Breaker Block Identifier [algo_aakash]Breaker Block Identifier is a market structure indicator that converts failed order block retests into scored, non-repainting breaker zones. Rather than flagging every order block that gets invalidated, the script requires a complete sequence of confirmed price events — order block formation, an opposing structure break, a retracement into the invalidated zone, and a failed retest of that zone — before a breaker is created, and then ranks the result with a transparent quality score.
Problem Statement
Order blocks are frequently invalidated by a structure break and later retested, but a retest failing to continue in the original direction is not automatically a tradable breaker block. Many public scripts draw a zone as soon as an order block is broken, without verifying that the subsequent retest actually failed, how deep that retest penetrated, or how convincingly price rejected the zone. This produces a high volume of low-quality zones that require manual filtering by the trader.
This indicator addresses that gap by treating breaker formation as a multi-stage state machine rather than a single condition, and by scoring every candidate that completes the sequence so weak retests can be filtered out programmatically instead of visually.
Methodology
Swing highs and lows are identified with ta.pivothigh/ta.pivotlow using a user-defined bar count on each side, so every structural level referenced by the script is a confirmed pivot, never a forming one.
An order block source candle is located as the last opposite-colored candle at or immediately before each confirmed swing pivot, within a fixed lookback. The candle must exceed a minimum size expressed as a multiple of ATR, and can optionally be required to close on above-average volume. Zone boundaries can be set to the candle body (open/close) or the full wick range (high/low).
Every order block candidate then moves through three internal states. In the Pending state the script waits for an opposing structure break (a close beyond the relevant swing high or low, optionally required to clear the level by a minimum ATR multiple). Once that break occurs the candidate becomes Flipped, and the script waits for price to retrace back into the now-invalidated zone. On entry into the zone the candidate becomes Retesting, and the script tracks the deepest penetration price reaches inside the zone on a bar-by-bar basis.
A Retesting candidate resolves in one of two ways. If price closes back through the zone in its original direction by the confirmation displacement threshold, the retest is judged to have held and the candidate is discarded with no breaker created. If price instead closes through the opposite edge of the zone by the same displacement threshold, and the tracked penetration depth met a minimum percentage of the zone's height (the Retest Qualification Filter), the retest is judged to have failed and the order block is converted into a breaker in the opposite direction of its original bias.
Each confirmed breaker is then scored from 0 to 100 using six independent, user-weighted factors: the displacement strength of the invalidating structure break, the ATR-relative size of the original order block candle, how closely the retest penetration matched a user-defined ideal depth (scored on a curve, so both shallow touches and near-total breaches score lower than a clean mid-zone tag), the wick-rejection ratio of the confirming candle, how quickly the retest resolved relative to the retest window, and the ATR-normalized distance price traveled before returning to retest. The six sub-scores are combined using auto-normalized weights, so a breaker only appears on the chart, gets drawn, and triggers alerts if it clears the configured minimum quality threshold.
Confirmed breakers remain in an Active/Touched state until price closes through the far edge of the zone by the invalidation displacement threshold, at which point the zone is marked invalidated, visually dimmed, and removed after a configurable linger period. A hard maximum-age limit and a per-direction cap on active zone count prevent unbounded object growth.
Signal Workflow
Step 1 — a confirmed swing pivot forms and an order block candidate is registered from the qualifying source candle behind it.
Step 2 — the candidate waits in a Pending state until an opposing structure break (BOS/CHoCH) closes beyond the originating swing level.
Step 3 — once flipped, the candidate waits for price to re-enter the invalidated zone, entering the Retesting state and tracking maximum penetration depth.
Step 4 — the retest resolves: a displacement close back through the zone in the original direction discards the candidate, while a displacement close through the opposite edge with sufficient penetration confirms a breaker.
Step 5 — the confirmed breaker is scored across six weighted factors and only drawn, labeled, and alerted on if it meets the minimum quality threshold.
Step 6 — the active breaker zone extends forward until price closes through its far edge by the invalidation displacement threshold, at which point it dims and is scheduled for removal.
Why This Indicator Is Different
Most public order block or breaker scripts draw a zone the moment an order block is invalidated by a structure break, without separately validating whether the ensuing retest actually failed.
This script models breaker formation as an explicit four-state pipeline (source candle, pending, flipped, retesting) and only creates a zone after the retest resolves against its original direction with a minimum measured penetration depth.
The Breaker Quality Score converts six independently disclosed factors, including retest penetration depth scored on a curve around a configurable ideal value rather than a simple threshold, into a single adjustable ranking rather than a cosmetic label.
Quality-score weighting is fully exposed, allowing the ranking to be tuned toward structure strength, retest precision, wick rejection, confirmation speed, or impulse distance depending on the trader's approach.
Zone fill transparency scales with the quality score, so higher-ranked breakers render more opaque and lower-ranked ones fade into the background without adding separate visual elements.
An optional formation preview renders the retest phase of a candidate before it resolves, giving visibility into why a breaker did or did not form without permanently cluttering the chart.
Inputs
Structure Settings
Swing Pivot Length
Displacement Filter on Structure Break
Structure Break Displacement (x ATR)
ATR Length
Order Block Detection
Use Candle Body for Zone Boundaries
Min Order Block Size (x ATR)
Candidate Expiry (bars)
Volume Confirmation Filter
Volume MA Length
Volume Multiplier Threshold
Breaker Conversion Rules
Retest Window (bars)
Confirmation Displacement (x ATR)
Min Retest Penetration (%)
Quality Score
Filter Breakers by Quality Score
Minimum Quality Score
Ideal Retest Penetration Ratio
Advanced weight sliders for structure break strength, impulse size, retest precision, wick rejection, confirmation speed, and distance traveled
Visual Settings
Bullish/Bearish Breaker Colors
Min/Max Fill Transparency
Show Zone Midline
Show Quality Label
Label Size
Formation Preview toggle and color
Lifecycle & Cleanup
Max Active Breakers (per side)
Invalidation Displacement (x ATR)
Invalidated Linger (bars)
Max Breaker Age (bars)
Info Panel
Show Info Panel
Panel Position
Alerts
Alerts are available for:
Bullish Breaker Block formed
Bearish Breaker Block formed
Structure confirmation on breaker conversion
Price entering an active breaker zone
Breaker invalidated
Practical Usage
Use the info panel's structure bias reading as directional context before evaluating individual breaker zones.
Treat a fresh, high-quality breaker aligned with the prevailing structure bias as a potential continuation zone rather than a standalone entry signal.
