Ranking System¶
This page explains how ranking is implemented in the InvestLens Universe Screener. The process runs in phases:
- Scouting
- ETF/Benchmark Matching
- Grouping
- Scoring
- Ranking
1. Scouting¶
InvestLens includes a background service that periodically scans Canadian and U.S. markets. It collects and refreshes data used for screening and grouping, including:
- Asset metadata (for example: sector, industry, listing details)
- Fundamentals, selected earnings-related fields, and dividend yield
- Benchmark membership information for supported indices
2. ETF/Benchmark Matching¶
This service decides what “benchmark index” an ETF most closely follows. Many ETFs do not come with a clean, reliable index identifier that works across all vendors and tickers, so InvestLens builds its own internal match. The result is saved in the platform as an ETF/Index mapping and is used to group ETFs consistently in the Universe Screener and to support index-based analytics.
The matcher looks at an ETF’s top holdings and compares them to the constituents of many candidate indices. It assigns a score from 0 to 100 based mainly on how many holdings overlap with each index, with small adjustments for sector similarity and name hints (for example, when an index code or common index terms appear in the ETF's name). This produces a ranked list of likely index matches, and InvestLens stores the best matches along with a summary of contributing factors.
3. Grouping¶
Assets are grouped into buckets as follows:
| Asset type | Group type | What it means |
|---|---|---|
| Stocks | Sector | Stocks grouped by sector |
| Stocks | Industry | Stocks grouped by industry |
| Stocks | Index | Stocks grouped by index membership |
| ETFs | ETF Category | ETFs grouped by ETF category |
| ETFs | ETF Index | ETFs grouped by the ETF's best matched index |
sector,industry,index membership, andETF categoryare provided by the vendor, while the ETF's best matched index is derived by InvestLens.
4. Stock ranking model¶
Stocks are scored using four components.
4.1 Stock components¶
| Component | Definition | Inputs used | Higher score means |
|---|---|---|---|
| Liquidity | Size proxy | Market capitalization | Larger, more liquid companies |
| Valuation | Measures relative "cheapness" using standard valuation multiples | P/E, Forward P/E | Lower valuation multiples (cheaper) |
| Quality | Measures profitability and operating strength | ROE, Operating margin | Stronger profitability and margins |
| Options Activity | Measures recent options-market signals | Multiple options-market indicators (activity, liquidity, positioning) | More active, more liquid options trading with more bullish positioning |
5. ETF ranking model¶
ETFs are scored using five components.
5.1 ETF components¶
| Component | Definition | Inputs used | Higher score means |
|---|---|---|---|
| Efficiency | Measures cost efficiency of holding the ETF | Net expense ratio | Lower ongoing fees |
| Scale | Measures ETF size as a liquidity proxy | Total assets (AUM) | Larger funds (often better liquidity) |
| Tracking Fit | Measures how well the ETF matches its reference index | ETF/Index match (internal mapping score) | Better index fit (as measured internally) |
| Structure | Measures portfolio breadth and turnover discipline | Holdings count, turnover | More diversified holdings and lower turnover |
| Income | Measures distribution yield relative to peers | Yield (ranked within listing-country groups, when available) | Higher yield vs peers in the same group |
6. Composite score and ranking¶
For each asset, InvestLens combines component scores into a Composite score (0–100) using configurable weights.
- Missing components are handled conservatively to avoid overconfidence.
- Scores are adjusted for data completeness so partial data does not produce extreme rankings.
- Assets are ranked within the group by Composite score (highest is best). Ties share the same rank.
7. Important limitations¶
- Rankings depend on upstream data completeness and may change as vendor data is updated.
- Rankings are designed for research and decision support, not execution-grade trading signals.
- Scores are relative within the selected group, not absolute measures of quality.
- Component definitions and weights are defaults and may be adjusted over time.