NeuPortal - Confluence MeterThe standard oscillator set on one shared 0-100 scale: RSI, Stochastic, Williams %R, CCI, MFI, MACD histogram and Momentum. Toggle any of them, read them against each other, and get a consensus line.
That part is ordinary. Here is the part that is not.
WHY CONFLUENCE IS USUALLY WORTH LESS THAN IT LOOKS
"Five indicators confirm the signal" is the oldest line in technical analysis, and it is mostly a restatement of one thing said five times. These oscillators are near-transformations of each other.
Measured over 19,580 four-hour bars of full Binance history on BTCUSDT, the rank correlations are: Stochastic to Williams %R 0.92, RSI to CCI 0.90, Stochastic to CCI 0.89, Williams %R to CCI 0.87. The median pairwise correlation across all 21 combinations is 0.80. ETHUSDT over the same span reproduces the table to two decimal places.
For n readings with average correlation r, the effective number of INDEPENDENT readings is about n / (1 + (n - 1) * r). Seven oscillators at 0.80 come to roughly 1.2.
Seven agreeing indicators is one indicator, counted seven times.
The weakest pair in the set is RSI against the MACD histogram at 0.51. If you want two oscillators rather than seven, those two carry the most different information.
WHAT THE SCRIPT DOES ABOUT IT
It does not take the numbers above on trust. It measures the correlation live, on your symbol, your timeframe and your chosen lengths, then prints two things side by side in the table:
- agreement, the count of enabled oscillators on the same side of 50
- effective independent readings, derived from the measured correlation
The first is what people want to see. The second tells them what it is worth. When the second reads 1.3, a unanimous seven-to-nothing agreement is not seven pieces of evidence.
HOW THE SHARED SCALE WORKS
RSI, Stochastic and MFI are natively 0-100. Williams %R is shifted from its -100..0 range. CCI, the MACD histogram and Momentum have no fixed bounds, so they are converted with a percentile rank against their own recent history: the reading becomes where this value sits relative to how this instrument has behaved lately.
That is a real transformation and it is disclosed rather than buried. A percentile-ranked MACD histogram is not the MACD histogram, so the raw value is printed in the table alongside the scaled one. Nothing is hidden behind the normalisation.
SETTINGS WORTH KNOWING
Percentile lookback controls how much history the unbounded oscillators are ranked against. Shorter reacts faster and is noisier. Longer is steadier and slower to acknowledge a change in regime.
Correlation window controls how much history is used to measure independence. Longer is more stable but averages across regimes, and correlation between oscillators is not constant.
WHAT THIS IS NOT
Not a strategy, not a signal, not a recommendation. An oscillator crossing 50 is not an entry. The two alerts are deliberately descriptive rather than directional, because an alert that said "buy" would contradict everything the script exists to point out.
Free and open source. Read the code, change the lengths, run it on your own instruments and see whether the correlation on your market matches ours.
Indicator
Keltner Position Divergence with Reliability ScoringOverview
Keltner-Position Divergence with Reliability Scoring turns where price sits inside its Keltner channel into a bounded oscillator, reads it for divergence against price, and then scores — in real time — whether those divergences have actually been worth acting on for the symbol on your chart, and which direction is carrying the edge. It is a context / research read, not a standalone buy or sell signal.
The idea
A Keltner channel frames price with an ATR envelope around a moving average. Where price sits inside that envelope — pinned to the upper band, mid, or pinned to the lower band — is a bounded read of stretch. When price makes a new high but its Keltner position does not confirm (a lower band-position high), that non-confirmation can precede a turn. This script measures the divergence between price and its Keltner position, then keeps a self-updating track record of whether such divergences pay.
Why these parts are combined (mashup rationale)
Three components form one pipeline, not three separate signals:
A Keltner-position oscillator — price's location within the ATR envelope (0 centre, +1 upper band, −1 lower band), z-scored so the bands and zones mean the same on every asset.
Confirmed-pivot divergence — regular and hidden, between that position line and price, with an optional triple-pivot mode for rarer, stronger disagreements.
A reliability harness — a binomial-proportion confidence test that asks whether each class of divergence has preceded a favourable move (a k×ATR travel over a fixed horizon) more often than a same-zone baseline, reported per direction with a Wilson confidence bound.
Part 1 builds the bounded stretch read, part 2 fires only where price and position disagree, part 3 decides whether that disagreement has actually paid on this instrument. Remove any one and the tool can no longer answer "is this Keltner divergence worth trading here?"
How to use it
Read the verdict panel first. GREEN = these divergences have beaten a same-spot baseline here; RED = they've lost to it (skip, or change the band width / timeframe); AMBER = not statistically established yet; GREY = still gathering data. "Best signal" names the direction with the strongest measured edge; "Reward : risk" is the average best-vs-worst move after a signal, in ATR. A divergence is price making a higher high / lower low while the Keltner-position line does the opposite — marked in the pane and, optionally, on the price chart. It is context, never a standalone trigger.
Settings worth knowing
The regime filter ("Only count signals in regime") restricts the track record to signals that fired in a chosen regime — reverting markets suit divergence, strong trends punish it — so you can measure the edge where it's supposed to work. Costs subtracted (×ATR) raises the bar a signal must clear so the score is net of costs. Band width, MA length and the z-score window adapt the read to any instrument.
Universality & non-repainting
It reads only the chart's own price (configurable source), so it runs on any symbol, any timeframe, with no external data. Pivots confirm a fixed number of bars after the fact, and the track-record harness logs, updates and resolves only on confirmed (closed) bars, so its statistics never inflate or shift intrabar. The live oscillator updates each bar like any oscillator. All figures are in-sample and past-only.
Outputs for other scripts
Generic EXP_* plots — oscillator, signal, probability, edge, edge lower-bound, sample count, regime, band position — are published to the Data Window for use from other scripts via input.source().
Originality
Standard Keltner tools just plot the channel. This one turns band-position into a divergence oscillator and keeps a self-updating, confidence-scored, per-class track record against a same-zone baseline — so you see not just that a divergence printed, but whether and how it has paid on the current market. Clean-room implementation; no third-party Pine code reused.
Concept credits
Keltner channel — Chester Keltner; ATR-band refinement — Linda Raschke
Average True Range — J. Welles Wilder
Binomial score confidence interval — Edwin B. Wilson
Trend-efficiency regime measure — Perry Kaufman
Disclaimer
For research and education only. Not financial advice, not a recommendation, and not a guarantee of future results. All figures are in-sample and past-only. Markets carry risk; do your own research and manage your own risk. Indicator
Composite Reversion OscillatorComposite Reversion Oscillator
A short-term mean-reversion oscillator that blends three different "how stretched is this?" reads into one 0–100 line: how overbought/oversold momentum is, how long the current up/down streak has run, and where the latest return ranks against its own recent history. Each measures a different face of over-extension; together they flag exhaustion more reliably than any one alone.
Why these parts are combined (not a mashup for show). A short momentum oscillator flags overbought/oversold but ignores persistence. A streak read (an oscillator of the consecutive up/down-close count) captures persistence it misses — three green closes isn't one. A return-rank read captures the size of the latest move relative to its own norm, which neither of the others sees. Averaging the three yields a composite that only reaches an extreme when momentum, streak and move-size all agree — far fewer false "oversold" prints.
What's different here. Rather than presenting the composite as a fixed rule, it forward-calibrates whether those agreed extremes actually revert on this symbol, with an out-of-sample split and a multiple-testing check — because mean-reversion edges are regime-dependent and decay, which is exactly where symbol-specific honesty matters most. Signals fire once per excursion (no zone-edge whipsaw).
How it works. Component 1: a short-period momentum oscillator of price. Component 2: the same oscillator applied to the signed consecutive-close streak. Component 3: the percentile rank of the latest return within a recent window. The composite is their average, mapped to a ±100 pane. A long fires on the cross up out of oversold (and locks out until the line recovers to mid); a short mirrors it. Each is labelled by a triple barrier — a profit target and equal stop in ATR units plus a time limit — split into in-sample and recent out-of-sample.
How to use. Read the Verdict (Long/Short/Watch/Wait) and the Conviction, which reads "High" only when that turn type shows a positive edge that survives the test here — otherwise it openly says so. Best used with your own trend and risk plan, not alone. Non-repainting.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Ease-of-Movement Flow OscillatorEase-of-Movement Flow Oscillator
A volume oscillator that measures how easily price moves — distance travelled relative to the volume required to travel it. Large travel on light volume = high ease (a frictionless drift); small travel on heavy volume = low ease (absorption — effort without result). Above zero, price advances with little resistance; below zero, it declines with little resistance. It adds an absorption warning and a plain-language forward-calibration layer, so you can tell at a glance whether a move is frictionless or being absorbed, and whether the signal has actually paid here.
Why these parts are combined (not a mashup for show). Ease of movement relates distance to the volume needed for it — a different question from "buying vs selling." A frictionless advance and an absorbed advance look identical on a price chart but behave differently next, so that's the core read. An effort-vs-result check (price making a new extreme while ease does not) flags absorption — heavy volume no longer moving price — which the raw line alone misses. Forward calibration removes blind faith: instead of assuming a cross "should" pay, it measures whether it actually has, with realistic profit/stop outcomes. Together they form one coherent volume-flow tool.
How it works. Distance moved = midpoint change; box ratio = (volume ÷ scale) ÷ range. Ease = distance ÷ box ratio, smoothed, standardized and soft-bounded to ±100 that auto-fits its own magnitude. A signal fires only when ease decisively clears a confirmation band beyond zero (filtering the constant zero-line chatter). Absorption divergence is detected from confirmed price pivots versus the ease line. Each signal is then labelled by a triple barrier — a profit target and equal stop in ATR units plus a time limit — split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row (Long/Short, Absorption, or Wait) and the Conviction row, which reads "High" only when that signal type shows a positive edge that survives the test on this symbol. Green above zero = easy up, red below = easy down; shaded bands = strong ease; the faint band lines mark where signals fire. Best used with your own trend and risk plan, not alone.
