[GYTS-CE] Kinetic Trend Envelope (adaptive trailing stop)Kinetic Trend Envelope (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Kinetic Trend Envelope?
The Kinetic Trend Envelope (KTE) is an adaptive directional trailing stop in the lineage of SuperTrend, rebuilt around the premise that volatility is kinetic energy . It measures per-bar motion with five academically grounded volatility estimators, then widens the envelope as energy rises and contracts it as motion settles.
In an uptrend, the lower band ratchets higher and never retreats; in a downtrend, the upper band ratchets lower. The direction changes when the active stop is breached, after which the opposite side becomes the new trailing stop.
💮 Why Use This Indicator?
Conventional trailing stops typically combine a price anchor with one symmetric ATR-derived width. The KTE extends that model with:
Asymmetric volatility profiling — Bullish- and bearish-candle volatility shape the upper and lower bands independently.
Three direction-switch methods — High/low, close, or a smoothed estimator controls flip sensitivity without moving the band anchor.
Five volatility estimators — ATR plus Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang covers different treatments of gaps, drift, and intrabar range.
The outputs are calibrated to a common width basis, so Volatility Factor remains interpretable across estimators and price scales. Fine adjustment may still be useful, but switching estimators should not require re-tuning by orders of magnitude.
↑ The KTE on a trending instrument. The thick line is the active trailing stop; the thin line shows the opposing side of the envelope. Both expand and contract with market energy.
↑ KTE beside TradingView's built-in SuperTrend, both using ATR with a 10-bar lookback. KTE's asymmetric profile changes how each side responds to directional volatility while the monotonic active band avoids premature loosening.
🌸 --------- HOW IT WORKS --------- 🌸
💮 Core Concept
The bands share a smoothed price estimator as their anchor, but use separate volatility profiles:
Upper band = estimator + (factor × bullish-candle volatility)
Lower band = estimator − (factor × bearish-candle volatility)
In a bullish state, the lower band is active and can only rise. In a bearish state, the upper band is active and can only fall. This monotonic constraint prevents a live trailing stop from loosening within the trend.
The selected direction-switch method changes only the breach test. It does not change the smoothed estimator anchoring the envelope, so a wick-sensitive trigger cannot drag the bands around with the wick.
💮 The Five Volatility Estimators
Each estimator reads a different part of the OHLC bar:
ATR (Wilder, 1978) — Familiar baseline that handles gaps through true range.
Parkinson (1980) — Uses high-low range; efficient under continuous, low-drift conditions.
Garman-Klass (1980) — Adds open-close information; favours continuous sessions without material gaps.
Rogers-Satchell (1991) — Drift-independent and well suited to trending, continuously traded instruments.
Yang-Zhang (2000) — Combines overnight gaps, open-close movement, and Rogers-Satchell; the gap-aware default.
Statistical efficiency does not guarantee a visibly tighter stop. At slow Adaptation Speed settings, long averaging makes the estimators look similar; at fast settings, their different treatments of gaps, drift, and range become more visible. Choose according to the instrument's behaviour rather than expecting one estimator always to produce the narrowest band.
↑ ATR and Yang-Zhang at Adaptation Speed 2. The long profile memory (low speed) smooths away most of the difference, so the two envelopes nearly overlap.
↑ ATR and Yang-Zhang at Adaptation Speed 8. The short profile memory (high speed) exposes their different volatility readings, producing visibly distinct envelope widths.
💮 Asymmetric Volatility Profiling and Adaptation Speed
The KTE stores volatility from bullish and bearish candles separately. Bullish samples determine the upper width; bearish samples determine the lower width. This allows the two sides to respond differently when upward and downward motion carry different energy.
Adaptation Speed controls the memory of this profile, not the speed of the price estimator and not the distance of the stop by itself. Its 1–10 scale maps logarithmically to an internal window:
Speed 3 — approximately 878 bars: stable and slow to re-weight
Default 3.5 — approximately 570 bars: general-purpose smoothing
Speed 8 — approximately 11 bars: highly responsive to recent volatility
Speed 10 — approximately 2 bars: extremely reactive and noisy
Faster does not necessarily mean closer to price. During a volatility burst, a fast profile recognises the expansion sooner and may widen the band sharply. Because the active stop cannot loosen, it can then remain flat until the estimator catches up. A slow profile dilutes the same burst across much more history, so its narrower band may appear to follow price faster.
This is why two instances matched during a calm period can separate during a shock, especially when they also use different Volatility Factor values. Compare Adaptation Speed with the same factor first; matching lines in one regime does not make two configurations equivalent elsewhere.
The profiles are also direction-conditioned: bullish samples are replaced by later bullish candles and bearish samples by later bearish candles. A recent high-volatility sample can therefore persist through a run of opposite-colour candles, producing deliberate step-like plateaux in the relevant band.
↑ Asymmetric profiling in action: the upper and lower widths respond independently to bullish- and bearish-candle volatility.
💮 Direction Switch Methods
The breach source sets the balance between responsiveness and false flips:
On high/low — Uses the current bar's wick and can switch on the breach bar. Fastest and most sensitive to noise.
On close — Uses the previous confirmed close; the switch appears on the following bar.
On estimator — Uses the previous smoothed estimator; the most conservative default, also switching on the following bar.
↑ The three switch methods share the same band geometry but change direction at different times.
🌸 --------- KEY FEATURES --------- 🌸
💮 Eight Estimator Filters
The configurable price anchor includes:
Ultimate Smoother, 2- or 3-pole — Low-noise, near-zero-lag passband response; the 2-pole version is the default.
Super Smoother, 2- or 3-pole — Ehlers low-pass filters for progressively stronger smoothing.
BiQuad — Second-order low-pass filter with an adjustable Q-factor.
ADXvma — Adapts to trend strength and tends to flatten in ranges.
MAMA — Cycle-adaptive MESA moving average.
A2RMA — Adaptive recursive moving average with adjustable gamma.
They are provided by the open-source FiltersToolkit library.
💮 Visual Layering
The display separates function from context:
Active band — Thick directional trailing-stop line
Opposing band — Thin reference for the inactive side
Channel fill — Visual separation between the estimator and each band
Estimator — Optional smoothed anchor
Palette, light/dark mode, widths, and transparencies can be adjusted independently.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Getting Started
Start with the defaults, observe several calm and volatile regimes, and change one dimension at a time:
Tune Volatility Factor for the preferred stop distance.
Tune Adaptation Speed for how quickly width should respond to regime changes.
Choose the direction-switch method for the preferred confirmation level.
Change the volatility estimator only when its assumptions better fit the instrument.
💮 Choosing a Volatility Estimator
Gapped equities — Yang-Zhang accounts for overnight movement.
Trending 24/7 markets — Rogers-Satchell is drift-independent without a separate gap component.
Continuous, range-led markets — Parkinson or Garman-Klass offers efficient range-based measurement under their assumptions.
Familiar baseline — ATR provides conventional true-range behaviour.
On continuous instruments, Rogers-Satchell and Yang-Zhang may look very similar because there are few gaps to distinguish them. Use the Volatility Toolkit to compare their raw behaviour on the intended instrument.
↑ Three estimators compared on one instrument, each reading a different combination of OHLC information.
💮 Tuning Width and Responsiveness
These controls solve different problems:
Volatility Factor — Sets the distance per unit of measured volatility.
Adaptation Speed — Sets the memory of the bullish/bearish profile; faster can widen the stop sooner during shocks.
Volatility Lookback — Sets how quickly the underlying per-bar volatility estimate changes.
Estimator Lookback — Sets the smoothness of the price anchor.
Use symptoms to guide adjustment:
Frequent flips on minor pullbacks — Increase Volatility Factor or use a more conservative switch method (e.g. "on estimator").
Excessive give-back — Decrease Volatility Factor or use a more responsive switch method (e.g. "on high/low").
Width reacts too slowly to regime changes — Increase Adaptation Speed or reduce Volatility Lookback.
Bands become erratic during shocks — Reduce Adaptation Speed or increase Volatility Lookback.
↑ A tight factor follows price more closely and flips more often; a loose factor tolerates larger pullbacks.
💮 Trading Applications
Discretionary trailing stop — Move a protective stop with the active band as it tightens.
Trend confirmation — Accept long signals only during a bullish KTE state, and short signals only while bearish.
Exit timing — Treat a direction change as an exit when the trade thesis is trend-following.
💮 Integration with GYTS Suite
The visible bands and estimator can be selected as sources by compatible Pine scripts. Two packed streams are also exposed:
🔗 STREAM KTE 🪜 Trailing Stoploss — Positive lower-band value in a bullish state; negative upper-band value in a bearish state.
🔗 STREAM KTE 🪜 Mechanism — Encodes the switch method and scale-invariant estimator relationship for compatible consumers.
The KTE is, first and foremost, a trailing stop, and these streams are built for stop management. The Order Orchestrator strategy consumes the Trailing Stoploss and Mechanism streams together : the first supplies the active stop level and its direction, the second makes the strategy's trailing-exit runner follow whatever switch method and estimator you set here. So the stop is configured once, in the KTE.
Beyond that primary role, the signed trailing-stop stream can also serve as a trend signal, since its sign flips with direction: it can be read through sign and magnitude as an entry/exit signal, including by Flux Composer . The KTE can also be paired with Market Regime Detector so flips are acted on only when the broader regime supports trend-following behaviour.
🌸 --------- LIMITATIONS --------- 🌸
Trailing-stop latency — Every trailing stop gives back some of the move between the trend extreme and the eventual breach.
Whipsaws in ranges — Low-energy chop can produce repeated flips; a regime filter may help when ranging conditions dominate.
Fast adaptation can widen the stop — Higher Adaptation Speed means faster volatility response, not guaranteed proximity to price.
Direction-conditioned memory — A bullish or bearish outlier remains in its own profile until enough matching-direction samples replace it, which can create plateaux after shocks.
Warm-up and sample size — Long profile windows need sufficient chart history; strongly one-sided markets may leave one side with few recent samples.
🌸 --------- CREDITS --------- 🌸
💮 Academic Sources
Wilder, J. W. (1978). New Concepts in Technical Trading Systems . Trend Research.
Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
Garman, M. B., & Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
Rogers, L. C. G., & Satchell, S. E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
Yang, D., & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
Ehlers, J. F. (2024). The Ultimate Smoother. Technical Analysis of Stocks & Commodities , 2024-04. TASC
Ehlers, J. F. (2004). Cybernetic Analysis for Stocks and Futures . Wiley. Covers SuperSmoother, MAMA and more.
💮 Inspiration
Thanks to Trendoscope for inspiring us with the Supertrend - Ladder ATR (2021). It derives long-side stop distance from bearish-candle ATR and short-side distance from bullish-candle ATR, which is one of the mechanisms that we tried to develop further with the KTE.
💮 Libraries Used
FiltersToolkit — Ultimate Smoother, Super Smoother, BiQuad, ADXvma, MAMA, and A2RMA
VolatilityToolkit — Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang estimators
MathTransform — Logarithmic scaling for Adaptation Speed
ColourUtilities — Palette management and light/dark-mode colour adjustment
Indicateur
Indicateur
Indicateur
Directional Call/Put Entry Indicator + Trigger Labels## Directional Call/Put Entry Indicator + VWAP Trigger Labels
FYI: I have many other indicators that I used that you might not have, so ignore those.
This indicator is designed to help identify directional option-trading setups by combining the 13 EMA channel, 89 EMA trend structure, VWAP, opening-range information, candle direction, and momentum conditions.
The script displays potential bullish and bearish continuation signals directly on the chart and includes separate trigger labels intended for put credit spread and call credit spread setups.
## Main Features
The indicator calculates and displays:
* Session VWAP
* 13 EMA high and low channel
* 89 EMA trend line
* Opening-range high, low, and midpoint calculations
* Bullish and bearish trend alignment
* 13 EMA slope and momentum direction
* Separation between the 13 EMA and 89 EMA
* Candle-direction confirmation
* ATR-based late-entry filtering
* Optional VIX values inside trigger labels
* Adjustable label placement and connector-line width
## Trend and Continuation Logic
Bullish conditions are evaluated by determining whether the 13 EMA is above the 89 EMA, whether the 13 EMA is rising, and whether price and momentum support continued upside movement.
Bearish conditions are evaluated by determining whether the 13 EMA is below the 89 EMA, whether the 13 EMA is falling, and whether price and momentum support continued downside movement.
The script also identifies stronger conditions when the entire 13 EMA channel is positioned above or below the 89 EMA channel and the distance between the moving averages is increasing.
## Late-Entry Filter
The indicator includes a late-move or chase filter designed to reduce signals after price has already extended too far from the 13 EMA channel.