Raise the minimum quality threshold on lower timeframes or noisy instruments to reduce the number of marginal zones drawn.
Use the retest penetration and displacement settings together to control how strict the failed-retest qualification is for your instrument and timeframe.
Combine the alert feed with a broader trade plan, since each alert marks a structural event, not an execution signal.
Limitations
Swing pivots require bars to form on both sides before they confirm, so structure breaks and order block placement are inherently delayed by the swing pivot length.
The order block source candle is located within a fixed lookback behind each pivot; if no qualifying candle exists in that window, no candidate is created for that pivot.
Quality scoring is a relative ranking based on disclosed, adjustable factors and does not predict the outcome of any individual breaker zone.
Volume-based filtering depends on the data provider's reported volume and may behave inconsistently on instruments with limited or unreliable volume data.
As with any structure-based tool, results will vary across instruments, timeframes, and market regimes.
Notes
This indicator is a market structure analysis tool intended to organize and rank breaker block formation through a disclosed, multi-stage validation process.
All structure breaks, state transitions, breaker confirmations, and invalidations are evaluated on confirmed bar closes only, so no element of the script repaints once drawn.
The output is intended to support structural analysis and is not a standalone buy or sell recommendation.
Indicator
Change of Character (CHoCH) Alert System [algo_aakash]Change of Character (CHoCH) Alert System is a market structure signal tool focused on a single event: a confirmed shift in directional bias. Rather than labeling every Break of Structure and CHoCH the way many public structure scripts do, this indicator deliberately ignores continuation breaks and limits both the chart and the alert feed to the moments where the prevailing character of the market actually flips.
Problem Statement
Most public CHoCH implementations classify a character change purely on the direction of a swing break, with no measure of how convincing that break actually was. This creates two practical issues for anyone building alerts around structure. Every minor swing wobble can trigger a notification, producing alert fatigue, and there is no way to separate a decisive character change from one that barely closed beyond the swing level. This script addresses both issues with a close-confirmed CHoCH-only detection engine and a built-in confidence grading step applied to every signal.
Methodology
The script maintains a single structure register holding the most recent confirmed swing high and swing low, located with standard pivot detection over a user-defined pivot length. When the adaptive swing filter is enabled, a newly confirmed pivot only replaces the stored swing if its distance from the last opposite-type pivot exceeds a configurable ATR-relative threshold, which keeps insignificant micro-swings out of the structure register before they can influence a signal.
A Change of Character is only evaluated on a confirmed candle close, so nothing in the detection logic repaints once a signal has printed. A bullish CHoCH requires a close above the last swing high while the tracked bias is bearish or undefined. A bearish CHoCH requires a close below the last swing low while the tracked bias is bullish or undefined. A break that occurs while the bias already agrees with the break direction is treated as ordinary continuation and is not flagged.
Two optional filters gate confirmation further. A displacement filter requires the breaking close to clear the swing level by a minimum ATR multiple, removing marginal breaks. A momentum filter requires the breakout candle's body to represent a minimum percentage of its total range, removing breaks driven mostly by wick with little real conviction behind the close.
Once a CHoCH is confirmed, the broken swing level is projected forward on the chart as an active structure line. If a later confirmed close moves back through that level, the structure is marked invalidated and the projection line is dimmed, separately from the detection of any new CHoCH.
Signal Workflow
Track the most recent confirmed swing high and swing low using pivot detection.
Apply the adaptive swing filter to reject pivots too close to the last opposite-type pivot.
On each confirmed candle close, test for a close beyond the stored swing level against the current bias.
Apply the displacement filter to confirm the close cleared the level by a minimum ATR multiple.
Apply the momentum filter to confirm the breakout candle's body-to-range ratio meets the minimum threshold.
Score the confirmed breakout candle on displacement in ATR units and body-to-range ratio to produce a Weak, Moderate, or Strong confidence grade.
Flip the tracked bias, plot the CHoCH label with its grade, and project the broken level forward as an active structure line.
Continue monitoring the active structure line and mark it invalidated if a later confirmed close moves back through it.
Why This Indicator Is Different
Many structure tools plot every Break of Structure alongside every CHoCH, leaving the trader to filter out which events represent an actual change in character.
This script omits BOS events entirely and reports only confirmed CHoCH signals, which are the events that correspond to a bias flip.
Each confirmed CHoCH is scored using two independent factors measured on the breakout candle itself, its ATR-normalized displacement past the level and its body-to-range ratio, rather than being treated as a single undifferentiated event.
The confidence grade is written into the alert message text at the moment the event fires, which requires composing the message dynamically rather than relying on a fixed template.
The swing level broken by a CHoCH remains tracked after the signal fires, so a later close back through that level produces a distinct invalidation alert rather than silently vanishing into the next structure calculation.
Detection is restricted to confirmed candle closes throughout, so the bias, the grade, and the invalidation state cannot change intrabar once printed.
Inputs
Structure Engine
Swing Pivot Length
Adaptive Swing Filter
Filter Threshold (ATR multiple)
Break Confirmation
Displacement Filter
Displacement Multiplier
Momentum Filter
Minimum Body % of Range
ATR Length
Visual Settings
Show Swing Points
Show Structure Projection
Projection Extension
Show Trend Background Wash
Color Candles After CHoCH
Show Confidence Grade
Label Size
Bullish, Bearish, and Projection colors
Status Panel
Show Status Panel
Panel Position
Alerts
Alert: Bullish CHoCH
Alert: Bearish CHoCH
Alert: Bullish Structure Invalidated
Alert: Bearish Structure Invalidated
Alerts
Alerts are available for:
Bullish CHoCH confirmed on a closed candle, with the confidence grade included in the alert message
Bearish CHoCH confirmed on a closed candle, with the confidence grade included in the alert message
Bullish structure invalidated after a confirmed close back below an active bullish level
Bearish structure invalidated after a confirmed close back above an active bearish level
Practical Usage
Use a shorter pivot length on intraday charts to react to structure earlier, combined with the displacement and momentum filters to avoid marginal breaks.
Use a longer pivot length on higher timeframes to isolate structurally significant character changes only.
Treat a Strong-grade CHoCH as a higher-conviction event than a Weak-grade CHoCH when weighing entry timing or position sizing.
Watch for a structure invalidated alert shortly after a CHoCH, since it indicates price has returned through the level that produced the signal.
Use the status panel as a quick reference for the current bias and the most recent CHoCH grade without needing to scan the chart for labels.