What's original. The absorption (effort-vs-result) flag, auto volume scaling, a noise-filtering signal band, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge.
Volume note. This needs real volume — use a futures contract such as NSE:NIFTY1!. On a cash index it reports "No volume" rather than printing noise.
Honesty & limitations. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future. Volume quality varies by feed and instrument.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Tail-Risk & Fragility OscillatorTail-Risk & Fragility Oscillator
A risk-shape meter — not a buy/sell oscillator. It measures the asymmetry (skewness) and tail-fatness (excess kurtosis) of recent returns to answer one question your momentum and trend tools cannot: is fragile, fat-tailed risk building right now, and on which side? It reads this in plain language, optionally from higher-resolution "realized" data, and forward-calibrates whether those fragile states have actually preceded moves on the symbol you're viewing.
Why these parts are combined (not a mashup for show). Skewness says which tail is heavier (where a violent move is more likely to come from). Excess kurtosis says how heavy the tails are (how likely an outsized move is at all). Neither alone is "fragility" — fragility is one tail heavy AND tails fattening together — so both are combined into one reading. Realized estimation (optional) measures these moments from intrabar returns rather than one value per bar, far less noisy. And a Cornish-Fisher value-at-risk turns skew + kurtosis into a single "expected bad-case move" you can size against. Together they form one coherent tail-risk tool.
How it works. Returns feed central moments over a window: skew = m3/σ³, excess kurtosis = m4/m2² − 3. With "Realized" on, the moments come from a lower-timeframe return stream (confirmed only). The signed wave is standardized skewness; a percentile of kurtosis flags fat tails; a Cornish-Fisher quantile combines both, scaled to the chart timeframe over the calibration horizon, into a value-at-risk. A "fragile-down" state (negative-skew extreme + fat tails) is then scored for a subsequent down move and "fragile-up" for an up move, using triple-barrier outcomes, split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row — "Downside-fragile" / "Upside-fragile" means a heavy tail is building on that side; "Tails normal" means no fragility. The Conviction row says whether that state has actually preceded the expected move on this symbol. Use it to size down, widen stops, or expect violence on the fragile side — layered on your own directional tool, never as a standalone entry. The "Bad-case move" row is the modelled adverse move over the next N bars at your chosen confidence.
What's original. Realized higher-moment estimation, a horizon-scaled Cornish-Fisher VaR readout, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge — on a risk axis (fragility) that most indicators ignore entirely.
Inputs. Price source (change it for any market), reading mode (Simple/Pro), moment and realized-estimation controls, risk thresholds and VaR confidence, full calibration settings, and an auto-adapting dashboard legible on dark or light charts. Defaults are tuned for NSE:NIFTY1! intraday.
Honesty & limitations. Moments from short windows are noisy and the VaR is a model estimate, not a guarantee. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a backtest; past behaviour doesn't predict the future.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own size. Indicator
Directional Strength OscillatorDirectional Strength Oscillator
A signed trend-strength oscillator that reads the tug-of-war between upward and downward movement and prints one line — positive in uptrends, negative in downtrends, crossing zero at trend changes. Unlike a plain directional reading, it dims itself when price is only chopping, flags weakening trends through divergence, and scores its own signals forward on your chart in plain language.
Why these parts are combined (not a mashup for show). Each part answers what the previous one leaves open. Up-movement vs down-movement relative to true range gives a clean, bounded read of who's winning and by how much — but it can read "strong" inside noisy, non-trending chop. A trend-efficiency filter (net travel over total path) measures whether price is actually going somewhere; folding it into the line removes the false-strong chop. A divergence check (price makes a new extreme while strength does not) flags weakening trends the raw line would miss. Together they form one directional-strength tool.
How it works. Up-movement = |high − prior low|, down-movement = |low − prior high|; each is summed over the length and divided by summed true range to get the up and down lines. Their difference is the raw strength; it's standardized, soft-bounded to ±100, then scaled by a 0–1 trend-efficiency factor. Signals are zero-crosses gated by a minimum quality, plus divergence against price (measured on the undimmed strength). Each signal is then labelled by a triple barrier — a profit target and equal stop in ATR units plus a time limit — so a "win" means the target hit before the stop. Results split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row (Long/Short signal, Watch, or Wait) and the Conviction row, which reads "High" only when that signal type shows a positive edge that survives the test on this symbol. Green line above zero = uptrend in control, red below = downtrend; shaded bands = strong trend; the trend-quality % tells you how clean the move is. Best used with your own entry and risk plan, not alone.
What's original. The trend-quality gate that removes false-strong chop, integrated divergence on the undimmed line, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge.
Inputs. High/Low sources (change them for any market), reading mode (Simple/Pro), engine, quality-gate, divergence and full calibration settings, and an auto-adapting dashboard legible on dark or light charts. Defaults are tuned for NSE:NIFTY1! intraday.
Honesty & limitations. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
Sharp Reversal OscillatorSharp Reversal Oscillator
A reversal-timing oscillator that re-shapes price into a near-Gaussian form so turning points snap into sharp, clear extremes instead of rounded, ambiguous ones — then scores its own turns forward on your chart, in plain language, so you can see at a glance whether to act or wait.
Why these parts are combined (not a mashup for show). Three steps are stacked, each fixing the previous one's flaw. Raw price excursions are fat-tailed, so it's unclear where an extreme really is; a distribution-normalizing transform stretches values near the edges, turning a compressed extreme into a clear spike. But that transform is easily biased by trend — in a strong move it pins to one side — so the input is first band-pass cleaned (slow trend and fastest noise removed), leaving the tradable swing it should sharpen. The normalization window is then set from the market's measured dominant cycle rather than a fixed guess, so it stays tuned as cycles stretch and compress. The three only work as one tool.
How it works. Band-pass clean → locate price within its recent range, scaled to (−1, 1) → distribution-normalizing transform, smoothed → signal when the line crosses its one-bar trigger from an extreme. The window optionally follows a dominant cycle measured by autocorrelation of the band-passed price. Each signal is then labelled by a triple barrier — a profit target and an equal stop in ATR units, plus a time limit — so a "win" means the target was hit before the stop. Results split into in-sample and recent out-of-sample, with a confidence interval and a multiple-testing check.
How to use. Read the Verdict row (Long/Short signal, Watch, or Wait). Check Conviction — it reads "High" only when that signal type shows a positive edge that survives the statistical test on this symbol; otherwise treat it as context. Green wave above zero is up-pressure, red below is down; shaded bands are extremes; the faint line is the trigger. Best used with your own trend and risk plan, not alone.
What's original. The band-pass-cleaned input, the self-tuning window, the forward triple-barrier calibration with an out-of-sample split, and a conviction read that openly admits when there's no proven edge — instead of presenting every signal as equally reliable.
Inputs. Price source (change it for any market), reading mode (Simple/Pro), engine and self-tuning controls, extreme level, full calibration settings, and an auto-adapting dashboard legible on dark or light charts. Defaults are tuned for NSE:NIFTY1! intraday.
Honesty & limitations. Edge figures are computed on this chart's own history with overlapping windows and no costs — context, not a guaranteed backtest; past behaviour doesn't predict the future, and the cycle estimate lags at regime shifts.
Disclaimer: for research and education only. Not financial advice. Trading carries risk of loss; manage your own positions. Indicator
RSI Slope Divergence HelperRSI Slope Divergence Helper compares the rolling slope of price with the rolling slope of RSI.
This is not a classic pivot-divergence detector. It does not wait for confirmed swing pivots. Instead, it compares rolling price behavior and rolling RSI behavior directly by converting both slopes into normalized, unitless values and displaying them in the same pane.
The purpose of this script is to help users observe when price slope and RSI slope are moving together, moving against each other, or moving with low slope. It is a context and visualization tool only. It does not provide trade-action instructions and it is not a trading system.
What it shows
- Normalized price slope.
- Normalized RSI slope.
- A spread histogram between the two normalized slopes.
- Neutral slope-relationship states.
- A compact dashboard.
- Optional factual markers.
- A neutral Divergence Footprint layer.
How the calculation works
The script first calculates RSI using the selected RSI source and RSI length.
For price, it estimates a rolling linear-regression slope by comparing the current linear-regression value with the prior linear-regression value. The price slope is expressed as a percentage of the prior fitted price value so it can be compared across different symbols and price levels.
For RSI, the script estimates a rolling linear-regression slope from RSI itself. Since RSI is already bounded from 0 to 100, its slope is measured in RSI points.
The two slope series have different units, so they are normalized separately:
- price slope is divided by its own rolling standard deviation
- RSI slope is divided by its own rolling standard deviation
This converts both slopes into comparable unitless values.
The displayed spread is:
normalized price slope - normalized RSI slope
A positive spread means the normalized price slope is above the normalized RSI slope. A negative spread means the normalized price slope is below the normalized RSI slope.
No request.security() is used. The script uses current chart bars only and does not use lookahead or future data.
Why it is different from classic RSI divergence scripts
Many RSI divergence scripts compare confirmed price pivots with confirmed RSI pivots. This script takes a different approach.
It focuses on rolling slope behavior:
- price slope
- RSI slope
- normalized slope spread
- duration of the current disagreement episode
- peak spread during the current episode
- spread motion
- phase gap
Because it is slope-based, it is intended as a visual helper for observing disagreement between price movement and RSI movement. It is not a reversal detector and it does not forecast future price behavior.
Divergence Footprint
The Divergence Footprint is a neutral context layer that describes the current slope-disagreement episode.
It can show:
- whether slope disagreement is active
- how many bars the current disagreement episode has persisted
- the peak absolute spread reached during the current episode
- whether the absolute spread is expanding, cooling, or holding
- the phase gap between normalized price slope and normalized RSI slope
The phase gap is calculated by applying an angle transform to each normalized slope and then comparing the two angles. It is descriptive only. It is not a probability, score, forecast, or confirmation tool.
Optional phase-gap and duration plots are off by default to keep the pane clean.
