Percentile Context [RC Tools]RC Tools — Percentile Context
─────────────────────────────────────────────────────────────
█ OVERVIEW
Not "is RSI over 70" — "where does today's reading actually sit in its own history?" This tool takes a metric of your choice (realised volatility, RSI, volume, rate of change, or any custom source you plug in) and ranks it as a percentile against its own trailing distribution. It's the statistical primitive underneath most technical analysis, made explicit instead of buried in a fixed threshold.
█ WHAT IT DOES
Plots a 0–100 percentile-rank line for the selected metric, flags "extreme" zones (default: below the 10th percentile or above the 90th), and shows a stats table with the current value, current percentile, all-time min/max seen on the chart, and how many bars it's been since the metric last hit either extreme.
█ THE THEORY BEHIND IT
Fixed thresholds ("RSI > 70 = overbought") assume a metric's meaningful range never changes. It does — across assets, and across time on the same asset. A percentile rank fixes this by asking a relative question instead of an absolute one: given everything this metric has done over its own trailing window, how unusual is today's reading? This is the same idea underneath the Regime Classifier's volatility-state measure, generalised to any metric.
█ HOW IT IS CALCULATED
The selected metric is computed per bar:
• Realised Volatility: stdev(log(close/close ), N)
• RSI: standard Wilder RSI
• Volume: raw bar volume
• Rate of Change %: (close − close ) / close × 100
• Custom Source: whatever series you plug into the source input (e.g. another indicator's plot)
The metric is then percentile-ranked against its own trailing window (default 750 bars ≈ 3 years on daily): what percentage of the last N readings were below today's value. Display values update ONLY on confirmed bar close — nothing here repaints.
█ SETTINGS & CONFIGURATION
• Metric (default Realised Volatility) — what gets ranked
• Custom Source — only used when Metric = Custom Source
• Realised Volatility / RSI / Rate of Change lookbacks (defaults 20 / 14 / 20)
• Percentile Ranking Window (default 750 bars) — longer = more stable, needs more history
• Low / High Extreme Thresholds (default 10 / 90)
• Paint Main Chart Background — off by default to avoid clashing with the Regime Classifier's background if you run both at once
█ HOW TO USE IT
Use it to calibrate how seriously to take a "normal" indicator reading. Example: RSI at 75 means something different on a stock that's rarely above 60 than on one that regularly touches 85 — the percentile rank makes that comparison explicit for the SAME asset over time. Also useful for volatility context ahead of position sizing: current realised vol at the 95th percentile is a different risk environment than the same absolute vol reading at the 40th percentile.
Works on any asset and timeframe with sufficient history for the percentile window.
█ LIMITATIONS
• Percentile rank describes the past relative to itself — it says nothing about direction or what happens next. A metric at its 99th percentile can stay there.
• Needs substantial history for a stable ranking. On short-history assets, treat the percentile as unreliable.
• "Extreme" is relative to the metric's OWN range. A percentile extreme on a low-volatility asset is not directly comparable in absolute terms to one on a high-volatility asset — that's the point of the tool, but it means percentiles aren't comparable across symbols.
• All-time min/max and "bars since" stats are only as long as the chart's available history, not a fixed universal record.
• This script does NOT repaint. Display values update on confirmed bar close only.
█ DISCLAIMER
For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any metric does not indicate future results. Trade at your own risk.
Indicator
Temporal Bias Architect [JOAT]Temporal Bias Architect
Introduction
Temporal Bias Architect is an open-source time-structure indicator that maps price action onto three nested cycle frameworks simultaneously: weekly, daily, and 90-minute. Each framework divides its period into four sequential phases — Accumulation (A), Manipulation (M), Distribution (D), and Continuation/Reversal (X) — derived from Daye Quarterly Theory. These phases correspond to observable behavioral patterns at each time level: accumulation of position, engineered moves against the dominant bias, distribution of that position, and the resulting continuation or reversal.
The resonance score adds a second analytical layer: when all three timeframe levels are in the same phase simultaneously, the market context is most aligned and the behavioral pattern is most likely to produce a tradeable move.
Core Concepts
1. Quarterly Theory Phase Mapping
Each trading week is divided into four days (Monday through Thursday). Each trading day is divided into four six-hour blocks. Each six-hour block is divided into four 90-minute segments. The indicator assigns each division the same four-phase labels in order (A, M, D, X), creating a fractal structure where the same behavioral sequence repeats at every time scale.
The phase for each level is derived directly from time to ensure accuracy:
int dIdx = math.min(3, hour / 6) // daily 6H phase
int qIdx = math.min(3, int((hour % 6) * 60 + minute) / 90) // 90-min phase
Each phase is rendered as a color-coded box at its corresponding price row in the indicator pane.
2. Three-Row Visual Layout
The indicator displays three horizontal rows of phase boxes: Weekly (top), Daily (middle), and 90-Minute (bottom). Each row is independently togglable. The boxes are sized proportionally and colored using configurable per-phase colors. Phase labels (A, M, D, X) are centered within each box.
3. Resonance Scoring
When two or more timeframe levels are in the same phase simultaneously, the resonance score increments. Score of 3/3 means weekly, daily, and 90-minute phases all show the same letter — a maximum alignment event. The background shading activates at 3/3 alignment to flag the condition visually.
4. Fibonacci Time Zone Projection
From the start of each new trading day, the indicator projects Fibonacci time ratios (1.0, 1.272, 1.618, 2.0, 2.618) forward using a configurable time unit (90-minute, daily 6H block, or full day). These projections appear as vertical dotted lines with ratio labels. They mark the temporal points where price structure has historically been more likely to change character.
5. Historical Phase Visibility
A toggle controls whether prior days' boxes remain visible or are hidden as each new period begins. With history enabled, the full phase map is visible across the visible chart range, providing context for how phases have sequenced in the past.
Features
Three-level phase mapping: Weekly, daily, and 90-minute Quarterly Theory phases displayed simultaneously
Configurable phase colors: Accumulation, Manipulation, Distribution, and X colors independently adjustable
Resonance score (1-3): Counts how many timeframe levels are in the same phase
3/3 alignment background: Gold background tint when all three levels align
Fibonacci time zone projection: Five Fibonacci ratios projected forward from session open
Configurable Fib time unit: 90-min, 6H, or daily unit for projection scaling
Historical phase boxes: Toggle to show or hide prior periods' phase mapping
Row labels: Left-edge labels identifying each horizontal row
Dashboard: Current weekly, daily, and 90-min phase, resonance score, and Fib time unit
Three alerts: Full resonance (3/3), new daily quarter, new weekly quarter
Input Parameters
General:
Show Historical Quarters: Toggle past period box visibility (default: false)
Auto-Detect Border Color: Adapts box border to chart background luminosity
Quarterly Cycles:
Show Weekly / Daily / 90-Min toggles
Show Phase Labels toggle
Label Size: Tiny, Small, Normal, or Large
Per-phase color inputs (A, M, D, X)
Fibonacci Time Zones:
Show Fibonacci Time Zones toggle
Fib Time Source: 0 = 90-min unit, 1 = daily 6H unit, 2 = weekly day unit
How to Use This Indicator
Step 1: Identify the Current Phase at Each Level
Check the dashboard rows for weekly, daily, and 90-minute phase. Each phase has a behavioral implication in Quarterly Theory: A = ranging accumulation, M = engineered spike against the prior move, D = directional distribution, X = reversal or continuation.
