AMG Kernel - Virtual Nature of Changing Values and Sentiment

Subscription Login Access: Private Network Connection

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

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

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

The Kernel visualizes relationships between understandings and shared common questions about how the 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 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.... - Learning visualization templates of value

The multidimentional 'etch-a-sketch' prototype accesses EDGAR data filings of Hundreds of Form Types for Thousands of Corporations reporting Continuous Regulated Market Core Integer Data - to train AI with integer data that originate in EDGAR filings.

Fiduciaries visualize overlays of Financial sentiment vectors on interactive dashboards to embed the causal manifestations of asset changes; and apply templates to relevant non-Financial value vectors (media, tech, social, rideshare, determinative....) of changing sentiment.