State model
The dashboard uses neutral state names:
- Warming up
- Aligned upward
- Aligned downward
- Upper disagreement
- Lower disagreement
- Flat / low slope
- Mixed slopes
Upper disagreement means price slope is positive while RSI slope is negative.
Lower disagreement means price slope is negative while RSI slope is positive.
These states describe the current relationship between the two slopes. They do not imply reversal or continuation.
Markers and alerts
Markers are optional and off by default.
The marker display mode can be set to:
- Off
- Disagreement only
- All events
When enabled, markers are small and factual:
- P+ R- means price slope is positive while RSI slope is negative.
- P- R+ means price slope is negative while RSI slope is positive.
- Align marks slope agreement returning after a prior slope-disagreement episode, when enabled.
Alerts use the same neutral event logic:
- Upper slope disagreement
- Lower slope disagreement
- Slope agreement restored
- Spread crossed above threshold
- Spread crossed below threshold
Alerts are confirmed on bar close by default. Intrabar mode is available, but realtime values can update until the bar closes.
Dashboard
The default dashboard is compact and auto-sized. It is designed to stay readable without covering the indicator pane.
Compact layout shows:
- State
- Price slope
- RSI slope
- Spread
- Footprint
- Event mode
Standard and Detailed layouts add more context, including RSI value, spread motion, phase gap, disagreement bars, episode peak spread, active warm-up bars, and bar status.
Visual customization
Users can adjust:
- table layout
- table position
- table text size
- header text size
- table colors
- row backgrounds
- state-row highlighting
- plot colors
- histogram transparency
- marker colors
- background tint
- fixed table sizing, when desired
By default, fixed table cell sizing is off, so the dashboard auto-sizes to its content. Markers and background tint are also off by default to keep the pane clean.
Visual settings do not affect the calculations.
Live behavior and robustness
The script includes:
- automatic warm-up floor
- guarded denominators
- minimum normalized slope threshold
- optional spread-threshold filter for events
- optional minimum persistence for disagreement events
- optional event cooldown
- confirmed-bar event handling by default
- realtime / confirmed bar status disclosure in the table
If there is not enough history, or if the normalization denominator is not usable, the script avoids producing misleading slope states and displays safe fallback text such as n/a or Warming up.
Limitations
This script is not financial advice and not a trading system.
Slope disagreement can persist.
Slope disagreement can disappear without a major price move.
Slope disagreement does not predict reversal or continuation.
RSI is a bounded oscillator and can remain extended while price continues moving.
Default settings are starting points, not optimized settings.
Normalization length, slope length, smoothing length, and thresholds affect sensitivity.
Japanese notes
価格の傾きとRSIの傾きを正規化して比較し、両者の乖離をスプレッドとDivergence Footprintで表示する補助ツールです。通常のピボット型RSIダイバージェンス検出ではありません。売買判断や将来の値動きを示すものではなく、状況把握のための可視化ツールです。既定ではCompact表示、マーカーと背景色はオフ、確定足イベント処理がオンです。 Indicator
Haar Wavelet RSI [Jamallo]Author's Note
This is the oscillator companion to the Haar Wavelet Range Filter. Both indicators share the same MODWT Haar wavelet foundation, creating a synergistic effect when used together — trend and momentum derived from the same mathematical decomposition of price.
Introduction
The Haar Wavelet RSI is a momentum oscillator that replaces the standard price-difference input of a traditional RSI with wavelet detail coefficients derived from a Maximal Overlap Discrete Wavelet Transform (MODWT) with a Haar basis. Instead of measuring bar-to-bar price change, it measures momentum at a specific frequency scale — filtering out the noise above and below that scale before the RSI calculation even begins.
How It Works
MODWT Haar Wavelet Decomposition
The script decomposes hl2 through up to 5 wavelet levels using a shift-invariant Haar transform. At each level, the detail coefficients capture the local price delta at that specific scale — Level 1 is 2-bar momentum, Level 3 is 8-bar momentum, Level 5 is 32-bar momentum. These detail coefficients become the input to the RSI in place of raw price change, meaning the oscillator is measuring directional energy at a single isolated frequency rather than the full noisy price series.
Wavelet RSI Calculation
The selected detail coefficient is split into its upward and downward components, smoothed with Wilder's RMA, and fed into the standard RSI formula. The math is identical to a conventional RSI — the only difference is what it is measuring. Because the detail coefficients are already frequency-isolated, the resulting RSI is inherently cleaner than applying RSI to raw price.
Adaptive Deadband Step-Hold
The wavelet RSI output is then passed through an adaptive deadband filter. The threshold is self-derived from the RSI's own recent volatility — a short rolling average of absolute RSI changes — scaled by the deadband multiplier. The RSI only updates when it departs from its held value by more than this threshold. Below the threshold it holds flat. This eliminates the continuous micro-oscillation that makes standard RSI difficult to read on noisy bars, producing a stepped line that moves with conviction or not at all.
Closing
This is not a standard RSI with cosmetic changes. The wavelet decomposition fundamentally changes what the oscillator is measuring — momentum at a defined frequency scale rather than raw bar-to-bar noise. The decomposition level is the most important setting: lower levels suit faster timeframes and shorter momentum cycles, higher levels filter more aggressively and are better suited to swing-level momentum reads. Indicator
Indicator
AG Pro Williams %R Exhaustion Map [AGPro Series]AG Pro Williams %R Exhaustion Map
Overview / What it does
AG Pro Williams %R Exhaustion Map is a bounded-oscillator reaction map built to study exhaustion behavior around the extreme ends of Williams %R. Instead of treating Williams %R as a simple overbought/oversold trigger, this script maps whether an extreme reading is only being touched briefly, held with persistence, beginning to release, failing to release, or unwinding with more structure. The goal is to organize extreme-zone behavior into readable states rather than reduce the tool to a basic reversal shortcut.
The script is designed for traders who want to understand when an extreme condition is still being sustained and when that same condition may be starting to lose efficiency. In practice, that means the script focuses less on isolated crossings and more on the sequence around them: entry into an extreme zone, time spent there, the first release attempt, the possibility of a failed release, and the confirmation of an exhaustion unwind. This sequence-based framing is what gives the tool its map identity.
Within the AG Pro series, this script is intentionally separate from tools that revolve around trend confirmation, centerline balance, divergence, or generic momentum shifts. It is also intentionally separate from the series' Stochastic-based exhaustion work. Stochastic can be useful for reading swing rhythm and rotational turns, while this Williams %R version is centered more tightly on bounded extreme persistence and release behavior. In other words, this script is not presented as an alternative skin for another oscillator. It is a different framework for reading how price behaves when an oscillator remains pinned near an edge and then attempts to escape that condition.
Unique Edge
The unique edge of this script is not that it plots Williams %R, but that it classifies the life cycle of an extreme reading. The script distinguishes between stretch, locked conditions, release attempts, failed releases, and exhaustion unwinds. That structure helps separate three situations that are often mixed together in standard oscillator use:
1) an extreme reading that is still being sustained,
2) an extreme reading that has started to weaken but may still fail, and
3) an extreme reading that is releasing with enough follow-through to qualify as an exhaustion unwind.
This matters because many standard oscillator workflows treat every exit from an extreme zone as if it carried the same informational value. This script does not. It places more emphasis on persistence, release quality, and post-release follow-through, which can help users avoid treating every early reversal attempt as equivalent.
Methodology
The script begins with Williams %R and user-defined extreme thresholds. From there, it evaluates how long the oscillator remains in the upper or lower extreme zone and how deeply it is embedded in that zone. This forms the basis of the lock-strength logic. A fast touch into an extreme area and an extended embedded condition are therefore not interpreted in the same way.
Once an extreme condition has persisted long enough, the script begins monitoring for a release. A release is not defined as any random movement away from the boundary. It requires the prior extreme condition to have had sufficient persistence and then looks for a buffered move away from the threshold. This helps reduce noise from trivial fluctuations around the extreme lines.
After a release is detected, the script continues to track what happens next. If the oscillator quickly slips back into the same extreme region, the move can be classified as a failed release. If the move continues far enough away from the release anchor within the confirmation window, it can be classified as an exhaustion unwind. This post-release tracking is a central part of the script's design because it helps distinguish between temporary relief and more meaningful exhaustion release.
The panel summarizes this process using state, side, lock strength, and release quality. Lock strength is intended to reflect how established the prior extreme condition was. Release quality is intended to reflect the quality of the release sequence, not forecast what price must do next. These metrics are descriptive and contextual. They are not guarantees.
Signals & Alerts
This script provides event-style labels and alert conditions for the main transitions in the exhaustion sequence. The alerts are deterministic and tied to explicit script conditions rather than discretionary interpretation.
Main event types:
- Bullish release detected
- Bearish release detected
- Bullish release failed
- Bearish release failed
- Bull exhaustion unwind confirmed
- Bear exhaustion unwind confirmed
How to interpret them:
- A release event marks the first qualified move away from a persistent extreme condition.
- A failed release marks a release attempt that reverted back into the prior extreme condition too quickly.
- An exhaustion unwind confirmation marks a release that traveled far enough from its anchor within the configured window to qualify as a more established unwind sequence.
These events are intended to help structure chart reading. They are not standalone trade instructions, and they are not framed as guaranteed reversal signals.
Key Inputs
Williams %R Length
Controls the oscillator lookback period.
Upper Extreme / Lower Extreme
Define the zones used to classify upper and lower exhaustion behavior.
Lock Bars
Controls how much persistence is required before an extreme condition is treated as locked rather than only stretched.
Release Buffer
Adds distance beyond the raw threshold so the script does not treat every minor edge fluctuation as a release.
Confirm Distance / Confirm Window
Control how far and how quickly a release must extend to qualify as an exhaustion unwind.
Fail Window
Controls how quickly a release can revert back into the extreme zone and still be classified as a failed release.
Event Memory Bars
Controls how long the release state is remembered on the chart.
