Preparing a follow-up
After reading an employment note, ask which evidence underpins its wage assessment and when that evidence was published.
Athena · Research assistant
Meet Athena, Troia’s AI macro research assistant
A useful research question often arrives after the headline has been read. A portfolio manager might want to know whether an inflation surprise changes the view on interest rates, or which part of the release supports that conclusion. Athena is Troia’s AI macro research assistant, designed to let teams explore those questions in ordinary language.
The illustrated exchange on the homepage shows the intended experience. A focused question gives the answer a defined scope. Asking for its source, observation date and assumptions then gives the team a way to check the reasoning.
Give the question a subject and a horizon
Name the release or policy issue and say what decision it informs. A question about the next Fed meeting calls for different evidence from a question about the inflation trend over the next year.
Research workflow
- Ask a focused questionSpecify the release, policy issue or investment horizon.
- Inspect the basisLook for the source, observation date and supporting analysis.
- Probe a dependencyAsk how the conclusion depends on an assumption or missing evidence.
Follow the answer back to the evidence
Athena’s research workflow centres on material available within Troia. For a specific claim, ask which release, period or policy communication supports it. Where the evidence is incomplete, a useful follow-up identifies the missing observation and the conclusion that depends on it.
In the investment process
Exploring an alternative explanation
Ask whether the same conclusion would hold if the surprise were concentrated in one volatile component. Check which part of the answer rests on that assumption.
Example research question
Which components of this inflation release support the conclusion, and what could challenge it?View the illustrative Athena exchange ↗