Factor Lens.
Why did the stock actually move? Decompose any name into the six style factors that drive most equity returns.
A regression you read like prose.
Quantle’s Factor Lens runs a six-factor OLS regression on every stock you open. The result is a row of betas with t-stats — instantly answering whether a name is really a growth bet, a quality bet, a low-vol stand-in, or something structurally different.
The intercept becomes annualized α with its own significance test. Most stocks don’t clear it. The ones that do are the ones worth your research time. Below the table, a rolling-β chart shows whether the exposures are stable or whether the company has quietly drifted regimes.
r_stock = α + β·F + ε
Daily returns of the target stock are regressed jointly on the daily returns of six style-ETF proxies plus an intercept. The estimator is ordinary least squares with sample standard errors. Significance markers follow conventional one-sided thresholds: |t| ≥ 1.65 at one star, 1.96 at two, and 2.58 at three.
The same regression is rolled in a 60-day window stepped every five bars to produce the time-series chart. Empty windows (less than 30 usable observations, or a degenerate covariance) are silently skipped — you see only what the data supports.
The annualized intercept α = β₀ × 252 is shown with its t-stat in the same row format. The convention here is deliberately strict: a positive α with |t| < 1.65 is ambient noise; only above that should you call it an effect.
Frequently asked
- Which factors are estimated?
- Market, Size, Value, Momentum, Quality and Low Volatility. Each is proxied by a liquid US ETF so the model produces tradable interpretations — SPY for Market, IWM for Size, IWD for Value, MTUM for Momentum, QUAL for Quality and USMV for Low Volatility.
- Why ETFs and not academic Fama–French series?
- ETF proxies give you exposures expressed in instruments you can actually trade or hedge with. The trade-off is interpretability: the betas are correlations to tradable styles, not pure orthogonal factors. Academic Ken French daily series ingestion is on the roadmap as an upgrade for users who want the canonical interpretation.
- What window does the regression use?
- The static β table runs on the full selected window — 1 year or 5 years. The rolling-β chart slides a 60-day window every five trading days. R² of the static regression is shown alongside the betas so you can judge model fit.
- How is significance flagged?
- Each factor row shows the OLS t-statistic and a star marker: one star at |t| ≥ 1.65, two stars at |t| ≥ 1.96, three at |t| ≥ 2.58. The annualized α (intercept × 252) is shown with its own t-stat — the bar most active managers do not clear after factor controls.
- Does it work on crypto or international names?
- Not yet. The tab is hidden on tickers without a meaningful equity-factor mapping — crypto, FX, and most international exchanges. A separate factor model for digital assets is on the roadmap.
- How is the alpha number useful?
- It tells you what return the stock generated above what the factors would predict. A persistently positive α with a significant t-stat suggests the security has done something the standard styles cannot explain. A persistently negative α suggests structural drag.
Run Factor Lens on any ticker.
The tab is one click into Symbol Detail. Free, no card, no install.
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