Visual Settings
Allow users to control event labels, minimum spacing between labels, background tint, and optional price-bar coloring.
Panel Settings
Allow users to control panel visibility, placement, font size, and theme.
How this differs from related AG Pro scripts
This script should not be confused with the series' other momentum or exhaustion tools.
Compared with Stochastic-based exhaustion work in the AG Pro series, this script is less about oscillator rhythm and more about the persistence and release structure of a bounded extreme condition. The emphasis here is on whether Williams %R remains pinned, whether the first escape attempt fails, and whether the unwind becomes established.
Compared with RSI-, CCI-, or MFI-oriented workflows, this script is not a centerline trend model, not a divergence engine, and not a money-flow proxy. Its purpose is narrower and more specific: to map the state transition of extreme Williams %R conditions.
Compared with broader trend or regime tools in the AG Pro series, this script is not trying to classify the full market environment by itself. It is better understood as a focused reaction map that can be used alongside a user's own structure, trend, or risk framework.
Limitations & Transparency
This is an indicator, not a strategy. It does not place orders, it does not calculate performance statistics, and it does not claim to predict future price direction. It visualizes oscillator-state transitions derived from Williams %R and user-defined thresholds.
Like all bounded oscillators, Williams %R can remain in extreme territory for extended periods during strong directional conditions. For that reason, an extreme reading should not automatically be interpreted as a reversal condition. This script attempts to improve that interpretation by separating stretch, lock, release, failed release, and unwind behavior, but it does not eliminate false positives.
Results can vary meaningfully with symbol, timeframe, volatility regime, and input configuration. Traders should expect the script to behave differently on very quiet markets, strongly trending markets, and highly reactive instruments. Label frequency and state persistence can also change materially when thresholds and confirmation settings are adjusted.
This tool is intended to support chart organization and decision framing. It should be used with the user's own market structure analysis, execution model, and risk management process.
Risk Disclosure
This script is provided for educational and analytical purposes only. It is not financial advice, not a solicitation, and not a promise of results. Trading and investing involve risk, including the risk of loss. No indicator can remove uncertainty from markets, and no exhaustion signal guarantees reversal, continuation, or trade success.
Users should validate any workflow with their own testing, judgment, and risk controls before using it in live decision-making.
Indicator
AG Pro CCI Reversion Quality [AGPro Series]AG Pro CCI Reversion Quality
Overview
AG Pro CCI Reversion Quality is a chart-based analysis framework designed to evaluate the quality of potential mean reversion conditions after meaningful CCI displacement. The script is not built around the simplistic idea that every overextended reading should immediately reverse. Instead, it focuses on whether a stretch condition begins to mature into a more structured, readable, and context-aware reversion environment.
The core objective is to separate raw CCI extremes from higher-quality reversion candidates. In many conventional oscillator workflows, a high positive or negative CCI reading is treated as a direct trigger. This script does not follow that approach. A strong stretch may still reflect healthy continuation, trend persistence, or unstable counter-trend conditions. For that reason, the script evaluates the quality of the reversion setup rather than the existence of a threshold breach alone.
The indicator is built for users who want a more selective framework around mean reversion. It examines whether price has deviated enough from an EMA-based reference mean, whether the reversion path remains meaningful, whether trend pressure is working against the setup, and whether recent structure suggests a cleaner or more crowded return path. The output is a contextual quality view rather than a one-dimensional overbought or oversold label.
This means the script should be understood as a decision-support tool for chart study and workflow organization. It is intended to help users distinguish between conditions that are immature, weak, blocked, developing, or stronger within a mean reversion context. It does not guarantee that price will reverse, and it does not assume that every stretch condition deserves a fade.
What the script does
The script monitors CCI displacement and then evaluates whether that displacement is beginning to convert into a more credible reversion environment. In practical terms, the workflow asks a sequence of questions. First, is there a meaningful stretch? Second, is the move beginning to lose directional quality or show reversion readiness? Third, is there enough room back toward the mean to matter? Fourth, is dominant trend pressure still strong enough to reduce the attractiveness of fading the move? Fifth, is nearby structure relatively clean, or is the path crowded by congestion and repeated mean interaction?
By combining those layers, the script attempts to reduce the noise associated with raw oscillator threshold logic. A positive stretch does not automatically imply a short setup. A negative stretch does not automatically imply a long setup. The script instead checks whether the overall reversion context is becoming more coherent.
This framework can be useful in discretionary workflows where users want to prioritize cleaner mean reversion candidates over mechanically reacting to every extreme oscillator reading. It is also useful for users who prefer a visual structure that summarizes context rather than one that continuously emits aggressive directional prompts.
Unique edge
The unique edge of this script is that it treats CCI as the starting point of the analysis, not the end point. Many oscillator-based studies stop at the detection of an extreme value. AG Pro CCI Reversion Quality continues beyond that stage and asks whether the extreme is maturing into a higher-quality reversion environment.
This makes the tool different from a basic CCI threshold script, a classic overbought/oversold marker, or a simple cross-based reversal detector. The script is not designed to label every extreme. It is designed to grade the environment around the extreme.
The indicator also keeps a clear distinction between stretch direction and stretch intensity. A market may be in a positive stretch or a negative stretch, but the degree of that stretch can still vary between mild, extended, and extreme conditions. In parallel, the script separately estimates reversion quality, trend pressure against the reversion idea, distance back to the reference mean, and structural friction. This multi-layered structure is meant to help users avoid treating all extreme readings as equivalent.
Another important difference is that the script explicitly accounts for context that can weaken a counter-trend reversion idea. Strong directional pressure, repeated interactions with the mean, and crowded local structure can all reduce the clarity of a fade. Instead of ignoring those conditions, the model reflects them in the displayed quality state.
Methodology
The script begins with a CCI calculation and identifies whether price is in a neutral regime, a positive stretch regime, or a negative stretch regime. It then classifies stretch intensity according to threshold-based displacement logic. The purpose of this stage is to define whether the market is extended enough for reversion analysis to become relevant.
From there, the indicator evaluates reversion readiness. This layer looks for signs that the stretch may be beginning to lose directional quality. Rather than relying on one isolated condition, the readiness component blends several pieces of information, such as directional change in CCI behavior, body structure, wick behavior, and simple stalling characteristics. This is meant to produce a broader view of whether reversion conditions are starting to organize.
The model then evaluates distance to mean. This matters because a reversion concept is less meaningful if price is already too close to the reference mean, while a more meaningful opportunity may exist when displacement remains materially extended. The reference anchor used here is an EMA-based mean, and the script also visualizes an ATR-based reversion zone around that mean.
Trend pressure is treated as a separate contextual penalty. This is a key design choice. A mean reversion idea that opposes strong directional pressure may be materially weaker than a similar stretch in a less forceful trend environment. The script therefore estimates how much prevailing directional pressure works against the reversion idea and reduces the effective quality view accordingly.
Structure friction is also included. This component is intended to reflect whether the recent path is relatively clean or crowded. Repeated interaction with the mean, compression, and congestion can reduce the clarity of a reversion path. Instead of assuming that all distance from the mean is equally attractive, the script attempts to reflect when the path back toward the mean is noisy or structurally inefficient.
All of these elements are combined into a composite Reversion Quality view. The final output is then expressed through panel information, chart labels, the zone display, and state logic.
State model
The state model is intentionally selective. It is meant to help users read context, not flood the chart with constant directional calls.
NEUTRAL indicates that there is no active stretch regime currently qualifying for reversion analysis.
WATCH indicates that a stretch exists and some reversion characteristics are forming, but the overall quality remains in an earlier or less mature stage.
READY indicates that the reversion quality has advanced enough to meet the preferred threshold defined by the user inputs. This does not imply certainty or guaranteed reversal. It simply means that the model sees a stronger monitored reversion context than it did at lower-quality states.
WEAK indicates that a stretch may exist, but the quality remains below the preferred threshold. This state is intentionally treated with caution.
BLOCKED indicates that the environment is materially impaired by elevated opposing pressure or structural friction. In other words, the stretch may exist, but the model does not consider the reversion context clean enough.
These states are designed to provide a workflow hierarchy rather than a promise hierarchy. The purpose is to help users prioritize and interpret, not to replace judgment.
Visual structure
The reference mean is displayed as an EMA-based mean line. Around it, the script plots an ATR-based reversion zone. This zone is intended to help users see the region surrounding the mean that is being used as the reversion anchor. The zone becomes more visually expressive when an active stretch context is present and more neutral when no active stretch is in focus.
The on-chart labels are designed to show the dominant local state when relevant. Depending on user settings, the script can display WATCH, READY, BLOCKED, and optionally WEAK labels. The label system is filtered by spacing logic so the chart remains more readable and does not endlessly repeat the same message on adjacent bars.
The information panel summarizes the active context. It is designed to show state, current reversion side, stretch direction, stretch intensity, reversion quality, trend pressure versus reversion, distance to mean, structure friction, setup bias, and a short risk note. The panel can also be repositioned from the settings, allowing the user to adapt placement to chart layout and personal preference.
The chart guide labels are included to make the mean and zone easier to identify visually. Their role is descriptive, not predictive.
Signals and alerts
The alert structure is built around monitored reversion states rather than trading promises. The available alert conditions include Ready Long Reversion, Ready Short Reversion, Watch Long Reversion, Watch Short Reversion, Reversion Quality Upgrade, and Reversion Quality Breakdown.
These alerts are designed to notify the user that the modeled reversion environment is changing. They should not be interpreted as guaranteed turning points. The script does not know future price behavior and does not claim to identify all reversals. It only identifies conditions that fit its internal reversion-quality logic.
Because different assets, sessions, and volatility structures behave differently, users should always validate whether the alert behavior matches their own chart-reading process and timeframe preference.
Key inputs
The script includes inputs for CCI length, reference mean length, multiple stretch thresholds, READY and WATCH thresholds, trend pressure filter strength, structure friction lookback, reversion zone width, label spacing, background highlight transparency, and visual display controls.
