Hash Dispersion Cone## Overview
The **Hash Dispersion Cone** is a forward-projecting statistical probability envelope built on realized volatility. Anchored to the current bar's close price, it projects where price is statistically expected to trade over the next N bars using log-normal volatility scaling — the same mathematical framework used by professional options desks and quantitative risk managers.
This is not a buy/sell signal generator. It is a **probability map** — a live, continuously recalculating field that shows the market's statistical boundaries given current realized volatility. When volatility is low, the cone is tight. When volatility is expanding, the cone widens in real time.
> *"Know your range before the market shows it to you."*
> — Hash Capital Research
---
## How It Works
### The Mathematics
The cone is constructed using the **square-root-of-time rule**, a foundational principle of financial mathematics. At each forward bar `t`, the projected price boundaries are calculated as:
```
Upper_k(t) = AnchorPrice × exp( +k × σ × √t )
Lower_k(t) = AnchorPrice × exp( −k × σ × √t )
```
Where:
- `k` = standard deviation multiplier (1 for 1σ, 2 for 2σ)
- `σ` = realized volatility per bar (selected method)
- `t` = number of bars forward
Using the **log-normal form** is intentional and correct. It keeps the cone asymmetric in price space — the upside boundary is always further from anchor than the downside boundary by an equal percentage amount. This reflects how asset prices actually behave: they cannot go below zero, but can theoretically rise without limit.
### Why the Cone Moves With Price
The cone repaints every bar because it is always anchored to the **current close**. This is by design. It answers the question: *"Given what volatility is right now, where could price go from here?"* — not where it could have gone from a past bar.
---
## Volatility Methods
Three realized volatility estimators are available. Each has distinct statistical properties suited to different market conditions.
### Close-to-Close (Default)
The standard log-return standard deviation:
```
σ = stdev( ln(Close / Close ), lookback )
```
Most widely understood. Can underestimate volatility on assets that gap frequently or have large intrabar swings. Best for: **daily timeframes, equities, stable assets**.
### Parkinson (High-Low)
Uses the high-low range instead of close-to-close returns:
```
σ² = mean / (4 × ln2)
```
Approximately **5x more statistically efficient** than Close-to-Close for the same lookback period. Captures intrabar volatility that close-to-close misses. Best for: **crypto, commodities, FX — any asset with large intrabar ranges**.
### Garman-Klass (OHLC)
The most efficient of the three estimators, using all four price points:
```
σ² = mean
```
Most accurate for intraday analysis where the open-to-close gap carries information. Best for: **intraday timeframes (1H, 4H), equities with significant opening gaps**.
---
## Inputs Reference
### Volatility Calculation
| Input | Default | Description |
|---|---|---|
| Lookback Period | 30 | Bars used to calculate σ. Lower = more reactive. Higher = smoother. |
| Volatility Method | Close-to-Close | Estimator used. See Volatility Methods above. |
| Vol Trend MA Length | 10 | SMA length applied to σ for regime classification. |
**Lookback Tuning Guide:**
- `10–20` bars → reactive, tracks recent volatility closely, cone resizes quickly
- `30` bars → balanced default, smooths out single-spike distortions
- `60–100` bars → slow-moving, regime-level volatility, stable cone width
### Projection
| Input | Default | Description |
|---|---|---|
| Forward Bars | 15 | How many bars ahead the cone projects. |
| Show 1σ Band | On | Displays ±1σ boundary (~68% probability zone). |
| Show 2σ Band | On | Displays ±2σ boundary (~95% probability zone). |
| Show Midline Anchor | On | Dotted horizontal line at anchor price. |
**Forward Bars Tuning Guide:**
- `5–10` bars → scalping and intraday setups
- `10–20` bars → swing trading (recommended for 4H/Daily)
- `20–50` bars → position trading and options expiry targeting
**Important:** Doubling forward bars does NOT double the projected range. Due to the √t rule, doubling projection bars widens the cone by only ~41%.
## Visual Guide
### Band Colors and Meaning
```
+2σ ──────────────────────────── Crimson solid (outer extreme, ~95%)
░░░░ TEAL FILL (upside risk zone) ░░░░
+1σ - - - - - - - - - - - - - - Green dashed (primary upside boundary, ~68%)
▓▓▓▓ NAVY FILL (highest-probability core) ▓▓▓▓
MID ····························· Grey dotted (anchor / flat scenario)
▓▓▓▓ NAVY FILL (highest-probability core) ▓▓▓▓
−1σ - - - - - - - - - - - - - - White dashed (primary downside boundary, ~68%)
░░░░ MAGENTA FILL (downside risk zone) ░░░░
−2σ ──────────────────────────── Crimson solid (outer extreme, ~95%)
```
### Three-Layer Fill System
**Navy Core (±1σ interior):** The highest-probability zone. Statistically, ~68% of all future closes are expected to land here. This is where price "wants" to stay in a low-volatility regime.
**Teal Upside Zone (+1σ to +2σ):** The upside risk corridor. Price entering this zone is statistically elevated — possible, but in the outer 14% of expected outcomes.
**Magenta Downside Zone (−1σ to −2σ):** The downside risk corridor. Mirror of the teal zone. Price here signals a statistically significant down-move.
---
## Trading Applications
### 1. Cone Width as Regime Filter
The most important signal is the **width of the cone itself**, not where price is within it.
- **Tight cone** = low volatility, compressed range → range-bound playbook (fade edges, mean revert to midline)
- **Wide cone** = high volatility, expanded range → momentum playbook (ride direction, wider stops)
Never take a counter-trend trade in a wide, expanding cone. Never chase a breakout in a tight, contracting cone.
### 2. Price at 1σ Edge = Mean Reversion Setup
When price reaches the projected +1σ or −1σ label price, it has statistically entered the outer 32% of expected outcomes.
**Setup:**
```
Condition 1: Vol Regime is STABLE (─)
Condition 2: Price has reached the ±1σ label level
Condition 3: Rejection candle confirms (wick, doji, engulf)
Entry: Fade the move back toward midline
Target: Anchor price (midline)
Stop: Just beyond the ±2σ label
R:R: Typically 2:1 to 3:1 depending on cone width
```
### 3. 2σ Touch = Extreme Signal
A touch of the ±2σ boundary represents a 2-standard-deviation move. Statistically, only ~5% of future closes are expected to exceed this level.
- In a **stable** or **contracting** regime: high-conviction mean reversion entry with defined risk to the 2σ line
- In an **expanding** regime: possible breakout continuation — wait for candle confirmation before fading
- Use the 2σ label price directly as a hard stop level for trades taken inside the cone
### 4. Vol Regime Arrow as Trade Filter
The regime classification in the dashboard acts as a meta-filter over all other signals.
- **▲ EXPANDING (red):** Do not counter-trend trade. Only take momentum entries in the direction of the move or stay flat. Cone edges are likely to be broken.
- **▼ CONTRACTING (green):** Volatility is compressing. A breakout is loading. Watch for the first expansion candle and trade the direction of the break. This is often the highest R:R setup the cone generates.
- **─ STABLE (white):** Range conditions active. Mean reversion setups at σ edges are highest probability in this state.
### 5. Stop Placement Reference
The σ label prices at the cone's right edge provide statistically-grounded stop levels:
- **Conservative stop:** Beyond ±2σ label (95% of moves contained)
- **Standard stop:** Beyond ±1σ label (68% of moves contained)
- **Tight stop:** A fixed percentage of the ±1σ distance
This gives every trade a volatility-adjusted stop rather than an arbitrary fixed-pip or percentage stop.
