A system includes a processor and a memory with instructions. The instructions include, in response to receiving a zoned graph request, determining a current breakeven point on a current date based on a strike price of an option. The instructions include estimating a future strike price of the option based on an expiration date of the option, determining a future breakeven point on the expiration date of the option based on the estimated future strike price, and determining a range as a current price corresponding to the current breakeven point to a future price corresponding to the future breakeven point. The instructions include, for each time between the current date and the expiration date, determining a middle breakeven point at the corresponding time based on the range and generating a zoned graph including the current breakeven point, the future breakeven point, and each middle breakeven point at the corresponding times.

A system includes a processor and a memory with instructions. The instructions include, in response to receiving a zoned graph request, determining a current breakeven point on a current date based on a strike price of an option. The instructions include estimating a future strike price of the option based on an expiration date of the option, determining a future breakeven point on the expiration date of the option based on the estimated future strike price, and determining a range as a current price corresponding to the current breakeven point to a future price corresponding to the future breakeven point. The instructions include, for each time between the current date and the expiration date, determining a middle breakeven point at the corresponding time based on the range and generating a zoned graph including the current breakeven point, the future breakeven point, and each middle breakeven point at the corresponding times.

Systems and methods are described in relation to specific technical improvements adapted for machine learning architectures that conduct classification on numerical and/or unstructured data. In an embodiment, two neural networks are utilized in concert to generate output data sets representative of predicted future states of an entity. A second learning architecture is trained to cluster prior entities based on characteristics converted into the form of features and event occurrence such that a boundary function can be established between the clusters to form a decision boundary between decision regions. These outputs are mapped to a space defined by the boundary function, such that the mapping can be used to determine whether a future state event is likely to occur at a particular time in the future.

Systems and methods are described in relation to specific technical improvements adapted for machine learning architectures that conduct classification on numerical and/or unstructured data. In an embodiment, two neural networks are utilized in concert to generate output data sets representative of predicted future states of an entity. A second learning architecture is trained to cluster prior entities based on characteristics converted into the form of features and event occurrence such that a boundary function can be established between the clusters to form a decision boundary between decision regions. These outputs are mapped to a space defined by the boundary function, such that the mapping can be used to determine whether a future state event is likely to occur at a particular time in the future.

A trade exchange system and method provide transparency and accountability for each idea producer and each follower of each idea producer with respect to trades executed based on a trade idea circulated by the idea producer. The trade exchange system and method may use application-programming interfaces (APIs) to gather data from a brokerage entity in order to verify the trades executed in response to the trade idea by the idea producer and the follower.

A trade exchange system and method provide transparency and accountability for each idea producer and each follower of each idea producer with respect to trades executed based on a trade idea circulated by the idea producer. The trade exchange system and method may use application-programming interfaces (APIs) to gather data from a brokerage entity in order to verify the trades executed in response to the trade idea by the idea producer and the follower.

A system for combining a plurality of financial services in a single investment application for checkbook-controlled retirement plans is disclosed. At least one device is in operable connection with a network. An application server is in operable communication with the network and is configured to host an application system displaying financial information for interacting with a plurality of financial services. The application system having a user interface module for providing access to the application system to the at least one device. The user interface in operable communication with a compliance database to interact with a compliance module. An integration module integrates the plurality of financial services and a funds transfer module to initiate and execute a transfer of funds between one or more of the plurality of financial services.

A system for combining a plurality of financial services in a single investment application for checkbook-controlled retirement plans is disclosed. At least one device is in operable connection with a network. An application server is in operable communication with the network and is configured to host an application system displaying financial information for interacting with a plurality of financial services. The application system having a user interface module for providing access to the application system to the at least one device. The user interface in operable communication with a compliance database to interact with a compliance module. An integration module integrates the plurality of financial services and a funds transfer module to initiate and execute a transfer of funds between one or more of the plurality of financial services.

A system, method, and computer media are provided for combining and transmitting information to a device and via a channel of a user. The method comprises receiving a plurality of news elements, which are stored in a database. A relevance score is determined of the news elements in the news element database for a plurality of user elements stored in a user portfolio in the memory of the processing system. News elements are selected from the database based on the relevance score. The method further comprises determining at least one of an active device and an active channel of the user, reformatting the selected news elements into story components based on the determined device and channel into story components, and transmitting the story components to the active device and via the active channel of the user.

Embodiments of the present invention provide a system for generating and transmitting tiered supplemental resources based on identifying event triggers. The system is configured for retrieving one or more digital artifacts from a data repository, generating one or more supplemental resources associated with the one or more digital artifacts, continuously monitoring one or more resource pools associated with one or more users to identify one or more event triggers, identifying at least one trigger associated with a resource pool of a user of the one or more users based on continuously monitoring the one or more resource pools associated with the one or more users, and transmitting at least one supplemental resource of the one or more supplemental resources to a digital supplemental resource wallet of the user.