These inputs are intended to let users adapt the framework to different instruments and chart conditions. The script is not presented as universally optimal out of the box for all markets or all styles. Some users may prefer a more selective threshold structure, while others may prefer earlier WATCH states. Similarly, different assets may respond differently to the same mean length or zone width.
The visual controls are included to help users keep the chart readable. Users can enable or disable signal labels, WATCH labels, WEAK labels, background highlights, guide labels, and the information panel. Label size and panel text size are also configurable.
How to interpret the tool
A useful way to interpret the script is to think of it as a contextual filter around reversion conditions. A high stretch value alone is not enough. The quality concept becomes more meaningful when stretch, readiness, distance to mean, and contextual penalties begin to align.
If the script is neutral, it is signaling that no active stretch regime is currently in focus. If it is in WATCH, the script sees an emerging reversion environment, but one that may still be early or incomplete. If it reaches READY, the model is identifying a stronger monitored reversion context according to its current thresholds. If the state is BLOCKED, the model is emphasizing that pressure or structure is reducing the attractiveness of the reversion idea.
The panel is especially helpful for separating why a setup is weak. In some cases, quality may be limited because distance to mean is too thin. In other cases, trend pressure may still be high. In others, structure friction may be elevated even if displacement exists. This decomposition is intentional because it gives the user a more transparent framework than a single opaque signal.
What this script is not
This script is not a simple CCI threshold indicator. It is not designed to mark every move above or below a fixed level as a reversal opportunity.
It is not a guaranteed turning-point detector. Markets can remain extended for longer than expected, and strong trends can continue even after oscillator readings become extreme.
It is not a standalone execution system. The script does not account for all trade management variables, liquidity considerations, news catalysts, slippage, or user-specific risk parameters.
It is not a substitute for independent chart reading. It is intended to support analysis, not replace it.
Limitations and transparency
Like any chart-based model, this script has limitations. CCI extremes can persist, and a stretch can remain extended longer than a reversion-focused framework may prefer. In strong continuation phases, what appears to be a mature stretch can still fail to revert meaningfully.
The reversion-quality approach is also sensitive to the interaction between volatility, price structure, and trend behavior. Different markets can produce different behavior profiles. A configuration that feels balanced on one asset or timeframe may feel too early or too conservative on another.
The structure friction layer is an estimate, not an objective statement of future path quality. The trend pressure component is likewise a contextual model, not a certainty model. The script uses observable chart information to organize conditions, but it does not predict future order flow.
Users should also understand that visualization choices are meant to improve readability, not imply certainty. The mean line, reversion zone, state labels, and background highlights are interpretive aids.
Risk disclosure
This script is provided for chart analysis, research, and workflow support. It does not provide financial, investment, legal, or tax advice. Nothing displayed by the script should be interpreted as a promise of outcome or a guarantee of reversal.
All markets involve risk. Mean reversion concepts can fail, continuation can persist, and volatility conditions can change rapidly. Users should apply independent judgment, appropriate risk controls, and broader market context before acting on any chart-based interpretation.
The script should be used as one analytical layer among many, not as a self-sufficient decision engine.
Summary
AG Pro CCI Reversion Quality is a selective mean reversion quality framework built around CCI displacement, EMA-based mean reference logic, distance-to-mean context, trend pressure, and structure friction. Its purpose is not to say that every extreme should fade. Its purpose is to help identify when an extreme begins to organize into a more structured reversion environment.
The model is intended for users who want a cleaner, more context-aware interpretation of stretch conditions than a traditional threshold-only oscillator can provide. By separating stretch direction, stretch intensity, reversion quality, and contextual penalties, the script aims to make mean reversion analysis more structured, more transparent, and more selective.
Indicator
Quantum Relative Performance Oscillator [Pineify]Quantum Relative Performance Oscillator
A sophisticated relative strength indicator that normalizes performance metrics to identify true momentum shifts between an asset and its benchmark.
The Quantum Relative Performance Oscillator (RPO) is an advanced technical indicator designed to measure and visualize how a specific asset performs relative to a benchmark index. Unlike traditional relative strength indicators that can drift over time, this indicator normalizes the RS ratio to center around zero, providing traders with a clearer, more accurate picture of momentum shifts.
The Quantum RPO addresses a fundamental limitation in traditional relative strength analysis. While standard RS indicators show whether an asset is outperforming or underperforming a benchmark, they don't easily reveal when that outperformance is accelerating or decelerating. This indicator solves that problem by normalizing the relative strength ratio and applying weighted moving average smoothing to create clear, actionable trading signals.
Key Features
Normalized RS Calculation: Centers the relative strength ratio around zero, eliminating long-term drift and making it easier to identify current momentum trends
Weighted Moving Average (WMA) Processing: Uses WMA instead of simple moving averages for more responsive calculations that give greater weight to recent price action
Dynamic Color Histogram: Visual representation of momentum acceleration and deceleration with intelligent color coding
Crossover Signals: Clear bullish and bearish momentum shift indicators when the RS Ratio crosses above or below the signal line
Customizable Benchmark: Compare any asset against a user-selected benchmark symbol (default: SPY)
Adjustable Parameters: Configurable lookback length and signal smoothing for different timeframes and trading styles
Built-in Alerts: Automated notifications for momentum shift events
How It Works
The indicator fetches closing prices for both the current asset and the user-defined benchmark symbol
It calculates the raw Relative Strength (RS) by dividing the asset's close price by the benchmark's close price
A Weighted Moving Average (WMA) is applied to the RS to establish a baseline equilibrium level
The RS Ratio is calculated as: (RS / WMA) * 100 - 100, which normalizes the value around zero
A Signal Line is created by applying additional WMA smoothing to the RS Ratio
The histogram (Performance Delta) shows the difference between the RS Ratio and Signal Line, indicating momentum strength
Trading Ideas and Insights
Momentum Confirmation: Use the RS Ratio crossing above zero as confirmation that an asset is gaining relative strength against its benchmark
Trend Reversal Signals: Watch for bullish crossovers (RS Ratio crossing above Signal Line) to identify potential trend reversals
Relative Strength Screening: Compare multiple assets using the same benchmark to identify the strongest performers in a sector
Divergence Detection: Look for situations where price makes new highs but the RS Ratio fails to confirm, indicating weakening relative momentum
Sector Rotation: Use different benchmarks (sector ETFs) to identify rotation between sectors
How Multiple Indicators Work Together
This indicator combines three separate but complementary calculations to create a comprehensive relative strength tool:
The raw RS calculation provides the fundamental comparison between asset and benchmark performance
The WMA normalization removes drift and creates a centered oscillator that oscillates around zero
The signal line smoothing filters out noise and provides clear crossover points for trading signals
The histogram visualization combines both elements to show the magnitude and direction of momentum in one clear display
Unique Aspects
Unlike traditional RS indicators that can drift indefinitely higher or lower over time, the Quantum RPO's normalized calculation ensures the oscillator remains centered, making it easier to identify overbought and oversold conditions in relative terms
The dynamic color histogram provides intuitive visual feedback about whether momentum is accelerating or decelerating, helping traders avoid false signals
The use of Weighted Moving Averages rather than simple moving averages provides more responsive calculations that adapt faster to changing market conditions
The built-in alert system allows traders to receive notifications automatically when momentum shifts occur, without needing to constantly monitor the chart
How to Use
Apply the indicator to any asset's chart
Select your preferred benchmark symbol in the settings (SPY for US stocks, BTCUSD for crypto, etc.)
Interpret the RS Ratio: Positive values indicate outperformance, negative values indicate underperformance
Use the Signal Line crossovers for entry signals: Buy when RS Ratio crosses above Signal Line, Sell when it crosses below
Monitor the histogram for momentum confirmation: Green columns rising indicate strengthening bullish momentum, red columns falling indicate strengthening bearish momentum
Set up alerts for bullish and bearish momentum shifts to receive notifications
Customization
Benchmark Symbol: Change the comparison asset (SPY, QQQ, BTCUSD, etc.)
Lookback Length: Adjust the period for WMA calculations (default: 20). Higher values produce smoother results with more lag; lower values are more responsive but may generate more false signals
Signal Length: Modify the smoothing period for the signal line (default: 9)
Color Customization: Customize the bullish (outperforming) and bearish (underperforming) colors to match your preferences
These parameters can be adjusted to suit different trading timeframes, from intraday scalping to long-term position trading
The Quantum Relative Performance Oscillator is a powerful tool for traders who want to understand not just whether an asset is outperforming its benchmark, but whether that outperformance is accelerating or losing steam. By normalizing the relative strength calculation and providing clear visual and alert-based signals, it helps traders make more informed decisions about entries, exits, and asset allocation across different markets and timeframes.
Indicator
Thermal Momentum Gauge [JOAT]Thermal Momentum Gauge
Introduction
The Thermal Momentum Gauge is an open-source institutional-grade pressure and volatility monitoring system that combines market pressure measurement, volatility temperature analysis, volume steam detection, and multi-factor explosion identification into a unified oscillator. This sophisticated system integrates multiple proven momentum methodologies to identify high-probability explosive move conditions where pressure, temperature, and steam factors converge.
The indicator is designed for traders who understand that explosive market moves occur when multiple pressure systems align simultaneously. By synthesizing RSI pressure, WaveTrend momentum, Money Flow Index analysis, Stochastic pressure, ATR temperature, Bollinger Band width, volume steam detection, and confluence scoring, this tool helps identify structural market explosion points with thermal precision.
Why This Integration Exists
This indicator combines seven distinct pressure and volatility measurement frameworks that complement each other:
Multi-Component Pressure System: Combines RSI, WaveTrend, MFI, and Stochastic RSI for comprehensive pressure measurement
Thermal Temperature Analysis: Uses ATR and Bollinger Band width to measure market volatility temperature
Volume Steam Detection: Analyzes volume spikes and directional volume pressure for steam identification
Explosion Detection Engine: Multi-factor confluence system that identifies when all pressure systems align
Momentum Confirmation System: Ensures signals occur at genuine turning points through momentum analysis
Pressure Zone Classification: Defines thermal zones from extreme oversold to extreme overbought
Signal Filtering System: Prevents overlapping signals while maintaining precision timing
Each component addresses different aspects of market thermal dynamics. Pressure measurement reveals directional bias, temperature analysis shows volatility energy, steam detection indicates volume explosions, and confluence scoring quantifies setup quality. Together, they create a comprehensive thermal view that traditional single-dimension momentum indicators cannot provide.