Limitations
Swing highs and lows depend on confirmed pivots, which require the full pivot length of bars to close on both sides before becoming available, introducing a disclosed confirmation lag.
The displacement and momentum filters reduce signal frequency by design, which means fewer but more selective CHoCH events compared to unfiltered structure break detection.
Structure invalidation reflects a return through a previously broken level and does not attempt to forecast subsequent price direction.
This indicator identifies structural events only and does not constitute financial advice or a complete trading system on its own.
Notes
All structural state, including the tracked bias, the active levels, and the confidence grade, is evaluated only on a confirmed candle close, so nothing in this script repaints once printed.
The only lag in the system is the standard pivot confirmation lag inherent to pivot-based swing detection, which is disclosed above rather than hidden.
Designed for dark theme charts. On light themes, consider darkening the projection line color for improved contrast.
Indicator
Indicator
Wyckoff Accumulation Phase Map [AGPro Series]Wyckoff Accumulation Phase Map
🟢 OVERVIEW
Wyckoff Accumulation Phase Map is the bullish counterpart of the Wyckoff Distribution Phase Map and completes the AGPro Wyckoff structural cycle. It is a retrospective structural mapping tool that locates and labels the seven core accumulation events — Preliminary Support (PS), Selling Climax (SC), Automatic Rally (AR), Secondary Test (ST), Spring, Last Point of Support (LPS) and Sign of Strength (SOS) — only after a bullish Change of Character (CHoCH) confirms that the prior downtrend has structurally broken. The indicator frames the active trading range as a shaded zone, plots SC and AR horizontal references, tracks the current phase (A, B, C, D, E) in a dedicated info panel, and introduces three accumulation-specific layers absent from the distribution companion: a Spring Quality Score, a Cause-to-Effect markup projection and a rolling volume footprint classifier.
🟢 COMPANION TO THE DISTRIBUTION PHASE MAP
This indicator is intentionally designed as the symmetric counterpart of Wyckoff Distribution Phase Map . The two scripts share a unified AGPro visual language and a CHoCH-gated reveal philosophy, but they operate on opposite market regimes and different event sets:
- Distribution map works on uptrends and draws PSY, BC, AR, UT, SOW and LPSY after a bearish CHoCH.
- Accumulation map works on downtrends and draws PS, SC, AR, ST, Spring, LPS and SOS after a bullish CHoCH.
- Distribution projects a potential markdown line from LPSY.
- Accumulation projects a Cause-to-Effect markup target from SOS.
- Accumulation additionally provides a 0-100 Spring Quality Score, which has no structural equivalent in the distribution schematic.
Both tools are standalone. Users running the full AGPro Wyckoff workflow can apply them together for complete cycle coverage, but neither depends on the other.
🟢 WHAT MAKES IT DIFFERENT
Most Wyckoff scripts on PulseWire react to every elevated swing low during a downtrend and label PS / SC / Spring on every modest dip. The result is a noisy chart, often with contradictory events stacked on top of each other. This indicator takes the opposite approach. During a qualified downtrend, the chart remains completely clean. Rolling trackers silently maintain candidate values for SC, PS and AR in memory, while a live Watching row in the panel shows what the engine is currently monitoring. Events are only drawn on the chart after a bullish CHoCH locks the schematic, at which point PS, SC and AR appear together as a confirmed retrospective bundle. ST, Spring, LPS and SOS then populate as post-CHoCH structure unfolds. A multi-tier expiry system closes both incomplete and fully-played-out accumulations, ensuring the active schematic on screen always reflects current market structure and not stale history.
🟢 METHODOLOGY
The engine runs in three coordinated layers.
Layer one qualifies a prior downtrend. A valid Wyckoff accumulation precondition requires four concurrent factors: structural lower highs and lower lows, a minimum ATR-multiple depth from the lookback-window high, a duration sustained across the full lookback window, and price currently located in the lower portion of that window. All four conditions must hold before any candidate can form.
Layer two rolls candidate values during that qualified downtrend. SC candidate is the running lowest pivot low with elevated or climactic volume. PS candidate is the prior elevated swing low that predates the SC. AR candidate is the highest post-SC swing high that remains within a structurally reasonable distance from SC. Candidates are automatically invalidated if price drifts far above the SC without a structural break or if the candidate ages beyond a configurable maximum.
Layer three watches for a bullish Change of Character, defined as the first bar that closes above the qualified AR candidate. On CHoCH confirmation, PS, SC and AR are snapshotted as labeled events, the trading range is drawn, and the state machine advances to forward detection. ST, Spring, LPS and SOS are then detected in sequence using a combination of price-to-SC, price-to-AR and volume-to-average filters. Volume context is computed against a configurable moving-average baseline with separate climactic, elevated and weak thresholds.
The Spring Quality Score blends four components into a 0-100 rating: penetration depth below SC, volume dry-up on the sweep bar, recovery strength measured by close position within the candle range, and close location relative to SC. The Cause-to-Effect projection draws a symmetrical markup target from the SOS bar using the trading range height.
🟢 SIGNALS AND ALERTS
The indicator fires three categories of alerts, all reserved for confirmed structural events:
- CHoCH Confirmation alert triggers when the structural break locks in, including the resolved SC and AR levels.
- Spring alert fires when the Spring is detected, including the Spring Quality score.
- Sign of Strength alert fires when SOS confirms with climactic volume above AR.
No alerts are emitted during the forming phase. This keeps notification volume low and focused on decisive structural moments.
🟢 KEY INPUTS
Core Engine inputs control swing lookback sensitivity, candidate maximum age, post-CHoCH timeout, prior downtrend lookback, minimum downtrend depth in ATR multiples, and the near-lows threshold used in downtrend qualification. Volume Analysis exposes the moving-average length and three separate multipliers for climactic, elevated and weak volume classification. Visual inputs toggle the trading range zone, SC and AR horizontal levels, the CHoCH dashed break line, the Cause-to-Effect projection, the floating summary label and the keep-historical-events mode, with full control over font size and zone transparency. The info panel can be repositioned to six anchor points and switched between dark and light themes.