This filter considers:
* Recent bullish or bearish candle count
* ATR-based price extension
* Whether price is reaching a recent high or low
These conditions help distinguish a potential early continuation setup from a move that may already be overextended.
## CCS Trigger Label
The bearish trigger label displays:
“CCS TRIGGER
BREAK BELOW 13”
This label is designed for a possible call credit spread setup.
The CCS trigger requires:
* The previous candle to have closed above the 13 EMA high
* The current candle to break and close below the 13 EMA low
* The current candle to be bearish
* The current candle to make a lower low
* The current candle to remain above VWAP
The label will not appear when the trigger candle closes below VWAP.
## PCS Trigger Label
The bullish trigger label displays:
“PCS TRIGGER
BREAK ABOVE 13”
This label is designed for a possible put credit spread setup.
The PCS trigger requires:
* The previous candle to have closed below the 13 EMA low
* The current candle to break and close above the 13 EMA high
* The current candle to be bullish
* The current candle to make a higher high
* The current candle to remain below VWAP
The label will not appear when the trigger candle closes above VWAP.
## Changes in This Version
The primary update in this version is the addition of strict VWAP-location filters for the CCS and PCS trigger labels.
### CCS Change
In the previous version, the CCS trigger could display based on the break below the 13 EMA without strictly enforcing the trigger candle’s location relative to VWAP.
The updated version requires the CCS trigger candle to close above VWAP before the label is created.
### PCS Change
In the previous version, the PCS trigger could display based on the break above the 13 EMA without strictly enforcing the trigger candle’s location relative to VWAP.
The updated version requires the PCS trigger candle to close below VWAP before the label is created.
### Label Text Update
The label text was also simplified.
The previous label wording included:
* “ONLY IF ABOVE VWAP”
* “ONLY IF BELOW VWAP”
Those phrases have been removed from the chart labels.
The labels now display only:
* “CCS TRIGGER — BREAK BELOW 13”
* “PCS TRIGGER — BREAK ABOVE 13”
The VWAP requirements remain enforced by the script logic even though they are no longer shown inside the labels.
## Result of the Update
The two trigger labels now follow specific VWAP-location rules:
* CCS triggers are restricted to setups above VWAP.
* PCS triggers are restricted to setups below VWAP.
This reduces conflicting labels and makes the trigger logic more consistent with the intended directional credit-spread setup.
## Important Notes
This indicator does not place trades, calculate option strikes, determine position size, or manage risk.
The labels are technical-condition alerts only. A signal does not guarantee that price will continue in the expected direction.
Users should independently evaluate:
* Overall market direction
* Support and resistance
* Volatility
* Economic announcements
* Option liquidity
* Credit received
* Spread width
* Maximum loss
* Exit and stop-loss rules
This script is intended for educational and informational purposes only and should not be considered financial advice.
Indicateur
TrendPulse: 9 EMA + VWAP Continuation StrategyTrendPulse combines 9 EMA trend structure, VWAP positioning, and continuation logic into a chart-ready intraday strategy. It includes fully customizable visual aids, signal markers, dashboard metrics, and active trade overlays for entry, stop, target, and break-even visualization, allowing traders to tailor the display to their own strategy and charting preferences. Trade overlays appear only while a position is active and automatically disappear once the trade is closed to help keep charts clean and uncluttered.
TrendPulse combines 9 EMA trend structure, VWAP positioning, and continuation logic into a chart-ready intraday strategy built for traders who want both structure and flexibility. The script is designed to help identify trend alignment, continuation opportunities, and trade management levels while keeping the chart readable and customizable.
This strategy includes fully customizable visual aids, signal markers, dashboard metrics, and active trade overlays for entry, stop, target, and break-even visualization. All visual elements can be adjusted to better fit individual trading styles, chart layouts, and preferred market conditions. Active trade overlays appear only while a position is live and automatically disappear after the trade closes, helping reduce chart clutter.
How It Works
TrendPulse evaluates price structure using a combination of:
fast and slow EMA trend bias
a dynamic basis line
9 EMA context
VWAP positioning
volatility and regime conditions
volume and liquidity filters
optional benchmark confirmation
The strategy looks for breakout and continuation behavior when market conditions support trend movement. It is especially useful for traders who want a structured framework for momentum continuation setups while still having the ability to customize the chart presentation.
Key Features
9 EMA and VWAP overlays
Dynamic basis line with bullish, bearish, and neutral coloring
Breakout and continuation entry logic
Relative volume and dollar-volume liquidity filters
Optional market benchmark filter
Risk-based position sizing
Stop, target, and break-even trade overlays
Optional ATR-based trailing logic
Compact on-chart dashboard
Tiny buy/sell triangle signal markers
Fully customizable colors and visibility controls
Trade overlays shown only during active positions to reduce clutter
How To Use It
TrendPulse is best used as a structured intraday tool for identifying trend continuation conditions.
General long idea Look for:
bullish trend alignment
price holding above important structure
supportive VWAP positioning
improving momentum or continuation behavior
sufficient liquidity and relative volume
General short idea Look for:
bearish trend alignment
price staying below important structure
weak VWAP positioning
downside continuation behavior
sufficient liquidity and relative volume
Entry logic
Depending on the selected mode, the strategy can look for:
Breakout setups
Continuation setups
or Both
This lets traders adapt the script to different market conditions and personal preferences.
Risk management
The script can calculate:
entry
stop
target
optional break-even behavior
optional trailing behavior
The active trade lines are shown only while a trade is open, then removed automatically once the position closes so the chart stays clean.
Dashboard Guide
The TrendPulse dashboard is designed to help traders quickly assess market condition, directional quality, momentum participation, and whether price may already be extended.
State
Shows the current market regime: Trend, Expand, Quiet, or Noisy.
Trend suggests cleaner directional structure and better follow-through potential.
Expand suggests volatility is increasing, which can support strong momentum but also faster reversals.
Quiet suggests a slower or compressed market where breakouts may fail more often.
Noisy suggests mixed or unstable behavior with less reliable continuation.
How to use it: This is a context filter. Trend and Expand conditions are generally more favorable than Quiet or Noisy conditions for momentum-based setups.
L / S
Shows the current Long Score and Short Score.
A higher Long Score suggests stronger bullish alignment.
A higher Short Score suggests stronger bearish alignment.
If both are weak or close together, directional edge may be limited.
How to use it: Helps identify which side has better structure and quality. A clear score imbalance can support directional bias, while similar or weak scores may suggest patience.
Chop
Measures how choppy or directional recent price action has been.
Lower values generally suggest cleaner trend behavior.
Higher values usually suggest more back-and-forth movement.
How to use it: Lower Chop is generally more favorable for continuation-style setups. Higher Chop often means a greater chance of fakeouts, failed breakouts, or messy follow-through.
ATR Exp
Shows the ATR expansion ratio, which compares current volatility to its recent average.
Higher values suggest the market is becoming more active.
Lower values suggest a quieter or less energized environment.
How to use it: Helps gauge whether a move has enough energy behind it to continue. Rising ATR Exp can support momentum, but very high expansion can also mean the move is becoming aggressive and may be approaching exhaustion.
Trend
Shows the current directional bias: Bull, Bear, or Flat.
Bull favors long-side continuation thinking.
Bear favors short-side continuation thinking.
Flat suggests weaker directional edge.
How to use it: A quick directional filter to help traders stay aligned with broader short-term structure instead of trading against it.
% vs 9 EMA
Shows the percent distance of price from the 9 EMA.
Positive values mean price is above the 9 EMA.
Negative values mean price is below the 9 EMA.
How to use it: Helps judge short-term extension. The farther price moves from the 9 EMA, the more likely it may be becoming overextended or moving toward a capitulation/exhaustion phase. Smaller distances often reflect healthier continuation positioning, while larger distances can warn against chasing entries too late.
% vs VWAP
Shows the percent distance of price from VWAP.
Positive values mean price is above VWAP.
Negative values mean price is below VWAP.
How to use it: Helps judge how far price has moved from the session’s average traded value. A modest distance can support trend control, but a large distance may indicate emotional expansion, late-stage extension, or growing mean-reversion risk. If both the 9 EMA and VWAP distances are highly stretched in the same direction, the move may be strong but also increasingly vulnerable to pullback or exhaustion.
Vol
Shows relative volume compared with recent average volume.
Higher values suggest stronger participation.
Lower values suggest weaker participation.
How to use it: Stronger volume can support the credibility of a breakout or continuation move. Weak volume may mean the setup looks good visually but lacks enough participation to sustain follow-through.
Best practice
The dashboard works best when read as a group rather than field by field. For example, Trend or Expand state, strong directional score imbalance, lower Chop, healthy ATR expansion, and supportive volume can point to a cleaner continuation environment. On the other hand, high Chop, weak score separation, and very stretched distance from both the 9 EMA and VWAP may suggest caution, delayed entries, or increased exhaustion risk.
Customization
One of the main goals of TrendPulse is flexibility.
Users can customize:
visibility of moving averages, basis, channels, VWAP, and 9 EMA
signal marker colors
dashboard location, size, and theme
trade overlay colors
score label visibility and sizing
background regime highlights
This allows traders to simplify the chart or make it more information-rich depending on how they use it.
Best Instruments
TrendPulse is generally best suited for:
liquid stocks
active ETFs
high-volume intraday names
momentum-focused equities
It tends to be more useful on instruments where:
volume is meaningful
spreads are not excessive
VWAP and momentum behavior matter intraday
It may be less effective on:
illiquid symbols
very low-volume names
assets with inconsistent intraday movement
heavily erratic charts with poor liquidity
Best Timeframes
This strategy is primarily designed for intraday use.
Most suitable timeframes:
1 minute
3 minute
5 minute
15 minute
Some traders may also experiment with:
30 minute
As always, settings may need adjustment depending on the instrument and timeframe being traded.
Notes
This script is intended as a structured strategy and visualization tool.
Users should test settings across different symbols and timeframes.
No single parameter set is ideal for every market.
Traders may prefer different combinations of breakout, continuation, and filtering logic depending on their own process.
Disclaimer
For educational and research purposes only.
This script does not constitute financial advice.
Always forward test, validate settings, and manage risk appropriately before using any strategy in live markets.
If you find TrendPulse useful, consider saving it, sharing feedback, and adapting the visuals and filters to match your own trading workflow.
Stratégie
Quiet Period Box with Key Earnings LevelThe green box is the new programming for the "Quiet Period" to show when a company doesn't comment on anything about the prospects for the company which means that analysts can have an undue influence on the stock price during the quiet period.
Once the company reports earnings, a "Green Triangle" is created to include the day before and the day after the earnings announcement to then reveal the important price level, or "Key Level" which is the mid-point of this price action around the earnings release.
How to USE the indicator: The interesting part of this analysis is how these reference price levels have an influence in the future trading of shares. If a stock is in a bullish trend, the mid-point of the earnings release is the ideal, low-risk point to enter long with a stop 1, 2 or 3 ranges on the other side of the "Key Level" in case it doesn't work out. The target can be a variety of techniques from using the width of the "quiet period" range added to the "earnings level" to derive a price target.
The inverse would also be true. If the general trend of a stock was down, the mid-point of the 'earnings level' would provide supply and stop the price advance after a down move on earnings. You can see for yourself looking back over the history of the stock whether or not this method would be a profitable approach or not.
What I like is having the knowledge of where the important levels are on a stock chart so when the price gets there I can then decide whether or not to take a trade. You can set alerts on the "earnings level" and the highs and lows of the "quiet period" box to alert you to when a stock is worth looking at.
Over a year ago, I made the "Earnings Level" free to all users here at TradingView after keeping it a fee-based private indicator for close to 10 years. I feel a great debt of gratitude for TradingView for creating this wonderful platform for all of us to share ideas and I wanted everyone to have this powerful indicator to help investors and traders alike.
Now with this "Quiet Period" box publication, the patterns in the chaos of market action can be more easily found and you can be more at peace with the volatility in each stock when you can see the stock has been in a pre-defined time-zone for comparison.
Wishing you all the best of good fortune in your investing and trading and I look forward to hearing your questions.
A huge thank you goes to Ivan Labrie here at TradingView @IvanLabrie for writing the code for this indicator. He is a champion of technical analysis and the many methods of the Time@Mode, Key Earnings, Risk, Reward, Psychology, Trend and options strategies.
Indicateur
MFx Structural Terrain Engine V1Description
Mfx Structural Terrain Engine is a market structure indicator designed to place price into a long-term structural context rather than relying on traditional overbought/oversold oscillators.
Instead of asking: "Is price high or low?"
the engine asks: "Where is price relative to its long-term structural growth path?"