---
## Timeframe Recommendations
| Timeframe | Lookback | Forward Bars | Vol Method | Best Use |
|---|---|---|---|---|
| 5m / 15m | 20 | 10 | Garman-Klass | Scalping entries |
| 1H | 30 | 15 | Parkinson or GK | Intraday swing |
| 4H | 30 | 15 | Parkinson | Swing trading (default) |
| Daily | 30–50 | 20 | Close-to-Close | Position trading |
| Weekly | 20 | 10 | Close-to-Close | Macro range framing |
---
## Asset Class Notes
**Crypto (BTC, ETH, SOL, etc.):**
Parkinson is recommended over Close-to-Close due to large intrabar ranges common in 24/7 markets. Cone will be noticeably wider than equities at equivalent timeframes, reflecting structurally higher realized volatility. The 2σ touch setup is especially reliable on 4H BTC during STABLE regimes.
**FX:**
Parkinson works well. Forward Bars of 10–15 on 4H aligns well with typical intraweek swing durations. Cone width is generally tighter than crypto, making σ edge touches more frequent.
**Equities / Indices:**
Garman-Klass recommended for intraday. Close-to-Close is standard for daily and above. Be aware that equity close-to-close can underestimate true vol during earnings season — consider switching to Garman-Klass temporarily.
**Commodities:**
Parkinson preferred. Energy and agricultural commodities have gap and range behavior similar to crypto.
---
## Technical Notes
- The cone redraws on every bar close. It is anchored to the current close and always projects forward from the most recent confirmed price. This is expected behavior — not a repaint flaw.
- Fills are capped at 16 segments per zone to remain within Pine Script's linefill object limit (~50 total). At default 15 forward bars, all fills render completely.
- The annualization factor is automatically adjusted for timeframe: Daily (√252), Weekly (√52), Monthly (√12), and intrabar (derived from `timeframe.in_seconds()`).
- All price labels use comma-formatted output (e.g., `74,161.34`) for readability at large price scales.
---
## Disclaimer
The Hash Dispersion Cone is an educational and analytical tool. Statistical probability does not guarantee any specific price outcome. All trading involves risk. Past statistical behavior does not guarantee future results. This indicator does not constitute financial advice.
---
*Published on PulseWire by Hash Capital Research * Indicator
Structural Deviation Compass [JOAT]Structural Deviation Compass
Introduction
The Structural Deviation Compass is an overlay indicator designed to map where price stands relative to its own statistical history. Rather than drawing fixed-distance envelopes or relying on a single moving average, it constructs a hybrid centerline from two distinct low-lag moving average types, then wraps that centerline in volatility-adaptive bands derived from Z-score normalization. A secondary oscillator layer — applied to RSI — creates a dual-confirmation signal gate that fires only when both price deviation and momentum reach simultaneous extremes. Shadow bands built from the Average True Range provide additional spatial context across three volatility tiers.
The indicator does not predict future price. It identifies statistically unusual deviations from an estimated mean structure and flags conditions where a reversion or continuation setup may be forming, subject to confirmation from the trader's own process.
Core Concepts
The ComboMA Centerline
The foundation of the indicator is a composite moving average called the ComboMA, formed by averaging two lines:
ALMA (Arnaud Legoux Moving Average): Uses a Gaussian-weighted kernel positioned asymmetrically along the lookback window. The offset and sigma parameters control how far toward the recent end the weight mass sits and how tightly it is concentrated. This produces a smooth line that tracks price closely while suppressing noise better than a simple EMA of the same length.
ZLMA (Zero-Lag Moving Average): Constructed by doubling a base EMA and subtracting a second EMA of that EMA — a technique that estimates and removes the inherent lag of an exponential average. The result is then smoothed once more to reduce the noise amplification that zero-lag constructions can introduce.
Averaging the two produces a centerline that carries reduced lag from the ZLMA side while retaining the smooth, noise-filtered character of the ALMA side. Neither line alone fully satisfies both goals; together they produce a more balanced result.
Z-Score Price Bands
Rather than plotting bands at a fixed multiple of a standard deviation (as Bollinger Bands do using a rolling standard deviation of price itself), the SDC first computes the deviation of close from the ComboMA, then Z-score normalizes that deviation series over a separate lookback window. The bands are then placed back on the price chart by multiplying the rolling standard deviation of deviations by the chosen Z-score threshold values.
The practical effect is that the band width reflects how unusual the current deviation is relative to the recent distribution of deviations — not simply how wide price has swung in a raw sense. Two threshold levels are provided, creating an inner and outer band pair on each side of the ComboMA.
RSI Z-Score
RSI is computed in the standard way, then subjected to the same Z-score normalization: the RSI value is compared to its own rolling mean and expressed in standard deviations. This removes the fixed-level bias of RSI (where 30/70 thresholds mean different things in different market regimes) and produces a momentum reading that is self-calibrating to recent RSI behavior.
Dual Z-Score Signal Gate
A long signal requires all of the following simultaneously:
Price Z-score below the negative trigger threshold (price is statistically far below the ComboMA)
RSI Z-score below the negative trigger threshold (momentum is statistically depressed)
RSI EMA below 38 (confirming a bearish momentum context rather than a pullback within strength)
The current bar closed above the prior bar's close (a micro-confirmation that selling pressure may be easing)
The bar is confirmed (signal does not repaint on the forming bar)
Short signals apply the mirror logic. The requirement for extremes in both dimensions simultaneously is intentionally strict — it filters out the many cases where price is extended but momentum is not, or vice versa.
ATR Shadow Bands
Three pairs of shadow bands are drawn around the ComboMA at 1x, 2x, and 3x of a rolling ATR. These are not signal bands — they serve as a spatial reference, helping to contextualize how far price has traveled from the estimated mean in volatility-adjusted terms. A move to the 3x ATR shadow in a low-volatility environment carries different significance than the same move in a high-volatility environment.
RGB Smooth Color Transition
The ComboMA line color transitions smoothly between a bull and bear palette by independently blending the red, green, and blue channels via EMA. Each channel tracks a target value set by the current bull/bear state, and converges toward it gradually. This avoids abrupt color flips and gives a visual sense of momentum continuity.
Gradient Bar Coloring
Individual bars are colored based on where the close sits within the band range relative to the ComboMA. Bars near the upper bands trend toward the bull color; bars near the lower bands trend toward the bear color. Bars near the ComboMA receive a neutral tone. This is a visual aid only and does not constitute a signal.
Information Table
A 9-row table displays the current readings for: market regime, price Z-score, RSI Z-score, RSI EMA, band width, signal strength, active signal, and ComboMA value. This gives a snapshot of the indicator's internal state without requiring the trader to hover over each plotted element.
---
Features
Hybrid ComboMA centerline combining ALMA and ZLMA
Volatility-adaptive Z-score bands at two threshold levels (inner and outer)
RSI Z-score normalization for regime-independent momentum reading
Dual Z-score signal gate requiring simultaneous extremes in price and momentum
Three-layer ATR shadow bands for spatial volatility context
Smooth RGB channel blending on the ComboMA line color
Gradient bar coloring based on position within band range
Real-time information table with 9 indicator state readings
Non-repainting signals (barstate.isconfirmed)
Fully toggleable visual components
---
Input Parameters
MA Length: Base length for the ZLMA and ATR calculations
ALMA Offset: Controls asymmetric weight positioning within the ALMA window (0 = old end, 1 = recent end)
ALMA Sigma: Controls weight concentration; lower values spread the weight, higher values tighten it
Z-Score Lookback: Rolling window for computing the mean and standard deviation of price deviations (default: 50)
Inner Band Threshold: Z-score level for the inner band pair (default: 1.5σ)
Outer Band Threshold: Z-score level for the outer band pair (default: 2.5σ)
RSI Length: Period for RSI calculation (default: 14)
RSI Z-Score Lookback: Rolling window for normalizing RSI
Signal Trigger: Z-score threshold required in both dimensions to generate a signal (default: 1.8σ)
ATR Multipliers: Multipliers for the three shadow band tiers (1x, 2x, 3x)
Visual Toggles: Individual on/off controls for bands, shadows, bar coloring, table, and signals
---
How to Use
Reading the centerline: The ComboMA acts as the estimated mean structure. Price consistently above it with a bull-colored line suggests sustained upward bias; price oscillating around it suggests a ranging environment.