🟢 HOW TO USE
Apply the indicator to any liquid instrument and any timeframe. During downtrends, observe the Watching row in the panel to monitor the forming SC candidate. When CHoCH prints, the full PS, SC and AR bundle appears and the trading range is shaded. From that point, use the Next Expected row to track what the engine is waiting for. The Confidence score progresses from 70 at CHoCH to 97 at SOS. The Spring Quality Score becomes populated when a Spring is detected and quantifies the character of the sweep. The Volume Footprint row rolls through Range forming, Supply exhausting, Weak hands shaken, Supply absorbed and Demand in control as the schematic matures. The floating summary label on the right edge of the chart provides an at-a-glance status even when the primary event labels are scrolled off to the left. The indicator works standalone but is designed to complement any market structure, order flow or supply-and-demand workflow.
🟢 LIMITATIONS AND TRANSPARENCY
This tool is a pattern-recognition and labeling engine, not a strategy or a trading signal generator. All events are detected retrospectively after their confirming bar has closed plus the swing lookback period. This is by design to eliminate redrawing. The Wyckoff schematic is a framework, not a deterministic forecast. Not every accumulation completes the full seven-event sequence, and markets frequently fail schematics entirely and resume the prior downtrend. The volume analysis assumes reliable reported volume, so thin or fragmented markets may produce weaker classification. The Spring Quality Score and Confidence score are internal heuristics tied to event progression and are not statistical probabilities. The Cause-to-Effect projection is a classical Wyckoff reference line derived from range height, not a mechanical target guaranteed to be reached. Past schematic completions do not predict future market behavior.
🟢 RISK DISCLOSURE
This indicator is published for educational and analytical purposes only. It does not constitute financial advice, a trading recommendation or an investment solicitation. Trading any financial instrument involves substantial risk, including the potential loss of principal. Past performance does not guarantee future results. Users are solely responsible for their own trading decisions, risk management and independent research. Always backtest thoroughly and trade within a risk framework you understand. Indicator
AG Pro BOS & CHoCH Auto Detector [AGPro Series]AG Pro BOS & CHoCH Auto Detector
OVERVIEW / WHAT IT DOES
AG Pro BOS & CHoCH Auto Detector is a market structure overlay designed to organize swing-based price action into a more readable workflow. Instead of leaving the chart covered with disconnected pivot labels or generic break markers, this script tracks structural swing progression, identifies when prior highs or lows are broken, and classifies those breaks as either BOS (Break of Structure) or CHoCH (Change of Character). The goal is not to predict the next move, but to help traders read whether price is continuing an existing structure or beginning to challenge it.
The script monitors HH, HL, LH, and LL development using pivot logic, then uses those reference points to detect structural breaks. A break in the direction of the active structure is treated as BOS, while the first meaningful break against the prior directional structure is treated as CHoCH. This distinction matters because many charts show every break in the same visual language, even though continuation and character shift do not carry the same analytical meaning. Here, those events are separated clearly.
A second layer of usefulness comes from presentation discipline. This script is built to keep structural information visible without turning the chart into a wall of labels. Swing density can be reduced, major structures can be emphasized, and the higher timeframe overlay can remain active in the background to keep local execution aligned with broader structure. The result is a structure map that stays informative without becoming visually noisy.
This tool is intended for traders who already use price structure as part of their chart reading and want a cleaner way to monitor continuation versus transition. It can support discretionary workflows around trend continuation, pullback analysis, structure failure, and higher timeframe context, while still remaining transparent about how its signals are formed.
UNIQUE EDGE
Many market structure tools stop at plotting swing points or printing BOS / CHoCH text when a level is crossed. AG Pro BOS & CHoCH Auto Detector is built around a more organized structure engine approach.
Its edge is not based on trying to forecast direction or force trade entries. Its edge is based on classification, hierarchy, and chart readability:
- It separates continuation breaks from character-change breaks instead of treating all structural violations as equivalent.
- It preserves the swing chain context behind each event, so BOS and CHoCH are not isolated labels detached from surrounding structure.
- It allows confirmation mode selection, so the user can decide whether structure breaks require close confirmation or can react to intrabar violations.
- It includes higher timeframe structure context directly on the chart rather than forcing the user to reconstruct that context manually.
- It includes swing-density controls so the visual output can be kept clean even when structure is active.
This makes the script less like a simple labeling utility and more like a workflow layer for structure-based chart reading.
METHODOLOGY
1) Swing Structure Detection
The script uses pivot-based highs and lows to identify structural reference points. Those pivots are then classified into HH, HL, LH, and LL sequences, allowing the chart to reflect whether structure is strengthening, weakening, or transitioning.
2) BOS Logic
When price breaks a prior structural level in the direction of the active trend, the event is labeled as BOS. In practical terms, this represents structural continuation rather than directional reversal.
3) CHoCH Logic
When price breaks against the previously established directional structure, the event is labeled as CHoCH. This is treated as a possible character shift, not as a guaranteed reversal. It highlights that the prior structure has been challenged.
4) Confirmation Mode
Users can choose whether structure breaks are confirmed by candle close or by intrabar price action. Close mode is more conservative and can reduce noise. Intrabar mode is more responsive and may show earlier breaks.
5) Higher Timeframe Overlay
An optional MTF layer allows the script to bring higher timeframe structure context onto the active chart. This can help users avoid reading local swings in isolation when broader structure is still dominant.
6) Visual Hierarchy
The script uses horizontal structure levels, event labels, optional arrows, controlled swing density, and a compact information panel to keep key structure events readable. The design priority is to preserve analytical clarity.
SIGNALS & ALERTS
This script can generate structure-based alerts for the following event types:
- Bullish BOS
- Bearish BOS
- Bullish CHoCH
- Bearish CHoCH
- Any structure break
These alerts are event-driven and tied to the script's structural logic. They are intended to notify the user when a relevant break occurs according to the selected confirmation mode. They are not trade instructions and should be interpreted within the user's broader process.
KEY INPUTS
Swing Pivot Length
Controls pivot sensitivity. Lower values detect swings faster but may produce more noise. Higher values are more selective.
Confirmation Mode
Choose between Close and Intrabar logic for structure break confirmation.
Max Structures to Show
Limits how many structural events remain plotted on the chart.
Swing Label Density
Lets users choose between fuller swing annotation and a cleaner major-structure view.
Max Swing Labels on Chart
Helps prevent excessive label build-up in active market conditions.
Enable MTF Overlay
Adds higher timeframe structure context to the active chart.
MTF Timeframe
Defines which higher timeframe structure layer is projected onto the chart.
Label Size / Panel Font Size / Line Settings
Allow visual tuning without changing structural logic.
LIMITATIONS & TRANSPARENCY
This script uses pivot-based structure logic. That means swing points are confirmed only after the required pivot bars are completed. Because of this, the tool is confirmation-based by design and does not attempt to label unfinished pivots as confirmed structure.