Core Components Explained
1. Multi-Component Pressure System (0-100 Scale)
The system combines four pressure measurements for comprehensive analysis:
RSI Pressure:
RSI Pressure = RSI(close, rsi_length) // Standard 0-100 scale
WaveTrend Pressure:
ESA = ema(hlc3, wt_channel_length)
D = ema(abs(hlc3 - ESA), wt_channel_length)
CI = (hlc3 - ESA) / (0.015 * D)
WT1 = ema(CI, wt_average_length)
WT Pressure = (WT1 + 100) / 2 // Normalize -100 to 100 → 0 to 100
MFI Pressure:
MFI Pressure = MFI(hlc3, mfi_length) // Money Flow Index 0-100
Stochastic RSI Pressure (Optional):
Stochastic RSI = Stochastic(RSI(close, rsi_length), stoch_length)
Stoch Pressure = sma(Stochastic RSI, 3)
Combined Pressure:
Total Pressure = (RSI + WT + MFI + Stoch) / 4 // With Stochastic
Total Pressure = (RSI + WT + MFI) / 3 // Without Stochastic
2. Thermal Temperature System (0-100 Scale)
Measures market volatility energy through dual methods:
ATR-Based Temperature:
ATR Percentage = (ATR(atr_length) / close) * 100
ATR Temperature = ATR Percentage * temperature_multiplier
Bollinger Band Width Temperature (Optional):
BB Basis = sma(close, bb_length)
BB Deviation = bb_multiplier * stdev(close, bb_length)
BB Width = ((BB Upper - BB Lower) / BB Basis) * 100
BB Temperature = BB Width * 5 // Scale to 0-100
Combined Temperature:
Temperature = min((ATR Temperature + BB Temperature) / 2, 100) // With BB
Temperature = min(ATR Temperature, 100) // Without BB
3. Volume Steam Detection (0-100 Scale)
Analyzes volume explosions and directional pressure:
Volume Steam Base:
Volume Ratio = volume / sma(volume, volume_length)
Steam Base = Volume Ratio * 50
Volume Delta (Optional):
Buy Volume = close > open ? volume : 0
Sell Volume = close < open ? volume : 0
Volume Delta = (Buy Volume - Sell Volume) / volume * 50
Combined Steam:
Steam = min(Steam Base + abs(Volume Delta), 100)
Steam Classifications:
- Steam Burst: Steam > steam_threshold (default 80)
- Extreme Steam: Steam > 90
- Volume Spike Direction: Bullish (close > open) or Bearish (close < open)
4. Explosion Detection Engine
Multi-factor confluence system with momentum confirmation:
Momentum Confirmation:
Pressure Momentum = change(Total Pressure)
Pressure Acceleration = change(Pressure Momentum)
Momentum Shift = (momentum > 0 AND momentum <= 0) OR (momentum < 0 AND momentum >= 0)
Confluence Score (0-5):
Confluence Components:
- Pressure Factor: Total Pressure > pressure_threshold ? 1 : 0
- Temperature Factor: Temperature > temperature_threshold ? 1 : 0
- Steam Factor: Steam > steam_threshold ? 1 : 0
- WaveTrend Extreme: WT Pressure > 80 OR WT Pressure < 20 ? 1 : 0
- Extreme Steam: Steam > 90 ? 1 : 0
Confluence Score = Sum of all factors (0-5)
Explosion Conditions:
Explosion = Confluence Score >= minimum_confluence AND (Momentum Shift OR abs(Pressure Acceleration) > 2)
Bull Explosion = Explosion AND Total Pressure > 50 AND Pressure Momentum > 0
Bear Explosion = Explosion AND Total Pressure < 50 AND Pressure Momentum < 0
Perfect Explosion (Rare):
Perfect Explosion = Confluence Score == 5 AND abs(Pressure Momentum) > 3
Perfect Bull = Perfect Explosion AND Total Pressure > 50 AND Pressure Momentum > 0
Perfect Bear = Perfect Explosion AND Total Pressure < 50 AND Pressure Momentum < 0
5. Thermal Zone Classification
The system defines seven thermal pressure zones:
Extreme Overbought: Pressure > 80 (Critical thermal level)
Overbought: Pressure 70-80 (High thermal level)
Neutral High: Pressure 55-70 (Warm thermal level)
Equilibrium: Pressure 45-55 (Neutral thermal zone)
Neutral Low: Pressure 30-45 (Cool thermal level)
Oversold: Pressure 20-30 (Low thermal level)
Extreme Oversold: Pressure < 20 (Critical thermal level)
6. Signal Filtering System
Prevents overlapping signals while maintaining precision:
Minimum Bars Between Signals = 8
Signal Filtering Logic:
- Perfect signals take priority over regular explosions
- Regular explosions are filtered if perfect signal occurred recently
- Warning signals are filtered if explosion signals are active
- Steam bursts are filtered to minimum 3 bars apart
Visual Elements
Thermal Pressure Wave: Main oscillator with thermal gradient coloring and glow effects
Component Pressures: Individual RSI, WT, MFI, and Stochastic lines (hidden by default)
Temperature Background: Heat map style background coloring based on volatility temperature
Steam Burst Histograms: Volume spike visualization with directional coloring
Thermal Zone References: Critical levels at 20, 30, 50, 70, 80 with neutral zone highlighting
Explosion Markers: Diamond shapes for perfect explosions, triangles for regular explosions
Warning Signals: Circle markers for approaching explosion conditions
Pressure Meter: Visual gauge showing current pressure level with thermal gradient
Dashboard: Comprehensive real-time display of all thermal components and status
How Components Work Together
The integration creates a thermal momentum analysis approach:
Layer 1 - Pressure Measurement: Multi-component system reveals directional pressure across four dimensions
Layer 2 - Temperature Analysis: Volatility measurement shows market energy and expansion potential
Layer 3 - Steam Detection: Volume analysis identifies explosive energy release conditions
Layer 4 - Momentum Confirmation: Ensures signals occur at genuine turning points, not random noise
Layer 5 - Confluence Scoring: Quantifies setup quality by counting aligned factors
Layer 6 - Explosion Detection: Identifies rare moments when all thermal systems align
Layer 7 - Signal Filtering: Prevents overlap while maintaining precision timing
Example scenario: Pressure reaches extreme oversold (Layer 1) with high temperature (Layer 2), volume steam burst (Layer 3), momentum shift confirmation (Layer 4), confluence score of 5 (Layer 5), triggering perfect bull explosion (Layer 6) with proper signal filtering (Layer 7). This represents maximum thermal alignment for explosive upward move.
Input Parameters
Pressure Settings:
RSI Length: Period for RSI calculation (default: 14)
WT Channel Length: WaveTrend channel period (default: 10)
WT Average Length: WaveTrend smoothing period (default: 21)
MFI Length: Money Flow Index period (default: 14)
Stochastic Length: Stochastic RSI period (default: 14)
Use Stochastic Pressure: Toggle fourth pressure component
Temperature Settings:
ATR Length: Average True Range period (default: 14)
Temperature Multiplier: Sensitivity adjustment (default: 10.0)
Use Bollinger Band Width: Toggle BB width temperature component
BB Length: Bollinger Band period (default: 20)
BB Multiplier: Bollinger Band deviation (default: 2.0)
Volume Settings:
Volume MA Length: Volume average period (default: 20)
Steam Threshold: Volume spike multiplier (default: 2.0)
Use Volume Delta: Toggle directional volume analysis
Show Volume Spikes: Toggle volume spike visualization
Explosion Settings:
Pressure Threshold: Minimum pressure for explosion (default: 80)
Temperature Threshold: Minimum temperature for explosion (default: 70)
Steam Threshold: Minimum steam for explosion (default: 80)
Minimum Confluence Score: Required factors for explosion (default: 3)
Show Explosion Warnings: Toggle warning markers
How to Use This Indicator
Step 1: Assess Thermal Pressure
Check the main pressure gauge and current thermal zone classification in the dashboard.
Step 2: Monitor Temperature Levels
High temperature (>70) indicates market energy building for potential explosive moves.
Step 3: Watch for Steam Bursts
Volume steam bursts (>80) show explosive energy release with directional bias.
Step 4: Check Confluence Score
Scores ≥3 indicate multiple thermal factors aligning for explosion potential.
Step 5: Wait for Momentum Confirmation
Explosions require momentum shifts or acceleration to confirm genuine turning points.
Step 6: Identify Explosion Signals
Perfect explosions (diamond markers) offer highest probability, regular explosions (triangles) offer good probability.
Step 7: Monitor Warning Signals
Warning markers indicate approaching explosion conditions - prepare for potential signals.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal thermal detection
Focus on extreme thermal zones (<20 or >80) for highest explosion probability
Perfect explosions are rare but offer exceptional risk:reward opportunities
Temperature confirmation adds conviction to pressure-based signals
Steam direction (bullish/bearish) should align with expected explosion direction
Confluence scores ≥4 significantly increase explosion probability
Warning signals help prepare for upcoming explosion opportunities
Thermal zone transitions often precede significant price movements
Indicator Limitations
Thermal pressure can remain extreme longer than expected during strong trends
Perfect explosions are rare - patience required for highest probability setups
Temperature spikes during news events may create false explosion signals
Steam bursts don't guarantee immediate price movement - timing varies
Confluence scoring is mathematical, not predictive of future performance
Component pressures may conflict, requiring interpretation skills
Signal filtering may delay signals in rapidly changing market conditions
Requires understanding of multi-factor thermal analysis concepts
Technical Implementation
Built with Pine Script v6 using:
Multi-component pressure calculation with optional Stochastic RSI integration
Dual-method temperature analysis using ATR and Bollinger Band width
Advanced volume steam detection with directional bias measurement
Multi-factor confluence scoring system with momentum confirmation
Thermal gradient coloring system with glow effects and heat map backgrounds
Anti-overlap signal filtering with priority-based signal management
Real-time pressure meter visualization with thermal zone classification
Comprehensive dashboard with component breakdown and explosion status
The code is fully open-source and can be modified to suit individual trading styles and preferences.