Reading the bands: The inner bands (±1.5σ by default) represent moderately unusual deviations. The outer bands (±2.5σ by default) represent statistically rare deviations. A touch or breach of the outer band does not by itself mean a reversal is due — it means the move is statistically uncommon and warrants attention.
Reading the shadow bands: Use the ATR shadows to understand how far, in volatility-adjusted terms, price has moved from the ComboMA. Price at the 3x shadow while also at the outer Z-score band is a more notable condition than either reading alone.
Acting on signals: The dual Z-score signals flag confluent extremes. They should be used as an alert layer within a broader trading framework — not as standalone entry triggers. Consider the broader trend context, the timeframe, and supporting structure before acting.
Using the table: Monitor the signal strength reading to understand how close the current state is to triggering a signal. This is useful for watching a developing setup in real time.
Timeframe notes: The indicator functions on any timeframe. Higher timeframes produce fewer but more structurally significant signals. Lower timeframes will produce more signals, many of which will be noise. Adjust the Z-score lookback and trigger threshold accordingly.
---
Limitations
This indicator does not predict future price movement. All readings are descriptive of past and current bar data.
The ComboMA, like all moving averages, will lag price during sharp trend changes. The ZLMA component reduces but does not eliminate this lag.
Z-score bands assume that price deviations are approximately normally distributed. In instruments with fat-tailed distributions or during extreme events, the statistical thresholds will underestimate the probability of outlier moves.
Signals are non-repainting on confirmed bars but will update on the forming bar until it closes. Always wait for bar close before acting on a signal.
A signal firing does not mean price will reverse. Trending markets can sustain extreme Z-score readings for extended periods.
The RSI EMA threshold (38 for longs) is a fixed filter that may not suit all instruments or regimes. It should be adjusted or disabled if it is filtering out valid setups in the instrument being traded.
The ATR shadow bands are informational only and carry no predictive weight.
Past signal performance on a given instrument is not indicative of future performance.
---
Originality Statement
The ALMA and ZLMA are established concepts. The ComboMA is not either of them — it is a blended centerline that takes the asymmetric-weight smoothness of ALMA and the lag-reduction property of ZLMA and produces a composite that neither achieves individually. The Z-score normalization of price deviations is a statistical adaptation that makes the bands self-calibrating to the instrument's deviation distribution rather than fixed. Applying the same normalization independently to RSI produces a momentum reading that is self-referential to recent RSI behavior rather than anchored to universal threshold levels. The signal gate that requires simultaneous Z-score extremes in both price deviation and RSI — not one or the other — creates a logical AND condition that is substantially stricter than conventional oscillator crossovers or single-band-touch triggers. The three ATR shadow tiers, smooth RGB color blending, and gradient bar coloring are supporting visual constructs that serve interpretation rather than adding trading logic. The combination of these elements into a single overlay tool — ComboMA centerline, adaptive Z-score bands, normalized momentum gate, ATR spatial context, and state table — represents an original integration not replicated by any standard built-in indicator.
---
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions.
-Made with passion by officialjackofalltrades
Indicator
Tactical Deviation MiniTactical Deviation Mini is an overlay indicator that shows up to three independent higher-timeframe VWAPs on one chart—1-hour, 4-hour, and 8-hour—each with 1σ, 2σ, and 3σ standard-deviation bands. By default, only the 4-hour VWAP and its bands are enabled; 1H and 8H are optional toggles. This keeps the chart readable while still letting you stack contexts when you want them.
Why it is useful
Many traders watch where price sits relative to VWAP and to volatility-sized bands across intraday structure. This script puts those references on the same pane as your execution timeframe, so you can compare alignment across 1H / 4H / 8H without switching charts. Optional band fills separate the 1σ–2σ and 2σ–3σ zones. An optional table summarizes sigma distance from VWAP (per enabled timeframe) and RSI(14) on the current bar for quick context.
How it works (concepts)
For each enabled timeframe, the script maintains a running volume-weighted mean of hlc3 and a running volume-weighted second moment so it can derive population-style variance and standard deviation on the fly. When a new bar opens on that higher timeframe, the cumulative sums reset, so each VWAP is anchored to that higher timeframe’s bar sequence (not to the chart’s session template unless your symbol’s bars happen to match that). Band width is standard deviation × your chosen multipliers (defaults 1, 2, 3).
Optional “dynamic” mode
When enabled, the script scales the deviation multipliers using recent volatility (ATR relative to price) so bands can widen in more volatile conditions and narrow in calmer ones. This is a heuristic adjustment, not a guarantee of any particular risk or outcome.
How to use it
Enable the timeframe(s) you want under Timeframe Selection.
Adjust σ multipliers if you want tighter or wider bands.
Toggle Show Deviation Clouds and opacity if you want filled zones.
Use Colors to separate 1H / 4H / 8H visually.
Read the table (if visible) for σ from VWAP and RSI; treat these as context, not instructions.
What this script does not do
It does not plot buy/sell markers, strategy orders, or alerts. It does not rank setups, predict direction, or estimate profitability. Past or hypothetical behavior of VWAP or bands does not imply future results.
Limitations and honesty
VWAP and σ bands depend on volume and bar data available on your symbol and timeframe. On some instruments or sessions, volume or bar construction may differ from what you expect, which affects VWAP and bands. RSI in the table is a standard momentum oscillator shown for reference only.
Disclaimer
This tool is for informational and educational purposes only and is not investment, tax, or trading advice. You are responsible for how you use any charting tool. No warranty is made as to accuracy, fitness, or results. Indicator
Volume Acceptance Zones [BigBeluga]Volume Acceptance Zones is a market structure tool designed to identify areas of price acceptance and statistically stretched extremes. By modeling market activity as a continuous distribution, the indicator highlights where price is actively accepted versus where it behaves as a statistical outlier.
The goal is not prediction, but context — separating balanced price behavior from structurally stretched conditions.
🔵 CONCEPTS
The indicator calculates a Volume-Weighted Balance Price , representing the center of gravity for participation over a selected range.
Price dispersion around this balance point is measured using volume-weighted standard deviation .
The area within ±1 standard deviation forms the Acceptance Zone , where the majority of activity is concentrated.
Prices beyond this zone are treated as outliers , where participation thins and market reactions become more likely.
These zones do NOT represent guaranteed probabilities — they describe participation density and behavioral extremes.
🔵 STANDARD DEVIATION, BELL CURVE & OUTLIERS
At the core of this indicator lies the concept of standard deviation , which describes how price activity clusters around a central value.
When activity is observed over time, it tends to form a distribution where:
Most activity concentrates near a central balance level.
Fewer observations occur as price moves further away from that balance.
This behavior can be visualized conceptually as a bell-shaped distribution — a practical way to describe market participation density.
Prices that move beyond the Acceptance Zone deviate meaningfully from the balance of participation.
These areas are treated as outliers , where price is statistically stretched relative to recent market behavior.
Outliers do not imply immediate reversals — they signal that price is operating in a low-acceptance environment.
Market responses in these zones often include rejection, consolidation, or strong continuation if acceptance builds.
🔵 NEW: INTEGRATED FREQUENCY PROFILE
While the zones are calculated using volume-weighted math, the visual profile has been updated to a Frequency-Based Distribution . This transition allows you to see "Time at Price" rather than just raw volume.