BOS and CHoCH are structural events, not certainty statements. A CHoCH may signal that the prior directional structure is being challenged, but it does not guarantee a lasting reversal. Likewise, a BOS indicates continuation within the script's structural framework, but not guaranteed follow-through.
The higher timeframe overlay is designed to add context, not to replace direct higher timeframe chart review. Users should still interpret local and higher timeframe structure together rather than relying on a single signal state.
This script is best used as a structure-mapping tool within a broader analytical framework. It is not a standalone trading system, not a predictor, and not a substitute for risk management.
RISK DISCLOSURE
This indicator is for chart analysis and educational use. It does not provide financial advice, does not guarantee outcomes, and should not be treated as a complete trading methodology on its own. Market structure tools can help organize price action, but all trading decisions remain the responsibility of the user.
Indicator
AG Pro ROC Momentum Shift Map [AGPro Series]AG Pro ROC Momentum Shift Map
Overview / What it does
AG Pro ROC Momentum Shift Map is a momentum-regime tool built around the Rate of Change (ROC) concept, but organized as a transition map rather than a standalone oscillator. Instead of treating ROC as a simple line that moves above or below zero, this script tracks how momentum shifts from one regime to another, whether that transition is strengthening or fading, and whether the current phase is fresh, mature, or beginning to stall.
The script is designed to help users read momentum behavior in a more structured way. It separates bullish and bearish momentum into shift and expansion phases, then adds context through transition-zone logic, baseline separation, freshness tracking, and exhaustion risk. This allows the chart to show not only direction, but also the condition of that direction.
This publication is not intended to forecast tops, bottoms, or future price movement. It is a context tool that organizes ROC behavior into states that may help users evaluate whether momentum is attempting to change character, continue, or lose efficiency.
Unique Edge
The main difference between this script and many ROC-based publications is that it does not present ROC as a raw crossing signal. It reframes ROC as a regime map with state logic, quality scoring, and momentum-stage classification.
Within the AG Pro series, this script also has a different purpose than the previously published tools. It is not a breakout-quality model, not a pullback validator, not a support/resistance reaction map, not a relative-strength rotation framework, and not a correlation-stress tool. Those scripts focus on structure, levels, cross-asset comparison, reclaim behavior, or directional pressure. This script focuses on internal momentum state transitions derived from ROC behavior itself.
More specifically:
- It differs from breakout or retest-oriented scripts because it does not judge price interaction with a key level.
- It differs from reaction-map scripts because it does not score how price behaves around predefined structures such as pivots, support/resistance, or moving-average reclaim zones.
- It differs from pressure or trend-strength tools because its goal is not to estimate directional force in isolation, but to classify whether momentum is transitioning, expanding, contracting, or stalling.
- It differs from relative-strength tools because it does not compare one symbol against another symbol or benchmark.
That distinction is the core of the script’s originality: it uses ROC to map momentum regime transitions, not merely to display momentum magnitude.
Methodology
The script begins with a Rate of Change calculation over a user-defined length and optionally smooths that series to reduce small fluctuations. A regime baseline is then derived from the ROC series to establish whether current momentum is operating above or below its local equilibrium.
A dynamic transition zone is built from ROC volatility. This zone is used to identify areas where momentum is attempting to move from one regime into another. Instead of using a rigid zero-line interpretation alone, the script evaluates whether ROC is operating inside or outside this transition area and whether slope supports the move.
The internal state engine classifies momentum into five main conditions:
- Bull Shift
- Bull Expansion
- Bear Shift
- Bear Expansion
- Neutral / Compression
To add structure beyond simple state assignment, the script estimates Shift Quality using a combination of zone positioning, slope behavior, separation from the regime baseline, and acceleration. A whipsaw-sensitive penalty reduces the score when repeated zero-line crossings suggest unstable momentum behavior.
The script also tracks how long the current state has been active. That information is used to classify the move as Fresh, Active, Mature, Stale, or Stalling. Expansion and contraction logic are then layered on top to provide a clearer view of whether momentum is broadening or fading. Finally, an exhaustion-risk estimate is derived from adverse slope, adverse acceleration, and contraction behavior against the current state.
Signals & Alerts
This script provides state-based informational events rather than trade promises. The built-in alert set is designed to mark notable momentum transitions in a deterministic way:
- Bull Shift Detected
- Bull Expansion Active
- Bear Shift Detected
- Bear Expansion Active
- Momentum Stalling
These alerts are best interpreted as momentum-context events. They are not guarantees of continuation, reversal, or trade outcome.
Key Inputs
Important inputs include:
- ROC Length: defines the main lookback used for Rate of Change.
- ROC Smoothing: reduces short-term noise in the raw ROC series.
- Regime Baseline Length: sets the local reference used for momentum separation.
- Transition Zone Length and Multiplier: control the width and sensitivity of the transition area.
- Quality Normalization Length: affects how the quality model normalizes slope and ROC magnitude.
- Whipsaw Lookback: influences how aggressively unstable zero-line rotation is penalized.
- Freshness thresholds: define how quickly a state progresses from fresh to mature or stale.
Users can also customize visual behavior such as histogram visibility, transition-zone display, background shading, labels, and panel presentation.
Limitations & Transparency
This script is an analytical indicator, not a prediction engine. ROC is a momentum derivative, so it can react quickly but can also become unstable in choppy or mean-reverting environments. During low-quality market conditions, momentum may rotate repeatedly around the transition zone and generate less reliable state changes.
Shift Quality is an internal scoring framework created to organize momentum transitions more clearly. It is not an objective universal measure of trade quality, and it should not be interpreted as proof of future performance.
Freshness, expansion, contraction, and exhaustion labels are contextual classifications based on the script’s internal logic. They are intended to help users structure momentum analysis, not to replace broader chart reading, trend assessment, market structure work, or risk management.
As with any indicator, outputs can vary depending on symbol characteristics, volatility regime, timeframe, and user settings. This script should be used as one analytical layer within a broader decision process.
Risk Disclosure
This indicator is for chart analysis and educational use. It does not provide investment advice, trading advice, or guaranteed results. Financial markets involve risk, and no indicator can ensure favorable outcomes. Users should evaluate the script in their own workflow, test settings carefully, and apply independent judgment before making trading decisions.
