An experiment in what an agentic-AI research framework can do — published in full so you can check its work, not a tip service to follow. Generic research and education, not advice, not a personal recommendation, not FCA-authorised. Hypothetical book, not real money. Capital at risk.
Portfolio Lab · Research Lab
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Concepts

The ideas our framework rests on — plain-English explainers of how we think, beneath the specific signals and ideas.

Evidence over narrative

A good story isn't a reason to buy. A claim only counts if there's evidence it predicts returns — and we throw out the ones that fail, even when they sound clever.

Confluence — stacking independent signals

Conviction should come from how many genuinely independent reasons agree, not how loudly one shouts. The trap is counting the same fact twice.

Mean reversion to a quality-backed trend

Prices revert to a long-run path — but only if the business is genuinely good. The difference between a beach ball held underwater and a falling knife.

Margin of safety — price is the risk

The risk isn't a wobbly chart, it's the price you paid. The gap between price and value is the cushion that lets you be wrong and survive — a hard pre-condition.

Signals are overlays, not bets

Most signals are real but short-lived — good at timing entry and size, bad at being the reason to hold for a year. Durable strands carry the position; signals sit on top.

How to test a signal honestly

The wrong benchmark, survivorship, trusting the white paper, forcing a straight line. The traps we design around so a result can actually prove us wrong.