Frequency Distribution: The profile counts the number of bars (occurrences) spent at each price bin. This highlights levels of high interest where the market finds it easy to trade, effectively acting as a Time-Price Opportunity (TPO) proxy.
Time-Based Sentiment: Each bin is split into Bull/Bear frequency. This shows which side was in control during the time spent at that specific level, identifying where buyers or sellers were more persistent.
Filtering Noise: By using frequency instead of raw volume, the profile avoids being skewed by single high-volume spikes, focusing instead on where the market established a sustained presence.
🔵 FEATURES
Acceptance Zone (±1σ)
Highlights the primary balance area where price is most actively accepted and rotational behavior is common.
Extreme Zones (±2σ)
Marks statistically stretched prices where acceptance weakens and reactions or trend continuation may occur.
Volume-Weighted Balance Line
Acts as a structural fair-value reference similar to an anchored VWAP.
Outlier Detection
Price closing beyond the acceptance zone is flagged as an outlier, helping identify exhaustion or breakout conditions.
Distribution Labels
Displays how price activity is distributed between acceptance and extreme zones, reinforcing the concept visually.
Flexible Anchoring
Calculations can be based on a fixed lookback or the visible chart range.
🔵 HOW TO USE
Treat the Acceptance Zone as a balance area where price is fairly valued and mean-reversion is common.
Observe how price behaves in Extreme Zones — rejection may signal reversion, while sustained acceptance may indicate trend continuation.
Frequency Nodes: Use the Frequency Profile to identify where the market is "stalling." High frequency nodes often act as magnets for price, while low frequency gaps (low time spent) often lead to fast price movement.
Use outlier signals in combination with trend bias, liquidity levels, or momentum tools.
🔵 CONCLUSION
Volume Acceptance Zones reframes market analysis around participation density. By distinguishing accepted price behavior from statistical outliers and providing a frequency-based view of time-at-price, the indicator helps traders understand when the market is balanced—and when it is structurally stretched. Indicator
NY AM Opening Range by GRCtrader📊 NY AM Opening Range by GRCtrader
=== OVERVIEW ===
This is a professional-grade opening range analysis tool designed for futures traders focusing on the critical 9:30 AM ET session. It automatically detects and visualizes the New York AM opening range, center encroachment levels, and standard deviation extensions—key support/resistance structures used in ICT/SMC trading methodology.
=== KEY FEATURES ===
✓ Automatic 9:30 AM ET Detection
- Auto-detects opening range bars across all US futures markets
- COMEX (Gold, Silver, etc.) auto-detection with proper timezone handling
- Customizable timezone offset for CT, PT, and other regional traders
✓ Opening Range Framework
- High/Low lines from 9:30 AM session
- Center Encroachment (C.E.) midpoint for directional bias
- Multiple historical sessions (configurable 1-20 sessions)
- Clean, professional styling with customizable colors
✓ Standard Deviation Bands
- 8 preset standard deviation multiples: 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 4.5
- Based on opening range size—scales automatically with volatility
- Dotted/dashed styling for clear visual separation
- Optional labels for quick reference trading
✓ Multi-Session Tracking
- View up to 20 historical opening ranges simultaneously
- Track mean reversion, range expansion, and structural shifts
- Identify trend bias and liquidity zones across sessions
=== USE CASES ===
• Range traders: Fade OR breaks and trade C.E. bounces
• Breakout hunters: Identify STDV targets beyond the range
• Macro traders: Monitor shift in opening range as volatility/bias indicator
• Day traders: Quick reference for high-probability rejection zones
• Market structure analysis: Understand intraday liquidity distribution
=== SETTINGS ===
• Futures Timezone Offset: Align charts to ET (default -1 for CT)
• Number of Opening Ranges: Display 1-20 historical sessions
• OR Line Width & Color: Customize high/low visualization
• C.E. Line Width & Color: Customize center encroachment display
• STDV Settings: Toggle, color, width, style (solid/dotted/dashed)
• Label Options: Size and visibility toggle for clean chart layout
=== TECHNICAL DETAILS ===
Built on Pine Script v6 with:
- Efficient 30-minute bar analysis
- Zero lag structure detection
- Dynamic line/label management (500 lines, 500 labels max)
- Full customization via Settings panel
=== OPEN SOURCE ===
This indicator is published as an open-source tool. Feel free to:
- Fork, modify, and redistribute for personal use
- Build derivatives and extended tools
- Share improvements with the community
- Use commercially with attribution
MPL 2.0 License: mozilla.org
=== DISCLAIMER ===
This tool is for analysis and education purposes. Past performance does not guarantee future results. Always use proper risk management, position sizing, and confirm signals with your trading strategy. No financial advice is implied. Indicator
Adaptive Linear Regression Structure [MarkitTick]💡 This indicator, is a sophisticated analytical tool designed to bridge the gap between classical statistical modeling and modern price action theory. By leveraging high-performance Ordinary Least Squares (OLS) calculations, it dynamically identifies the most statistically significant market structures—specifically linear regression channels—based on historical pivot points. Unlike static channels that rely on arbitrary lookback periods, this script scans a historical "horizon" of structural pivots to find the model with the highest mathematical "fit," providing traders with a non-repainting, objective view of trend exhaustion and volatility boundaries.
✨ Originality and Utility
● Dynamic Model Selection
Most linear regression indicators require the user to manually define a start and end point, or they use a fixed lookback period. This script is original because it treats the starting point of the regression as a variable. It scans multiple historical pivots (Highs and Lows) and performs a competitive analysis between different potential channels. The channel that is eventually displayed is the one that achieves the highest performance score, calculated via a combination of the Coefficient of Determination ($R^2$) and the natural log of the duration. This ensures the channel is both mathematically reliable and structurally relevant.
● Market Structure Integration
The utility of the indicator is enhanced by its "Market Structure Registry." Instead of calculating regressions on every single bar blindly, the script identifies "Pivot Highs" and "Pivot Lows" to use as anchors. This aligns the statistical modeling with the way professional traders view the market, focusing on major turning points rather than noise.
● Institutional-Grade Telemetry
The inclusion of a real-time HUD (Heads-Up Display) dashboard provides traders with immediate transparency into the model's health. By displaying the $R^2$ value and Z-Score, the indicator moves beyond simple "lines on a chart" and offers a quantitative assessment of how well the current price action respects the established trend.
🔬 Methodology and Concepts
● The OLS Kernel
At the heart of the script is a custom-built OLS (Ordinary Least Squares) method. It calculates the slope ($\beta$) and the intercept ($\alpha$) of the best-fit line through the closing prices of the selected period. The mathematical goal is to minimize the sum of the squared errors ( LSE:SSE $), ensuring the median line represents the "true" equilibrium of price over that duration.
● Heuristic Performance Scoring
The indicator does not just look for the highest correlation. It uses a "Performance Score" heuristic:
Score = $R^2$ * ln(Duration)
This formula rewards models that maintain a high degree of linearity over longer periods. A short-term channel with a high $R^2$ might be dismissed in favor of a long-term channel that has a slightly lower $R^2$ but significantly more structural weight.
● Volatility-Adjusted Envelopes
The upper and lower boundaries are not arbitrary. They are calculated based on the standard deviation of the residuals (the distance between actual price and the regression line). By applying a user-defined "Deviation Factor," the script creates volatility bands that expand or contract based on how "noisy" the trend is.
🎨 Visual Guide
● The Regression Channel
• Median Vector: A solid line representing the linear mean of the current trend. It is colored Cyan for bullish slopes and Orange for bearish slopes.
• Volatility Bands: Two solid lines flanking the median. These represent the "Deviation Factor" boundaries (defaulting to 2.0 standard deviations).
• Fill Core: A transparent background fill between the upper and lower bands, allowing for easy visualization of the "fair value" zone. The color dynamically shifts between Cyan and Orange based on the trend bias.