Step 2: Use the Resonance Score
A 3/3 resonance reading means all three time levels are in the same phase. The background shading triggers at this condition. Cross-timeframe alignment amplifies the behavioral tendency associated with that phase.
Step 3: Watch Fibonacci Time Projections
Fibonacci time ratios project when structural turning points may occur based on elapsed session time. Price approaching a projected Fib line while also in a key phase provides temporal context for setup timing.
Indicator Limitations
Quarterly Theory describes observed behavioral tendencies, not mechanical guarantees — the same phase can produce different outcomes depending on higher-timeframe context
Fibonacci time projections are probabilistic reference zones, not precise reversal targets
The three-level phase structure works best on liquid instruments during regular trading hours; crypto markets with no session boundaries produce less distinct phase behavior
Originality Statement
The simultaneous three-level Quarterly Theory phase renderer with a resonance scoring system and Fibonacci time zone projection in a single Pine Script v6 publication is the original contribution. The resonance score — quantifying cross-timeframe phase alignment from 1 to 3 — adds an analytical layer not present in standalone ADMX or ICT quarterly theory tools.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Quarterly Theory phase labels are observational frameworks and do not predict price direction. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicator
Market State Forecast Projection EngineThis indicator is a **forecast projection tool**. It looks at the current market environment, searches history for the most similar environments, then plots what usually happened afterward. It is not trying to predict the future with certainty. It is saying: “When the market looked like this before, what tended to happen next?”
The engine defines the current market environment using three things:
* **Trend**, based on moving averages.
* **Momentum**, based on RSI.
* **Volatility**, based on ATR.
Then it finds the closest historical matches, studies their future paths, and draws a forecast line with optional upper and lower bands.
---
## What You See on the Chart
### Forecast Midline
The main forecast line shows the **average path** of the selected historical matches.
In simple terms:
* If similar past situations usually moved higher, the line slopes up.
* If similar past situations usually moved lower, the line slopes down.
* If similar past situations were mixed, the line may be flat or choppy.
### Upper Band
The upper band shows the stronger side of historical outcomes.
It means:
* Some similar historical setups moved better than the average.
* The upper band gives you a visual idea of the upside range from those past examples.
* It is not a guaranteed target.
### Lower Band
The lower band shows the weaker side of historical outcomes.
It means:
* Some similar historical setups moved worse than the average.
* The lower band gives you a visual idea of downside risk from those past examples.
* It is not a guaranteed support level.
### Band Width
The space between the bands matters.
* Tight bands mean historical outcomes were more consistent.
* Wide bands mean historical outcomes were scattered and less reliable.
* A forecast with wide bands should be treated with more caution.
---
## Main Inputs
### Non-Repaint Mode
**Default: On**
This controls whether the forecast uses the live candle or the last completed candle.
Use **Non-Repaint Mode On** when:
* You want more stable signals.
* You want the forecast to update only after the candle closes.
* You care about cleaner historical testing.
Use **Non-Repaint Mode Off** when:
* You want the forecast to react during the current live candle.
* You accept that the forecast may change before the candle closes.
For most use cases, leave this **On**.
---
## Model Group
### Forecast Horizon
This controls how far into the future the indicator projects.
Example:
* On a daily chart, `20` means 20 trading days.
* On a 1-hour chart, `20` means 20 hours.
* On a 5-minute chart, `20` means 20 five-minute candles.
Use a lower value when:
* You are trading short-term moves.
* You want a tighter forecast window.
* You do not want the projection stretched too far.
Use a higher value when:
* You are looking for swing-trade context.
* You want to see the broader projected path.
* You are using higher timeframes.
A practical range is usually:
* `10–20` for shorter-term analysis.
* `20–50` for swing-style analysis.
---
### Search Depth
This controls how much history the engine searches.
Example:
* `1000` means the engine searches roughly 1,000 prior bars.
* `2000` means it searches more history.
* `500` means it searches less history.
Use a higher Search Depth when:
* You want a larger historical sample.
* You are on a short timeframe with lots of bars.
* You want more possible market-state comparisons.
Use a lower Search Depth when:
* You want the model to focus on more recent market behavior.
* You are on a slower chart like daily or weekly.
* You want less influence from older market regimes.
The tradeoff is simple:
* More history gives more examples.
* Less history may be more relevant to the current market regime.
---
### Pattern Matches
This controls how many of the closest historical matches are used.
This is one of the most important inputs.
If set to `30`, the engine finds the **30 closest historical market states** and builds the forecast from those.
Use fewer matches when:
* You want stricter, more specific comparisons.
* You want only the closest historical examples.
* You are okay with a forecast that may be more reactive.
Use more matches when:
* You want a smoother forecast.
* You want less noise from individual examples.
* You want a broader historical sample.
General interpretation:
* `10–20` = stricter, more selective.
* `25–40` = balanced.
* `50+` = broader, smoother, but less specific.
---
### Weight Closer Matches
This controls whether the best matches receive more influence.
When turned **On**:
* The closest historical matches matter more.
* Weaker matches still count, but less heavily.
* The forecast becomes more focused on the most similar examples.
When turned **Off**:
* Every selected match is treated equally.
* The forecast becomes more democratic.
* A very close match and a weaker match have the same influence.
For most users, leave this **On**.
---
## Advanced Model Inputs
### Forecast Model
This chooses how the engine defines the market environment.
All models use:
* EMA trend.
* RSI momentum.
* ATR volatility.
The difference is how each model emphasizes those ingredients.
---
### Conservative
Use **Conservative** when you want a slower, smoother model.
It is designed to:
* React less aggressively.
* Favor more stable market environments.
* Put more importance on trend and volatility.
* Reduce noisy forecast changes.
Best for:
* Daily charts.
* Swing trading.
* Slower-moving stocks or ETFs.
* Users who want fewer false shifts.
---
### Balanced
Use **Balanced** as the general-purpose default.
It is designed to:
* Give trend, momentum, and volatility a normal balance.
* Work across many markets.
* Avoid being too slow or too fast.
Best for:
* Most users.
* Most chart timeframes.
* General market forecasting.
* Starting point before testing other models.
---
### Aggressive
Use **Aggressive** when you want a faster model.
It is designed to:
* React more quickly to changing momentum.
* Give more influence to short-term market shifts.
* Be more sensitive to fresh moves.
Best for:
* Intraday trading.
* Fast-moving markets.
* Crypto.
* Momentum names.
* Traders who want earlier, more responsive shifts.
The downside is that it may be noisier.
---
### Trend Following
Use **Trend Following** when you want the model to emphasize persistent directional moves.
It is designed to:
* Care more about trend structure.
* Care less about short-term momentum noise.
* Favor markets that continue moving in the same direction.
Best for:
* Strong trending stocks.
* Indexes.
* Breakout environments.
* Higher-timeframe directional trading.
This model is less ideal in sideways or choppy markets.
---
### Mean Reversion
Use **Mean Reversion** when you want the model to focus on stretched conditions.
It is designed to:
* Emphasize momentum extremes.
* Look for environments where price may snap back or reverse.
* Care less about long-term trend persistence.
Best for:
* Range-bound markets.
* Overbought/oversold setups.
* Countertrend analysis.
* Shorter-term reversal ideas.