The indicator combines:
Structural Power Law modeling
Long-term moving average context
Adaptive terrain zones
Multi-timeframe structural analysis to classify where price currently resides within the broader market cycle.
The engine is designed to work across multiple asset classes including cryptocurrencies, equities, ETFs, indices, commodities, and forex using asset-specific structural profiles and automatic higher-timeframe routing.
Rather than producing buy or sell signals, it provides a structural framework for evaluating opportunity, fair value, accumulation, and potential exhaustion.
Features
Multi-asset structural profiles
Automatic higher-timeframe routing (TradFi & Crypto)
Structural Power Law spine
Long-term structural moving average
Adaptive terrain bands
Market cycle positioning
Structural zone classification
Structural confidence scoring
Clean structural dashboard
Supported Markets
The Structural Terrain Engine is designed to analyze a wide range of markets, including:
Bitcoin
Cryptocurrencies
Stocks
ETFs
Market Indices
Commodities
Forex
Each asset class can use its own structural profile while the indicator automatically adapts its higher-timeframe context for continuous (crypto) and session-based (traditional) markets.
Terrain Zones...The terrain is divided into six structural regions.
Generational Opportunity...Historically represents periods of extreme structural undervaluation.
Deep Opportunity...Price remains significantly below structural value while long-term risk has historically been reduced.
Accumulation...Price begins transitioning back toward structural equilibrium.
Fair Value...Price is trading near its expected long-term structural path.
Extended...Price is becoming increasingly stretched above structural value.
Campaign Exhaustion...Historically associated with elevated structural risk and mature market cycles.
Dashboard Metrics
Market State...Summarizes the current structural zone together with the model's confidence.
Example: Deep Opportunity - Moderate Confidence
Price vs Spine: Shows where price is relative to the selected structural spine.
1.00× = Price is exactly on the structural model.
Above 1.00× = Price is trading above structure.
Below 1.00× = Price is trading below structure.
Distance to Spine: Displays the absolute price difference between the current market price and the structural spine.
Cycle Position: Normalizes price into a 0–100 structural cycle score.
Lower values generally represent deeper structural opportunity.
Higher values indicate progressively later-cycle conditions.
Current Zone: Displays the terrain region price currently occupies.
Model Alignment: Measures how closely the structural models agree with one another.
Higher values indicate stronger agreement between the independent structural models.
Signal Confidence: Represents the overall confidence of the structural assessment.
Higher confidence suggests stronger structural evidence supporting the current terrain classification.
Structural Growth: Shows how quickly the structural spine is advancing over time.
Positive values indicate structural expansion.
Timeframe Routing: The indicator automatically selects a higher-timeframe context based on the current chart.
Chart Context
15m 1H
30m 2H
1H 4H
3H 6H
6H 1D (TradFi) / 12H (Crypto)
12H 2D
1D 3D
3D 1W
1W 2W
2W 1M
Manual timeframe selection is also available.
Inputs
Structural Model
Asset Profile
Select the structural profile best suited for the instrument.
Examples include:
Bitcoin
Crypto
Equities
Commodities
Custom
Structural Spine
Choose which structural model is used as the primary reference.
Available options include:
Structural
Power Law
Context
Timeframe Routing
Choose how the higher-timeframe context is selected.
Options: Profile Default, Auto TradFi, Auto Crypto, Manual, Manual Higher Timeframe...Overrides automatic timeframe routing.
Terrain: Show Terrain Bands...Displays the structural valuation bands.
Show Structural Moving Average: Displays the higher-timeframe structural moving average.
Show Power Law: Displays the structural Power Law spine.
Show Zone Labels: Displays terrain zone labels beside the chart.
Zone Label Offset: Moves zone labels closer to or farther from price.
Zone Label Size: Adjusts the size of terrain labels.
Blending: Adjust how different structural models contribute to the final structural spine.
A reserved external-model weighting is included for future integration of additional verified structural models.
Who Is This For?
The Structural Terrain Engine is intended for investors and traders who want to understand where price sits within a larger structural cycle, rather than relying solely on short-term indicators. It can be used as a standalone market framework or alongside existing technical analysis for timing, confirmation, and risk management.
How to Use: The indicator is designed for structural analysis—not short-term trading signals.
Many traders use it to:
Identify long-term accumulation areas.
Gauge whether price is historically extended.
Monitor structural trend health.
Add higher-timeframe context to lower-timeframe decisions.
Evaluate market cycle progression.
Compare multiple asset classes using a consistent structural framework.
The terrain should be interpreted as a probabilistic framework rather than a prediction engine.
Notes
Confirmed higher-timeframe calculations do not repaint.
Structural models are intended for long-term market analysis.
Automatic timeframe routing adapts differently for traditional markets and 24/7 crypto markets.
The indicator is designed to provide structural context and should be used alongside sound risk management and additional market analysis. Indicateur
Volumetric Sweep Gravity Engine [PhenLabs]📊 Volumetric Sweep Gravity Engine
Version: PineScript™ v6
📌 Description
The Volumetric Sweep Gravity Engine detects true liquidity stop-hunts and only keeps the ones backed by real volume absorption. Instead of marking every wick beyond a swing, VSGE scores each sweep with volume expansion, wick geometry, and a candle delta proxy — then projects a Fibonacci golden-zone magnet where price is most likely to get pulled next.
Traders get a clean, high-contrast chart: absorption boxes that intensify with score strength, gold-tinted gravity zones, dotted magnet lines, dual glow signal markers, and a live PhenLabs command dashboard. Built for fast visual reads on crypto, indices, FX, and metals without clutter.
🚀 Points of Innovation
Triple-factor absorption score (volume × wick ratio × delta proxy) filters weak fake sweeps
Liquidity pool tracking from confirmed swing highs/lows with ATR-buffered sweep rules
Automatic Fibonacci golden-zone gravity targets (0.618–0.786) after valid sweeps
Score-reactive zone transparency — stronger absorption draws hotter, more opaque boxes
Dotted magnet projection lines from signal price into the golden-zone midpoint
Live VSGE dashboard with bias, last event, ABS score, GZ magnet, BSL/SSL pools, and vol pulse
🔧 Core Components
Liquidity Pool Engine: Confirms swing highs (BSL) and swing lows (SSL), then watches for wick violations with optional close-back-inside stop-hunt logic
Absorption Scorer: Composites volume-vs-SMA, wick-to-body geometry, and signed volume delta into a 0–100 score with configurable weights
Gravity Projector: Measures the impulse leg and maps the 61.8–78.6 golden zone as the expected rebalance magnet
Visual Command Layer: Absorption boxes, golden zones, magnet lines, glow markers, pool rails, and a gold-framed dashboard
🔥 Key Features
Bullish and bearish volumetric sweep signals with min score gate
Optional EMA trend filter and ATR volatility floor to skip dead markets
Toggleable pool lines, absorption boxes, labels, bar coloring, and magnet lines
Max active zone cap to keep charts clean on lower timeframes
Alert conditions for bull sweeps, bear sweeps, and any sweep
Fully open-source Pine v6 with organized input groups and tooltips
🎨 Visualization
Neon triangle + soft glow circle markers tagged “VSGE” for screenshot-ready signals
Absorption boxes labeled with live ABS % and opacity scaled to conviction
Dashed golden-zone rectangles with centered GOLDEN ZONE text
Dotted gold magnet lines pulling toward the zone midpoint
BSL/SSL pool rails in bear/bull tints for structural context
Top-right dark dashboard with gold border, bias coloring, and vol pulse readout
📖 Usage Guidelines
Swing Lookback — Default: 5 — Range: 2-30 — Higher = fewer, more structural pools
Sweep Buffer (ATR mult) — Default: 0.05 — Range: 0-1 — Extra wick extension required beyond the pool
Require Close Back Inside — Default: true — Enforces classic stop-hunt reclaim closes
Min Sweep Wick (ATR) — Default: 0.15 — Range: 0.05-2 — Rejects tiny liquidity nicks
Volume SMA Length — Default: 20 — Range: 5-100 — Baseline for absorption volume
Absorption Volume Mult — Default: 1.4 — Range: 1-5 — Minimum volume expansion vs SMA
Min Wick/Body Ratio — Default: 1.5 — Range: 0.5-10 — Ensures rejection-style geometry
Min Absorption Score — Default: 55 — Range: 0-100 — Composite gate for signals
Golden Zone Low/High (Fib) — Default: 0.618 / 0.786 — Retracement band for gravity targets
Impulse Lookback Bars — Default: 8 — Range: 3-40 — Bars used to size the impulse leg
Max Active Zones — Default: 6 — Range: 1-20 — Limits drawn boxes/lines/labels
EMA Trend Filter — Default: off — Optional 200 EMA directional gate
Min ATR Volatility Filter — Default: on — Skips low-volatility chop vs ATR SMA
✅ Best Use Cases
Intraday liquidity-grab reversals on crypto, Nasdaq, Gold, and major FX pairs
Confirming stop-hunts before entering toward the golden-zone magnet
Filtering pure wick noise by requiring volumetric absorption
Screenshot-friendly SMC setups for education, social posts, and journal reviews
⚠️ Limitations
Delta is a candle-geometry proxy, not true bid/ask order-flow data
Pivot pools confirm with lag equal to the swing lookback
Golden zones are probabilistic magnets, not guaranteed fill targets
Dense lower-timeframe charts may need higher min score or lower max zones
💡 What Makes This Unique
Fuses liquidity sweeps + volumetric absorption scoring + Fibonacci gravity in one engine — a combination missing from pure sweep or pure Fib tools
Score-reactive visuals make conviction readable at a glance for SEO screenshots and live trading
PhenLabs-style command dashboard turns structure, score, and magnet price into a single decision panel
🔬 How It Works
Map liquidity pools from confirmed swing highs (BSL) and swing lows (SSL)
Detect sweeps when price wicks beyond a pool by ATR buffer and optionally closes back inside
Score absorption using volume expansion, wick/body geometry, and signed delta proxy
If score clears the minimum gate, draw the absorption box and project the 0.618–0.786 golden gravity zone with a magnet line
Update the live dashboard (bias, last event, ABS score, GZ magnet, pools, vol pulse) and fire alerts
💡 Note:
Use VSGE as a confluence layer with your own risk rules, higher-timeframe bias, and position sizing. This is an analytical aid for studying liquidity and absorption behavior — not financial advice. Indicateur
Multi-Timeframe Trend Matrix [JOAT]Multi-Timeframe Trend Matrix
Reads several timeframes with several methods at once and scores their agreement into a single alignment signal — without lookahead.
What it is
Trading a single timeframe blinds you to the larger context; watching many by eye is slow and inconsistent. This indicator evaluates a grid of timeframes and trend methods, turns the whole grid into one alignment score, and signals when top-down agreement forms. It is an original multi-timeframe aggregation tool built to avoid the common pitfalls of higher-timeframe requests.
How it works
• The matrix — a set of higher and lower timeframes is each assessed by several independent trend methods (such as a moving-average relationship, a directional trend measure and a momentum read). Each cell of the grid returns simply bullish or bearish, so the picture is easy to interpret.
• No lookahead — every higher-timeframe value is pulled with lookahead disabled, so the indicator never borrows future data from an unclosed higher-timeframe bar. This is a deliberate, disclosed design choice that keeps the signals honest and non-repainting on historical bars.
• Alignment score — the grid is condensed into one signed score representing how strongly all timeframes and methods agree. Full agreement produces a strong reading; a split grid produces a weak, near-neutral one.
• State-machine signals — a Buy fires when alignment turns sufficiently bullish from a non-bullish state; a Sell is the mirror. Requiring a state change means the matrix will not re-signal the same direction repeatedly — the signals are self-spacing.
Trade levels
Each signal draws a red risk box to the ATR stop and a green reward box to the third target, with inner dividers and right-edge labels for entry, stop and each take-profit at your R multiples.
The dashboard
An adjustable alignment-matrix panel displays every timeframe-by-method cell as bullish or bearish, a bipolar alignment-score headline, the active signal, a conviction estimate, and a live first-target-before-stop tally from closed bars only. The grid shows exactly which timeframes agree and which disagree.
How to use it
• Works on any asset; pick a base timeframe and let the grid supply the higher-timeframe context.
• Favour entries when the grid is broadly aligned; be cautious when it is mixed.
• Use it as a top-down filter alongside your own entry method, or take its aligned signals directly.
Settings
The set of timeframes, the methods and their lengths, the alignment threshold, ATR risk multiple and target R multiples, plus visual and dashboard controls.
Originality and usefulness
The contribution is the aggregation framework: a disciplined, lookahead-free multi-timeframe, multi-method grid condensed into one transparent alignment score with a state-machine trigger. Seeing the full grid — not just a final arrow — is what lets a trader trust or override the signal for themselves.