● Signal Labels
• LONG Labels: Cyan labels appearing below price when a "Mean Reversion" setup is detected (price crossing above the lower band).
• SHORT Labels: Orange labels appearing above price when a "Mean Reversion" setup is detected (price crossing below the upper band).
• Details: Labels include the Entry Price (EP), Take Profit (TP) at the median, and a suggested Stop Loss (SL).
● Telemetry Dashboard (HUD)
• Model Quality (R²): A value between 0.0 and 1.0. Values above 0.7 indicate a very strong trend.
• Trend Bias: Explicitly states "BULLISH" or "BEARISH."
• Deviation (Z-Score): Measures how many standard deviations the current price is away from the mean.
• Duration: Displays how many bars the current model covers.
📖 How to Use
● Mean Reversion Strategy
The primary use case is identifying overextended price action. When price moves outside the volatility bands (high Z-Score) and then crosses back inside, it suggests a return to the median "equilibrium" price.
• Bullish Entry: Look for a Cyan "LONG" label when price recovers from the lower band.
• Bearish Entry: Look for an Orange "SHORT" label when price pulls back from the upper band.
● Trend Strength Assessment
Use the $R^2$ value in the dashboard to filter trades. If the $R^2$ is low (e.g., below 0.5), the market is in a "Random Walk" phase, and the regression lines may be less reliable. High $R^2$ values suggest a "Trending" phase where the channel boundaries act as significant support and resistance.
● Dynamic Take Profits
The median line (the Cyan/Orange vector) serves as a dynamic take-profit target. Since the line is based on a linear slope, the price target adjusts every bar to reflect the ongoing trend.
⚙️ Inputs and Settings
● Algorithmic Core
• Scan Horizon: Determines how many historical pivots the script should evaluate. A higher number increases the "search depth" but requires more processing.
• Deviation Factor: Controls the width of the channel. A value of 2.0 covers approximately 95% of price action if the distribution is normal.
• Structural Sensitivity: Controls the lookback for the Pivot High/Low detection. Smaller values find more "local" structures; higher values find "major" structures.
● Signal Processing
• Quality Threshold (R²): This is a "gatekeeper" setting. If no model reaches this minimum quality, the indicator will not display a channel, protecting the user from weak or chaotic patterns.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Statistical Basis (OLS)
The indicator is grounded in the Gauss-Markov theorem. By calculating the slope via the covariance of time and price divided by the variance of time, it provides the "Best Linear Unbiased Estimator" (BLUE) of the current price trajectory.
● Information Theory & Heuristics
The scoring mechanism (using the natural log of N) draws inspiration from Information Criteria (like AIC or BIC). In statistical modeling, increasing the sample size ($N$) usually improves the model's reliability but can introduce "lag." By using the log of duration, the script balances the benefit of a larger sample size against the need for current relevance.
● Standardized Residuals (Z-Scores)
The "Z-Metric" displayed in the dashboard is a calculation of:
$Z = (Price - Estimated Price) / Standard Error$
This standardizes the distance of price from the mean across different assets and timeframes, allowing for a universal interpretation of "overbought" or "oversold" conditions based on the specific volatility of the current trend.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
Indicator
Piv X**Title:** Piv X: Confluence-Based Market Structure & Volume Analyzer
**Introduction**
Piv X is a comprehensive market structure analysis tool designed to grade the quality of Pivot Points using a composite "Confluence Score." Unlike standard indicators that simply identify local highs and lows based on price alone, this script evaluates the *strength* of every pivot by cross-referencing it against volume data, momentum divergences, multi-timeframe structure, and institutional key levels.
**Concept & Methodology**
The core functionality of this script builds upon a **Dynamic Pivot Quality Scoring System**. When a pivot point is detected (using an ATR-based dynamic lookback), the script runs a background analysis on 10+ technical factors to assign a "Confluence Score" (0-100).
The score is calculated based on the accumulation of the following factors:
1. **Volume Anomalies**: Detects volume spikes at the pivot, suggesting institutional participation.
2. **Momentum Divergence**: Checks for RSI and Williams %R divergences relative to price action to identify exhaustion.
3. **Liquidity Mechanics**: Identifies "Swing Failure Patterns" (SFP) and "Sweeps" where price pierces a previous structure but closes back inside.
4. **Multi-Timeframe Alignment**: Verifies if the pivot aligns with Higher Timeframe (HTF) trends and structures to filter out counter-trend noise.
5. **Key Level Interaction**: Rewards pivots that form near Daily/Weekly Highs or Lows.
6. **Fair Value Gap (FVG) Fills**: Detects if the pivot is reacting to a market imbalance fill.
**Unique Feature: Williams %R Divergence Anchored VWAP**
This tool introduces a logic-driven Anchored VWAP. Instead of arbitrarily anchoring VWAPs to high/low dates, the script automatically anchors a VWAP from the exact candle where a Williams %R Momentum Divergence is confirmed. This allows traders to visualize the "true cost basis" of participants who entered specifically on the momentum reversal signal.
**How to Use**
1. **Golden Zones (High Confluence)**: Pivots that achieve a high Confluence Score (e.g., >80) are highlighted with a distinct "Golden" border and background. These represent high-probability Support/Resistance levels backed by multiple forms of technical evidence.
2. **Standard Zones (Normal Confluence)**: Pivots with moderate scores are shown in standard Green/Purple. These are valid structure points but may require additional confirmation before trading.
3. **Trend Filtering**: The "Trend System" overlay (using EMA Clouds and RSI filters) provides visual context for the dominant trend direction, helping traders avoid taking structure signals against the main flow.
4. **Market Structure Shifts (MSS)**: The script automatically plots CHoCH (Change of Character) lines to alert traders when the sequence of Higher Highs or Lower Lows has been broken, often signaling a trend reversal.
**Settings**
* **Pivot Detection**: Adjust the ATR Multiplier to control the sensitivity of pivot detection.
* **Filters**: Toggle specific scoring factors (like Session Logic or HTF Confluence) to customize how strict the Scoring System is.
* **Visuals**: Enable/Disable specific VWAP periods (Weekly, Monthly, Yearly) to keep the chart clean.
**Disclaimer**
This tool is intended for market analysis and educational purposes only. Past performance of these setups does not guarantee future results.
Indicator
Tactical DeviationThis indicator is a mean-reversion system grounded in statistical deviation from the Volume Weighted Average Price (VWAP). Unlike standard Bollinger Bands or static envelopes, the "Tactical Deviation" script integrates Multi-Timeframe Analysis, Dynamic Volatility Scaling, and Market Structure Validation to identify high-probability exhaustion points.
Underlying Concepts & Methodology
The core philosophy of this script is that price tends to revert to its volume-weighted mean after reaching statistical extremes. However, identifying true extremes requires more than just standard deviation. This script employs a three-layer validation filter:
Multi-Timeframe Confluence: The script calculates VWAP and Standard Deviation bands simultaneously for Daily, Weekly, and Monthly timeframes. It allows traders to visualize where short-term price action deviates significantly from longer-term volume trends. A key feature is the "Confluence Mode," which filters out noise by only flagging opportunities where price is overextended on multiple timeframes (e.g., Daily AND Weekly) simultaneously.
Dynamic Volatility Adjustment (Originality): Standard deviation bands are often too static. This script includes a "Dynamic Multiplier" algorithm that ingests Average True Range (ATR) data to adjust the band width.
Logic: Multiplier_Adjusted = Base_Multiplier * (1 + (ATR / Price * 10))
This ensures that during high-volatility events, the bands expand to prevent premature signals, while finding tighter entries during consolidation.
