Indicator
MR Probability based on IA MRMR Probability Companion
Setup guide, backtest reference, and practical workflow notes for the custom PulseWire companion indicator.
Version 3 — Updated with Backtest Engine, Probability Engine, and full input reference.
Purpose: This tool adds a historical probability and backtest layer to the existing IA-Mean-Reversion indicator so you can evaluate signal quality and layer into trades more intelligently.
Best use case: Swing and intraday execution where you want more confidence than a simple buy/sell dot alone can provide.
Contents
1. What this indicator does
2. Setup instructions
3. How probability is calculated
4. Backtest engine — what it measures and how to read it
5. Inputs and what each one does
6. Visual elements and functions
7. Suggested workflow
8. Mobile layout suggestions
9. Important notes and best practices
10. Quick reference
1. What This Indicator Does
The MR Probability Companion is a supporting indicator built to work alongside the paid IA-Mean-Reversion script. It does not generate the original mean reversion logic itself.
Instead, it reads the oscillator plot from that script and converts it into an execution aid with two core engines:
• Probability Engine — calculates how often the oscillator has historically reverted from each threshold level.
• Backtest Engine — tracks every historical signal per tier and reports wins, losses, win rate, and average bars to revert.
In practice: this gives you a way to compare weak, moderate, strong, and extreme signals instead of treating every dot the same — and now shows you the actual historical track record per level.
2. Setup Instructions
1. Add IA-Mean-Reversion to your chart.
2. Add the MR Probability Companion script to the same chart.
3. Open the settings for the probability script.
4. Find the input labeled Link to IA-Mean-Reversion : Plot.
5. Select the Plot output from the IA-Mean-Reversion indicator in the dropdown.
6. Do not select shapes, buy alert output, sell alert output, or signal markers.
7. After linking correctly, confirm that the oscillator line, labels, tables, or badge begin updating.
Most common mistake: If the script looks blank or probabilities stay empty, the source is almost always linked to the wrong output. The correct source is the IA mean reversion Plot value — not Shapes, not Alerts.
3. How Probability Is Calculated
The Probability Engine studies historical oscillator values over your selected lookback window.
1. It checks when the oscillator reached or crossed a threshold level such as 0.5, 1.0,
1.5, or 2.0.
2. It counts those events as hits.
3. For each hit, it looks forward a set number of bars using the Reversion Time (Bars) setting.
4. If the oscillator returns sufficiently back toward the mean (below 50% of the threshold) within that window, it counts as a successful reversion.
5. The final percentage is the ratio of successful reversions to total hits.
Interpretation: A probability of 78% at Level 3 means that in the sampled history, moves reaching that stretch level reverted within the chosen bar window about 78% of the time.
This is a historical tendency, not a guaranteed forecast.
4. Backtest Engine
The Backtest Engine is a separate, more detailed study that runs alongside the Probability Engine. While the Probability Engine gives you a single percentage, the Backtest Engine gives you the full breakdown per level.
What It Measures
• Every time the oscillator crosses a threshold level (L1, L2, L3, L4), it is counted as a signal.
• The script then checks whether the oscillator reverted back below 50% of that threshold within the Reversion Time (Bars) window.
• If it did, the signal is counted as a win. If not, it is a loss.
• For winning trades, the number of bars it took to revert is tracked and averaged.
Backtest Table Columns
Column Meaning
BACKTEST The level name and threshold value (e.g. L1 · 0.5, L2 · 1.0).
SIGNALS Total number of historical threshold crossings found in the lookback window.
WINS How many of those signals successfully reverted within the bar window.
Shown in green.
LOSSES How many signals failed to revert. Shown in red/pink.
WIN RATE Percentage of wins out of total signals. Color coded: green ≥75%, yellow ≥55%, red below 55%.
AVG BARS Average number of bars it took for winning trades to revert. Helps estimate how long to hold.
How to Use the Backtest Results
• If L3 shows a 78% win rate with an average of 6 bars, that tells you L3 signals on this symbol and timeframe have historically been reliable and relatively fast.
• If L1 shows a 52% win rate, it may not be worth acting on L1 signals alone — wait for L2 or higher.
• Compare win rates across levels to understand which tier gives you the best edge on the current instrument.
• Use AVG BARS to set realistic expectations for how long a trade may take to play out.
Key insight: The backtest table lets you stop guessing which level is "good enough" and instead use actual historical data to decide where to start layering.
5. Inputs and What Each One Does
Input What it does Why it matters
Link to IA-MeanReversion :
Plot Reads the oscillator value from the original indicator. Most important setting. Without it, the script cannot function.
Level 1 Threshold Defines the earliest stretch zone. Useful for spotting early entries or first layers.