Notes and limitations
• Higher-timeframe values update only as those bars close, so alignment can shift when a higher-timeframe bar completes — this is expected and prevents lookahead bias.
• Strong alignment can still precede a reversal; agreement is context, not certainty.
• The tally reflects only past bars on the current chart and is not a forecast.
• Educational and analytical tool, not financial advice.
— made with passion by officialjackofalltrades
Indicateur
Rogue Overnight Volume ProfileRogue Overnight Volume Profile
The Rogue Overnight Volume Profile is an institutional-style overnight volume profile designed specifically for futures traders who use overnight auction structure to prepare for the Regular Trading Hours (RTH) session.
Unlike traditional session volume profiles that remain fixed throughout the day, Rogue Overnight Profile automatically builds the overnight distribution, identifies the most important price levels, and projects them into the current trading session for easy decision making.
Features:
Overnight Volume Profile
Automatically builds a complete volume profile during the overnight session.
Adjustable profile resolution with up to 1,000 price rows.
Value Area (default 70%)
Point of Control (POC)
Value Area High (OVAH)
Value Area Low (OVAL)
Customizable profile colors and placement.
Dynamic Overnight Levels
The indicator automatically calculates and plots:
OVAH (Overnight Value Area High)
OPOC (Overnight Point of Control)
OVAL (Overnight Value Area Low)
These levels begin at the start of the completed overnight profile and extend just beyond current price during the New York session, keeping the chart clean while maintaining important reference levels.
Historical overnight levels are retained for previous sessions to assist with market structure analysis.
Developing Overnight Range:
Monitor the overnight auction as it forms with an optional shaded developing range, allowing traders to visualize overnight balance before the market opens.
Weekly VWAP
Includes a built-in Weekly VWAP with customizable color and line width to provide higher-timeframe context and institutional bias.
5-Period Moving Average
A configurable 5-period moving average (EMA or SMA) can be displayed to help identify short-term momentum and trend direction.
First Touch Detection
Automatically identifies the first interaction with overnight profile levels during the New York session.
Supported first-touch signals include:
OVAH First Touch
OPOC First Touch
OVAL First Touch
These areas often act as important decision points where responsive buyers or sellers may enter the market.
Break & Retest Detection
The indicator can also detect break-and-retest setups after price establishes acceptance above or below an overnight level.
Bullish and bearish retest opportunities are labeled automatically, making it easier to identify continuation setups around key profile references.
Fully Customizable
Every major component can be enabled, disabled, or customized, including:
Session times
Profile resolution
Value Area percentage
Historical sessions displayed
Colors
Labels
Weekly VWAP
Moving Average
Touch detection
Retest detection
Designed For
Nasdaq Futures (NQ)
S&P Futures (ES)
Dow Futures (YM)
Russell Futures (RTY)
Crude Oil (CL)
Any market where overnight auction structure influences the regular session.
Best Used For
Identifying overnight support and resistance.
Planning opening scenarios.
Fade and acceptance trades around OVAH, OPOC, and OVAL.
Breakout confirmation.
Break-and-retest continuation setups.
Understanding overnight market positioning before the RTH open.
Disclaimer: This indicator is intended as a decision-support tool and does not provide financial advice. Always incorporate sound risk management and additional market context before entering any trade. Indicateur
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Forward P/E (MUST COMPLETE STEP 1 FOR INDICATOR TO WORK)Forward P/E Valuation Indicator (MUST COMPLETE STEP 1 FOR THE INDICATOR TO WORK)
1. Set up the indicator
Use the indicator on a 1-day chart. Its one- and three-year calculations assume daily bars.
First, add these TradingView indicators to your chart:
a. P/E forward
b. Price/earnings to growth ratio, usually shown as PEG ratio
c. Then add the custom Forward P/E Valuation indicator.
Open the "Forward P/E Valuation indicator" settings → Inputs and select:
P/E forward → Choose the P/E forward from the dropdown
Price/earnings to growth ratio → Choose the PEG ratio from the dropdown
After selecting the correct sources, click to add a checkmark to the following boxes:
a. P/E forward source linked correctly
b. PEG source linked correctly
Now, the "Forward P/E Valuation" indicator will work.
2. Recommended settings
The default settings are appropriate for most stocks:
Chart band lookback: 3 Years
Forward EPS trend threshold: 2%
Primary-driver lookback: 21 bars
Primary-driver threshold: 3%
Growth-supported premium threshold: 15%
Growth-supportive PEG: 1.5×
Use the three-year lookback for the main interpretation. Switch to one year only when you want to emphasize the stock’s recent valuation regime.
How to read the dashboard:
Read the first four rows first. They summarize the model’s conclusion.
Overall Valuation Status
This compares the current forward P/E with its selected historical range.
Rank
Status
0%–5% = Deep Discount
Above 5%–10% = Cheap
Above 10%–25% = Below Normal
Above 25%–Below 75% = Normal
75%–Below 90% = Above Normal
90%–Below 95% = Expensive
95%–100% = Extreme Expensive
A low percentile means the forward P/E is low relative to its own history. It does not automatically mean the stock is undervalued.
Valuation + Growth Signal
This combines valuation, growth, estimate direction, and PEG.
Signal
Meaning
Attractive Discount
Historically inexpensive with supportive growth or rising estimates
Potential Value
Cheap, but growth confirmation is limited
Value-Trap Risk
Cheap while growth or estimates are deteriorating
Growth-Supported Premium
Expensive, but strong growth may justify the premium
Multiple Risk
Expensive without enough growth support
High-Risk Premium
Expensive while estimates or growth are deteriorating
Improving Fundamentals
Normal valuation with rising estimates
Balanced
Normal valuation with stable estimates
The strongest favorable reading is Attractive Discount. The most concerning is High-Risk Premium.
Valuation + Estimate Direction
This gives a simpler valuation-versus-estimates interpretation.
Reading
Interpretation
Discount + Upgrades
Favorable valuation with improving estimates
Discount + Stable Estimates
Potential value, but no estimate catalyst
Discount + Cuts
Possible value trap
Normal + Upgrades
Improving fundamentals at a normal valuation
Premium + Upgrades
Expensive but supported by estimate improvement
Premium + Cuts
Highest-risk combination
Primary Driver
This explains what caused the recent movement over approximately 21 trading days.
Driver
Meaning
Earnings-Led Advance
Price rose mainly because forward EPS improved
Price + Estimate Expansion
Both estimates and the valuation multiple improved
Price-Led Multiple Expansion
Price rose without much earnings improvement
Estimate Upgrades / Price Lag
Estimates improved, but price has not responded
Price-Led Multiple Compression
Price fell more than estimates, making valuation cheaper
Estimate Cuts
Forward earnings expectations weakened
Price Up Despite Estimate Cuts
Price rose while estimates declined; caution
Stable / Consolidation
No major price, EPS, or P/E movement
The Context column shows the actual price, EPS, and P/E percentage changes used in the classification.
Supporting dashboard rows
TradingView Forward P/E
This is the directly linked TradingView forward-P/E value. It drives the historical ranks, medians, bands, and valuation status.
Implied Forward EPS
Calculated as:
Implied Forward EPS=Stock PriceForward P/E\text{Implied Forward EPS} = \frac{\text{Stock Price}}{\text{Forward P/E}}Implied Forward EPS=Forward P/EStock Price
Example:
210÷21=$10.00210\div21=\$10.00210÷21=$10.00
This is the earnings denominator implied by TradingView’s forward-P/E reading.
Current P/E Ratio
Calculated from:
Price÷Trailing-12-Month EPS\text{Price}\div\text{Trailing-12-Month EPS}Price÷Trailing-12-Month EPS
A forward P/E materially below the current P/E generally indicates expected earnings growth.
Forward EPS Growth Proxy
Compares implied forward EPS with the latest reported fiscal-year diluted EPS.
General interpretation:
Negative: expected earnings deterioration
0%–10%: limited growth
10%–15%: moderate growth
Above 15%: strong growth
This is a proxy, not a perfect analyst-consensus growth measure.
PEG Ratio
The PEG value comes from the linked TradingView PEG indicator.
Below 1.0×: low valuation relative to growth
1.0×–1.5×: generally growth supportive
1.5×–2.0×: moderate premium
Above 2.0×: valuation increasingly dependent on sustained growth
Do not use PEG alone. Cyclical or temporarily depressed earnings can distort it.
1Y / 3Y P/E Rank
Shows where the current forward P/E falls relative to its one- and three-year history.
Example:
12% / 38%
The stock is inexpensive compared with the past year, but closer to normal compared with the past three years.
1Y / 3Y Median P/E
Shows the stock’s typical forward P/E over each period.
If the current P/E is below both medians, the stock is trading below its recent historical norms.
Forward EPS Trend
Rising: latest detected revision above +2%
Stable: between −2% and +2%
Falling: below −2%
Rising estimates generally strengthen a favorable valuation signal. Falling estimates weaken it.
Estimate Freshness
Fresh: 0–100 days
Aging: 101–180 days
Stale: more than 180 days
This measures how long it has been since the model detected a meaningful change in implied forward EPS. It is not necessarily the exact analyst-revision date.
Model Confidence
High: 80%–100%
Medium: 60%–79%
Low: below 60%
Confidence reflects source links, historical coverage, available EPS data, freshness, and use of a daily chart.
Low confidence means insufficient data—not necessarily a negative stock outlook.
Two practical examples
Favorable setup
Overall Valuation: Cheap
Valuation + Growth: Attractive Discount
Valuation + Estimate Direction: Discount + Upgrades
Primary Driver: Earnings-Led Advance
Forward EPS Trend: Rising
Confidence: High
Interpretation: the stock is historically inexpensive, estimates are improving, and earnings rather than pure multiple expansion are supporting the move.
Warning setup
Overall Valuation: Expensive
Valuation + Growth: High-Risk Premium
Valuation + Estimate Direction: Premium + Cuts
Primary Driver: Price Up Despite Estimate Cuts
Forward EPS Trend: Falling
Confidence: High
Interpretation: the stock is historically expensive while earnings expectations are weakening. Price strength is being supported primarily by multiple expansion, which increases downside risk.
Best quick-reading rule
The most favorable combination is:
Discount + Upgrades + Attractive Discount + Earnings-Led Advance
The most concerning combination is:
Premium + Cuts + High-Risk Premium + Price Up Despite Estimate Cuts
Here is the code:
//@version=6
indicator("Forward P/E Linked Metrics ", shorttitle="Forward PE", overlay=false, max_bars_back=2000, precision=2)
// ============================================================================
// PURPOSE
// ============================================================================
// This version links only the TradingView plots that are available through
// input.source():
//
// Required linked sources:
// 1. TradingView "P/E forward"
// 2. TradingView "Price/earnings to growth ratio" / "PEG ratio"
//
// The regular current P/E is calculated internally:
// Current P/E = Current price / TTM EPS
//
// The model recovers the forward EPS denominator from the linked forward P/E:
// Implied forward EPS = Current price / Linked forward P/E
//
// If the linked P/E-forward plot is TradingView's live price-to-forward-EPS
// series, this inversion recovers the underlying forward EPS estimate while
// preserving an exact match with TradingView's displayed forward P/E.
//
// Use primarily on a 1D chart so 252 and 756 bars approximate 1 and 3 years.