Structural & Volume Validation: Many mean-reversion indicators fail by "catching a falling knife." To mitigate this, this script does not signal solely on band touches. It requires two additional confirmations:
Pivot Confluence: The price must be interacting with a recent Swing Low (for longs) or Swing High (for shorts) specifically calculated within a user-defined lookback period.
Volume Injection: A signal is only valid if volume exceeds its moving average by a defined factor (default 1.5x) or shows significant momentum, confirming institutional participation at the reversal point.
Features & Settings
Deviation Clouds: Visualizes the 1σ-3σ zones with customizable transparency to highlight areas of statistical significance without cluttering the chart.
Signal Filter:
RSI Filter: Optional integration to ensure momentum is also overbought/oversold alongside price deviation.
Pivot Lookback: Adjusts the sensitivity of the market structure detection.
Info Panel: A dashboard displaying the current deviation (in Sigma) for all three monitored timeframes in real-time.
How to Use
This tool is designed for mean reversion trading.
Identify Extremes: Watch for price entering the outer deviation clouds (2σ or 3σ) on the Daily or Weekly VWAP.
Wait for Confirmation: Do not enter blindly on a band touch. Wait for the signal triangle, which confirms that Volume, RSI (if enabled), and Pivot Structure have aligned to suggest a probable reversal.
Risk Management: Use the VWAP itself (the center line) as a dynamic take-profit target, as price statistically gravitates back to this volume-weighted center. Indicator
Std Dev Channel [fmb]What it is
A professional regression channel that combines standard deviation divisions, an extreme price envelope, and a trend quality gauge. It is designed for fast read-and-act decisions on any timeframe, with sensible presets and log-space math for instruments that trend exponentially.
Why it’s different
Most channels draw fixed ±1σ and ±2σ around a regression line. This tool adds:
- Fibonacci-spaced σ divisions for precise scaling
- An objective MaxEnvelope of actual extremes with optional 1.272 and 1.618 extensions
- Pearson’s R labelling that classifies the trend as Strong Up, Moderate, Weak, or Strong Down
- A log-space option so channels behave correctly on long trends and high beta charts
How it works
Base line
- Linear regression of the last Length bars, drawn as a ray.
- Optional colour change by regime using Pearson’s R.
Divisions (StdDev or MaxEnvelope)
- StdDev basis: σ of residuals around the regression line.
- MaxEnvelope basis: distances from the base line to the farthest highs and lows in the lookback.
- Divisions can be Fibonacci multiples (0.382, 0.618, 1.000, 1.272 by default) or uniform steps.
Outer rails
- ENV 1.0 touches the farthest highs and lows within the window.
- Optional extensions at 1.272 and 1.618 highlight stretch and breakout zones.
Trend quality (Pearson’s R)
- R is computed on the same series and window.
- Default thresholds: Strong when |R| ≥ 0.70, Weak when |R| < 0.40.
- The label reads: R 0.XXX • Class, plotted near the most recent base value.
Log-space math
- When enabled, the model runs on ln(price) and converts the outputs back to price.
- Safer on multi-year charts and large percentage trends.
Presets
- Swing: Length 125, StdDev basis, Fib divisions, ENV 1.0 and 1.272 on
- Intraday: Length 240, StdDev basis, simple ±1 and ±2 style divisions, ENV off by default
- Position: Length 200, StdDev basis, compact Fib set for higher timeframes
You can turn preset overrides off to make every input respond instantly.
Inputs you will actually use
- Length, Source, Log-space ON or OFF
- Basis: StdDev or MaxEnvelope
- Divisions: Fib list or Step and Max multiple
- Outer rails: show ENV 1.0, show 1.272, show 1.618
- Labels and sizes, extend left or right
- Hide divisions or outer rails automatically when the regime is Weak
Alerts included
- Close crosses above or below ENV 1.0
- Close crosses above or below ENV 1.272 and 1.618 (if enabled)
Practical playbook
Trend following
- In Strong Uptrend: buy pullbacks near 0.382 to 0.618 above the base with stops just beyond the next lower division.
- In Strong Downtrend: sell bounces into 0.382 to 0.618 below the base with stops just beyond the next upper division.
Mean reversion
- When R is Moderate or Weak, fade moves that tag ENV 1.0 back toward the base.
- If price closes through an ENV extension, treat it as potential regime change and stand down on fades.
Breakouts
- A close through ENV 1.0 with R rising toward Strong often precedes trend acceleration.
- Use the next division or the 1.272 rail as the first target and trail on the base.
Tips
- Keep Length stable across symbols you compare. Consistency beats curve fitting.
- Use log-space on multi-year equities and crypto. Use linear for short intraday work.
- If you want a classic look, disable Fib and rails, set Step 1.0 and Max 2.0.
Notes
- The tool draws more lines when Fib divisions are active. If it feels busy, show divisions only and hide labels, or keep ENV 1.0 plus one extension.
- Pearson’s R is descriptive, not predictive. Combine with price structure and volume for entries. Indicator
Deviation Momentum For Loop | Lyro RSThe Deviation Momentum For Loop is a directional momentum tool that evaluates the persistence of price deviation from a moving average over a historical range using a custom loop-based scoring function. It quantifies relative momentum strength by comparing current deviation to previous values, assigning a net score used to assess trend bias, reversals, and volatility-adjusted strength.
Key Features
Deviation-Based Momentum: Calculates standardized deviation from a selected moving average by subtracting the MA from price and normalizing via standard deviation and a scaling constant. This standardization adjusts for volatility and creates a consistent scoring base across assets and timeframes.
Historical For-Loop Scoring: Implements a user-defined for-loop function that compares current deviation to values from earlier bars (configurable range). Each comparison adds or subtracts from a cumulative score based on whether current deviation exceeds historical ones, producing a dynamic momentum read.
Threshold-Based Signal Logic: Applies user-defined thresholds for long and short signals. If the loop score exceeds the long threshold, a bullish bias is inferred; if it drops below the short threshold, a bearish bias is indicated. These thresholds are plotted for visual clarity.
Multi-Palette Visual System:
Predefined Palettes – Choose from Classic, Mystic, Accented, or Royal schemes for bullish and bearish colors.
Custom Colors – Toggle on custom color selection to manually define bullish (UpC) and bearish (DnC) tones.
Dynamic Visuals – Oscillator line, threshold markers, background shading, bar and candle coloring are applied in real time based on trend state
.
Glow and Overlay Effects: Layered glow lines and optional bar/candle coloring reinforce signal strength and trend status directly on the chart.
Built-In Alerts: Provides alert conditions when the for-loop score crosses above or below the defined thresholds, enabling automated monitoring of trend conditions.
How It Works
MA Calculation – Applies the selected moving average to the chosen price source (e.g., close, open, high). Offers 16 moving average types including SMA, EMA, WMA, TEMA, JMA, FRAMA, ZLSMA, KAMA, and others via the LyroRS/LMAs/1 library.
Deviation Computation – Measures the deviation of price from its moving average, normalized by standard deviation and scaled by a fixed constant factor to account for volatility.
Loop Function – Iterates from user-defined indices (From → To) and compares current deviation to past deviations. Increments score for each instance where current > past, decrements when current < past. The resulting value is plotted as the primary oscillator.
Signal Logic – Long and short threshold values are configurable inputs. Crossing above the long threshold signals bullish bias; crossing below the short threshold signals bearish pressure.
Color Coding & Visual Feedback
Palette or custom colors reflect oscillator's directional state.
Additional glow lines increase signal emphasis.
Background shading highlights crossovers with mid-threshold for enhanced visibility.
Optional bar and candle coloring aligns price visualization with indicator signals.
Practical Use
Momentum Confirmation – Use a score rising above the long threshold as a potential bullish signal; falling below the short threshold may indicate bearish strength.
Volatility Normalization – Standardized deviation ensures consistency across assets of different volatility profiles.