This model may fight strong trends, so use it carefully in momentum-heavy markets.
---
## Historical Lookback Inputs
### Lookback Bars
This lets you move the forecast backward in time.
Example:
* `0` means current forecast.
* `50` means show what the forecast would have looked like 50 bars ago.
* `250` means show what the forecast would have looked like 250 bars ago.
Use this for:
* Visual backtesting.
* Studying old setups.
* Checking whether the forecast was useful historically.
* Comparing forecast paths against what actually happened.
This is one of the most valuable testing features.
---
### Lock to Candle
This lets you anchor the forecast to a specific candle time instead of a simple bar offset.
Use it when:
* You want to test a specific time of day.
* You trade a regular session open.
* You want repeatable historical anchors.
Example:
* You can lock to the 13:30 UTC candle, which often corresponds to the U.S. stock market open during daylight saving time.
When this is off, the indicator uses **Lookback Bars** instead.
---
### Days Back
This works with **Lock to Candle**.
It tells the indicator how many matching anchor candles to go back.
Example:
* `0` = most recent matching candle.
* `1` = one matching session back.
* `2` = two matching sessions back.
Use this when:
* You want to test the most recent open.
* You want to test yesterday’s open.
* You want to step through past sessions one by one.
---
### Hour UTC
This is the UTC hour used for candle locking.
Use it with **Minute UTC** to identify the exact candle you want.
Example:
* `13` means 13:00 UTC.
* Combined with `30`, it means 13:30 UTC.
This is useful because PulseWire symbols and sessions can vary, but UTC gives a consistent anchor.
---
### Minute UTC
This is the UTC minute used for candle locking.
Example:
* Hour UTC = `13`
* Minute UTC = `30`
Together, that means:
* Lock to the 13:30 UTC candle.
Use this for precise historical testing.
---
### Auto Previous Session
This controls what happens if today’s target candle has not printed yet.
When turned **On**:
* The indicator automatically uses the most recent previous matching candle.
* This keeps the forecast visible even before today’s target time exists.
When turned **Off**:
* If today’s target candle has not printed, the lock may show no match and fall back.
For most users, leave this **On**.
---
## Bias Logic Inputs
### Bias Threshold %
This controls how strong the bull or bear probability must be before the indicator labels the forecast bullish or bearish.
Example:
* If Bias Threshold is `60`, Bull Probability must be at least 60% before a bullish label can appear.
* If Bear Probability is at least 60%, a bearish label can appear.
Use a lower threshold when:
* You want more frequent bias labels.
* You are okay with weaker directional evidence.
Use a higher threshold when:
* You want stricter signals.
* You only want stronger historical agreement.
Practical range:
* `60%` = balanced.
* `70%+` = more conservative.
* `50–55%` = loose and more signal-heavy.
---
### Minimum Bull/Bear Edge %
This controls how large the gap must be between Bull Probability and Bear Probability.
Example:
* Bull Probability = 65%
* Bear Probability = 35%
* Edge = 30 percentage points
If the minimum edge is `15`, this would qualify.
But:
* Bull Probability = 58%
* Bear Probability = 42%
* Edge = 16 percentage points
This may still fail if Bull Probability is below the Bias Threshold.
This input prevents weak differences from being labeled as strong directional bias.
Use a higher edge when:
* You want cleaner bias labels.
* You want the model to avoid borderline calls.
Use a lower edge when:
* You want more frequent directional bias.
* You accept more uncertainty.
---
## Display Inputs
### Show Forecast Midline
This turns the main forecast line on or off.
Turn it **On** when:
* You want to see the projected average path.
Turn it **Off** when:
* You only want the info box probabilities.
* You want a cleaner chart.
---
### Show Confidence Bands
This turns the upper and lower forecast bands on or off.
Turn it **On** when:
* You want to see the historical range of outcomes.
* You care about uncertainty.
* You want to know whether the forecast is tight or messy.
Turn it **Off** when:
* You only want the central forecast.
* The chart feels too cluttered.
---
### Band Width Multiplier
This controls how wide the bands are.
Higher values make the bands wider.
Lower values make the bands tighter.
Use lower values when:
* You want a cleaner, tighter visual range.
* You want bands closer to the average forecast.
Use higher values when:
* You want to see a broader range of historical outcomes.
* You want a more conservative uncertainty envelope.
Default `1.0` is a good starting point.
---
## Forecast Midline Style Inputs
### Forecast Midline Color
Controls the color of the main projection line.
The default aqua color makes it visually distinct from price candles.
### Forecast Midline Width
Controls how thick the midline is.
Use a thicker line when:
* You want the forecast to stand out.
* You are using a busy chart.
Use a thinner line when:
* You want a cleaner chart.
* You use many overlays.
### Forecast Midline Type
Controls whether the line is:
* Solid.
* Dashed.
* Dotted.
Solid is usually best for the main forecast line.
---
## Upper Band Style Inputs
### Upper Band Color
Controls the color of the upper forecast band.
The default green tone suggests upside range.
### Upper Band Width
Controls how thick the upper band is.
A thin dashed line usually works best because it should be secondary to the midline.
### Upper Band Type
Controls whether the upper band is solid, dashed, or dotted.
Dashed is usually best because it visually communicates “range” rather than “target.”
---
## Lower Band Style Inputs
### Lower Band Color
Controls the color of the lower forecast band.
The default red tone suggests downside range.
### Lower Band Width
Controls how thick the lower band is.
A thin line keeps it useful without dominating the chart.
### Lower Band Type
Controls whether the lower band is solid, dashed, or dotted.
Dashed is usually best for the same reason as the upper band.
---
## Info Box Inputs
### Show Info Box
This turns the dashboard on or off.
Turn it **On** when:
* You want the probabilities and diagnostics visible.
* You are actively evaluating the forecast.
Turn it **Off** when:
* You only want the chart projection.
* You want a cleaner visual layout.
---
### Info Box Position
Controls where the dashboard appears.
Options:
* Top Left.
* Top Right.
* Bottom Left.
* Bottom Right.
Use the position that interferes least with price action on your chart.
---
### Text Size
Controls the dashboard text size.
Use:
* **Tiny** for compact charts.
* **Small** for normal use.
* **Normal** if you want easier reading.
* **Large** for presentations or large monitors.
---
### Background
Controls the info box background color.
A darker background usually works best on most PulseWire chart themes.
### Border
Controls the info box border color.
This helps separate the dashboard from the chart.
### Header Text
Controls the title/header text color.
### Header Background
Controls the top header row background.
This gives the dashboard its polished look.
---
## Info Box Metrics
### Bull Prob %
This shows the weighted percentage of selected historical matches that ended bullish.
Simple meaning:
> Of the similar historical market states, how many tended to move up?
A high number means bullish outcomes dominated the selected historical matches.
---
### Bear Prob %
This shows the weighted percentage of selected historical matches that ended bearish.
Simple meaning:
> Of the similar historical market states, how many tended to move down?
A high number means bearish outcomes dominated the selected historical matches.
---
### Direction Bias
This shows the final label after applying the bias rules.
Possible outputs:
* Bullish.
* Bearish.
* None.
* Weak Data.
* No Matches.
A bullish or bearish label only appears when the probability and edge requirements are met.
---
### Bull/Bear/Flat
This shows how many selected matches ended:
* Bullish.
* Bearish.