//
// Added decision framework:
// 1. Overall Valuation Status
// 2. Valuation + Growth Signal
// 3. Valuation + Estimate Direction
// 4. Primary Driver
// ============================================================================
// 1. LINK TRADINGVIEW METRICS
// ============================================================================
grpLinks = "1. Link TradingView Metrics"
forwardPESource = input.source(
close,
"P/E forward",
tooltip="Select the plot from TradingView's built-in P/E forward indicator.",
group=grpLinks,
display=display.none)
pegRatioSource = input.source(
close,
"Price/earnings to growth ratio",
tooltip="Select the plot from TradingView's PEG ratio indicator.",
group=grpLinks,
display=display.none)
confirmForwardPELinked = input.bool(
false,
"P/E forward source linked correctly",
group=grpLinks,
display=display.none)
confirmPEGLinked = input.bool(
false,
"PEG source linked correctly",
group=grpLinks,
display=display.none)
// ============================================================================
// 2. MODEL SETTINGS
// ============================================================================
grpModel = "2. Model Settings"
minValidEPS = input.float(
0.01,
"Minimum valid implied forward EPS",
minval=0.0001,
step=0.01,
group=grpModel,
display=display.none)
maxValidEPS = input.float(
1000.0,
"Maximum valid implied forward EPS",
minval=1.0,
step=10.0,
group=grpModel,
display=display.none)
minValidPE = input.float(
0.1,
"Minimum valid P/E",
minval=0.0,
step=0.1,
group=grpModel,
display=display.none)
maxValidPE = input.float(
500.0,
"Maximum valid P/E",
minval=1.0,
step=5.0,
group=grpModel,
display=display.none)
maxValidPEG = input.float(
100.0,
"Maximum valid PEG",
minval=1.0,
step=1.0,
group=grpModel,
display=display.none)
chartLookback = input.string(
"3 Years",
"Chart band lookback",
options= ,
group=grpModel,
display=display.none)
trendThreshold = input.float(
2.0,
"Forward EPS revision trend threshold %",
minval=0.0,
step=0.25,
group=grpModel,
display=display.none)
revisionDetectionPct = input.float(
0.05,
"Minimum implied EPS change counted as a revision %",
minval=0.001,
step=0.01,
group=grpModel,
display=display.none)
freshDays = input.int(
100,
"Fresh estimate: maximum calendar days",
minval=1,
group=grpModel,
display=display.none)
staleDays = input.int(
180,
"Aging estimate: maximum calendar days",
minval=2,
group=grpModel,
display=display.none)
primaryDriverLookback = input.int(
21,
"Primary driver lookback bars",
minval=5,
maxval=252,
group=grpModel,
display=display.none)
primaryDriverThreshold = input.float(
3.0,
"Primary driver movement threshold %",
minval=0.5,
step=0.5,
group=grpModel,
display=display.none)
growthSupportThreshold = input.float(
15.0,
"Growth-supported premium threshold %",
minval=0.0,
step=1.0,
group=grpModel,
display=display.none)
attractivePEGThreshold = input.float(
1.5,
"PEG threshold considered growth supportive",
minval=0.1,
step=0.1,
group=grpModel,
display=display.none)
// ============================================================================
// 3. VISUALS & DASHBOARD
// ============================================================================
grpVisual = "3. Visuals & Dashboard"
showMedianLine = input.bool(
true,
"Show historical median",
group=grpVisual,
display=display.none)
showPercentileBands = input.bool(
true,
"Show percentile bands",
group=grpVisual,
display=display.none)
showNormalZoneFill = input.bool(
true,
"Fill normal valuation zone",
group=grpVisual,
display=display.none)
showExtremeBackground = input.bool(
false,
"Highlight 5th / 95th percentile extremes",
group=grpVisual,
display=display.none)
showDashboard = input.bool(
true,
"Show dashboard",
group=grpVisual,
display=display.none)
dashboardPosition = input.string(
"Top Right",
"Dashboard position",
options= ,
group=grpVisual,
display=display.none)
// ============================================================================
// CONSTANTS
// ============================================================================
bars1Y = 252
bars3Y = 756
dayMs = 86400000.0
selectedLength = chartLookback == "1 Year" ? bars1Y : bars3Y
// ============================================================================
// COLOR PALETTE — LIGHT CHART / DARK DASHBOARD
// ============================================================================
clrSlate0 = color.rgb(45, 52, 64)
clrSlate1 = color.rgb(55, 62, 74)
clrSlate2 = color.rgb(69, 76, 88)
clrText = color.rgb(248, 249, 251)
clrMuted = color.rgb(205, 211, 220)
clrDarkText = color.rgb(42, 49, 60)
clrGreenText = color.rgb(18, 145, 88)
clrRedText = color.rgb(211, 52, 69)
clrAmberText = color.rgb(181, 112, 8)
clrTeal = color.rgb(35, 190, 208)
clrAqua = color.rgb(70, 198, 235)
clrBlue = color.rgb(72, 116, 235)
clrGreen = color.rgb(40, 178, 109)
clrAmber = color.rgb(245, 179, 48)
clrOrange = color.rgb(245, 153, 36)
clrRed = color.rgb(235, 74, 91)
clrGrayLine = color.rgb(116, 125, 140)
clrLightCyan = color.rgb(126, 216, 233)
clrLightBlue = color.rgb(202, 232, 242)
clrLightGray = color.rgb(205, 209, 215)
clrLightMint = color.rgb(214, 241, 226)
clrLightAmber = color.rgb(250, 232, 192)
clrLightRed = color.rgb(249, 220, 225)
// ============================================================================
// HELPERS
// ============================================================================
f_valid_eps(_value) =>
not na(_value) and _value >= minValidEPS and _value <= maxValidEPS ? _value : na
f_valid_pe(_value) =>
not na(_value) and _value >= minValidPE and _value <= maxValidPE ? _value : na
f_valid_peg(_value) =>
not na(_value) and _value > 0.0 and _value <= maxValidPEG ? _value : na
f_x(_value) =>
na(_value) ? "n/a" : str.tostring(_value, "#.##") + "x"
f_pct(_value) =>
na(_value) ? "n/a" : str.tostring(_value, "#.##") + "%"
f_eps(_value) =>
na(_value) ? "n/a" : str.tostring(_value, "#.##")
f_rank_text(_value) =>
na(_value) ? "n/a" : str.tostring(_value, "#") + "%"
f_position(_selection) =>
_selection == "Top Left" ? position.top_left :
_selection == "Bottom Right" ? position.bottom_right :
_selection == "Bottom Left" ? position.bottom_left :
position.top_right
f_rank_color(_rank, _ready) =>
color _result = clrGrayLine
if _ready and not na(_rank)
if _rank >= 95
_result := clrRed
else if _rank >= 90
_result := clrOrange
else if _rank >= 75
_result := clrAmber
else if _rank <= 5
_result := clrBlue
else if _rank <= 10
_result := clrAqua
else if _rank <= 25
_result := clrTeal
else
_result := clrGrayLine
_result
f_rank_fill_color(_rank, _ready) =>
color _result = clrLightGray
if _ready and not na(_rank)
if _rank >= 95
_result := clrLightRed
else if _rank >= 75
_result := clrLightAmber
else if _rank <= 25
_result := clrLightCyan
else
_result := clrLightGray
_result
// ============================================================================
// LINKED METRICS
// ============================================================================
linkedForwardPE = confirmForwardPELinked ? f_valid_pe(forwardPESource) : na
linkedPEG = confirmPEGLinked ? f_valid_peg(pegRatioSource) : na
// Regular trailing P/E calculated internally using TradingView's documented
// price-to-TTM-EPS method.
epsTTMRaw = request.financial(
syminfo.tickerid,
"EARNINGS_PER_SHARE",
"TTM",
gaps=barmerge.gaps_off,
ignore_invalid_symbol=true,
currency=syminfo.currency)
epsTTM = f_valid_eps(epsTTMRaw)
currentPERatio = f_valid_pe(
not na(epsTTM) and epsTTM > 0.0 ? close / epsTTM : na)
// Invert TradingView's linked forward P/E to recover its implied forward EPS.
impliedForwardEPS = f_valid_eps(
not na(linkedForwardPE) and linkedForwardPE > 0.0 ? close / linkedForwardPE : na)
// Latest annual diluted EPS is used only as a baseline for a growth proxy.
priorFYDilutedEPSRaw = request.financial(
syminfo.tickerid,
"EARNINGS_PER_SHARE_DILUTED",
"FY",
gaps=barmerge.gaps_off,
ignore_invalid_symbol=true,
currency=syminfo.currency)
priorFYDilutedEPS = f_valid_eps(priorFYDilutedEPSRaw)
forwardEPSGrowthProxy =
not na(impliedForwardEPS) and not na(priorFYDilutedEPS) and priorFYDilutedEPS > 0.0 ?
((impliedForwardEPS / priorFYDilutedEPS) - 1.0) * 100.0 :
na
// The PEG identity is PEG = P/E ÷ growth rate. When both linked metrics are
// available, this recovers the growth rate implicit in TradingView's PEG.
pegImpliedGrowthPct =
not na(currentPERatio) and not na(linkedPEG) and linkedPEG > 0.0 ?
currentPERatio / linkedPEG :
na
// ============================================================================
// IMPLIED FORWARD EPS TREND AND FRESHNESS
// ============================================================================
impliedEPSChangePct =
not na(impliedForwardEPS) and
not na(impliedForwardEPS ) and
impliedForwardEPS != 0.0 ?
((impliedForwardEPS / impliedForwardEPS ) - 1.0) * 100.0 :
na
impliedEPSChanged =
not na(impliedEPSChangePct) and
math.abs(impliedEPSChangePct) >= revisionDetectionPct
var float latestPublishedEstimate = na
var float priorPublishedEstimate = na
var int lastEstimateUpdateTime = na
if impliedEPSChanged
priorPublishedEstimate := latestPublishedEstimate
latestPublishedEstimate := impliedForwardEPS
lastEstimateUpdateTime := time
// Seed the latest available estimate without falsely labeling it a revision.
if na(latestPublishedEstimate) and not na(impliedForwardEPS)
latestPublishedEstimate := impliedForwardEPS
estimateRevisionPct =
not na(latestPublishedEstimate) and
not na(priorPublishedEstimate) and
priorPublishedEstimate != 0.0 ?
((latestPublishedEstimate / priorPublishedEstimate) - 1.0) * 100.0 :
na
string estimateTrendText = "No prior revision"
color estimateTrendColor = clrMuted
if not na(estimateRevisionPct)
if estimateRevisionPct > trendThreshold
estimateTrendText := "Rising"
estimateTrendColor := clrGreen
else if estimateRevisionPct < -trendThreshold
estimateTrendText := "Falling"
estimateTrendColor := clrRed
else
estimateTrendText := "Stable"
estimateTrendColor := clrAmber
estimateAgeDays =
not na(lastEstimateUpdateTime) ?
(time - lastEstimateUpdateTime) / dayMs :
na
string freshnessText = "No revision date"
color freshnessColor = clrMuted
if not na(estimateAgeDays)
if estimateAgeDays <= freshDays
freshnessText := "Fresh"
freshnessColor := clrGreen
else if estimateAgeDays <= staleDays
freshnessText := "Aging"
freshnessColor := clrAmber
else
freshnessText := "Stale"
freshnessColor := clrRed
// ============================================================================
// HISTORICAL RANKS AND MEDIANS — 1Y / 3Y ONLY
// ============================================================================
var int validHistoryBars = 0
validHistoryBars := not na(linkedForwardPE) ? nz(validHistoryBars ) + 1 : 0
has1Y = validHistoryBars >= bars1Y
has3Y = validHistoryBars >= bars3Y
hasSelectedHistory = validHistoryBars >= selectedLength
rank1YRaw = ta.percentrank(linkedForwardPE, bars1Y)
rank3YRaw = ta.percentrank(linkedForwardPE, bars3Y)
median1YRaw = ta.percentile_linear_interpolation(linkedForwardPE, bars1Y, 50)
median3YRaw = ta.percentile_linear_interpolation(linkedForwardPE, bars3Y, 50)
rank1Y = has1Y ? rank1YRaw : na
rank3Y = has3Y ? rank3YRaw : na
median1Y = has1Y ? median1YRaw : na
median3Y = has3Y ? median3YRaw : na
selectedRankRaw = ta.percentrank(linkedForwardPE, selectedLength)
selectedP95Raw = ta.percentile_linear_interpolation(linkedForwardPE, selectedLength, 95)
selectedP90Raw = ta.percentile_linear_interpolation(linkedForwardPE, selectedLength, 90)
selectedP50Raw = ta.percentile_linear_interpolation(linkedForwardPE, selectedLength, 50)
selectedP10Raw = ta.percentile_linear_interpolation(linkedForwardPE, selectedLength, 10)
selectedP05Raw = ta.percentile_linear_interpolation(linkedForwardPE, selectedLength, 5)
selectedRank = hasSelectedHistory ? selectedRankRaw : na
selectedP95 = hasSelectedHistory ? selectedP95Raw : na
selectedP90 = hasSelectedHistory ? selectedP90Raw : na
selectedP50 = hasSelectedHistory ? selectedP50Raw : na
selectedP10 = hasSelectedHistory ? selectedP10Raw : na
selectedP05 = hasSelectedHistory ? selectedP05Raw : na
// ============================================================================
// DECISION FRAMEWORK
// ============================================================================
// Overall valuation status is based on the selected 1Y or 3Y percentile rank.
