Individual - Scope of EDGAR Filings, Data, & Analytics,

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The AMG Kernel trains AI with continuous market asset data signals to infer truthful predictive templates of sentiment at the forefront of change.

Regulated Financial data source 40+ million SEC EDGAR filings (Incl. ETF) for output in any general format.

The Filtered sentiment source data are transformed for analytics to learn How relevant and specialized capital values are changing in unique sets or groupings.

The Kernel visualizes relationships between shared understandings and common questions about how structured sentiment is changing; and formalizes truthful answers.

The EDGAR filings are filtered and embedded in fixed periods of annual, quarterly, monthly, weekly, daily;

and intraday fixed and flexible intervals of action:

The Financial market data reside in object storage (AWS cloud data buckets, eg.):

s3://valuevector1 - Retail and Professional investor cash demand for securities in open-end mutual fund (including ETF) net flow metadata.
s3://valuevector2 - Professional market demand for securities in portfolio asset, price, and share data filings submissions to the SEC.
s3://valuevector3,4,5.... - Fiduciary and Customer Learning Visualization Templates of Value

Fiduciaries display unique overlays of Financial sentiment value vectors on interactive dashboards to visualize the causal manifestations of asset changes - and train truthful inferences to relevant non-Financial value vectors (media, tech, social, rideshare, determinative....), where analytics of change is also important.

The multidimentional 'etch-a-sketch' prototype accesses EDGAR data filings of Hundreds of Form Types for Thousands of Corporations reporting Continuous Regulated Market Core Data -- Data to train AI with truthful inferences formed from continuous data in EDGAR filings.