DailyIQ Methodology

DailyIQ is designed to combine market structure, news flow, and macro context into a format that helps users make faster sense of market conditions. The platform is not a black box predictor. It is a scoring and context system built to surface what deserves attention.

Our methodology has three main goals: represent market conditions faithfully, avoid indexing thin or placeholder content, and make the reasoning behind scores easier for users and search engines to understand.

Technical scores combine multiple indicators across timeframes, including momentum, trend, volatility, and participation-oriented measures. The exact weight of each indicator can evolve, but the model is always trying to answer the same question: how constructive or fragile is the current technical condition.

Sentiment scores aggregate recent article tone, confidence, recency, and coverage intensity. Macro pages use the same principle at the theme level rather than the single-stock level. The output is a directional context score, not a recommendation.

DailyIQ does not expose every possible dynamic page equally to search engines. Stock, ETF, and earnings pages must satisfy quality gates before they become indexable or enter the sitemap. That includes minimum content requirements, featured-symbol rules, and freshness checks.

This policy exists to reduce thin content, protect crawl budget, and ensure that indexable pages represent the strongest version of the site's analysis instead of incomplete inventory.

We revise site copy, educational pages, and search-oriented hubs to improve clarity, accuracy, and internal linking over time. Public market information can change quickly, so users should treat all analysis as time-sensitive context rather than timeless truth.

When users report an issue, we prefer to correct the page, tighten the index set if necessary, and document the framework more clearly instead of expanding low-confidence content into search.