Indicator
Indicator
FluxPulse Momentum [JOAT]FluxPulse Momentum - Adaptive Multi-Component Oscillator
FluxPulse Momentum is a composite oscillator that blends three distinct momentum components into a single, smoothed signal line. Rather than relying on a single indicator, it synthesizes adaptive RSI, normalized rate of change, and a Kaufman-style efficiency ratio to provide a multi-dimensional view of momentum.
What This Indicator Does
Combines RSI, Rate of Change (ROC), and Efficiency Ratio into one weighted composite
Applies EMA smoothing to reduce noise while preserving responsiveness
Displays overbought/oversold zones with optional background highlighting
Generates buy/sell signals when the oscillator crosses its signal line in favorable zones
Provides a real-time dashboard showing current state, momentum direction, and efficiency
Core Components
Adaptive RSI (50% weight) — Standard RSI calculation normalized around the 50 level
Normalized ROC (30% weight) — Rate of change scaled relative to its recent maximum range
Efficiency Ratio (20% weight) — Measures directional movement efficiency, inspired by Kaufman's adaptive concepts
The final composite is smoothed twice using EMA to create both a fast line and a signal line.
Signal Logic
// Buy signal: crossover in lower half
buySignal = ta.crossover(qmo, qmoSmooth) and qmo < 50
// Sell signal: crossunder in upper half
sellSignal = ta.crossunder(qmo, qmoSmooth) and qmo > 50
Signals are generated only when the oscillator is positioned favorably—buy signals occur below the 50 midline, sell signals occur above it.
Dashboard Information
The on-chart table displays:
Current oscillator value with gradient coloring
Momentum state (Overbought, Oversold, Bullish, Bearish, Neutral)
Momentum direction and acceleration
Efficiency ratio percentage
Active signal status
Inputs Overview
RSI Length — Period for RSI calculation (default: 14)
ROC Length — Period for rate of change (default: 10)
Smoothing Length — EMA smoothing period (default: 3)
Overbought/Oversold Levels — Threshold levels for zone detection
Await Bar Confirmation — Wait for bar close before triggering alerts
How to Use It
Watch for crossovers between the main line and signal line
Use overbought/oversold zones to identify potential reversal areas
Monitor the histogram for momentum acceleration or deceleration
Combine with price action analysis for confirmation
Alerts
Buy Signal — Bullish crossover in the lower zone
Sell Signal — Bearish crossunder in the upper zone
Overbought/Oversold Crosses — Level threshold crossings
This indicator is provided for educational purposes. It does not constitute financial advice. Always conduct your own analysis before making trading decisions.
— Made with passion by officialjackofalltrades Indicator
Indicator
Period Range AnalyzerThis indicator analyzes a specific periodic range, which can start from a fixed date or a defined lookback period. It draws percentage levels and colored zones between the highest and lowest price. It also displays a detailed information table, which shows the price's position within the range in "Trend" mode, and the relative strength of currency pairs in "Forex" mode. The current price position is also indicated by a label with a percentage value and the name of the corresponding zone.
User Guide
Calculation Method
This setting determines how the indicator defines the range used for the calculation.
Lookback Period: In this mode, the indicator uses the last N candles (the number can be specified in the "Lookback Period (bars)" field). The range (the highest and lowest price) is "floating," meaning it is recalculated with each new candle based on the last N candles.
Date Based: In this mode, the calculation starts from a fixed date and time you select. The indicator finds the opening price of the start date and continuously tracks the highest and lowest price from that point on. This mode is ideal for measuring performance from a specific event (e.g., start of a week/month/year, news).
Data Handling Note: If you select a date in "Date Based" mode for which no data is available on the current timeframe (e.g., switching to a very low timeframe), the indicator will automatically use the earliest available candle as the starting point. All calculations (Open, Max, Min, Range, Percentage, Change, Trend) are based on this actual start date.
Start Date & Time
This setting is only active in "Date Based" mode.
Here you can specify the fixed starting point for the calculation.
The specified time is in the Exchange timezone.
Important limitation: Due to PulseWire platform limits, visual elements (levels, zones) are only drawn for a maximum of 250 candles back. If the set date is older than this, the calculation still applies to the entire period (from the set date), but the drawing only covers the last 250 candles. The table always displays accurate data for the entire period.
When switching to a higher timeframe, the range may restart from a slightly later bar due to PulseWire's bar alignment. For best accuracy, set your timeframe first, then select the start date.
Table Mode
This setting controls what data the information table displays.
Trend: This is the default mode, which works on any symbol (stock, index, crypto, etc.). It displays information related to the trend and the range.
Forex: This is a special mode used to measure the strength of currency and crypto pairs. It only works on symbols with exactly 6 characters (e.g., "EURUSD", "BTCUSD"). It treats the first 3 characters as the base currency (e.g., EUR) and the last 3 as the quote currency (e.g., USD). If the symbol does not have 6 characters, the table will automatically display in "Trend" mode.
Trend
This trend determination operates based on the formation order of the high and low within the analyzed range:
Its switch is located in the “Table Additional Rows” menu.
Bullish: Indicated if the low was formed before the high (on different candles). Or if they formed on the same candle, it was a bullish candle.
Bearish: Indicated if the high was formed before the low (on different candles). Or if they formed on the same candle, it was a bearish candle.
Neutral: Indicated if the high and low formed on the same candle, and it was a "doji" candle (close = open).
Upper & Lower Threshold
These settings (Upper Threshold (%) and Lower Threshold (%) in the "Label Coloring" section) primarily determine the state (Bullish/Bearish/Neutral) of the top row of the table.
The logic is not based on the percentage change of the price movement, but on the current price's position within the range, where the bottom of the range is 0% and the top is 100%.
Upper Threshold (%): The percentage level (e.g., 60.0) above which the indicator considers the price position "Bullish" (or "Strong").
Lower Threshold (%): The percentage level (e.g., 40.0) below which the indicator considers the price position "Bearish" (or "Weak").
If the price is between the two (e.g., between 40% and 60%), the signal is Neutral.
Secondary function: These thresholds also control the color of the label next to the price, provided the "Dynamic Label Coloring" option is enabled.
Indicator
Indicator
Daily Percent Change LabelDaily Percent Change Label
Overview
This Pine Script displays the percentage change from the previous day's closing price as a text label near the current price level on the chart. It works seamlessly across any timeframe (daily, hourly, minute charts) by referencing the daily chart's previous close, making it perfect for traders tracking daily performance.
The label is displayed with a semi-transparent background (green for positive changes, red for negative changes) and white text, ensuring a clean and readable appearance.
