer goods or website interactions by aggregating historical significance scores and calculating a reference significance score for a benchmark. A relative significance score is derived for each of the consumer goods or website interactions based upon the significance score for each of the consumer goods or website interactions and the relative significance score. A consumer priority index is derived indexed to a relevant measure based on the aggregated significance scores and the reference significance score.
1. A computing system comprising:
memory storing computer readable instructions stored thereon, and an enterprise data warehouse, the enterprise data warehouse including a plurality of objects, and the enterprise data warehouse storing a mapping of the plurality of objects to a plurality of users, each of the plurality of objects including a set of time-series data, each data point of the set of time-series data including a floating-point value, a date, and an identifier of one of the plurality of users; and
processing circuitry configured to execute the computer readable instructions to cause the computing system to,
receive an inquiry regarding a first user of the plurality of users and a first period of time,
identify a first set of objects of the plurality of objects that correspond to the first user based on the mapping from the enterprise data warehouse, and
generate a user interface for display to the first user, the user interface including a representation of a significance index for the first user in response to the received inquiry, the generating the user interface including,
generating the significance index for the first user by calculating a weighted average of significance scores for the first set of objects, wherein a weight for each object of the first set of objects is determined based on an amount of the object associated with the first user in proportion to a total amount of the first set of objects, and
wherein the processing circuitry is further caused to generate the significance index by,
determining a significance score for a first object of the plurality of objects by,
identifying a first set of users associated with the first object based on the mapping from the enterprise data warehouse,
for each user of the first set of users, calculating an individual increase metric based on a relative proportion of (i) a value of an increase of the first object by the user to (ii) total purchasing power of the user,
calculating an overall increase metric based on a median of the individual increase metrics for the first set of users,
for each user of the first set of users, calculating an individual decrease metric based on a relative proportion of (i) a value of a decrease of the first object by the user to (ii) total purchasing power of the user,
calculating an overall decrease metric based on a median of the individual decrease metrics for the first set of users, and
determining the significance score based on a ratio of the overall increase metric and the overall decrease metric.
2. The computing system of claim 1 , wherein the processing circuitry further causes the computing system to:
receive a user input indicating a simulated change in holdings of the first user, the change indicating a second set of objects selected from the plurality of objects;
generate a simulated significance index by calculating a weighted average of significance scores for the second set of objects; and
generate an updated user interface for display to the first user that includes the simulated significance index.
3. The computing system of claim 2 , wherein the processing circuitry further causes the computing system to:
automatically rebalance the holdings of the first user based on the simulated significance index.
4. The computing system of claim 1 wherein each object of the plurality of objects is associated with the first user.
5. The computing system of claim 1 wherein the processing circuitry further causes the computing system:
index the significance index against a measure that is selected from a group consisting of time of day, day of week, and month.
6. The computing system of claim 5 wherein:
at least one of the plurality of objects is a stock; and
each user of the plurality of users corresponds to a respective portfolio.
7. The computing system of claim 6 wherein the processing circuitry further causes the computing system:
index the significance index against the measure in order to show an active investor portfolio confidence trend.
8. The computing system of claim 1 wherein each object of the plurality of objects is selected from a group consisting of stocks, stock indexes, custom lists of stocks, real estate, and collectibles.
9. The computing system of claim 1 wherein the processing circuitry further causes the computing system to:
apply a consideration factor to the significance score of the first object of the plurality of objects.
10. The computing system of claim 9 wherein the processing circuitry further causes the computing system to:
in response to the consideration factor being greater than one and the first object including funds provided on margin or credit, increase the significance score of the first object.
11. The computing system of claim 9 wherein the processing circuitry further causes the computing system to:
in response to the first object involving a hedging transaction, reduce the significance score for the first object.
12. The computing system of claim 1 wherein the plurality of users excludes the first user.
13. The computing system of claim 1 , wherein the processing circuitry further causes the computing system to:
determine securities currently being traded by other users included in the first set of users; and
update the user interface to further display the determined securities based on the significance indices of the respective other users.
14. The computing system of claim 13 , wherein the processing circuitry further causes the computing system to update the user interface to display securities being bought by the other users with a positive significance index as recommendation information to the first user.
15. The computing system of claim 13 , wherein the processing circuitry further causes the computing system to update the user interface to display securities being sold by the other users with a negative significance index as recommendation information to the first user.
16. The computing system of claim 13 , wherein the processing circuitry further causes the computing system to:
identify at least one second user from the other users by comparing an amount of change in the significance indices of each of the respective other users over a desired time period with a desired significance index threshold; and
update the user interface to further display securities traded by the identified at least one second user during the desired time period as recommendation information to the first user.
17. A computing method comprising:
receiving, using processing circuitry, an inquiry regarding a first user of a plurality of users and a first period of time;
identifying, using the processing circuitry, a first set of objects of a plurality of objects that correspond to the first user based on a mapping from an enterprise data warehouse, wherein the enterprise data warehouse stores:
for each of the plurality of objects:
a set of time-series data,
wherein each data point of the set of time-series data includes a floating-point value, a date, and an identifier of one of the plurality of users and the mapping of the plurality of objects to the plurality of users;
generating, using the processing circuitry, a user interface for display to the first user, the user interface including a representation of a significance index in response to the received inquiry, the generating the user interface including,
generating the significance index for the first user by calculating a weighted average of significance scores for the first set of objects, wherein a weight for each object of the first set of objects is determined based on an amount of the object associated with the first user in proportion to a total amount of the first set of objects, the generating the significance index including,
determining a significance score for a first object of the plurality of objects by,
identifying a first set of users associated with the first object based on the mapping from the enterprise data warehouse,
for each user of the first set of users, calculating an individual increase metric based on a relative proportion of (i) a value of an increase of the first object by the user to (ii) a total purchasing power of the user,
calculating an overall increase metric based on a median of the individual increase metrics for the first set of users,
for each user of the first set of users, calculating an individual decrease metric based on a relative proportion of (i) a value of a decrease of the first object by the user to (ii) the total purchasing power of the user,
calculating an overall decrease metric based on a median of the individual decrease metrics for the first set of users, and
determining the significance score based on a ratio of the overall increase metric and the overall decrease metric.
18. The computing method of claim 17 further comprising:
receiving, using the processing circuitry, a change in holdings of the first user, wherein the change indicates a second set of objects selected from the plurality of objects,
generating, using the processing circuitry, a simulated significance index by calculating a weighted average of significance scores for the second set of objects; and
generating, using the processing circuitry, an updated user interface for display to the first user that includes the simulated significance index.
19. The computing method of claim 17 wherein each object of the plurality of objects is associated with the first user.
20. The computing method of claim 17 further comprising:
indexing, using the processing circuitry, the significance index against a measure that is selected from a group consisting of time of day, day of week, and month.
21. The computing method of claim 20 wherein:
at least one of the plurality of objects is a stock, and
each user of the plurality of users corresponds to a respective portfolio.
22. The computing method of claim 21 further comprising:
indexing, using the process circuitry, the significance index against the measure in order to show an active investor portfolio confidence trend.
23. The computing method of claim 17 wherein each object of the plurality of objects is selected from a group consisting of stocks, stock indexes, custom lists of stocks, real estate, and collectibles.
24. The computing method of claim 17 further comprising:
applying, using the processing circuitry, a consideration factor to the significance score of the first object of the plurality of objects.
25. The computing method of claim 24 further comprising:
increasing, using the process circuitry, the significance score of the first object in response to the consideration factor being greater than one and the first object including funds provided on margin or credit.