Level 2 Threshold Defines the moderate stretch zone. Often more meaningful than Level 1 for execution.
Level 3 Threshold Defines the strong stretch zone. Often where higher-conviction opportunities start to appear.
Level 4 Threshold Defines the extreme stretch zone. Useful for exhaustion-style mean reversion setups.
Historical Window
(Bars) Controls how far back the script studies past behavior. Larger windows provide more examples but may reflect older conditions. Default: 200.
Reversion Time
(Bars) Controls how many bars are allowed for a reversion to count as a win. Smaller values are stricter; larger values are more forgiving. Default:
10.
Show % on
Signals Places labels on qualifying signal points. Shows direction, probability, and level directly on the oscillator.
Show Oscillator
Line Displays the live linked mean reversion value as a line. Helps monitor current extension in real time.
Show Full Table Toggles the main analytics table on or off. Useful on desktop when you want deeper stats visible.
Show Backtest
Results Table Toggles the backtest table on or off. Shows wins, losses, win rate, and avg bars per level.
Show Mini Badge
(Mobile) Toggles the compact badge on or off. Best choice for mobile charting or minimal clutter.
Compact Table
Mode Shrinks the table by shortening labels. Helps preserve chart space while keeping core info visible.
Table Position Moves the full analytics table to a different chart area. Lets you avoid covering candles or important indicator zones.
Backtest Table
Position Moves the backtest table independently. Lets you place both tables without overlap.
Table Text Size Changes the table text size. Useful when switching between desktop and mobile screens.
Mini Badge
Position Moves the compact badge independently. Lets you place the badge in the least intrusive area.
6. Visual Elements and Functions
Oscillator Line
This line mirrors the linked IA mean reversion value. Color changes based on direction: red when above L1 (sell-side stretch), green when below negative L1 (buy-side stretch), orange when neutral.
Threshold Lines
Horizontal levels mark the defined stretch zones. L4 lines are drawn with a heavier weight to highlight extreme territory. Positive readings represent sell-side stretch; negative readings represent buy-side stretch.
Signal Labels
When a fresh threshold event occurs, labels appear like BUY 64% L2 or SELL 81% L3.
These summarize direction, historical reversion probability, and the tier level in one glance.
• Buy labels: green tones — brighter green for higher probability.
• Sell labels: red/pink tones — deeper red for higher probability.
Full Analytics Table
Shows the current state of each level including zone name, threshold value, historical hit count, reversion percentage, and active status indicator.
Backtest Results Table
Shows the full historical track record per level: total signals, wins, losses, win rate (color coded), and average bars to revert on winning trades.
Mini Badge
Compact mobile-friendly summary showing active direction, current tier, and probability estimate. Ideal when the full tables take too much chart space.
Alerts
Four built-in alert conditions:
• High probability SELL at L3+ (win rate threshold configurable)
• High probability BUY at L3+
• Extreme SELL at L4
• Extreme BUY at L4
7. Suggested Workflow
If you trade with a top-down process, the indicator fits naturally into that workflow.
1. Use 1D and 4H charts to identify higher-timeframe reversion bias.
2. Watch whether the oscillator is reaching L2, L3, or L4 territory.
3. Check the Backtest Table to see which level has the strongest historical win rate on this symbol and timeframe.
4. Use the Probability label on the signal dot to confirm the current setup quality.
5. Drop to lower timeframes for execution when higher-timeframe context and current level align.
6. Use AVG BARS from the backtest table to set realistic trade duration expectations.
7. Consider smaller initial size at L1 and L2, then add on stronger or more statistically favorable levels.
Key advantage: You no longer need to wait only for the most extreme level every time. If mid-level signals show strong historical win rates, they become actionable layering opportunities too — and now you have the data to back that decision.
8. Mobile Layout Suggestions
• Set Show Full Table = Off for the cleanest chart.
• Set Show Mini Badge = On for a small at-a-glance summary.
• Set Show Backtest Results Table = Off on mobile; review it on desktop when planning trades.
• Use Compact Table Mode if you still want the larger table but need it reduced.
• Move tables and badge using the position settings so they do not block price action.
• Use a smaller text size when charting on a phone.
9. Important Notes and Best Practices
• All percentages and win rates are historical tendencies, not prediction guarantees.
• If the Signals count in the backtest table is very low (under 10), the win rate is less trustworthy due to small sample size.
• Thresholds may need to be adjusted depending on the symbol, timeframe, and volatility regime.
• The script is most useful as a decision-support tool, not a standalone trading system.
• Always combine the probability score and backtest results with market structure, trend context, key levels, and your own risk rules.
• If you change the Historical Window or Reversion Time inputs, the backtest results will update to reflect the new parameters.