Features
Accurate Daily Percent Change: Calculates the percentage change based on the previous day's closing price, even on intraday timeframes (e.g., 1-hour, 5-minute).
Dynamic Label: Shows the percentage change as a label aligned with the current price, updating in real-time.
Color-Coded Background: Semi-transparent green background for positive changes and red for negative changes.
Customizable: Adjust label position, size, color, and style to fit your preferences.
Minimal Impact: No additional plots or graphs, keeping the chart uncluttered.
How to Use
Add the Script:
Copy and paste the script into the Pine Editor in PulseWire.
Click "Add to Chart" to apply it.
Check the Output:
A text label (e.g., "+2.34%" or "-1.56%") appears near the current price with a semi-transparent background.
The label is colored green (positive) or red (negative) and updates in real-time.
Switch Timeframes:
Works on any timeframe. The percentage change is always calculated relative to the previous day's close.
Customization Options
Modify the label.new function to customize the label:
Label Position:
Change style=label.style_label_left to label.style_label_right or label.style_label_down to adjust label placement.
Adjust bar_index with an offset (e.g., bar_index + 1) to move the label horizontally.
Text Color:
Modify textcolor=color.white to another color (e.g., color.rgb(255, 255, 0) for yellow).
Background Color:
Adjust color=percent_change >= 0 ? color.new(color.green, 50) : color.new(color.red, 50) to change transparency (e.g., color.new(color.green, 0) for no transparency).
Text Size:
Change size=size.normal to size.small or size.large for smaller or larger text.
Code Details
Timeframe Handling: Uses request.security with the "D" timeframe to fetch the previous day's closing price, ensuring accuracy on intraday charts.
Performance: Updates only on the last bar (barstate.islast) for optimal performance.
Dynamic Styling: Background color changes based on the direction of the price change.
Notes
The label is positioned near the current price for easy reference. To move it closer to the Y-axis, adjust the bar_index offset.
For different reference points (e.g., weekly close), modify the request.security timeframe (e.g., "W" for weekly).
Ensure the script is copied correctly without extra spaces or characters. Use a plain text editor (e.g., Notepad) for copying.
Feedback
Please share your feedback or customizations in the comments! If you find this script helpful, give it a thumbs-up or let others know how you're using it. Happy trading!
Indicator
Custom Performance TableThis script generates a table designed to provide a concise yet highly customizable overview of the performance of multiple financial instruments, displayed directly on the chart. The table can include up to 40 tickers, each individually configurable, with values updated in real time based on either the current chart timeframe or a specific user-selected timeframe.
NOTE : The update frequency of the table values depends on the refresh rate of the chart's main ticker to which the indicator is applied. To ensure a consistent and reliable data feed, especially when monitoring heterogeneous instruments, it is recommended to apply the indicator to a highly liquid and continuously traded asset, such as BTCUSD.
PERFORMANCE CALCULATION MODES
You can choose from three different performance calculation modes:
1) Change % (Percentage Change)
Displays the percentage change of the current price compared to the previous candle within the selected timeframe.
(Current Price - Previous Price) / Previous Price * 100
This mode provides an immediate and straightforward measure of each instrument's percentage movement, useful for quick visual comparisons of relative strength among assets.
2) Z-Score
The Z-Score measures how much the current price variation deviates from the historical average variation, relative to the standard deviation of those variations.
(Current Variation - Average Variation) / Standard Deviation of Variations
The result indicates how statistically unusual a movement is:
- Values near 0 suggest normal variations.
- Values above ±2 indicate statistically significant deviations.
This is a valuable tool for identifying overbought/oversold conditions or market stress events and is often used in mean reversion strategies.
NOTE : Due to technical constraints, Z-Score can only be calculated when the selected timeframe matches the chart's timeframe exactly.
3) RAROC (Risk-Adjusted Return on Capital)
RAROC expresses an asset's performance in relation to the risk taken, measured through its volatility (standard deviation of price).
Percentage Change / Standard Deviation of Price
It allows for an assessment of return efficiency in relation to volatility.
A high RAROC value indicates a high return relative to the risk, making it a useful tool for comparing assets with different risk profiles. It is especially suitable for portfolio selection and allocation purposes.
TABLE CONFIGURATION
Each ticker can be customized with its own label, colors, and position in the table.
Each row can display the ticker name or a custom label, which, at the user's discretion, can either replace the name or be shown as an informational tooltip.
The table can be placed anywhere on the chart using horizontal and vertical offset parameters. Thanks to offset support, you can, for example, create financial market overview layouts. This can be done by completely “cleaning” the chart from price and indicators using PulseWire settings, and then displaying multiple tables simultaneously (see the example chart published here).
Advanced customization options are also available for the table's appearance, including font settings, colors, borders, and more.
CALCULATION TIMEFRAME
The indicator allows the user to force a specific timeframe (Daily, Weekly, Monthly, Yearly) when applied to intraday charts.
However, for Z-Score mode, the selected timeframe must match the chart's timeframe exactly to ensure correct computation. Otherwise, the script will halt until settings are properly adjusted.
USAGE NOTES
Custom Performance Table is a flexible and adaptable tool, suitable for both intraday operations and medium- to long-term analysis. It is designed for traders and analysts who need to compare assets based on quantitative metrics, whether simple (like percentage change) or more advanced and risk-adjusted (such as Z-Score and RAROC). Indicator
Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes. Indicator
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Indicator
Average Bullish & Bearish Percentage ChangeAverage Bullish & Bearish Percentage Change
Processes two key aspects of directional market movements relative to price levels. Unlike traditional momentum tools, it separately calculates the average of positive and negative percentage changes in price using user-defined independent counts of actual past bullish and bearish candles. This approach delivers comprehensive and precise view of average percentage changes.
FEATURES:
Count-Based Averages: Separate averaging of bullish and bearish %𝜟 based on their respective number of occurrences ensures reliable and precise momentum calculations.
Customizable Averaging: User-defined number of candle count sets number of past bullish and bearish candles used in independent averaging.
Two Methods of Candle Metrics:
1. Net Move: Focuses on the body range of the candle, emphasizing the net directional movement.
2. Full Capacity: Incorporates wicks and gaps to capture full potential of the bar.
The indicator classifies Doji candles contextually, ensuring they are appropriately factored into the bullish or bearish metrics to avoid mistakes in calculation:
1. Standard Doji - open equals close.
2. Flat Close Doji - Candles where the close matches the previous close.
Timeframe Flexibility:
The indicator can be applied across any desired timeframe, allowing for seamless multi-timeframe analysis.