Multi-Timeframe Adaptation – The wide selection of moving averages and loop depth settings allows calibration for scalping, swing, or long-term analysis.
Visual Clarity – Color-coordinated candles, bars, oscillator lines, and background simplify interpretation of signal context and trend structure.
Customization
Select from 16 moving average types to control sensitivity and smoothing.
Adjust loop depth (From/To) to define how far back deviation is compared.
Set custom threshold levels to reflect your preferred sensitivity to momentum shifts.
Customize visuals with predefined palettes or manual color settings for full chart integration.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals. Indicator
LogTrend Retest EngineLogTrend Retest Engine (LTRE)
LogTrend Retest Engine (LTRE) is an advanced trend-continuation overlay designed to identify high-probability breakout retests using logarithmic regression , volatility-adjusted deviation bands , and market regime filtering .
Unlike traditional channels or moving averages, LTRE models price behavior in log space , allowing it to adapt naturally to exponential market moves common in crypto, indices, and long-term trends.
🔹 How It Works
Logarithmic Regression Core
Performs linear regression on log-transformed price and time
Produces a structurally accurate trend midline that scales with price growth
Volatility-Adjusted Deviation Bands
Dynamic upper and lower zones based on statistical deviation
ATR weighting expands or contracts bands as volatility changes
Adaptive Lookback (Optional)
Automatically adjusts regression length using volatility pressure
Faster response in high-volatility environments, smoother in consolidation
🔹 Market Regime Detection
LTRE actively filters conditions using:
R² trend strength (trend quality, not just slope)
Volatility compression vs expansion
User-defined minimum trend strength threshold
Signals are disabled during ranging or low-quality conditions .
🔹 Breakout → Retest Signal Logic
LTRE does not chase breakouts.
Signals trigger only when:
1. Price breaks cleanly outside the deviation band
2. Market regime is confirmed as trending
3. Price performs a controlled retest within a user-defined tolerance
BUY
Break above upper band → retest → trend confirmed
SELL
Break below lower band → retest → trend confirmed
This structure is designed to reduce false breakouts and late entries.
🔹 Visual & Projection Tools
Clean midline and deviation bands
Optional filled zones
Optional future trend projection for forward structure planning
On-chart statistics for trend strength and volatility compression
🔹 Best Use Cases
Trend continuation & pullback strategies
Crypto, Forex, Indices, and equities
Works best on 15m and higher timeframes
⚠️ Disclaimer
LTRE is a decision-support tool , not a complete trading system. Always use proper risk management and confirm signals with additional structure, volume, or higher-timeframe context.
Built for traders who wait for structure — not noise.
Indicator
Indicator
Range Deviations PRO | Trade SymmetryRange Deviations PRO — Extended Session Levels
An enhanced version of the original Range Deviations by @joshuuu, retaining the full core logic while adding a key upgrade:
🔹 All session ranges, midlines, and deviation levels now extend into the next trading session, giving seamless multi-session context.
Supports Asia, CBDR, Flout, ONS, and Custom Sessions — with options for half/full standard deviations, equilibrium, and range boxes exactly as in the original.
Extending these levels helps identify:
• Liquidity sweeps
• Trap moves / false breaks
• Daily high/low projections
• Premium–discount behavior across sessions
Ideal for traders using ICT concepts who want clearer continuation of session structure into the next day.
Credit: Original logic by @joshuuu — enhancements by TradeSymmetry.
Disclaimer: Educational use only. Not financial advice. Indicator
LibBrStLibrary "LibBrSt"
This is a library for quantitative analysis, designed to estimate
the statistical properties of price movements *within* a single
OHLC bar, without requiring access to tick data. It provides a
suite of estimators based on various statistical and econometric
models, allowing for analysis of intra-bar volatility and
price distribution.
Key Capabilities:
1. **Price Distribution Models (`PriceEst`):** Provides a selection
of estimators that model intra-bar price action as a probability
distribution over the range. This allows for the
calculation of the intra-bar mean (`priceMean`) and standard
deviation (`priceStdDev`) in absolute price units. Models include:
- **Symmetric Models:** `uniform`, `triangular`, `arcsine`,
`betaSym`, and `t4Sym` (Student-t with fat tails).
- **Skewed Models:** `betaSkew` and `t4Skew`, which adjust
their shape based on the Open/Close position.
- **Model Assumptions:** The skewed models rely on specific
internal constants. `betaSkew` uses a fixed concentration
parameter (`BETA_SKEW_CONCENTRATION = 4.0`), and `t4Sym`/`t4Skew`
use a heuristic scaling factor (`T4_SHAPE_FACTOR`)
to map the distribution.
2. **Econometric Log-Return Estimators (`LogEst`):** Includes a set of
econometric estimators for calculating the volatility (`logStdDev`)
and drift (`logMean`) of logarithmic returns within a single bar.
These are unit-less measures. Models include:
- **Parkinson (1980):** A High-Low range estimator.
- **Garman-Klass (1980):** An OHLC-based estimator.
- **Rogers-Satchell (1991):** An OHLC estimator that accounts
for non-zero drift.
3. **Distribution Analysis (PDF/CDF):** Provides functions to work
with the Probability Density Function (`pricePdf`) and
Cumulative Distribution Function (`priceCdf`) of the
chosen price model.
- **Note on `priceCdf`:** This function uses analytical (exact)
calculations for the `uniform`, `triangular`, and `arcsine`
models. For all other models (e.g., `betaSkew`, `t4Skew`),
it uses **numerical integration (Simpson's rule)** as
an approximation of the cumulative probability.
4. **Mathematical Functions:** The library's Beta distribution
models (`betaSym`, `betaSkew`) are supported by an internal
implementation of the natural log-gamma function, which is
based on the Lanczos approximation.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
priceStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) *in price units* for the current
bar, according to the chosen `PriceEst` distribution assumption.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ ≥ 0 ; `na` if undefined (e.g. zero range).
priceMean(estimator, offset)
Estimates **μ̂** (mean price) for the chosen `PriceEst` within the
current bar.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ in price units.
pricePdf(estimator, price, offset)
Probability-density under the chosen `PriceEst` model.
**Returns 0** when `p` is outside the current bar’s .
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
price (float) : series float Price level to evaluate.
offset (int) : series int To offset the calculated bar
Returns: series float Density value.
priceCdf(estimator, upper, lower, steps, offset)
Cumulative probability **between** `upper` and `lower` under
the chosen `PriceEst` model. Outside-bar regions contribute zero.
Uses a fast, analytical calculation for Uniform, Triangular, and
Arcsine distributions, and defaults to numerical integration
(Simpson's rule) for more complex models.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
upper (float) : series float Upper Integration Boundary.
lower (float) : series float Lower Integration Boundary.
steps (int) : series int # of sub-intervals for numerical integration (if used).
offset (int) : series int To offset the calculated bar.
Returns: series float Probability mass ∈ .
logStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) of *log-returns* for the current bar.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ (unit-less); `na` if undefined.
logMean(estimator, offset)
Estimates μ̂ (mean log-return / drift) for the chosen `LogEst`.
The returned value is consistent with the assumptions of the
selected volatility estimator.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ (unit-less log-return). Library
Angle Market Structure [BigBeluga]🔵 OVERVIEW
Angle Market Structure is a smart pivot-based tool that dynamically adapts to price action by accelerating breakout and breakdown detection. It draws market structure levels based on pivot highs/lows and gradually adjusts those levels closer to price using an angle threshold. Upon breakout, the indicator projects deviation zones with labeled levels (+1, +2, +3 or −1, −2, −3) to track price extension beyond structure.
🔵 CONCEPTS
Adaptive Market Structure: Uses pivots to define structure levels, which dynamically angle closer to price over time to capture breakouts sooner.