string overallValuationText = "Insufficient history"
color overallValuationColor = clrGrayLine
color overallValuationBg = clrLightGray
if not na(linkedForwardPE) and hasSelectedHistory and not na(selectedRank)
if selectedRank >= 95
overallValuationText := "Extreme Expensive"
overallValuationColor := clrRed
overallValuationBg := clrLightRed
else if selectedRank >= 90
overallValuationText := "Expensive"
overallValuationColor := clrOrange
overallValuationBg := clrLightAmber
else if selectedRank >= 75
overallValuationText := "Above Normal"
overallValuationColor := clrAmber
overallValuationBg := clrLightAmber
else if selectedRank <= 5
overallValuationText := "Deep Discount"
overallValuationColor := clrBlue
overallValuationBg := clrLightCyan
else if selectedRank <= 10
overallValuationText := "Cheap"
overallValuationColor := clrAqua
overallValuationBg := clrLightCyan
else if selectedRank <= 25
overallValuationText := "Below Normal"
overallValuationColor := clrTeal
overallValuationBg := clrLightCyan
else
overallValuationText := "Normal"
overallValuationColor := clrGrayLine
overallValuationBg := clrLightGray
cheapValuation = hasSelectedHistory and not na(selectedRank) and selectedRank <= 25
premiumValuation = hasSelectedHistory and not na(selectedRank) and selectedRank >= 75
veryExpensiveValuation = hasSelectedHistory and not na(selectedRank) and selectedRank >= 90
growthPositive =
(not na(forwardEPSGrowthProxy) and forwardEPSGrowthProxy >= 10.0) or
estimateTrendText == "Rising"
growthStrong =
(not na(forwardEPSGrowthProxy) and forwardEPSGrowthProxy >= growthSupportThreshold) or
(not na(linkedPEG) and linkedPEG <= attractivePEGThreshold)
growthWeak =
(not na(forwardEPSGrowthProxy) and forwardEPSGrowthProxy <= 0.0) or
estimateTrendText == "Falling"
// Combines valuation, expected growth, estimate direction, and linked PEG.
string valuationGrowthText = "Awaiting data"
color valuationGrowthColor = clrGrayLine
color valuationGrowthBg = clrLightGray
if hasSelectedHistory and not na(selectedRank)
if cheapValuation
if growthWeak
valuationGrowthText := "Value-Trap Risk"
valuationGrowthColor := clrRed
valuationGrowthBg := clrLightRed
else if growthPositive or growthStrong
valuationGrowthText := "Attractive Discount"
valuationGrowthColor := clrGreen
valuationGrowthBg := clrLightMint
else
valuationGrowthText := "Potential Value"
valuationGrowthColor := clrTeal
valuationGrowthBg := clrLightCyan
else if premiumValuation
if growthWeak
valuationGrowthText := "High-Risk Premium"
valuationGrowthColor := clrRed
valuationGrowthBg := clrLightRed
else if growthStrong
valuationGrowthText := "Growth-Supported Premium"
valuationGrowthColor := clrAmber
valuationGrowthBg := clrLightAmber
else
valuationGrowthText := "Multiple Risk"
valuationGrowthColor := clrOrange
valuationGrowthBg := clrLightAmber
else
if estimateTrendText == "Rising"
valuationGrowthText := "Improving Fundamentals"
valuationGrowthColor := clrGreen
valuationGrowthBg := clrLightMint
else if estimateTrendText == "Falling"
valuationGrowthText := "Estimate Deterioration"
valuationGrowthColor := clrRed
valuationGrowthBg := clrLightRed
else
valuationGrowthText := "Balanced"
valuationGrowthColor := clrGrayLine
valuationGrowthBg := clrLightGray
// A direct matrix combining the valuation regime with estimate direction.
string valuationEstimateText = "Awaiting data"
color valuationEstimateColor = clrGrayLine
color valuationEstimateBg = clrLightGray
if hasSelectedHistory and not na(selectedRank)
string valuationBucket = cheapValuation ? "Discount" : premiumValuation ? "Premium" : "Normal"
string directionBucket = estimateTrendText == "Rising" ? "Upgrades" : estimateTrendText == "Falling" ? "Cuts" : "Stable Estimates"
valuationEstimateText := valuationBucket + " + " + directionBucket
if cheapValuation and estimateTrendText == "Rising"
valuationEstimateColor := clrGreen
valuationEstimateBg := clrLightMint
else if cheapValuation and estimateTrendText == "Falling"
valuationEstimateColor := clrRed
valuationEstimateBg := clrLightRed
else if premiumValuation and estimateTrendText == "Falling"
valuationEstimateColor := clrRed
valuationEstimateBg := clrLightRed
else if premiumValuation and estimateTrendText == "Rising"
valuationEstimateColor := clrAmber
valuationEstimateBg := clrLightAmber
else if estimateTrendText == "Rising"
valuationEstimateColor := clrGreen
valuationEstimateBg := clrLightMint
else if estimateTrendText == "Falling"
valuationEstimateColor := clrRed
valuationEstimateBg := clrLightRed
else
valuationEstimateColor := clrGrayLine
valuationEstimateBg := clrLightGray
// Primary driver compares price, implied forward EPS, and forward P/E changes.
priceChangePct =
not na(close ) and close != 0.0 ?
((close / close ) - 1.0) * 100.0 :
na
forwardEPSChangePct =
not na(impliedForwardEPS) and
not na(impliedForwardEPS ) and
impliedForwardEPS != 0.0 ?
((impliedForwardEPS / impliedForwardEPS ) - 1.0) * 100.0 :
na
forwardPEChangePct =
not na(linkedForwardPE) and
not na(linkedForwardPE ) and
linkedForwardPE != 0.0 ?
((linkedForwardPE / linkedForwardPE ) - 1.0) * 100.0 :
na
string primaryDriverText = "Insufficient data"
color primaryDriverColor = clrGrayLine
color primaryDriverBg = clrLightGray
if not na(priceChangePct) and not na(forwardEPSChangePct) and not na(forwardPEChangePct)
bool priceUp = priceChangePct > primaryDriverThreshold
bool priceDown = priceChangePct < -primaryDriverThreshold
bool epsUp = forwardEPSChangePct > primaryDriverThreshold
bool epsDown = forwardEPSChangePct < -primaryDriverThreshold
bool peUp = forwardPEChangePct > primaryDriverThreshold
bool peDown = forwardPEChangePct < -primaryDriverThreshold
if priceUp and epsUp
primaryDriverText := peUp ? "Price + Estimate Expansion" : "Earnings-Led Advance"
primaryDriverColor := clrGreen
primaryDriverBg := clrLightMint
else if priceDown and epsDown
primaryDriverText := peDown ? "Price + Estimate Deterioration" : "Estimate Cuts Dominate"
primaryDriverColor := clrRed
primaryDriverBg := clrLightRed
else if priceUp and epsDown
primaryDriverText := "Price Up Despite Estimate Cuts"
primaryDriverColor := clrOrange
primaryDriverBg := clrLightAmber
else if priceDown and epsUp
primaryDriverText := "Estimate Upgrades / Price Lag"
primaryDriverColor := clrTeal
primaryDriverBg := clrLightCyan
else if peUp and priceUp
primaryDriverText := "Price-Led Multiple Expansion"
primaryDriverColor := clrAmber
primaryDriverBg := clrLightAmber
else if peDown and priceDown
primaryDriverText := "Price-Led Multiple Compression"
primaryDriverColor := clrTeal
primaryDriverBg := clrLightCyan
else if epsUp
primaryDriverText := "Estimate Upgrades"
primaryDriverColor := clrGreen
primaryDriverBg := clrLightMint
else if epsDown
primaryDriverText := "Estimate Cuts"
primaryDriverColor := clrRed
primaryDriverBg := clrLightRed
else if peUp
primaryDriverText := "Multiple Expansion"
primaryDriverColor := clrAmber
primaryDriverBg := clrLightAmber
else if peDown
primaryDriverText := "Multiple Compression"
primaryDriverColor := clrTeal
primaryDriverBg := clrLightCyan
else
primaryDriverText := "Stable / Consolidation"
primaryDriverColor := clrGrayLine
primaryDriverBg := clrLightGray
// ============================================================================
// MODEL CONFIDENCE
// ============================================================================
chartIsDaily = timeframe.isdaily and timeframe.multiplier == 1
int confidenceScore = 0
confidenceScore += not na(linkedForwardPE) ? 40 : 0
confidenceScore += has3Y ? 25 : has1Y ? 15 : 0
confidenceScore += not na(impliedForwardEPS) ? 10 : 0
// Internally calculated trailing P/E contributes to confidence when available.
confidenceScore += not na(currentPERatio) ? 5 : 0
confidenceScore += not na(linkedPEG) ? 5 : 0
confidenceScore +=
not na(estimateAgeDays) ?
estimateAgeDays <= freshDays ? 10 :
estimateAgeDays <= staleDays ? 5 : 1 :
0
confidenceScore += chartIsDaily ? 5 : 0
confidenceScore := int(math.max(0, math.min(100, confidenceScore)))
string confidenceLevel =
confidenceScore >= 80 ? "High" :
confidenceScore >= 60 ? "Medium" :
"Low"
color confidenceColor =
confidenceScore >= 80 ? clrGreen :
confidenceScore >= 60 ? clrAmber :
clrRed
historyCoverageText =
has3Y ? "Full 3Y" :
has1Y ? "1Y available" :
"Limited"
sourceStatusText =
confirmForwardPELinked and confirmPEGLinked ? "2/2 linked" :
confirmForwardPELinked ? "1/2 linked" :
"Set P/E forward source"
// ============================================================================
// DISPLAY TEXT
// ============================================================================
rankText = f_rank_text(rank1Y) + " / " + f_rank_text(rank3Y)
medianText = f_x(median1Y) + " / " + f_x(median3Y)
estimateTrendContext =
na(estimateRevisionPct) ?
"Awaiting second revision" :
"Last revision: " + f_pct(estimateRevisionPct)
freshnessContext =
na(estimateAgeDays) ?
"No implied EPS revision observed" :
str.tostring(estimateAgeDays, "#") + " calendar days"
confidenceContext =
historyCoverageText + " / " + (chartIsDaily ? "1D chart" : "Use 1D chart")
overallValuationContext =
na(selectedRank) ?