* Flat.
Example:
* `18 / 9 / 3`
This means:
* 18 bullish historical outcomes.
* 9 bearish historical outcomes.
* 3 flat historical outcomes.
This gives you a quick look at the underlying distribution.
---
### Match Count
This shows how many historical matches were actually used.
If Pattern Matches is set to `30`, Match Count should usually show `30`.
If it shows less, there may not have been enough valid historical data.
---
### Fit Quality
This tells you how closely the selected historical matches resemble the current market state.
High Fit Quality means:
* The current market environment closely resembles the selected historical examples.
Low Fit Quality means:
* The engine found matches, but they were not very close.
Important:
* Fit Quality is not win rate.
* Fit Quality is not probability.
* Fit Quality is not accuracy.
* It only measures how good the historical comparisons are.
Best interpretation:
* High Fit Quality + strong Bull/Bear Probability = more compelling.
* High Fit Quality + split probabilities = similar markets existed, but outcomes were mixed.
* Low Fit Quality = be cautious.
---
### Model
This shows which Forecast Model is active.
Examples:
* Balanced.
* Conservative.
* Aggressive.
* Trend Following.
* Mean Reversion.
This is useful for screenshots and reviewing past setups.
---
### Anchor
This tells you where the forecast is anchored.
Examples:
* `0 bars · NR` means current forecast using Non-Repaint Mode.
* `50 bars · NR` means historical forecast from 50 bars ago.
* `Locked` means it is anchored to a specific UTC candle.
This helps you know whether you are looking at a current forecast or a historical replay.
---
### Search Depth
This shows the actual number of bars being searched.
It may be lower than your input if the chart does not have enough loaded history.
---
## Best Practical Way to Use It
A clean workflow would be:
* Start with **Balanced** model.
* Keep **Non-Repaint Mode On**.
* Use **Pattern Matches around 30**.
* Use **Search Depth around 1000**.
* Watch **Fit Quality**.
* Watch **Bull/Bear Probability**.
* Treat the forecast line as a scenario path, not a guaranteed prediction.
* Use **Lookback Bars** to test whether the forecast was historically useful.
* Avoid trusting any forecast where the bands are very wide and probabilities are split.
The strongest setup is usually when:
* Fit Quality is high.
* Bull or Bear Probability is clearly dominant.
* The forecast bands are not extremely wide.
* The projection agrees with price structure.
Indicator
Indicator
Candle DNA Morphology | AnonycryptousCandle DNA Morphology | Anonycryptous
Description & user manual
Why is this indicator different:
Most candle analysis tools work with names. They look at a candle and call it an engulfing, a hammer, a doji, a shooting star. They compare shape against a fixed template and fire a signal when the match is close enough. The problem is that names are approximations. A hammer in a trending market is not the same as a hammer at a structural level with elevated volume. A name cannot capture that. A fixed template cannot either.
Candle DNA Morphology works differently.
It does not use names. It does not use templates. It compares the current candle to every historical candle within a configurable lookback window and finds the one that is mathematically closest — across up to eight normalized dimensions simultaneously. Body size, wick proportions, body position within the range, relative volume, candle size relative to recent volatility, trend alignment, and structural context. Then it tells you what happened after that historical candle, directly on the chart, with a single marker you can hover.
Other tools that use candle similarity show you statistics. Continuation rates. Reversal percentages. Tables to read and interpret. You still have to decide what the numbers mean and whether they matter right now.
Candle DNA Morphology does not show you statistics. It shows you a signal — the exact historical candle that matched, marked on the chart, with the date, the score, the direction, the R value, the percentage move, and the price move of what followed. No table to interpret. No calculation required. The information is in the hover.
The score tells you how close the match was. The tier tells you how rare it is. The color tells you the direction. Everything else is in the tooltip.
Important notice
Candle DNA Morphology generates signals based on historical pattern similarity and price behavior.
These signals are not financial advice.
They do not predict the future.
They do not guarantee profitability.
The outcome values shown — R, percentage, and price — are historical measurements from the matched candle in the past. They reflect what happened then, on that instrument, at that price level. The market may behave differently now. Similar candles can produce different results. These values are context, not certainty.
All trading decisions are made entirely by the user.
Always manage your own risk. Always apply your own judgment.
1. Overview
Candle DNA Morphology is a candle fingerprint matching indicator built around the mathematical similarity between the current candle and historical ones — and what those historical candles preceded.
What it includes:
- Up to 8-dimensional candle fingerprint matching using Euclidean distance
- Configurable lookback window from 50 to 1000 bars
- Three signal quality tiers: standard, elite, and ultra
- Hoverable triangle markers on signal bars with full match details in the tooltip
- Diamond marker and vertical line on the exact historical matched candle
- Configurable cooldown between signals to prevent clustering
- Signal mode selector: current bar, match bar, or both
- Dynamic score normalization — score stays 0-100 regardless of how many dimensions are active
- Vertical signal line and background glow on qualifying bars
- Live dashboard with score bar, tier, bias, match date, outcome in R / percentage / price, cooldown countdown, active dimensions, and ATR
- All times displayed in the timezone you select in the dashboard settings
- Four alerts: bull match, bear match, elite match (90+), ultra match (95+)
2. How the fingerprint works
Every candle is described by a set of normalized values between 0 and 1. These values capture the shape and context of the candle without using price or time units — which is what makes the engine self-calibrating across instruments and timeframes.
The five core dimensions are always active:
Body ratio. The size of the body relative to the total candle range. A full-body candle scores near 1. A doji scores near 0.
Upper wick. The upper wick as a proportion of the total range. A long upper wick scores high. A candle with no upper wick scores 0.
Lower wick. Same logic for the lower wick.
Body position. Where the body sits within the range — 0 is at the bottom, 1 is at the top. A bullish candle with a close near the high scores near 1. A bearish candle with a close near the low scores near 0.
Relative volume. Volume divided by the 20-bar average, capped at 3x and normalized. A spike at 2x average scores higher than a quiet bar at 0.8x.
Three optional dimensions can be enabled independently:
Atr percentile (dimension 6). How large the current candle is relative to recent volatility. Measures the candle range against the 14-bar ATR, normalized to a 0-2x cap. A large candle matches better with historically large candles.
Trend alignment (dimension 7). How far the close sits above or below EMA 21, normalized to the ATR. A bullish candle well above the EMA matches better with historical bullish candles that were also above the EMA.
Candle context (dimension 8). The relationship between the current candle and the previous one. Inside bars score 0. Outside bars score 1. Normal bars score 0.5. This dimension helps the engine recognize structural setups like inside bar breakouts.
3. Scoring and tiers
Similarity is measured using Euclidean distance — the straight-line distance between two candles in multi-dimensional space. The closer two candles are in this space, the more similar they are.
The maximum possible distance scales automatically with the number of active dimensions, so the score always ranges from 0 to 100 regardless of configuration. A score of 100 would mean a perfect match across all active dimensions. A score of 70 means a strong structural similarity. A score of 95 or above is exceptionally rare.
Three tiers determine how signals are displayed:
Standard (70-89). Green for bull, red for bear. The match is meaningful but not uncommon.
Elite (90-94). Gold marker with a star prefix ★. The match is close enough to be notable. These appear infrequently.
Ultra (95+). Cyan marker with a diamond prefix ◈. A near-identical historical candle was found. Very rare. When one fires, it is worth attention.