Originality Statement
This indicator is original in its thermal momentum integration approach. While individual components (RSI, WaveTrend, MFI, ATR, volume analysis) are established concepts, this integration is justified because:
It synthesizes seven distinct thermal and momentum methodologies into a unified system
The multi-component pressure system provides comprehensive momentum analysis beyond single indicators
Thermal temperature analysis combines volatility measurements for energy assessment
Volume steam detection adds explosive energy context to momentum signals
Multi-factor confluence scoring quantifies setup quality across all thermal dimensions
Perfect explosion detection identifies rare, high-probability explosive move conditions
Each component contributes unique thermal information: pressure measurement reveals directional momentum, temperature analysis shows volatility energy, steam detection indicates volume explosions, confluence scoring quantifies alignment, and momentum confirmation ensures signal quality. The integration's value lies in identifying moments when all thermal systems align simultaneously for explosive market moves.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Thermal momentum analysis and explosion detection are analytical concepts that do not guarantee future price movement. Past performance and backtested results do not guarantee future results. Market conditions change, and thermal patterns that worked historically may not work in the future.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Smart Fear & Greed Index [MarkitTick]💡 This comprehensive technical tool is designed to quantify market sentiment on an asset-specific basis, translating complex price action into a singular, normalized gauge of "Fear" and "Greed." While traditional Fear & Greed indices rely on macro-economic data (like put/call ratios or junk bond demand) generally applied to the broad S&P 500, this script calculates a localized index for the specific chart you are viewing. It synthesizes Momentum, Volatility, Volume, and Price Positioning into a bounded 0-100 oscillator, aiming to identify psychological extremes where market reversals are statistically more likely to occur.
✨ Originality and Utility
● Asset-Specific Sentiment Analysis
Most sentiment tools are external to the chart (e.g., news sentiment or broad market indices). The Smart Fear & Greed Index is unique because it internalizes this logic, creating a bespoke psychological profile for any ticker—whether it is Crypto, Forex, or Stocks. It allows traders to see if *this specific asset* is overheated (Greed) or oversold (Fear) relative to its own recent history.
● The "Buy the Fear, Sell the Greed" Logic
The script employs a contrarian color-coding philosophy aligned with the famous investment adage: "Be fearful when others are greedy, and greedy when others are fearful."
When the indicator shows Fear (Low values), it colors the zone Green, signaling a potential buying opportunity (discount).
When the indicator shows Greed (High values), it colors the zone Red, signaling potential downside risk (premium).
● Integrated Divergence Detection
Unlike standard oscillators that leave interpretation entirely to the user, this tool includes an automated divergence engine. It detects discrepancies between the sentiment index and price action, plotting lines and labels to highlight potential exhaustion points before they become obvious on the price chart.
🔬 Methodology and Concepts
The calculation is driven by a custom User-Defined Type (UDT) called QuantEngine , which aggregates four distinct technical "pillars" to form the final Composite Index.
• Pillar 1: Momentum (RSI)
The engine utilizes the Relative Strength Index to measure the velocity and magnitude of directional price movements. High momentum contributes to the "Greed" score, while collapsing momentum contributes to "Fear."
• Pillar 2: Volatility (Inverted Normalized ATR)
This component interprets volatility through a psychological lens.
Low Volatility is interpreted as complacency or "Greed" (steady uptrends often have low vol).
High Volatility is interpreted as "Fear" (panic selling and erratic ranges often spike volatility).
The script normalizes the Average True Range (ATR) and inverts it so that stability adds to the score, and instability subtracts from it.
• Pillar 3: Volume Strength
Volume is analyzed relative to its moving average. However, raw volume isn't enough; the engine applies directional logic.
High relative volume on an Up-Close adds to the Greed score.
High relative volume on a Down-Close subtracts, adding to the Fear score.
• Pillar 4: Price Position (Stochastic)
This calculates where the current close sits relative to the recent High-Low range. Closing near the highs indicates confidence (Greed), while closing near the lows indicates pessimism (Fear).
• The Composite & Smoothing
These four metrics are averaged to create a raw composite, which is then smoothed via an Exponential Moving Average (EMA) to filter out noise and produce the final, readable "Smart Fear & Greed" line.
🎨 Visual Guide
● The Oscillator Line
This is the primary fluctuating line that moves between 0 and 100.
Values > 50 suggest positive sentiment.
Values < 50 suggest negative sentiment.
● Color-Coded Zones
The plot changes color dynamically to reflect the psychological state:
Red (70-100): Extreme Greed. The market may be irrationally exuberant.
Orange (60-70): Greed. Strong bullish conviction.
Yellow (40-60): Neutral. Indecisive or transitionary market.
Light Green (30-40): Fear. Sentiment is turning bearish.
Bright Green (0-30): Extreme Fear. Panic selling, often a precursor to a value bounce.
● Background Highlights
A semi-transparent Red Background appears when the index breaches 75, warning of a potential "Top."
A semi-transparent Green Background appears when the index drops below 25, highlighting a potential "Bottom."
● Divergence Elements
Red Lines/Labels ("Bear"): Bearish Divergence. Price makes a Higher High, but the Index makes a Lower High. This suggests momentum is waning despite rising prices.
Green Lines/Labels ("Bull"): Bullish Divergence. Price makes a Lower Low, but the Index makes a Higher Low. This suggests selling pressure is drying up.
📖 How to Use
• Identifying Reversals
Wait for the oscillator to enter "Extreme" zones. Do not trade immediately upon entry; wait for the line to exit the extreme zone to confirm the reversal. For example, if the line hits 80 (Red) and then crosses back down below 70, it signals that Greed is fading.
• Trend Continuation
In a strong trend, the indicator may hover in the Greed (Orange) or Fear (Light Green) zones for extended periods. In these cases, use the Neutral (Yellow) zone crosses as re-entry signals in the direction of the trend.
• Divergence Confirmation
Use the automated divergence lines as high-conviction triggers. If the background turns Green (Extreme Fear) AND a Bullish Divergence label appears, it provides a stronger technical case for a long position than the zone alone.
⚙️ Inputs and Settings
● Calculation Settings
Global Lookback Period (Default: 21): The core lookback window for RSI, ATR, Volume, and Stochastic calculations. Increasing this makes the index slower and less reactive; decreasing it makes it faster.
Smoothing Length (Default: 5): Determines how smooth the final line is. Higher numbers reduce "whipsaws" but add lag.
Color Main Chart Candles : Colors the chart bars based on Fear/Greed sentiment.
● Divergence Settings
Divergence Lookback (Default: 5): Determines the pivot strength required to register a high or low for divergence checks.
Show Divergence Lines/Labels: Toggles to hide visual clutter if you only want to see the oscillator.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Normalization Theory
The core scientific principle here is Min-Max Normalization. The script takes heterogeneous data types—Price (Dollars/Cents), Volume (Shares/Contracts), and Volatility (Points)—and standardizes them into a unit-less distribution between 0 and 100. This allows for the summation of disparate market forces into a single vector.
● Mean Reversion and Oscillator Bounds
The indicator relies on the statistical concept of Mean Reversion. Markets, like elastic bands, can only stretch so far from their average valuation (represented by the 50 line) before snapping back. The "Extreme" zones (Upper and Lower deciles) represent areas of statistical improbability where the likelihood of a continuation decreases and the likelihood of a reversion increases.
● Divergence and Momentum Theory
The divergence logic is grounded in the principle that momentum precedes price. Mathematically, price is the integral of velocity. When the derivative (momentum/sentiment) approaches zero or reverses while the function (price) continues, it signals a non-sustainable anomaly in the data series, often resolved by a price correction.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
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Indicator
FluxPulse Momentum [JOAT]FluxPulse Momentum - Adaptive Multi-Component Oscillator
FluxPulse Momentum is a composite oscillator that blends three distinct momentum components into a single, smoothed signal line. Rather than relying on a single indicator, it synthesizes adaptive RSI, normalized rate of change, and a Kaufman-style efficiency ratio to provide a multi-dimensional view of momentum.
What This Indicator Does
Combines RSI, Rate of Change (ROC), and Efficiency Ratio into one weighted composite
Applies EMA smoothing to reduce noise while preserving responsiveness
Displays overbought/oversold zones with optional background highlighting
Generates buy/sell signals when the oscillator crosses its signal line in favorable zones
Provides a real-time dashboard showing current state, momentum direction, and efficiency
Core Components
Adaptive RSI (50% weight) — Standard RSI calculation normalized around the 50 level
Normalized ROC (30% weight) — Rate of change scaled relative to its recent maximum range
Efficiency Ratio (20% weight) — Measures directional movement efficiency, inspired by Kaufman's adaptive concepts
The final composite is smoothed twice using EMA to create both a fast line and a signal line.
Signal Logic
// Buy signal: crossover in lower half
buySignal = ta.crossover(qmo, qmoSmooth) and qmo < 50
// Sell signal: crossunder in upper half
sellSignal = ta.crossunder(qmo, qmoSmooth) and qmo > 50
Signals are generated only when the oscillator is positioned favorably—buy signals occur below the 50 midline, sell signals occur above it.
