Curriculum·R410 Copy Trading, Vaults, and Agentic Execution·about 32 min
Agentic execution and AI trading
By the end of this lesson you can
- →Separate a claim about a method from evidence about a result
- →State why a model's description cannot be verified from outside, and what can
- →Compute the sample an agentic system needs before its expectancy is distinguishable from zero
- →Apply the permission controls that bound an autonomous system's authority
Senior · enrolled learners
This lesson opens with The SEC's first AI washing actions, 18 March 2024.
- What happened
- On 18 March 2024 the SEC announced settled charges against two investment advisers, Delphia (USA) Inc. and Global Predictions Inc., for making false and misleading statements about their use of artificial intelligence. Global Predictions had described itself as the first regulated AI financial adviser and advertised expert AI-driven forecasts. Delphia, a robo-adviser, claimed it used artificial intelligence to analyze client data in order to make intelligent investment decisions and predict which companies and trends were about to succeed. In an SEC examination in July 2021 Delphia admitted that it had not created an algorithm to analyze client data, and continued to market a proprietary algorithm in various statements through August 2023. The firms paid civil penalties of $225,000 and $175,000 respectively, being $400,000 in total, in what the SEC described as its first enforcement actions of this kind.
- The decision point
- Delphia admitted to a regulator in July 2021 that the algorithm did not exist and continued describing it for a further twenty-five months, which is possible only because a claim about a method cannot be checked from outside. Nobody could inspect the model. What could have been checked was the record it produced, which per R405-04 requires a sample and per part three is the only evidence about an automated system that exists at all.
- Recorded loss
- $400,000
What you will be able to answer
- →What can and cannot be verified?
- →How long did the false claim persist?
- →What sample does an agent need?
- →What bounds an autonomous system's authority?
Orientation and Year One are open: anyone can read them without an account. From Year Two onward the lessons are for enrolled learners, because progress through the later years only means anything if it is tracked against a record.
It is free. We do not sell the list and there is nothing to buy at the end of it.
Sources and review
- https://www.sec.gov/newsroom/press-releases/2024-36
- https://www.wilmerhale.com/en/insights/client-alerts/20240327-sec-brings-two-more-ai-washing-enforcement-actions-against-investment-advisers-continuing-its-pursuit-of-misstatements-related-to-ai
- https://www.debevoise.com/insights/publications/2024/03/ai-enforcement-starts-with-washing-the-sec-charges
- https://www.bleepingcomputer.com/news/security/crypto-platform-3commas-admits-hackers-stole-api-keys/
Confidence high·Volatility high·Reviewed 2026-08-07·Owner unassigned
Contested
Both matters were settled without admissions beyond the findings recited in the orders, and the penalties were small relative to the sums in most cases in this course. They are used here because they are the clearest documented instance of the specific gap this lesson describes, which is that a claim about a method is unverifiable from outside. Nothing here is a claim about any other firm.
This lesson makes no assessment of whether machine learning methods can produce a trading edge. Per P6 that is an open question with serious work on both sides, and per R405-04 it is answerable only through out-of-sample records rather than through descriptions. The lesson is about what evidence is available to you.
F109-04 owns delegated signing authority and R409-02 owns the API key exposure on bot platforms. This lesson owns the evidentiary question and the permission bounds specific to autonomous execution. Keep the splits.