4. Understanding the signal
When a signal fires, two things appear on the chart depending on your signal mode setting.
A triangle on the current bar points in the direction the market moved after the historical match — up for a bullish outcome, down for a bearish one. Hovering the triangle with your cursor or S-Pen shows the full match details: the date and time of the historical candle, the score, the tier, the bias, the outcome in R, and the R value.
When a signal fires, two dotted lines and a vertical connector appear on the chart. The first dotted line runs horizontally from the signal bar close — this is the entry reference level, the price from which all R, percentage, and dollar measurements are calculated. The second dotted line shows the target level — where the market would reach if the historical outcome repeats. A vertical connector at the end of the forward window closes the structure. All three lines run exactly as many bars as your forward outcome setting.
The target level is calculated using the current ATR, not the historical ATR from the matched candle. This makes it relevant to the current market conditions. Hovering the target line shows both values — the target using the current ATR and the target using the historical ATR — so you can see how much volatility has changed between then and now. If the current ATR is significantly higher than the historical ATR, the target is further away than it was in the original setup. If it is lower, the target is closer.
A diamond and a vertical line on the historical matched candle shows you exactly which bar was used as the reference. The line runs through the full range of that candle so there is no ambiguity about which bar matched. The color follows the signal tier.
In addition to the dotted lines, the indicator can draw historical projection candles to the right of the signal bar. This feature is off by default and can be enabled in the visuals settings. When enabled, candles appear to the right of the signal bar showing the exact OHLC of the bars that followed the historical matched candle. Each candle has a body and centered wicks, drawn in the tier color of the signal. They scale correctly with chart zoom. A small label above the first candle reads "Historical projection" to make it immediately clear that these are historical bars, not predictions. The number of projection candles follows your forward outcome setting. Body transparency and wick transparency are independently configurable in settings.
The bias shown in the dashboard and the tooltip is the direction the market moved after the matched candle — not a prediction of what will happen now. It is historical context, not a guarantee.
All times shown in this indicator use the timezone you select in the dashboard settings. The default is UTC. Set it to your local timezone — for example UTC+2 for Amsterdam, UTC-4 for New York, UTC+9 for Tokyo — and all match times will display in your local time automatically.
5. Understanding the outcome values
The dashboard and tooltip show three outcome measurements for the historical matched candle. All three describe the same move — the price action in the bars following that historical candle — expressed in different units.
Outcome (R). How far price moved after the matched candle, expressed as a multiple of the ATR at that historical bar. This is the primary measurement. It is instrument-independent and works the same on BTC, SOL, MNQ, or any other asset. A value of +2.4R means price moved 2.4 times the ATR upward in the forward window.
Outcome (%). The same move expressed as a percentage of the close price at the matched candle. This gives a more intuitive sense of the magnitude for traders who think in percentage terms.
Outcome (price). The same move expressed in the currency of the instrument. This is the raw price distance the market covered — for example, $1,075 on Bitcoin or $0.87 on SOL. This value is calculated using the ATR and close price at the historical match bar, not at the current price.
The target line on the chart uses the current ATR rather than the historical ATR. This is intentional — the current ATR reflects how the market is moving right now, making the projected target more relevant to your actual trade. The historical ATR is still shown in the target line tooltip for reference, so you can see whether volatility has expanded or contracted since the original setup occurred. A large difference between the two ATR values means the market is in a different volatility regime than it was at the time of the match.
An important note on the price value: this reflects the historical move at the time and price of the matched candle. If Bitcoin was at 60,000 when the match occurred and is now at 78,000, the same R move produces a larger dollar value today than it did then. The price outcome is historical context — it shows what that candle type led to in dollar terms at that moment, not what the current setup will produce now.
This is not your personal risk-to-reward ratio. The R value gives you the historical move size. Your stop loss placement determines your actual R:R.
6. Bias and cooldown
The bias shown in the dashboard reflects the outcome direction of the current best match. It shows bull when the matched historical candle was followed by an upward move, and bear when it was followed by a downward move.
Bias changes when a new bar closes and the engine finds a different best match with a different historical outcome direction, or when the cooldown expires and a new signal fires pointing in a new direction.
During cooldown, the dashboard shows — wait. The last match date and all three outcome values remain visible. No new signal fires until the cooldown bar count has elapsed. The cooldown countdown shows how many bars remain before the next signal is allowed, or ready when it can fire freely.
Cooldown prevents signal clusters from forming on consecutive bars where the same setup repeats. On faster timeframes with many morphologically similar candles, a cooldown of 15 bars or more is strongly recommended.
7. Self-calibration
All fingerprint dimensions are normalized to values between 0 and 1. Volume is measured relative to its own 20-bar average. Candle size is measured relative to the ATR. Trend alignment is measured in ATR units. There are no fixed price thresholds anywhere in the engine.
This means the indicator adapts automatically to different instruments and timeframes. A BTC candle and an MNQ candle with the same proportional shape, same relative volume, and same relationship to their respective EMAs will produce the same fingerprint score — even though one trades at 78,000 and the other at 20,000.
When switching instruments, only the min match score typically needs a small adjustment. SOL and other volatile assets produce more morphological variation, so a slightly lower score threshold (75-80) often works better. More structured instruments like futures perform well at 85-90.
8. Settings guide
8.1 Match engine
Lookback window (bars). How many historical bars to scan for fingerprint matches. Range: 50-1000. Recommended: 500 on 1m-5m charts, 1000 on 15m and above. A larger window finds better matches but takes longer on lower timeframes.
Min match score (0-100). The minimum similarity score required to fire a signal. 70-79 is standard, 80-89 is strong, 90-94 is elite, 95+ is ultra. Start at 85 and adjust from there.
Cooldown between signals (bars). Minimum bars between signals. On a 5m chart, 15 bars equals 75 minutes. On a 1H chart, 15 bars equals 15 hours. Lower values produce more signals. Higher values enforce a minimum spacing between setups.
Dimension 6 — Atr percentile. Adds candle size context relative to recent volatility. Recommended: on.
Dimension 7 — Trend alignment. Adds EMA 21 directional context. Recommended: on.
Dimension 8 — Candle context. Adds inside/outside bar structural context. Recommended: on.
8.2 Outcome filter
Forward outcome (bars). How many bars after the historical match are used to measure the resulting move. Match this to your typical trade duration. On a 5m chart with 6 bars, the engine looks at 30 minutes of forward price action to determine the outcome direction and magnitude.
Min outcome move (ATR x). The historical match only qualifies if the resulting move exceeded this ATR multiple within the forward window. Filters out matches where the historical candle led to no meaningful move. Recommended: 1.0-2.0.
8.3 Visuals
Signal mode. Current bar only shows only the triangle. Match bar only shows only the diamond and vertical line on the historical candle. Both shows both simultaneously.
Show score on marker. When on, the triangle displays the score as text. When off, the triangle is clean. Hover always shows the full details regardless.
Signal bar background. Subtle glow on the signal bar in the tier color.
Vertical signal line. A faint vertical box through the signal bar. Useful for identifying signal bars when zoomed out.
Timezone. Select your local timezone from the dropdown. All match times in the dashboard and tooltips display in this timezone. Default is UTC. Amsterdam = UTC+2, London = UTC+1 (summer) or UTC, New York = UTC-4 (summer), Tokyo = UTC+9.
