Editorial Standards
How DailyIQ handles sourcing, corrections, disclosure, and search quality controls for public market content.
Finance content carries real decision risk, so clarity and restraint matter. DailyIQ is designed as informational support, not return promises.
Editorial standards are built around transparency, update discipline, and clear limits on what the platform does and does not claim.
DailyIQ publishes market education, score methodology, and research workflows to help users understand what the platform is measuring. Content is for informational purposes only and is not investment advice or a recommendation to buy or sell any security.
Who Writes And Reviews This Content
Learning Center articles are written by Kunal Jha, the founder of DailyIQ. He is not a licensed financial advisor, and DailyIQ does not provide personalized investment advice.
Before an education article is published, it is reviewed for factual accuracy by a CFA and CA charterholder. That reviewer checks definitions, formulas, and worked examples; they do not endorse any position, strategy, or security discussed in the article.
How AI Is Used, And Where It Is Not
DailyIQ uses AI in two clearly separated ways. Per-symbol pages for stocks, ETFs, earnings events, and sectors are generated programmatically from the platform's own market data, technical indicators, and news sentiment, with language models used to turn those measured inputs into readable analysis. These pages are produced at scale and are labelled as platform-generated analysis.
The Learning Center is different. Those articles are written by hand, not generated, and carry a named author byline plus the review step described above.
Generated pages are constrained to the market data DailyIQ has actually ingested. Prices, fundamentals, 52-week ranges, analyst targets, peer comparisons, and sentiment scores are passed to the model as measured inputs rather than left to it to recall, and the live figures displayed in charts and data tables are read directly from the database, not from generated text.
Language models can still misstate or misframe a number in prose. Generated analysis is not individually fact-checked before publication, so treat the surrounding commentary as interpretation and the data tables as the source of record. If you spot an error, report it through the contact page and it will be corrected or the page pulled.
Sourcing And Refresh Policy
Educational and methodology pages are updated for clarity, accuracy, and practical usefulness. Macro pages are refreshed as release context changes.
If a page is stale or incomplete, it is revised or deprioritized for indexing until quality is restored.
Disclosure And User Expectations
DailyIQ content is educational and informational. It is not personalized investment, tax, or legal advice.
Signals are decision inputs. Users should validate key assumptions independently and size risk to their own constraints.
Corrections And Search Quality
Correction requests and factual issues are triaged and addressed directly in the relevant page or framework section.
Search quality controls, including index gates and sitemap rules, are used to keep public coverage focused on stronger pages.
Understand the methodology behind the scores
See how DailyIQ combines technical indicators, news sentiment, freshness checks, and editorial review to decide what gets surfaced and indexed.