HOW TO USE
Select Method of Bar Metrics:
Net Move: For analyzing markets where price changes are consistent and bars are close to each other.
Full Capacity: Incorporates wicks and gaps, providing relevant figures for markets like stocks
Set the number of past candles to average:
🟩 Average Past Bullish Candles (Default: 10)
🟥 Average Past Bullish Candles (Default: 10)
Why Percentage Change Is Important
Standardized Measurement Across Assets:
Percentage change normalizes price movements, making it easier to compare different assets with varying price levels. For example, a $1 move in a $10 stock is significant, but the same $1 move in a $1,000 stock is negligible.
Highlights Relative Impact:
By measuring the price change as a percentage of the close, traders can better understand the relative impact of a move on the asset’s overall value.
Volatility Insights:
A high percentage change indicates heightened volatility, which can be a signal of potential opportunities or risks, making it more actionable than raw price changes. Percents directly reflect the strength of buying or selling pressure, providing a clearer view of momentum compared to raw price moves, which may not account for the relative size of the move.
By focusing on percentage change, this indicator provides a normalized, actionable, and insightful measure of market momentum, which is critical for comparing, analyzing, and acting on price movements across various assets and conditions. Indicator
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Stock Data Table█ OVERVIEW
This is a table that shows some information about stocks. It is divided into four sections:
1) Correlation
2) Shares
3) Daily Data
4) Extended Session Data
The table is completely modular, which means you can add or remove each element from the settings menu, and it will automatically rearrange its spaces.
It is also highly customizable, to the extent that you can change almost any color, remove or change titles, invert section rows, and much more.
1) Correlation
The script checks if the stock is listed on NASDAQ, and if so, uses the QQQ (Nasdaq-100 ETF) as the reference index in the first cell; otherwise, it uses the SPY (S&P 500 ETF). The length of the correlation is shown in the second cell. The table then displays the correlation between the reference index and the other index, and the correlation between the reference index and the stock.
To make it easier to interpret the correlation values, each row's last cell is color-coded with a gradient to highlight the type of correlation, and the direction of the gradient can be customized.
The correlation coefficient is a statistical measure that quantifies the strength and direction of the relationship between two variables, indicating how changes in one variable are associated with changes in the other variable, so it can be used to identify patterns and trends.
If you are interested in correlation, I suggest taking a look at my dedicated indicator:
2) Shares
This feature provides you with quick access to key information about shares and market capitalization.
On one row, you can view the total shares outstanding and the market capitalization for the fiscal year or the quarterly year. The total shares outstanding represents the total number of shares of the stock that have been issued and are currently outstanding, regardless of whether they are held by insiders or public investors. The market capitalization is a widely used measure of the company's value as determined by the stock market, calculated by multiplying its current stock price with the total number of outstanding shares.
The other row shows the float, which is the number of shares of a company that are available for public trading, and the corresponding free-float market cap, calculated by multiplying the company's current stock price with the float. Because Pine Script does not allow retrieving information about quarterly year float, you can view the float and the free-float market cap of the fiscal year only. The data can be displayed at all times or only when the difference between the total shares outstanding and the float is significant enough to result in a difference between the market cap and free-float market cap.
The classification for market cap and free-float market cap is set in this way:
Mega Cap: $200 billion or more
Large Cap: between $10 billion and $200 billion
Mid Cap: between $2 billion and $10 billion
Small Cap: between $300 million and $2 billion
Micro Cap: less than $300 million
Penny Stocks: less than $5 (customizable)
Comparing the free-float market cap to the market cap can provide insights into the liquidity of a stock. In fact, if the float is relatively small compared to the total shares outstanding, it may be more difficult to find buyers or sellers, which could lead to increased volatility. On the other hand, a larger float indicates that the stock is more liquid and may be easier to trade, potentially resulting in lower volatility. However, market conditions can change quickly and significantly, especially for intraday traders, and the free-float can also change as insiders or other large shareholders buy or sell shares. Therefore, comparing the data of the fiscal year with that of the quarterly year may not provide the most up-to-date and accurate information for making trading decisions. This limitation can be mitigated by combining those data with other indicators and tools, such as technical analysis or news events, to gain a better understand of the stock's performance and potential trading opportunities.
3) Daily Data
This section is available on daily charts only due to the lack of accuracy of real-time daily data on other time frames. Here, you can view the Average Daily Volume (ADV) over a preferred time range (20 days by default), and the Daily Change, which represents the percentage difference between the closing price on two consecutive trading days.
ADV is useful in measuring the stock's volatility, as it provides an indication of how much trading activity there is in it. Generally speaking, stocks with higher trading volume tend to be less volatile than stocks with lower trading volume. High trading volume means there are more buyers and sellers actively trading the stock, which makes it easier for investors to buy and sell shares at fair prices. This increased liquidity can help to stabilize the stock price, reducing the potential for large swings in either direction. On the other hand, stocks with lower trading volume may experience greater volatility, as there are fewer buyers and sellers actively trading the stock. This can result in larger price swings, as it may be more difficult for investors to buy or sell shares at fair prices.
The daily percentage change can provide an indication of the stock's volatility, with larger values indicating greater volatility and risk. It can also be compared to that of a benchmark such an index or other stocks in the same sector, helping to determine whether the stock is outperforming or underperforming relative to them.
4) Extended Session Data
The fourth section is available on intraday charts only. This section provides two pieces of information: the Extended Session Change and the Pre-Market Volume.
The Extended Session Change indicates the percentage difference between the previous day's closing price and the latest price in the extended session. This gives you the extent and the direction of the price gap that occurred during extended trading hours.
The Pre-Market Volume shows the sum of all shares traded during the pre-market session. This can be helpful in understanding how much interest the stock gained before the market opened.
By default, the two rows will be visible at all times. They will stop updating after the end of their respective time range, and resume updating when it starts again. However, you can choose to automatically hide them outside of their time ranges.
Both the extended session and pre-market time ranges can be customized. Please note that if you select time ranges outside of the regular market session (as set by default), you must enable the extended session to view the corresponding rows.
█ GENERAL NOTES
• Total Shares Outstanding, Float, Average Daily Volume and Pre-Market Volume cells use a customizable color system based on two thresholds, to help you quickly identify whether the value is "too low/acceptable/too high" or "too low/not enough high/acceptable".
• If you cannot see certain data, that simply means it is not available. Indicator
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