8.4 Dashboard
Score bar — visual meter 0-100 in tier color.
Tier — standard, ★ elite (90+), or ◈ ultra (95+).
Bias — ▲ bull or ▼ bear, or — wait during cooldown.
Match date — date and time of the historical matched candle in your selected timezone.
Outcome (R) — price move after the match in ATR multiples with forward bar count.
Outcome (%) — same move as a percentage of the historical close price.
Outcome (price) — same move in currency units at the historical price level.
Lookback — current lookback window setting.
Min score — current minimum score setting.
Cooldown — bars remaining until next signal, or ready.
Dimensions — how many dimensions are active and which ones (ATR, EMA, CTX).
ATR (14) — current ATR value.
9. Recommended starting settings
For 1m-5m scalping:
Lookback 500, min score 85, cooldown 15 bars, forward outcome 3 bars, min outcome move 1.0.
For 15m-1H:
Lookback 1000, min score 88, cooldown 8 bars, forward outcome 6 bars, min outcome move 1.5.
For 4H and above:
Lookback 1000, min score 90, cooldown 5 bars, forward outcome 4 bars, min outcome move 2.0.
10. How to use
Load the indicator and set signal mode to both. This gives you the triangle on the current signal bar and the diamond with border box on the historical matched candle simultaneously.
When a signal fires, hover the triangle with your cursor or S-Pen. Read the match date (UTC), score, bias, and outcome values. Then locate the diamond on the chart — the bordered box marks exactly which candle was matched. Look at what followed it on the chart. That is your reference.
The three outcome values give you the same historical move in three different units. Use whichever is most natural for how you think about size. The R value is instrument-independent. The percentage gives quick context. The price value shows the raw historical distance.
Watch the cooldown counter in the dashboard. When it shows ready, the next qualifying signal will fire without restriction. When it shows a bar count, the engine is waiting before it can fire again.
If you see too many signals, raise the min match score or increase the cooldown. If you see too few, lower the min outcome move or reduce the min score.
Candle DNA Morphology works best as a confluence tool. It tells you what the current candle morphology historically preceded. Your other indicators — levels, sessions, volume, trend — confirm whether the context justifies acting on it.
11. Disclaimer
This indicator is provided for educational and informational purposes only. Nothing in this document constitutes financial advice or any form of recommendation. Trading financial instruments involves substantial risk of loss. Past performance is not indicative of future results. You may lose all of your invested capital.
Anonycryptous accepts no responsibility or liability for any losses incurred as a result of using this indicator.
Indicator
Performance Comparison (Zeiierman)█ Overview
Performance Comparison (Zeiierman) is a period-mapping comparison engine that shows how the current month, quarter, or year is evolving relative to its historical structure.
It takes completed historical periods, compresses each into a normalized timeline, and overlays them on the active period so you can compare paths, pace, expansion, and finish. Instead of only asking where the price is now, the script asks how this period is behaving relative to past periods at the same stage of development.
The indicator displays all curves in Percentage Accumulated terms, meaning each period starts at the same zero point and then tracks total return from that period start. This makes it easier to compare period structure on an equal footing, regardless of the asset’s raw price level.
█ How It Works
⚪ 1) Period Segmentation
The script groups price into repeating time buckets based on the selected Period:
Monthly
Quarterly
Yearly
Each new month, quarter, or year starts a fresh period, while completed periods are stored for later comparison.
⚪ 2) Timeline Normalization
Because historical periods do not all contain the same number of bars, each is remapped to a shared normalized progress scale from start to end.
This allows the script to compare:
the beginning of one period to the beginning of another
the midpoint of one period to the midpoint of another
the final stage of one period to the final stage of another
So even if one quarter had more bars than another, both can still be compared on the same visual path.
⚪ 3) Value Mapping
The script uses Percentage Accumulated only.
Each period begins at 0% and then tracks cumulative return from that period’s starting price:
Percentage Accumulated = current price/period starting price − 1
This means all periods are anchored to the same starting point, making relative path comparison much cleaner than raw price comparison.
⚪ 4) Historical Curve Engine
Completed periods are collected into comparison buckets across the normalized timeline. From these buckets, the script can draw:
Historical paths
Median path
Average path
This creates a period-based structure model rather than a simple price overlay.
⚪ 5) Current Period Tracking
The active period is plotted on top of the historical framework, so you can see:
whether the current action is stronger or weaker than normal
whether it is tracking near the median path
whether it is diverging from the average or historical range
where the current period sits in time through the timeline bar
⚪ 6) Similarity Table
The table compares the current period against past visible periods using four path metrics:
MAE: Average distance from the current path. Lower is better.
Max Dev: Largest divergence at any point. Lower is better.
Dir Match %: How often did both paths move in the same direction? Higher is better.
End Diff: Difference at the latest comparable point. Closer to zero is better.
This helps identify which historical period most closely resembles the current one.
█ Why It Is Useful
⚪ Structural Context
The script does not just show whether the price is up or down. It shows whether the current period is unfolding in a way that is typical, weak, extended, delayed, or abnormal relative to history.
⚪ Period-Based Comparison
It is especially useful for traders and analysts who think in recurring cycles, such as:
monthly structure
quarterly seasonality
yearly progression
█ How to Use
⚪ Historical Comparison
Use the historical paths to see how prior periods behaved across the full normalized timeline.
⚪ Median Path
Use the median as the most typical historical path. This is often the cleanest benchmark for “normal” behavior.
⚪ Average Path
Use the average to measure the broad mean tendency of past periods.
⚪ Current Period
Use the current path to judge whether the live period is:
leading
lagging
tracking normally
diverging sharply from history
⚪ Similarity Table
Use the table to find the closest historical analog to the current period.
Low MAE and Max Dev suggest close path similarity.
High Dir Match % suggests similar movement behavior.
End Diff near zero suggests similar positioning at the current stage.
█ Settings
Period — groups data into Monthly, Quarterly, or Yearly periods.
Completed Periods to Compare — number of finished historical periods used in the comparison engine.
Chart Resolution — number of normalized steps used to draw each path.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Indicator
P/B Ratio (Per Share) vs Median + Bollinger Band- 📝 This indicator highlights potential buying opportunities by analyzing the Price-to-Book (P/B) ratio in relation to Bollinger Bands and its historical median.
- 🎯 The goal is to provide a visually intuitive signal for value-oriented entries, especially when valuation compression aligns with historical context.
- 💡 Vertical green shading is applied when the P/B ratio drops below the lower Bollinger Band, which is calculated directly from the P/B ratio itself — not price. This condition often signals the ticker may be oversold.
- 🟢 Lighter green appears when the ratio is below the lower band but above the median, suggesting a possible shorter-term entry with slightly more risk.
- 🟢 Darker green appears when the ratio is both below the lower band and below the median, pointing to a potentially stronger, longer-term value entry.
- ⚠️ This logic was tested using 1 and 2-day time frames. It may not be as helpful in longer time frames, as the financial data PulseWire pulls in begins in Q4 2017.
- ⚠️ Note: This script relies on financial data availability through PulseWire. It may not function properly with certain tickers — especially ETFs, IPOs, or thinly tracked assets — where P/S ratio data is missing or incomplete.
- ⚠️ This indicator will not guarantee successful results. Use in conjunction with other indicators and do your due diligence.