"Selected rank unavailable" :
chartLookback + " rank: " + f_rank_text(selectedRank)
valuationGrowthContext =
"Growth: " + f_pct(forwardEPSGrowthProxy) + " / PEG: " + f_x(linkedPEG)
valuationEstimateContext =
overallValuationText + " / EPS trend: " + estimateTrendText
primaryDriverContext =
"Price " + f_pct(priceChangePct) + " / EPS " + f_pct(forwardEPSChangePct) + " / P/E " + f_pct(forwardPEChangePct)
// ============================================================================
// PLOTS
// ============================================================================
lineColor = f_rank_color(selectedRank, hasSelectedHistory)
plot(
linkedForwardPE,
title="Linked TradingView Forward P/E",
color=lineColor,
linewidth=3,
display=display.pane)
medianPlot = plot(
showMedianLine ? selectedP50 : na,
title="Selected Historical Median",
color=color.new(clrGrayLine, 5),
linewidth=2,
display=display.pane)
upperPlot = plot(
showPercentileBands ? selectedP90 : na,
title="Selected 90th Percentile",
color=color.new(clrOrange, 20),
linewidth=1,
display=display.pane)
lowerPlot = plot(
showPercentileBands ? selectedP10 : na,
title="Selected 10th Percentile",
color=color.new(clrAqua, 20),
linewidth=1,
display=display.pane)
plot(
showPercentileBands ? selectedP95 : na,
title="Selected 95th Percentile",
color=color.new(clrRed, 10),
linewidth=1,
display=display.pane)
plot(
showPercentileBands ? selectedP05 : na,
title="Selected 5th Percentile",
color=color.new(clrBlue, 10),
linewidth=1,
display=display.pane)
fill(
upperPlot,
lowerPlot,
color=showPercentileBands and showNormalZoneFill ? color.new(clrAqua, 91) : na,
title="Historical Normal Zone")
isExtremeExpensive = hasSelectedHistory and selectedRank >= 95
isDeepDiscount = hasSelectedHistory and selectedRank <= 5
bgcolor(
showExtremeBackground and isExtremeExpensive ? color.new(clrRed, 90) :
showExtremeBackground and isDeepDiscount ? color.new(clrBlue, 90) :
na)
// ============================================================================
// DASHBOARD
// ============================================================================
var table dash = table.new(
f_position(dashboardPosition),
3,
15,
border_width=1,
border_color=color.new(clrMuted, 75))
if showDashboard and barstate.islast
color bgHeader = clrSlate0
color bgDark = clrSlate1
color bgMed = clrSlate2
color peBg = f_rank_fill_color(selectedRank, hasSelectedHistory)
color epsBg = clrLightGray
color currentPEBg = clrLightBlue
color growthBg = not na(forwardEPSGrowthProxy) and forwardEPSGrowthProxy >= 0 ? clrLightMint : clrLightRed
color pegBg = clrLightBlue
color rankBg = f_rank_fill_color(selectedRank, hasSelectedHistory)
color medianBg = clrLightGray
color trendBg = estimateTrendText == "Rising" ? clrLightMint : estimateTrendText == "Falling" ? clrLightRed : clrLightAmber
color freshBg = freshnessText == "Fresh" ? clrLightMint : freshnessText == "Aging" ? clrLightAmber : freshnessText == "Stale" ? clrLightRed : clrLightGray
color confBg = confidenceScore >= 80 ? clrLightMint : confidenceScore >= 60 ? clrLightAmber : clrLightRed
table.cell(dash, 0, 0, "Metric", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgHeader)
table.cell(dash, 1, 0, "Current", text_color=clrText, text_size=size.small, text_halign=text.align_center, bgcolor=bgHeader)
table.cell(dash, 2, 0, "Context", text_color=clrText, text_size=size.small, text_halign=text.align_right, bgcolor=bgHeader)
table.cell(dash, 0, 1, "Overall Valuation Status", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 1, overallValuationText, text_color=overallValuationColor, text_size=size.normal, text_halign=text.align_center, bgcolor=overallValuationBg)
table.cell(dash, 2, 1, overallValuationContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 2, "Valuation + Growth Signal", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 2, valuationGrowthText, text_color=valuationGrowthColor, text_size=size.normal, text_halign=text.align_center, bgcolor=valuationGrowthBg)
table.cell(dash, 2, 2, valuationGrowthContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 3, "Valuation + Estimate Direction", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 3, valuationEstimateText, text_color=valuationEstimateColor, text_size=size.normal, text_halign=text.align_center, bgcolor=valuationEstimateBg)
table.cell(dash, 2, 3, valuationEstimateContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 4, "Primary Driver", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 4, primaryDriverText, text_color=primaryDriverColor, text_size=size.small, text_halign=text.align_center, bgcolor=primaryDriverBg)
table.cell(dash, 2, 4, primaryDriverContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 5, "TradingView Forward P/E", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 5, f_x(linkedForwardPE), text_color=clrDarkText, text_size=size.normal, text_halign=text.align_center, bgcolor=peBg)
table.cell(dash, 2, 5, "Direct linked P/E forward plot", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 6, "Implied Forward EPS", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 6, f_eps(impliedForwardEPS), text_color=clrDarkText, text_size=size.normal, text_halign=text.align_center, bgcolor=epsBg)
table.cell(dash, 2, 6, "Price ÷ linked forward P/E", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 7, "Current P/E Ratio", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 7, f_x(currentPERatio), text_color=clrDarkText, text_size=size.normal, text_halign=text.align_center, bgcolor=currentPEBg)
table.cell(dash, 2, 7, "Price ÷ trailing 12M EPS", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 8, "Forward EPS Growth Proxy", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 8, f_pct(forwardEPSGrowthProxy), text_color=not na(forwardEPSGrowthProxy) and forwardEPSGrowthProxy >= 0 ? clrGreenText : clrRedText, text_size=size.normal, text_halign=text.align_center, bgcolor=growthBg)
table.cell(dash, 2, 8, "Implied forward EPS vs prior FY", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 9, "PEG Ratio", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 9, f_x(linkedPEG), text_color=clrDarkText, text_size=size.normal, text_halign=text.align_center, bgcolor=pegBg)
table.cell(dash, 2, 9, na(pegImpliedGrowthPct) ? "Direct linked PEG plot" : "TTM P/E ÷ PEG = " + f_pct(pegImpliedGrowthPct), text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 10, "1Y / 3Y P/E Rank", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 10, rankText, text_color=clrDarkText, text_size=size.small, text_halign=text.align_center, bgcolor=rankBg)
table.cell(dash, 2, 10, "Lower percentile = cheaper", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 11, "1Y / 3Y Median P/E", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 11, medianText, text_color=clrDarkText, text_size=size.small, text_halign=text.align_center, bgcolor=medianBg)
table.cell(dash, 2, 11, "Linked forward P/E history", text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 12, "Forward EPS Trend", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 12, estimateTrendText, text_color=estimateTrendText == "Rising" ? clrGreenText : estimateTrendText == "Falling" ? clrRedText : clrAmberText, text_size=size.normal, text_halign=text.align_center, bgcolor=trendBg)
table.cell(dash, 2, 12, estimateTrendContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
table.cell(dash, 0, 13, "Estimate Freshness", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgDark)
table.cell(dash, 1, 13, freshnessText, text_color=freshnessText == "Fresh" ? clrGreenText : freshnessText == "Aging" ? clrAmberText : freshnessText == "Stale" ? clrRedText : clrDarkText, text_size=size.normal, text_halign=text.align_center, bgcolor=freshBg)
table.cell(dash, 2, 13, freshnessContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgDark)
table.cell(dash, 0, 14, "Model Confidence", text_color=clrText, text_size=size.small, text_halign=text.align_left, bgcolor=bgMed)
table.cell(dash, 1, 14, confidenceLevel + " (" + str.tostring(confidenceScore) + "%)", text_color=confidenceScore >= 80 ? clrGreenText : confidenceScore >= 60 ? clrAmberText : clrRedText, text_size=size.normal, text_halign=text.align_center, bgcolor=confBg)
table.cell(dash, 2, 14, sourceStatusText + " / " + confidenceContext, text_color=clrMuted, text_size=size.small, text_halign=text.align_right, bgcolor=bgMed)
if not showDashboard and barstate.islast
table.clear(dash, 0, 0, 2, 14)
// ============================================================================
// ALERTS
// ============================================================================
crossedAbove90 = ta.crossover(selectedRank, 90)
crossedBelow10 = ta.crossunder(selectedRank, 10)
enteredExpensive = hasSelectedHistory and crossedAbove90
enteredCheap = hasSelectedHistory and crossedBelow10
newEstimateIncrease = impliedEPSChanged and not na(estimateRevisionPct) and estimateRevisionPct > trendThreshold
newEstimateDecrease = impliedEPSChanged and not na(estimateRevisionPct) and estimateRevisionPct < -trendThreshold
newStaleEstimate =
not na(estimateAgeDays) and
not na(estimateAgeDays ) and
estimateAgeDays > staleDays and
estimateAgeDays <= staleDays
newAttractiveDiscount =
valuationGrowthText == "Attractive Discount" and
valuationGrowthText != "Attractive Discount"
newValueTrapRisk =
valuationGrowthText == "Value-Trap Risk" and
valuationGrowthText != "Value-Trap Risk"
newHighRiskPremium =
valuationGrowthText == "High-Risk Premium" and
valuationGrowthText != "High-Risk Premium"
alertcondition(
enteredExpensive,
title="Forward P/E Entered Expensive Zone",
message="Linked TradingView forward P/E entered the selected lookback's 90th-percentile expensive zone.")
alertcondition(
enteredCheap,
title="Forward P/E Entered Cheap Zone",
message="Linked TradingView forward P/E entered the selected lookback's 10th-percentile cheap zone.")
alertcondition(
newEstimateIncrease,
title="Implied Forward EPS Increased",
message="The forward EPS implied by TradingView's linked forward P/E increased by more than the configured trend threshold.")
alertcondition(
newEstimateDecrease,
title="Implied Forward EPS Decreased",
message="The forward EPS implied by TradingView's linked forward P/E decreased by more than the configured trend threshold.")
alertcondition(
newStaleEstimate,
title="Implied Forward EPS Became Stale",
message="The implied forward EPS has not changed within the configured stale-data threshold.")
alertcondition(
newAttractiveDiscount,
title="Attractive Discount Signal",
message="Forward P/E is historically discounted while growth and estimate direction remain supportive.")
alertcondition(
newValueTrapRisk,
title="Value-Trap Risk Signal",
message="Forward P/E is historically discounted, but growth or forward EPS estimates are deteriorating.")
alertcondition(
newHighRiskPremium,
title="High-Risk Premium Signal",
message="Forward P/E is historically elevated while growth or forward EPS estimates are deteriorating.")
Indicateur
RTI Trend State + MacroCoverRTI Trend State + MacroCover
A trend-state oscillator built on the Relative Trend Index (RTI) — a stochastic-position measure of where price sits inside its recent high/low range, then EMA-smoothed:
raw = 100 * (close - lowest(low, n)) / (highest(high, n) - lowest(low, n))
RTI = EMA(raw, smooth) -> a 0-100 line
How the state works
The 0-100 RTI is converted into a persistent LONG / FLAT / SHORT state through a hysteresis band , so it does not flip on noise around the mid-line:
RTI above the upper band -> LONG
RTI below the lower band -> SHORT
in between -> holds the last state
The gap between the two bands is the hysteresis — widen it for fewer, steadier flips; narrow it for a more reactive read.
MacroCover (optional long bias)
When the state would be SHORT but price trades above a slow EMA (default 200), the short is covered to FLAT — i.e. it won't fight the higher-timeframe uptrend. Turn MacroCover off for a symmetric long/short reading.
On the chart
The RTI line (0-100) colored by state: green long, red short, gray flat.
Dashed upper/lower bands and a dotted mid-line.
State background tint and flip markers where the state changes.
A compact table with the current RTI value, state and macro side.
The RTI value plus state_-1_0_1 and ema_macro are available in the Data Window for tooltips and cross-checks.
Inputs
RTI engine — Lookback n (30), EMA smoothing (3), upper/lower bands (55 / 45).
MacroCover — on/off and macro EMA length (200).
Timeframe — use the chart timeframe, or lock the calculation to a fixed resolution.
Visual — toggle the state background, flip markers and table.
Notes
Works on any symbol and any timeframe.
Non-repainting : values are computed on confirmed bars, and the optional higher-timeframe request uses lookahead_off.
This is a discretionary / confluence tool, not financial advice or a complete trading system.
Indicateur
Buy/Sell Signals [WynTrader]Buy/Sell Signals
Hello dear Friend
Here is my Buy/Sell Signals indicator that may help you easily run a Buy/Sell backtest Strategy, seeing, at a glance, performance results.
█ OVERVIEW
This indicator identifies trend changes and generates Buy/Sell signals as accurately as possible. Its strength lies in the results Table, which lets you evaluate signal performance directly on the chart — compared to a simple Buy & Hold strategy — without running a full backtest.
█ CONCEPTS
This Buy/Sell Signals , compared to other tools that detect trend shifts, is simple, easy to use, and demonstrates its efficiency on its own, at a glance.
The Table results allow you to quickly evaluate signal performance, both on their own and compared to a Buy & Hold strategy. The Table calculations are fully s ynchronized with the visible chart (WYSIWYG – What You See Is What You Get). You can also scroll the chart across different date ranges to see how a stock or product performs under various market conditions.
You can adjust the variables to suit your goals. The design is simple, with clear parameters and instant readability of Buy/Sell Signals on the chart and in the Table results, without complex interpretation needed.
A Table shows the effectiveness of the signals on the current visible chart, providing immediate, realistic feedback performance. The Buy & Hold strategy results are also included for comparison with the Buy/Sell swing strategy. The Buy & Hold results start from the first Buy signal to ensure a fair comparison. Changing the parameters instantly updates the Table, giving a quick, immediate performance check.
█ FILTERS (Buy/Sell parameters)
This indicator generates Buy/Sell signals using optional and adjustable filters:
- Bollinger Bands Lookback Trend Filter
- High-Low vs Candle Range Threshold %
- Distance from Fast and Slow MAs Threshold %
Results are displayed in a Table on the chart, based on the currently visible start and end dates.
█ TABLE RESULTS (Buy/Sell signals performance)
The Results Calculation presented in the Table is based on the Current Chart Visible Range . The Table shows the:
- Calculation Results of the Buy and Sell Signals activated on the chart
- Number of Trades (Signals)
- Winning Points
- Win Rate %
The Buy & Hold calculation starts at the first Buy encountered.
█ CAUTION
The Graal Indicator, even with AI, doesn't exist yet — maybe one day, but not now — depending on the chart product, volatility, probabilities, and unpredictable market behaviour. Don't rely on this tool to make trade decision, it's only a tool to, maybe, help assess a change of trend.
Seeing Buy/Sell signals on a chart is appealing, but assessing their performance in a Table makes it even more convincing — and without running a full backtest, you get a clear overview of performance immediately.
█ WYNTRADER
My name is WynTrader. I cumulate 24 years of experience. In 2001, I took an intensive technical analysis course taught by an exceptional friend, Cyril, who taught me everything I know.
After testing thousands of TradingView indicators over these 24 years, I've found none to be 100% accurate all the time. This Buy/Sell Signals indicator may outperform some others but is still not perfect. So, just be aware, and don't be fooled by this tool.
Enjoy!
WynTrader Indicateur
Breakout & Retest Entry Signals & the Break-vs-RetestOVERVIEW
"Wait for the retest" is the most repeated piece of advice in breakout trading. It is also, as far as I can tell, completely untested by the people who repeat it.