Breakout Acceleration: Pivot high levels decrease and pivot low levels increase each bar using a user-defined angle (based on ATR), improving reactivity.
Deviation Zones: Once a breakout or breakdown occurs, 3 deviation levels are projected to show how far price extends beyond the breakout point.
Count Labels: Each successful structure break is numbered sequentially, giving traders insight into momentum and trend persistence.
Visual Clarity: The script uses colored pivot points, trend lines, and extension labels for easy structural interpretation.
🔵 FEATURES
Calculates pivot highs and lows using a customizable length.
Applies an angle modifier (ATR-based) to gradually pull levels closer to price.
Plots breakout and breakdown lines in distinct colors with automatic extension.
Shows deviation zones (+1, +2, +3 or −1, −2, −3) after breakout with customizable size.
Color-coded labels for trend break count (bullish or bearish).
Dynamic label sizing and theme-aware colors.
Smart label positioning to avoid chart clutter.
Built-in limit for deviation zones to maintain clarity and performance.
🔵 HOW TO USE
Use pivot-based market structure to identify breakout and breakdown zones.
Watch for crossover (up) or crossunder (down) events as trend continuation or reversal signals.
Observe +1/+2/+3 or -1/-2/-3 levels for overextension opportunities or trailing stop ideas.
Use breakout count as a proxy for trend strength—multiple counts suggest momentum.
Combine with volume or order flow tools for higher confidence entries at breakout points.
Adjust the angle setting to fine-tune sensitivity based on market volatility.
🔵 CONCLUSION
Angle Market Structure enhances traditional pivot-based analysis by introducing breakout acceleration and structured deviation tracking. It’s a powerful tool for traders seeking a cleaner, faster read on market structure and momentum strength—especially during impulsive price moves or structural transitions. Indicator
Indicator
Dynamic Gap Probability ToolDynamic Gap Probability Tool measures the percentage gap between price and a chosen moving average, then analyzes your chart history to estimate the likelihood of the next candle moving up or down. It dynamically adjusts its sample size to ensure statistical robustness while focusing on the exact deviation level.
Originality and Value:
• Combines gap-based analysis with dynamic sample aggregation to balance precision and reliability.
• Automatically extends the sample when exact matches are scarce, avoiding misleading signals on rare extreme moves.
• Provides real “next-candle” probabilities based on historical occurrences rather than fixed thresholds or untested heuristics.
• Adds value by giving traders an evidence-based edge: you see how similar past deviations actually played out.
How It Works:
1. Calculate gap = (close – moving average) / moving average * 100.
2. Round the absolute gap to nearest percent (X%).
3. Count historical bars where gap ≥ X% above or ≤ –X% below.
4. If exact X% count is below the minimum occurrences threshold, include gaps at X+1%, X+2%, etc., until threshold is reached.
5. Compute “next-candle” green vs. red probabilities from the aggregated sample.
6. Display current gap, sample size, green probability, and red probability in a table.
Inputs:
• Moving Average Type (SMA, EMA, WMA, VWMA, HMA, SMMA, TMA)
• Moving Average Period (default 200)
• Minimum Occurrences Threshold (default 50)
• Table position and styling options
Examples:
• If price is 3% above the 200-period SMA and 120 occurrences ≥3% are found, with 84 green next candles (70%) and 36 red (30%), the script displays “3% | 120 | 70% green | 30% red.”
• If price is 8% below the SMA but only 20 exact matches exist, the script will include 9% and 10% gaps until it reaches 50 samples, then calculate probabilities from that broader set.
Why It’s Useful:
• Mean-reversion traders see green-probability signals at extreme overbought or oversold levels.
• Trend-followers identify continuation likelihood when red probability is high.
• Risk managers gauge reliability by inspecting sample size before acting on any signal.
Limitations:
• Historical probabilities do not guarantee future performance.
• Results depend on timeframe and symbol, backtest with your data before trading.
• Use realistic slippage and commission when overlaying on strategy scripts. Indicator
Indicator
Indicator
Head Hunter HHHead Hunter HH - Advanced Market Structure & Volume Analysis Indicator
This indicator combines volume analysis, price action, and VWAP to identify high-probability trading opportunities across multiple timeframes.
Key Features:
• Smart Volume Analysis: Detects institutional volume patterns using dynamic thresholds
• VWAP-Based Market Structure: Multiple standard deviation bands for precision entry/exit
• Daily Level Integration: Previous day's high, low, close, and current day's open
• Advanced Signal Classification: Regular, Super Strong, and Scalp signals
Signal Types:
1. Regular Signals (White/Purple Triangles)
• Volume-confirmed reversals
• Institutional price levels
• Technical momentum alignment
2. Super Strong Signals (Green/Red Diamonds)
• High-volume breakouts
• Strong momentum confirmation
• Multiple timeframe alignment
3. Scalp Signals (Green/Magenta Circles)
• Quick reversal opportunities
• VWAP deviation analysis
• Volume surge confirmation
Visual Components:
• VWAP with Standard Deviation Bands
• 50 MA (optional)
• Daily Reference Levels
• Color-coded signals based on strength
• Bar color changes on confirmed signals
Best Practices:
• Most effective on higher timeframes (1H+)
• Use with major pairs/instruments
• Combine signals with support/resistance
• Monitor volume confirmation
• Wait for candle close confirmation
This indicator helps identify institutional order flow and high-probability reversal zones by analyzing volume patterns, price action, and market structure, providing traders with multiple confirmation layers before entry.
Note: Results may vary based on market conditions and timeframe selection. Always use proper risk management. Indicator
Indicator
ZVOL — Z-Score Volume Heatmapⓩ ZVOL transforms raw volume into a statistically calibrated heatmap using Z-score thresholds. Unlike classic volume indicators that rely on fixed MA comparisons, ZVOL calculates how many standard deviations each volume bar deviates from its mean. This makes the reading adaptive across timeframes and assets, in order to distinguish meaningful crowd behavior from random volatility.
📊 The core display is a five-zone histogram, each encoded by color and statistical depth. Optional background shading mirrors these zones across the entire pane, revealing subtle compression or structural rhythm shifts across time. By grounding the volume reading in volatility-adjusted context, ZVOL inhibits impulsive trading tactics by compelling the structure, not the sentiment, to dictate the signal.
🥵 Heatmap Coloration:
🌚 Suppressed volume — congestion, coiling phases
🩱 Stable flow — early trend or resting volume
🏀 High activity — emerging pressure
💔 Extreme — possible climax or institutional print
🎗️ A dynamic Fibonacci-based 21:34-period EMA ribbon overlays the histogram. The fill area inverts color on crossover, providing a real-time read on tempo, expansion, or divergence between price structure and crowd effort.
💡 LTF Usage Suggestions:
• Confirm breakout legs when orange or red zones align with range exits
• Fade overextended moves when red bars appear into resistance
• Watch for rising EMAs and orange volume to front-run impulsive moves
• Combine with volatility suppression (e.g. ATR) to catch compression → expansion transitions
🥂 Ideal Pairings:
• OBVX Conviction Bias — to confirm directional intent behind volume shifts
• SUPeR TReND 2.718 — for directional filters
• ATR Turbulence Ribbon — to detect compression phases
👥 The OBVX Conviction Bias adds a second dimension to ZVOL by revealing whether crowd effort is aligning with price direction or diverging beneath the surface. While ZVOL identifies statistical anomalies in raw volume, OBVX tracks directional commitment using cumulative volume and moving average cross logic. Use them together to spot fake-outs, anticipate structure-confirmed breakouts, or time pullbacks with volume-based conviction.
🔬 ZVOL isn’t just a volume filter — it’s a structural lens. It reveals when crowd effort is meaningful, when it's fading, and when something is about to shift. Designed for structure-aware traders who care about context, not noise. Indicator