- 🤖 This script was iteratively refined with the help of AI to ensure clean logic, minimalist design, and actionable signal clarity.
- 📢 Idea is based on the script "Historical PE ratio vs median" by haribotagada
- 💬 Questions, feedback, or suggestions? Drop a comment — I’d love to hear how you’re using it or what you'd like to see changed. Indicator
P/E Ratio vs Median + Bollinger Band- 📝 This indicator highlights potential buying opportunities by analyzing the Price-to-Earnings (P/E) ratio in relation to Bollinger Bands and its historical median.
- 🎯 The goal is to provide a visually intuitive signal for value-oriented entries, especially when valuation compression aligns with historical context.
- 💡 Vertical green shading is applied when the P/E ratio drops below the lower Bollinger Band, which is calculated directly from the P/E ratio itself — not price. This condition often signals the ticker may be oversold.
- 🟢 Lighter green appears when the ratio is below the lower band but above the median, suggesting a possible shorter-term entry with slightly more risk.
- 🟢 Darker green appears when the ratio is both below the lower band and below the median, pointing to a potentially stronger, longer-term value entry.
- ⚠️ This logic was tested using 1 and 2-day time frames. It may not be as helpful in longer time frames, as the financial data PulseWire pulls in begins in Q4 2017.
- ⚠️ Note: This script relies on financial data availability through PulseWire. It may not function properly with certain tickers — especially ETFs, IPOs, or thinly tracked assets — where P/S ratio data is missing or incomplete.
- ⚠️ This indicator will not guarantee successful results. Use in conjunction with other indicators and do your due diligence.
- 🤖 This script was iteratively refined with the help of AI to ensure clean logic, minimalist design, and actionable signal clarity.
- 📢 Idea is based on the script "Historical PE ratio vs median" by haribotagada
- 💬 Questions, feedback, or suggestions? Drop a comment — I’d love to hear how you’re using it or what you'd like to see changed. Indicator
Indicator
Dynamic Candle Balance Indicator (Binary)
Dynamic Candle Balance Indicator
The Dynamic Candle Balance Indicator is a powerful tool designed to identify imbalances in candle colors on a chart, which can indicate potential reversals or changes in market direction. This indicator is specifically developed for traders operating on short timeframes, such as 1-minute candles, and is particularly useful for identifying opportunities in binary options.
How to Use:
Set Parameters
Initial Position: Specify the number of initial candles to be considered for calculation.
Count: Determine the total number of candles to be analyzed, including the initial position.
Interpret Results:
Green: Indicates the number of bullish candles (where the closing price is higher than the opening price).
Red: Indicates the number of bearish candles (where the closing price is lower than the opening price).
Absent: Indicates the number of candles that were not considered due to the selected interval.
Performance Analysis:
The indicator calculates the percentage of green and red candles relative to the total number of analyzed candles, providing insights into market balance or imbalance.
Identify Trading Opportunities:
Significant imbalances between candle colors can indicate potential reversals or changes in market direction.
Traders can use this information to make informed decisions about their trading strategies, such as identifying entry or exit points.
Example:
In the last 40 candles, there were 13 green candles and 27 red candles, indicating a higher likelihood of the next candle being green.
Usage Tips:
The indicator is most effective when used on a 1-minute timeframe for binary options trading, especially during periods of high imbalance.
Adjust the parameters according to your trading strategy and the timeframe being analyzed.
Combine the Dynamic Candle Balance Indicator with other technical analysis tools to confirm trading signals.
Legal Disclaimer:
This indicator is provided for educational and informational purposes only. It represents a theory and should be used as part of a comprehensive trading strategy. Past performance is not indicative of future results. Traders should always conduct their own analysis before making trading decisions.
Try out the Dynamic Candle Balance Indicator and leverage its functionalities to identify trading opportunities on short-term charts, especially in 1-minute timeframes for binary options trading during periods of high imbalance. Remember to test the indicator on a practice account before using it on a real account. Indicator
Historical Correlation [LuxAlgo]The Historical Correlation tool aims to provide the historical correlation coefficients of up to 10 pairs of user-defined tickers starting from a user-defined point in time.
Users can choose to display the historical values as lines or the most recent correlation values as a heat map.
🔶 USAGE
This tool provides historical correlation coefficients, the correlation coefficient between two assets highlight their linear relationship and is always within the range (-1, 1).
It is a simple and easy to use statistical tool, with the following interpretation:
Positive correlation (values close to +1.0): the two assets move in sync, they rise and fall at the same time.
Negative correlation (values close to -1.0): the two assets move in opposite directions: when one goes up, the other goes down and vice versa.
No correlation (values close to 0): the two assets move independently.
The user must confirm the selection of the anchor point in order for the tool to be executed; this can be done directly on the chart by clicking on any bar, or via the date field in the settings panel.
For the parameter Anchor period , the user can choose between the following values NONE, HOURLY, DAILY, WEEKLY, MONTHLY, QUARTERLY and YEARLY. If NONE is selected, there will be no resetting of the calculations, otherwise the calculations will start from the first bar of the new period.
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negative correlated asset or going short a positive correlated asset.
Traders generally need to develop awareness, a key point is to be aware of the relationships between the assets we hold or trade, the historical correlation is an invaluable tool in our arsenal which allows us to make better informed decisions.
On this chart we have an example of historical correlations for several futures markets.
We can clearly see how positively correlated the Nasdaq100 and Dow30 are with the SP500 over the whole period, or how the correlation between the Euro and the SP500 falls from almost +85% to almost -4% since 2021.
As we can see, correlations, like everything else in the market, are not static and vary over time depending on many factors, from macro to technical and everything in between.
🔹 Heatmap
The chart above shows the tool with the default settings and the Drawing Mode set to 'HEATMAP'.
We can see the current correlation between the assets, in this case the FX pairs.
The highest positive correlation is +90% (+0.90) between EURUSD and GBPUSD.
The highest negative correlation is -78% (-0.78) between EURUSD and USDJPY.
The pair with no correlation is AUDUSD and EURCAD with 1% (0.01)
On the above chart we can see the current correlations for the futures markets.
Currently, the assets that are less correlated to the SP500 are NaturalGas and the Euro, the more positive correlations are Nasdaq100 and Dow20, and the more negative correlations are the Yen, Treasury Bonds and 10-Year Notes.
🔶 DETAILS
🔹 Anchor Period
This chart shows the standard FX correlations with the Anchor Period set to `MONTHLY`.
We can clearly see how the calculations restart with the new month, in this case we can clearly see the differences between the correlations from month to month.
Let us look at the correlation coefficient between GBPUSD and USDJPY
In January, their correlation started at close to -100%, rose to close to +50%, only to fall to close to 0% and remain there for the second half of the month.
In February it was -90% in the first few days of the month and is now around -57%.
And between AUDUSD and EURCAD
Last month their correlation was negative for most of the month, reaching -70% and ending around -14%.
This month their correlation has never gone below +21% and at the time of writing is close to +53%.
🔶 SETTINGS
Anchor point: Starting point from which the tool is executed
Anchor period: At the beginning of each new period, the tool will reset the calculations
Pairs from 1 to 10: For each pair of tickers, you can: enable/disable the pair, select the color and specify the two tickers from which you wish to obtain the correlation
🔹 Style
Drawing Mode: Output style, `LINES` will show the historical correlations as lines, `HEATMAP` will show the current correlations with a color gradient from green for correlations near 1 to red for correlations near -1.