Dashboard Information
The on-chart table displays:
Current oscillator value with gradient coloring
Momentum state (Overbought, Oversold, Bullish, Bearish, Neutral)
Momentum direction and acceleration
Efficiency ratio percentage
Active signal status
Inputs Overview
RSI Length — Period for RSI calculation (default: 14)
ROC Length — Period for rate of change (default: 10)
Smoothing Length — EMA smoothing period (default: 3)
Overbought/Oversold Levels — Threshold levels for zone detection
Await Bar Confirmation — Wait for bar close before triggering alerts
How to Use It
Watch for crossovers between the main line and signal line
Use overbought/oversold zones to identify potential reversal areas
Monitor the histogram for momentum acceleration or deceleration
Combine with price action analysis for confirmation
Alerts
Buy Signal — Bullish crossover in the lower zone
Sell Signal — Bearish crossunder in the upper zone
Overbought/Oversold Crosses — Level threshold crossings
This indicator is provided for educational purposes. It does not constitute financial advice. Always conduct your own analysis before making trading decisions.
— Made with passion by officialjackofalltrades Indicator
Indicator
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them. Indicator
Cumulative Volume Delta Divergence [TradingFinder] Periodic EMA🔵 Introduction
The Cumulative Volume Delta (CVD) is a powerful tool in technical analysis that is derived from market volume or trading activity. The Cumulative Volume Delta Divergence Detector Indicator helps traders identify Cumulative Volume Delta Divergences (CVD Divergence), which can provide reliable trading signals.
These divergences, such as bullish and bearish CVD divergences, act as key indicators of potential trend reversals in financial markets. By analyzing CVD divergences, traders can gain insights into the strength of buying and selling pressure and make more informed predictions about price trends.
The CVD indicator is particularly effective for traders who engage in day trading and scalping, as it helps identify price reversal points by analyzing volume and price behavior.
Using the CVD indicator in combination with other technical tools such as support and resistance levels and candlestick patterns allows for a more accurate market analysis.
🔵 How to Use
Divergences are one of the most important technical analysis signals that indicate the current strength of a price move may not be sustainable.
Cumulative Volume Delta Divergence helps traders identify potential trading opportunities that may not be visible on the price chart alone.
This type of divergence examines the relationship between buying and selling volume and price, enabling traders to better understand price trends.
🟣 Bullish CVD Divergence
A bullish CVD divergence occurs when the price makes a lower low, but the CVD indicator shows a higher low. This indicates increasing buying pressure in the market, even though the price is declining. In other words, despite the price dropping, buyers are gradually gaining strength, which could signal a price reversal and the start of a bullish trend.
How to use this signal : In this scenario, traders looking to go long can use this signal as a favorable opportunity to enter the market. After a bullish divergence, the market typically tends to move upward.
To reduce risk, traders can wait for further confirmation from the price chart. For example, if the price breaks through the previous high after the divergence or breaks a resistance level, this could be a more reliable signal for entering the market.
🟣 Bearish CVD Divergence
A bearish CVD divergence is the opposite of a bullish divergence. In this type of divergence, the price makes a higher high, but the CVD indicator shows a lower high. This indicates decreasing buying pressure and weakening momentum in the current bullish trend. A bearish divergence often serves as a warning of a potential market reversal to the downside.
How to use this signal : Traders can use this divergence as an opportunity to exit long positions or enter short positions. When the CVD indicator makes a lower high compared to the price, it signals weakness in buyer strength.
If traders receive further confirmation from the price chart, such as a break of key support levels or an increase in selling volume, this can serve as a stronger signal for the beginning of a bearish trend.
🟣 How to Build a Trading Strategy with Cumulative Volume Delta Divergence
Using CVD divergence alone may not be sufficient. Traders should combine this tool with other technical analysis techniques and indicators to have more confidence in their decisions. For example, when observing a CVD divergence, traders can also analyze volume, trend lines, or candlestick patterns to get a more accurate market analysis.
Additionally, risk management should always be a priority. Using stop-loss orders and properly sizing trades can help traders minimize their losses if they make a mistake.
🔵 Setting
Divergence Fractal Period : Determines the period of swings. The minimum and default value is 2.
CVD Period : You can set the period of " Periodic " and " EMA " modes.
Cumulative Mode : It has three modes "Periodic" and "EMA". In "Periodic" mode, it accumulates the volume periodically and in "EMA" mode, it calculates the moving average of the volume.
Market Ultra Data : If you turn on this feature, 26 large brokers will be included in the calculation of the trading volume. The advantage of this capability is to have more reliable volume data. You should be careful to specify the market you are in, FOREX brokers and Crypto brokers are different.
🔵 Conclusion
The Cumulative Volume Delta (CVD) indicator is a powerful tool in technical analysis, helping traders better identify price trends and make more accurate market predictions. By identifying CVD divergences, traders can anticipate price reversals and time their market entries and exits accordingly.
Bullish and bearish CVD divergences each provide valuable signals that can help traders identify the best entry and exit points in the market. A bullish CVD divergence signals strength in buying that will likely lead to a price increase, while a bearish CVD divergence indicates weakness in the bullish trend and the potential for the beginning of a bearish trend.
Overall, combining CVD with other technical analysis tools and employing risk management strategies can help traders make better trading decisions and capitalize on available market opportunities.
Indicator
KST con HMA---------- ENGLISH DESCRIPTION ----------
The indicator created is called "KST with HMA" and is used to measure the impulse of an asset's price.
The code begins by defining four variables representing ROC (Rate of Change) period lengths for calculating the KST (Know Sure Thing) and a variable for the length of the HMA (Hull Moving Average).
Next, an HMA function is defined to calculate the Hull Moving Average, a type of weighted moving average that adjusts for price volatility.
ROC values are then calculated for the four periods defined above and KST values are calculated as a weighted sum of the ROC values. These values are then normalized with the HMA and the standard deviation of the HMA is calculated. The normalized value is finally plotted with three different color lines: black for values greater than 1, red for values less than -1, and green for values between -1 and 1.
Finally, a black dashed line is plotted to represent the zero line. The green line indicates a phase of market uncertainty or lateralization, while the indicator can be used to identify buy points above zero and sell points below zero.
---------- ITALIAN DESCRIPTION ----------
L'indicatore creato è chiamato "KST con HMA" e viene utilizzato per misurare l'impulso del prezzo di un asset.
Il codice inizia definendo quattro variabili che rappresentano le lunghezze dei periodi di ROC (Rate of Change) per il calcolo del KST (Know Sure Thing) e una variabile per la lunghezza dell'HMA (Hull Moving Average).
Successivamente viene definita una funzione HMA per il calcolo della Hull Moving Average, un tipo di media mobile ponderata che si adatta alla volatilità del prezzo.
Vengono poi calcolati i valori ROC per i quattro periodi definiti in precedenza e calcolati i valori KST come somma ponderata dei valori ROC. Questi valori vengono poi normalizzati con l'HMA e viene calcolata la deviazione standard dell'HMA. Il valore normalizzato viene infine plottato con tre diverse linee di colore: nero per valori superiori a 1, rosso per valori inferiori a -1 e verde per valori tra -1 e 1.
Infine, viene plottata una linea tratteggiata nera per rappresentare la linea zero. La linea verde indica una fase di incertezza o lateralizzazione del mercato, mentre l'indicatore può essere utilizzato per individuare punti di acquisto sopra lo zero e di vendita al di sotto dello zero. Indicator
TRIX with Momentum----------- ENGLISH --------------
This indicator is called "TRIX with Momentum" and is used to analyze the momentum of an asset's price and predict potential trend reversals. The logic of operation is based on the combination of two indicators: the Triple Exponential Moving Average (TRIX) and the momentum oscillator.
The TRIX is calculated using three exponential moving averages (EMA) of the asset's closing price, with a user-defined length (set to 14 by default). The TRIX is then normalized and centered around 0 to facilitate analysis of its relationship with the momentum oscillator.
The momentum oscillator is calculated using the EMA of the normalized TRIX with a user-defined length (set to 14 by default).
The indicator plots the normalized TRIX and the momentum oscillator on a chart, using different colors to indicate whether the TRIX is above or below 0. Additionally, the color of the y-axis label changes based on the position of the oscillator, while the color of the x-axis label remains gray.
The indicator uses a weighted average between the normalized TRIX and the momentum oscillator to create a colored background of the chart, which changes based on the weighted average. If the weighted average is positive, the chart's background is green, otherwise it is red. Finally, a horizontal line is drawn at point 0 to facilitate visual analysis of the chart.
------------ ITALIANO -------------
Questo indicatore è chiamato "TRIX with Momentum" ed è utilizzato per analizzare il momentum del prezzo di un asset e prevedere eventuali inversioni di trend. La logica di funzionamento è basata sulla combinazione di due indicatori: il TRIX (Indicatori di media mobile Tripla Esponenziale) e l'oscillatore momentum.
L'indicatore consente all'utente di impostare la lunghezza del TRIX e dell'oscillatore momentum come input personalizzato. Il TRIX viene calcolato utilizzando tre medie mobili esponenziali (EMA) della chiusura dei prezzi dell'asset, mentre l'oscillatore momentum viene calcolato utilizzando l'EMA del TRIX normalizzato.
Il TRIX normalizzato viene centrato intorno allo 0 per facilitare l'analisi della sua relazione con l'oscillatore momentum. L'indicatore plotta il TRIX normalizzato e l'oscillatore momentum su un grafico, utilizzando diversi colori per indicare se il TRIX è sopra o sotto lo 0.
L'indicatore utilizza una media pesata tra il TRIX normalizzato e l'oscillatore momentum per creare uno sfondo colorato del grafico, che cambia in base alla media pesata. L'utente può impostare il peso da dare al TRIX e all'oscillatore momentum come input personalizzato, e il peso dell'oscillatore momentum verrà automaticamente impostato come complementare al peso del TRIX.
Se la media pesata è positiva, lo sfondo del grafico è verde, altrimenti è rosso. Viene tracciata anche una linea orizzontale al punto 0 per facilitare l'analisi visiva del grafico.
Infine, il colore dell'etichetta dell'asse y cambia in base alla posizione dell'oscillatore, mentre il colore dell'etichetta dell'asse x rimane sempre grigio.
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