ChartLists Methodology

ChartLists is an independent, non-commercial chart discovery platform designed to help you scan a curated global universe quickly and shortlist candidates for deeper review. We publish clean charts and a small set of practical signals built on end-of-day data. This is not a brokerage tool, a real-time terminal, or financial advice.

For traders, investors, and chart nerds

The platform is built around one core problem: you can’t seriously review hundreds of charts daily if every screen looks like a Christmas tree of indicators. ChartLists keeps the core visuals consistent and uses lightweight ranking metrics so your brain can do what it’s good at: pattern recognition.

What ChartLists shows

1) Markets watchlist (macro “mood board”)

We maintain a curated set of market indicators—indexes, sectors, styles, futures, rates, commodities, FX, and crypto—so you can see broad risk tone without opening 20 tabs.

2) Stock watchlists (curated universe + selected subset)

• Curated global universe (~10000 stocks): representation from all major stock markets- segmented in 6 market groups - USA, China/HK, India, Europe/UK/Canada, APAC, and rest of the world (Latin America, Middle East, Africa) The universe list of stocks is updated every week.
• Selected universe: a smaller, faster-to-browse subset focused on “worth-your-time” charts. This is updated on daily or more frequent basis.
• Universe changes: lists are reviewed periodically; symbols can be added/removed as liquidity/quality changes.

3) Grouping (themes first, randomness last)

Stocks are organized into practical sector/industry buckets (intentionally fewer than “every micro-industry”), so you can scan themes and leadership clusters quickly.

4) Multiple layouts (same data, different scanning lens)

Different layouts combine time range + interval + chart style so you can switch from “trend check” to “base check” to “pullback check” fast. The goal is speed: your eyes should answer “worth 30 seconds?” before your coffee gets cold.

Data foundations

1) Price & volume data

• Primary source: public provider data (commonly Yahoo Finance via yfinance).
• Frequency: end-of-day (EOD). Not real-time.
• Accuracy: data can be delayed, incomplete, or wrong—especially around splits/dividends and thin symbols.

2) Corporate actions and “adjusted” prices

When available, performance calculations typically prefer adjusted prices (to reflect splits/dividends). If adjusted data is missing for a symbol or window, calculations may fall back to close. If you’re making a real decision, always verify.

How to read our charts

1) Candle vs area charts

• Candles: best for structure (bases, breakouts, support/resistance, range contraction).
• Area charts: best for quick “shape” and trend direction at speed.

2) The asterisk (*) on some area charts

Some area charts (often shorter interval views) are smoothed to reduce noise. A common smoothing approach is using a short EMA on a typical price series (HLC3). This doesn’t “predict” anything—it just makes fast scanning less visually chaotic.

Indicators and how we calculate them

1) Typical price (HLC3)

We sometimes use HLC3 (a “typical price”) instead of Close to reduce single-print effects:
HLC3 = (High + Low + Close) / 3

2) SMA (Simple Moving Average)

SMA(N) = (sum of last N prices) / N
Used as a stable, widely-recognized trend reference (e.g., SMA200 as long-term trend context).

3) EMA (Exponential Moving Average)

EMA weights recent prices more heavily:
EMA(t) = α·Price(t) + (1−α)·EMA(t−1) where α = 2/(N+1)

Short EMAs (3/5/9/13/21/34) are commonly used to visualize momentum, pullbacks, and trend “lanes.” We keep overlays consistent so you can compare charts quickly.

4) Volume (display + interpretation)

Volume is shown as a compact overlay band to keep charts dense. Typical reading:

• Expansion during breakout attempts
• Dry-up during bases / tight consolidations
• Abnormal spikes that can signal news / institutional activity (or just chaos)

5) True Range (TR) and ATR (Average True Range)

We use ATR as a robust volatility measure:
TR = max(High−Low, |High−PrevClose|, |Low−PrevClose|)
ATR(N) = average(TR over last N bars)

6) Vola. (Volatility)

Vola is normalized so you can compare “how wild” a stock is across price levels:
Vola = ATR(21) / AvgPrice(21)

7) Liq. (Liquidity)

Liquidity is a quick tradability proxy (in the symbol’s native trading currency):
Liq = AvgPrice(21) × AvgVolume(21)

8) Period changes (12MChg, 3MChg, etc.)

Percent returns are computed over approximate trading windows:

• 12M ≈ 252 trading days
• 6M ≈ 126 trading days
• 3M ≈ 63 trading days
• 1M ≈ 21 trading days

Conceptually:
Return% = (Price(today) / Price(N bars ago) − 1) × 100

9) Extn (Extension)

Extn measures how stretched price is versus a short-term baseline. On ChartLists, Extn is defined as variance vs EMA9 of HLC3 (Daily).

A practical implementation is:
Baseline = EMA9(HLC3)
Gap = Close − Baseline

To make Extn comparable across symbols with different volatility, Gap can be normalized by recent volatility (commonly ATR-based). If you see Extn displayed as a normalized value, think “distance in volatility units,” not “% move”. (Translation: a +2% stretch means very different things for a utility vs a biotech.)

10) PF / RS (Performance Grade / Relative Strength)

PF/RS is a relative ranking signal intended to answer: “Has this been a leader versus its peer universe?”

The typical approach:

• Compute returns across multiple windows (commonly 12M, 9M, 6M, 3M, 1M).
• Combine those returns with weights (longer windows usually matter more).
• Rank symbols within a peer universe (market group/list) and convert rank to a score/grade.
• Optionally include “RS change” over the last ~1M to reward improving leaders and penalize fading leaders.

Because PF/RS is built on percentage returns, it is generally agnostic to price level. Across currencies, it is still useful directionally, but large FX moves can distort cross-market comparisons. Best practice: treat PF/RS as most meaningful within the same market universe.

11) SE (Sales & Earnings rating) and fundamentals

SE is a compact two-letter label: Sales rating (first letter) + Earnings rating (second letter). It’s built for scanning, not as a full financial model.

• Sales rating: based on revenue growth measures (e.g., quarterly YoY + TTM growth where available).
• Earnings rating: based on EPS (diluted) growth measures (e.g., quarterly YoY + TTM growth where available).

Fundamental fields can be missing or inconsistent across regions and companies. Treat SE as a directional filter and verify fundamentals from trusted financial sources.

12) Market-cap segments

Market-cap segments are based on market-cap rank within the respective market group at extraction time.

• MegaCap
• LargeCap
• MidCap
• SmallCap
• MicroCap

How to use ChartLists (a sane workflow)

• Step 1: scan Markets first (risk-on/off tone, leadership, rates/FX/commodities pressure).
• Step 2: scan grouped lists (find where leadership is clustering).
• Step 3: shortlist charts that look actionable (trend, base, pullback, breakout attempt).
• Step 4: verify on a full charting platform + confirm news/earnings/liquidity before doing anything real.

What we intentionally don’t do

• No real-time quotes, no intraday execution logic, no alerts (yet).
• No “100 indicators” pages. (Your eyes deserve better.)
• No promise that the universe is complete or that data is perfect.
• No claim that scores predict outcomes—these are ranking signals for scanning only.

Update cadence

We try to refresh charts daily, but updates are not guaranteed. Universe membership and group classifications are reviewed periodically (often weekly). If you spot a misclassification or broken metric, email us with the symbol + screenshot.