This tool settles it — on your instrument, with your settings — by taking BOTH entries on the SAME breaks and grading them against the same control:
PER-TRADE EDGE expectancy vs control · n
Break entry +0.09R +0.02R · n=412
Retest — CLEAN +0.31R +0.02R · n=118
Retest — DEEP -0.04R +0.02R · n=76
clean vs deep (t) 3.41 CLEAN IS BETTER
BUT — HOW OFTEN DO YOU GET IT?
Breaks that ever retested 47.0% (194/412)
after a run of >3 closes 31.2% vs 55.8% otherwise
False-break rate 13.3%
EXPECTED VALUE PER BREAK
Take every break +0.09R (100% of breaks)
Wait for the retest +0.06R (47% of breaks)
VERDICT NO DIFFERENCE — pick either
That last block is the entire point. A better per-trade edge is worthless if you only get the trade half the time — so the WAIT policy is scored as P(retest) x E , because on every break that never retests you get NOTHING. The two are then compared with a significance test, and the verdict is allowed to be "no difference".
It is a research and framing tool. NOT a strategy, NOT a signal service, NOT a validated edge.
WHAT IT ALREADY FOUND — measured live on NIFTY futures
timeframe breaks retested false breaks verdict
1m 334 49.4% 29.6% NO DIFFERENCE
3m 323 53.3% 13.6% NO DIFFERENCE
5m 328 53.4% 14.0% NO DIFFERENCE
15m 306 51.0% 12.7% TAKE THE BREAK
1h 274 50.0% 16.4% NO DIFFERENCE
TWO THINGS JUMP OUT.
The retest rate is 50-53% on every timeframe. Bulkowski, measuring throwbacks across 10,348 chart patterns on US daily stocks, found 50-60%. A completely different market, a completely different method, and the same number. That is a real phenomenon, not an artefact of the detector.
The false-break rate is 26.5% on the 1m and 13-15% everywhere else. THE ONE-MINUTE BREAK IS TWICE AS LIKELY TO BE A LIE. That is not folklore, it is this instrument's own number, and it is exactly the kind of thing a trader should know before choosing a timeframe.
And the verdict, on four of the five: NO DIFFERENCE — pick either. Once the geometry is honest and the test is a real one, the great break-versus-retest argument simply does not resolve on this instrument at most speeds. On the 15m it does resolve — and it says TAKE THE BREAK, which is the opposite of what almost everyone will tell you.
That is what a measurement looks like. It disagrees with the folklore on one timeframe, refuses to take a side on four others, and does not care what you were hoping for. No tool that needs to sell you a signal would ever print "NO DIFFERENCE".
THE ONE THING EVERYONE GETS BACKWARDS
Thomas Bulkowski measured throwbacks and pullbacks across 10,348 chart patterns. His finding:
"Do throwbacks hurt performance? YES: 97% of the time chart patterns with upward breakouts
perform better post-breakout WITHOUT a throwback."
"Do pullbacks hurt performance? YES: 91% of chart pattern types with downward breakouts
perform better if a pullback does NOT occur."
Read that again. The retest is not a gift. It is a SYMPTOM — evidence that the move is weak, that supply came back, that the break did not have the strength to run.
And yet "wait for the retest" is good advice for a completely different reason: it gives you a better price and a tighter stop.
BOTH ARE TRUE AT ONCE. They are two opposing effects on the same trade, and they have never been put on one scale and netted out. That is what this script does. The retest may still win — a better entry can outweigh a weaker move — but nobody has ever checked, and the answer is different on every instrument and every timeframe.
A CLEAN RETEST AND A DEEP ONE ARE NOT THE SAME EVENT
Bulkowski again, and this is his sharpest single finding on the subject: during a throwback, if price REMAINS ABOVE the breakout price the subsequent rise averages 40%. If it drops BELOW the breakout price and then recovers, the rise averages 29%. That is 400 samples versus 2,767.
Pooling those two throws away the strongest signal in the whole idea. So they are separated:
CLEAN retest — price came back and touched the level, but never CLOSED back through it.
DEEP retest — price CLOSED back through the level, then recovered.
They are graded separately, tested against each other, and labelled separately on the chart. If clean beats deep on your instrument, then "wait for the retest" is not one rule — it is two, and only one of them works.
AND CAN YOU SEE IT COMING?
The real, unpriced cost of a WAIT policy is that roughly half the time you never get filled. So it matters enormously whether you can predict which breaks will retest.
Bulkowski found that if price has more than three consecutively higher closes ending the day before the breakout, the throwback probability drops materially. So the panel reports the retest rate SPLIT BY THAT:
after a run of >3 closes 31.2% vs 55.8% otherwise
If the split is real on your instrument, then after a strong run into the break you should simply TAKE IT — because the retest you are waiting for is probably never coming.
IS YOUR VOLUME FILTER EARNING ITS KEEP?
Every trader is taught that a breakout must be confirmed by volume. Bulkowski's volume study says that after an ABOVE-average-volume breakout, FAILURES DOUBLE and the likelihood of a throwback TRIPLES, while the move itself is barely better.
That is testable — but only if the low-volume breaks are allowed into the sample. So VOLUME IS NOT A GATE ON THE RECORD. Every break is recorded; volume gates only the SIGNAL. The panel then reports what your filter is actually worth:
Break ON volume +0.11R n=246
Break OFF volume +0.06R n=166
on vs off (t) 0.82 no difference — it is doing nothing
The record is a fact about the market. The filter is a decision about the trade. They are kept apart, and this is what happens when you stop assuming and start measuring.
IDENTICAL GEOMETRY — and why this is not a detail
The target used to be THE NEXT OPPOSING LEVEL. That quietly destroyed the entire experiment.
The BREAK entry sits PAST the level (it closed through it). The RETEST entry sits BACK AT the level. So the retest is systematically FARTHER from the next opposing level, and was therefore being handed a BIGGER R:R for the SAME RISK — on every single trade, by construction. Live, that produced an R:R of 5.0 on one timeframe and 0.66 on another, and the on-chart key was cheerfully claiming "identical geometry" while the geometry was tilted toward the retest.
The trade now uses a FIXED R multiple, identical for the break, the retest and the control. The next opposing level is still drawn, and still tested — separately, as a descriptive statistic, with its hit rate reported next to its distance in R.
THE ANTI-BIAS GUARDS
ENTRY IS THE CLOSE, for both entries and for the control. Entering the retest AT the level — a better price than the close — while the break enters at its close would hand the retest a free head start on every trade, and settle the oldest argument in trading by rigging it.
THE CONTROL IS DIRECTION-MATCHED. Breaks run with the trend, so a direction-skewed event set measured against a symmetric 50/50 control inherits the drift for free and calls it an edge. Longs are compared only with control longs, shorts only with control shorts, and the control is blended back using the events' OWN direction mix.
EVERY VERDICT IS A TEST, NOT A COMPARISON. Break-vs-wait, clean-vs-deep, volume-on-vs-off — each is a Welch t-test that has to clear |t| > 1.96 before it is allowed to be a finding. For the wait policy, the variance of P(retest) x E is propagated by the delta method, because it is a product of two estimates and both carry error. A verdict that flips on a tenth of an R is not a verdict, it is noise wearing a costume.
Both barriers on one bar: the STOP is assumed first — conservative, and the only assumption that cannot flatter the result. Unresolved trades at the horizon are marked to market, not booked as losses.
THE LEVELS
Levels come from the extrema of a KERNEL-SMOOTHED price series (Nadaraya-Watson) rather than raw pivots, so they track the structure rather than the noise. A break requires a CLOSE beyond the level with displacement, not a wick. A false break is one that closes back inside quickly. All of it is computed on confirmed bars; the kernel is causal and never looks forward.
NON-REPAINT
The kernel confirms an extremum a half-window late, so a level appears some bars AFTER the swing that created it. That lag is the price of not repainting and it is paid deliberately. Levels, breaks, false breaks, retests, signals and every calibration event are computed on CONFIRMED bars only. Nothing is drawn and then moved.
DATA AND SCOPE
Any symbol, any timeframe. ATR-normalised throughout. Volume improves the SIGNAL but is not required, and it never gates the RECORD.
EXPORTS (Data Window — consume from other scripts via input.source())
EXP_Level, EXP_Break, EXP_FalseBreak, EXP_Retest, EXP_Entry, EXP_Stop, EXP_Target, EXP_NextLevel, EXP_WaitEdge
CONCEPT CREDIT
Support/resistance, polarity and the breakout-retest idea are long-standing public trading concepts with no single author; the written tradition runs through Charles Dow, Richard Wyckoff and Edwards & Magee. The formal TRADING-RANGE BREAK was first tested at scale by William Brock, Josef Lakonishok and Blake LeBaron, Journal of Finance 47(5), 1992 — and their results were later shown to be vulnerable to data-snooping (Sullivan, Timmermann and White, 1999), which is exactly why this tool measures the rule on YOUR instrument rather than asserting it.
The throwback and pullback statistics that motivate the clean/deep split, the run-length predictor and the volume test are from Thomas Bulkowski ("Encyclopedia of Chart Patterns"; thepatternsite.com). His numbers are measured on US daily stocks. Whether they hold on YOUR instrument is precisely the question this script exists to answer — and it may well answer "no".
Nadaraya-Watson kernel regression — Nadaraya and Watson (1964); its use for technical pattern recognition — Lo, Mamaysky and Wang, Journal of Finance 55(4), 2000. Triple-barrier forward labelling — Marcos Lopez de Prado. Welch's t-test — B. L. Welch. ATR — J. Welles Wilder.
The break-vs-wait availability weighting, the delta-method significance test, the clean/deep retest split, the volume-filter test and the direction-matched control are the author's own. Clean-room implementation; no third-party Pine code is reused. Not affiliated with, nor endorsed by, any of the above.
HONESTY AND LIMITATIONS
Calibration is IN-SAMPLE, with no costs or slippage, and uses overlapping windows. A proven in-sample edge is NOT a guarantee out-of-sample. Real fills, spreads and commissions will reduce it — and they will hurt the break entry more than the retest entry, because the break enters into momentum.
Bulkowski's throwback statistics are measured on US daily stocks over decades. They are the reason the questions are asked. They are NOT the answer, and this tool will tell you so if your instrument disagrees.
The verdict is allowed to be "NO DIFFERENCE — pick either", and on many instruments it will be. That is a real result. A tool that cannot report its own failure is an advertisement, not a measurement.
Nothing in this script predicts price.
DISCLAIMER
Research and educational tool only. NOT financial advice, NOT a recommendation, and NO guarantee of results. Entry, stop and target output is arithmetic, not advice. Trading carries risk of loss. Test out-of-sample and make your own decisions. The author accepts no liability for any use.
Indicateur
Anchored VWAP Hand-Off 2.03Anchored VWAP Hand-Off 2.03 is a multi-leg cascading VWAP indicator. It starts with a classic Anchored VWAP from a user-selected date (Leg 1), then automatically creates new "hand-off" VWAP legs (up to 24) every time price crosses the previous VWAP. Each new leg resets its calculation from the bar of the cross, creating a dynamic chain of VWAPs that follow price action.
Key Features:
Source: Typically close (customizable).
Trigger: EMA(1) of the source (essentially price itself).
Color Logic: Each VWAP leg changes color based on whether price is above (bullish) or below (bearish) it. Supports unified color mode.
Up to 24 cascading legs (user controls how many are shown).
Visual anchor line at the start date.
Main Use Cases:
Dynamic Support & Resistance
The multiple VWAP legs act as adaptive moving support/resistance zones. Traders watch for bounces off these lines or breaks through several legs at once.
Trend Strength & Momentum
Strong trends often break multiple hand-off legs quickly.
Choppy/consolidating markets produce many frequent hand-offs (more lines clustering).
Mean Reversion Setups
Price tends to return to the nearest active VWAP legs. Useful for fade-the-extreme strategies.
Breakout / Breakdown Confirmation
When price decisively breaks through several VWAP legs in sequence, it often signals a high-probability directional move.
Intraday & Swing Trading
Particularly popular on stocks, futures, and crypto for finding "fair value" shifts after news events or strong moves. The hand-off mechanism makes it more responsive than a single static anchored VWAP.
Visual Market Structure
Helps traders see how "value" is migrating over time as new legs form.
Best Timeframes: Works on all, but especially useful on 5min to daily charts.Pro Tip: Start with 8–12 legs. Too many legs can make the chart noisy. Use the anchor date on significant events (earnings, breakout days, macro events, etc.).This indicator is an evolution of standard Anchored VWAP, designed to solve the problem of a single anchored VWAP becoming stale after big moves.
Indicateur
Indicateur
Indicateur
