AlgovestIQ Research · Reference reviewed September 4, 2026
AIQ research methodology
Definitions, calculation logic, source attribution and limitations for reading and citing AlgovestIQ research. Scores describe observed evidence; they are not buy or sell instructions or probabilities of future returns.
How the AIQ Score is built
The AIQ Score is a proprietary 0–100 research score. It brings together several types of market and company evidence into one easy-to-read number, so investors can quickly see whether a stock’s current setup looks stronger, weaker or mixed.
| Factor | Interpretation |
|---|---|
| Momentum | Whether price action and trend evidence are improving or weakening. |
| Value | Whether the stock looks expensive or inexpensive relative to its financial profile. |
| Quality | Whether the business shows stronger profitability, balance-sheet and operating evidence. |
| Risk Resilience | How well the stock has handled volatility and downside pressure. |
These inputs are combined inside AlgovestIQ’s scoring model. The public score is designed to be interpretable, but the exact weighting mix, thresholds and model logic are not published.
SentimentPulse and short-term timing signals are shown separately from the AIQ Score. They can help explain market tone, but they are not the same thing as the core research score.
Always read the score with its source dates and available coverage. Missing or stale inputs can affect a score, and ETFs are evaluated differently from operating companies.
Factors can disagree
A security can have strong Quality and weak Momentum. Read the supporting and conflicting factors together. These dimensions are not guaranteed to be statistically independent. Momentum does not establish institutional accumulation, and a Quality score does not establish a leading indicator of price performance.
AIQ Edge and state labels
AIQ Edge is a separate 1–10 relative measure. Peer calculations can use sector and capitalization cohorts, smoothing and coverage safeguards; fallback paths may use a score-derived proxy. Check the displayed cohort and coverage before treating an Edge value as a precise peer rank. It is not a return estimate.
Market and signal state labels have their own rules and versions. A newly observed trigger differs from a condition that remains active. An AIQ score change is a proprietary state change, while a ranked opportunity list describes the current cohort.
Updates, history and comparison windows
Research uses scheduled data snapshots. Read each module’s data-through date, comparison date and coverage; the date this reference was reviewed is not a market-data timestamp. Sources may update at different times.
Daily comparisons require the prior eligible trading session. Missing history is unavailable, not a zero change. Weekly comparisons and changes in cohort membership must retain their actual windows. Model changes, corrections and missing observations can affect comparability.
Limitations
Coverage, stale inputs, corporate actions, revisions, liquidity and asset-specific inputs can affect results. Scores summarize the implemented model rather than intrinsic value or personal suitability. Descriptive research does not establish causality, a future-return advantage or a backtested strategy.
Source attribution
AIQ scores, state classifications and research summaries are derived by AlgovestIQ from financial, price, technical, macro and news inputs. Refer to the individual research page for available source dates and evidence. Provider coverage and publication timing vary. A citation to AlgovestIQ does not grant permission to redistribute underlying third-party datasets.
Inspect current evidence
Citations and corrections
Cite “AlgovestIQ Research”, the research page title, its canonical URL and the data-through date. State the metric and comparison window. Live pages change; use a dated study with retained evidence when citing a historical finding.
For a correction, include the page URL, symbol, observation date and the disputed value at [email protected]. Corrections should preserve the distinction between a source revision and a methodology change.
Reference history
September 4, 2026: canonical methodology reference introduced; factor framework, missing-data normalization, separate sentiment/timing and evidence limitations clarified. This is a documentation revision, not a scoring-model change.