Indicator
Historical Price Projection [LuxAlgo]The Historical Price Projection tool aims to project future price behavior based on historical price behavior plus a user defined growth factor.
The main feature of this tool is to plot a future price forecast with a surrounding area that exactly matches the price behavior of the selected period, with or without added drift.
Other features of the tool include:
User-selected period up to 500 bars anywhere on the chart within 5000 bars
User selected growth factor from 0 (no growth) to 100, this is the percentage of drift to be used in the forecast.
User selected area wide
Show/hide forecast area
🔶 USAGE
This tool generates a price projection with exactly the same price behavior over the period selected by the user, plus a growth factor .
The user must confirm the selection of the anchor point in order for the tool to be executed; this can be done directly on the chart by clicking on any bar, or via the date field in the settings panel.
As we can see on this chart, the four phases of the market cycle are clearly defined and marked, so we choose the distribution phase as our anchor point because in our analysis, we want to see how the market would behave if we were currently at the same point in the cycle.
In the image above, the growth factor parameter is set to 0 so that the projection matches the selection. The tool will use up to 500 bars after the selection point.
The growth factor is defined as the percentage of drift that the tool will use.
Drift is defined as follows:
For periods with a positive return: average negative return within the period
For negative return periods: average positive return within the period
On the chart above, we have selected the same period but added a growth factor of 10, so that the tool uses a 10% drift in its calculations of future prices.
As the return in the selected period is negative, the added drift will make the projection more bearish than the prices from the selection.
On this chart we have changed the selected period, we have chosen the accumulation phase of the last cycle as the anchor point, again with a growth factor of 10%.
As we can see, prices explode higher, making the projection very bullish, as the added effect of both the bullish selected period and the 10% drift is taken into account.
This last chart is a long-term chart, a quarterly chart of the Dow, and it will serve as a review exercise.
What if... everything goes south and the crash of '29 is repeated?
The answer is in the chart, and it is not for the faint of heart
In this case we have chosen a growth factor of 0 to see exactly the same price behaviour projected into the future.
🔶 SETTINGS
🔹 Data Gathering
Anchor point: Starting point for data collection, up to 500 bars will be used.
🔹 Data Transformation
Growth Factor: Values from 0 to 100, is the amount of drift used to calculate the next price in the series.
Area Width: Values from 0 to 100, controls the width of the area around the forecast as an increment/decrement of the growth factor.
🔹 Style
Price line width: Size of the price line.
Bullish color
Bearish color
Show Area: Show forecast area.
Area color
Indicator
Indicator
Price Range Volume Profile [Pt]█ Introduction
The Price Range Volume Profile (PRVP) is a revolutionary indicator. This tool stands out from its peers due to its unique ability to capture the entire price chart history, thus providing a comprehensive volume profile of the entire asset's trading history, as available on PulseWire chart. It's worth noting that I believe this tool is the first of its kind to accomplish such a feat. A much recommended tool if you are a volume profile trader.
█ Main Features
► Historical Lookback: This feature dives deep into the past, grasping all the historical data of an asset. It's equipped to handle up to 20,000 bars, although users without a premium PulseWire account are advised to keep it at a maximum of 10,000 bars, or just use the "Full Historical Lookback" feature.
► Volume Profile / POC: Displays the distribution of volume across price levels for the selected price range. The Point of Control (POC), which is the price level with the highest traded volume, is also highlighted.
► Customization: Users have the flexibility to adjust the profile's appearance, including profile width, horizontal offset, and the option to fill the background of the profile range.
► Time Weighting: This feature allows users to give more weight to recent trading activity, which can be especially useful for intraday traders or during times of high volatility. Note that this feature will impact the volume profile and POC level.
► Settings Table: A settings table is displayed on the chart for users to quickly reference their input parameters.
█ Input Parameters
► Lookback Timeframe: Determines the period for which the volume profile is generated.
► Price Range: The percentage distance to consider for the profile, adjusted above and below the current closing price.
► Profile Step size: The granularity of the volume profile. Users can opt for automatic step size based on a predefined calculation or set their preferred tick step size.
► Historical Bars Lookback: Determines the number of bars to include in the volume profile calculation.
► Profile Visuals: Adjust the appearance and layout of the volume profile on the chart.
► Extra: Additional settings including the display of a settings table and its location.
█ Basic Understanding of Volume Profile - How to use PRVP?
Volume Profile is a valuable tool for traders who want insights into where the majority of trading activity has occurred. Here are some tips to make the most of it:
► Understand the Basics: Before using the Volume Profile, ensure you understand the difference between it and the standard volume histogram. While both represent volume, the former displays it against price while the latter shows it against time.
► Identify High Volume Nodes (HVN) and Low Volume Nodes (LVN):
◊ HVN: Areas where there's a lot of trading activity and where the price has spent a lot of time. These areas can act as strong support or resistance.
◊ LVN: Areas where there's a lack of trading activity. Prices might move quickly through these areas, and they can act as potential breakpoints or accelerators for price movement.
► Locate the Point of Control (POC): This is the price level with the highest traded volume for a specified period. It often acts as a magnet for price, and it can serve as a pivot or reference point.
► Trend Confirmation: A shift in the volume profile from one price level to another can confirm a trend. For instance, if higher volume starts to build at higher price levels, it may indicate a strong uptrend.
► Watch for Volume Gaps: If there's a significant gap in the volume profile, prices may move quickly through these levels as there's little historical trading activity to act as support or resistance.
█ Other Usage Tips
◊ For optimal performance, ensure that the chosen timeframe aligns closely with the chart timeframe. Differences in timeframes may lead to minor discrepancies in the volume profile.
◊ To address any errors arising from too many levels displayed on the volume profile, consider increasing the Profile Step size or reducing the Price Range. Indicator
Indicator
Indicator
Indicator
Indicator
Seasonal tendency: week-on-week % change and 10yr Averages-shows week-on-week % change, and 10yr averages of these % changes
-scan across the 10yr averages to get a good idea of the seasonality of an asset
-best used on commodities with strong seasonal tendencies (Gold, Wheat, Coffee, Lean hogs etc)
-works only on daily timeframe
-by default it will compare SMA(length) in the following way, BTC: Sunday cf previous Sunday | ES/Gold: Monday cf previous Monday
-for most assets, 5 daily bars in a week (SMA(5)) => that's the default. For BTC can change this to 7.
~~inputs:
-change input year to show any previous decade of asset's history; the table will display over that year on the chart
-choose expression for Average of % change week on week: SMA, ohlc4, vwma, vwap (default SMA)
-choose number of daily bars in a week (i.e. SMA length)
-change label sizes/colors
~~notes:
-When applied to current year: will print the 10yr average for previous weeks in the year; 9yr average for future weeks in the year
-drawings and SMA plot on the above chart are just to show visually how the week's average is calculated, and how this lines up with the label
-current week of year will highlight in large font orange by default
-the first 2 weeks of the year are omitted because of a bug i can't figure out, which throws out bad numbers.
-cannot print all the values for each of previous 10yrs; 'code too long' error. Could likely do this via using matrices but would require a rewrite
17th Dec 2022
@twingall Indicator
Indicator
Indicator
Indicator