• Pine Script has loop limits — if you encounter a "loop too long" error, reduce the Historical Window (Bars) input.
10. Quick Reference
If you want to... Use this
See detailed stats on every level Turn on the full analytics table
See historical win rate per level Turn on the backtest results table
Know how long winning trades typically last Check AVG BARS in the backtest table
Keep the chart clean on mobile Use the mini badge and turn off both tables
Make the display smaller Enable compact mode and reduce table text size
Know if the signal is early or extreme Watch the current tier and threshold lines
React only to stronger setups Use alerts for high-probability L3 and L4 events
Decide which level to start layering at Compare win rates across L1–L4 in the backtest table
Fix blank display or 0% probabilities Re-link the source input to IA-Mean-Reversion
: Plot
This document is a concise operating guide for the MR Probability Companion indicator. Version 3 — includes Backtest Engine, updated input reference, and workflow notes.
Indicator
RSI Sequential Exhaustion & Divergence**RSI Sequential Exhaustion & Divergence — Multi-Factor Oscillator**
**What it is**
A single RSI-based reversal oscillator for spotting momentum exhaustion, then filtering and grading those signals so only the better-supported ones stand out. It is one integrated tool, not a pile of separate indicators sharing a pane.
**What it plots**
- The RSI line with a glow/gradient style coloured by momentum side, plus overbought/oversold/midline levels and an optional zone fill.
- Sequential Exhaustion signal arrows (▲/▼) at qualifying turns.
- Regular and hidden price–RSI divergence as lines and small labels, de-cluttered so the pane stays readable.
- A compact 5-row dashboard: Signal (direction · conviction % · age), RSI state, Confluence score, Context (trend/range + volatility state), and a Data-health read.
- An optional calibration panel and a set of hidden data-window outputs (EXP_*) for chaining into other scripts.
**Why these components are combined (and how they work together)**
Each part is here to fix a specific weakness of the part before it, so the result is one filtered, graded signal:
1. A bare RSI overbought/oversold reading whipsaws, and naive divergence over-fires. So the script uses two *structured* exhaustion cues instead: **Sequential Exhaustion** (the RSI makes three consecutive deeper pushes into an extreme zone and the fourth bar turns back out — a defined trigger, not just "RSI is low"), and a **divergence engine** that adds an independent reversal cue and is de-cluttered with a cooldown plus a minimum-gap filter.
2. Both cues are counter-trend by nature, and counter-trend entries fail in two situations: strong directional trends, and volatility cascades. To handle the first, an **HTF trend-bias filter** and an **ADX regime filter** suppress signals when a higher timeframe or strong ADX says the trend is intact. To handle the second, a **volatility-cluster filter** (a self-exciting intensity built from returns) proportionally raises the bar for new signals exactly when clustering makes mean-reversion most dangerous — and because it is price-only, it also works on volume-less symbols.
3. To tell which surviving signals are worth more, a **Confluence grade (0–5)** fuses five reasonably-independent reads of the same bar (HTF bias, ranging regime, a recent divergence, volume, and the RSI momentum turn). **Multi-timeframe agreement (3×/5×/15×)** is deliberately kept *separate* and applied as a conviction *multiplier* rather than blended into the score, because it is the one genuinely independent check — full agreement boosts conviction, contradiction damps it.
4. To stay honest about whether any of this is working on your symbol, a **calibration tracker** logs every signal and, after a fixed horizon, records whether price actually followed through (a move of at least X·ATR in the signal's direction), reporting a measured *past* hit-rate by grade tier with a Wilson 95% confidence interval. A **data-integrity read** (bar range, HTF-feed freshness, volume reliability) surfaces an OK / DEGRADED / CRITICAL status so the tool never silently scores on bad data.
**What is original here**
The individual techniques — RSI, divergence, ADX, ATR, volume reads, self-exciting intensity, Wilson intervals — are publicly documented. The original work is the integration: a structured RSI-exhaustion trigger gated by a proportional volatility-cluster filter, graded by a confluence score that is scaled by independent higher-timeframe agreement, and continuously audited by a built-in self-calibration tracker that reports honest past follow-through by tier. Components were chosen so each covers a distinct weakness; redundant filters were left out to keep one clear signal.
**How to use**
1. Add it to a chart. Defaults suit intraday index/futures; direction works on any symbol, while the volume confluence factor needs real traded volume.
2. Take signals in the direction the context filters allow. Prefer a higher conviction % and stronger higher-timeframe agreement; treat low-grade cues as noise (raise "Min confluence to allow signal" to suppress them).
3. Respect the volatility-cluster warning — it marks regimes where mean-reversion is most likely to fail.
4. Use the optional calibration panel as a sanity check on the tool's own past signals, never as a forward prediction.
5. Spot vs futures: a cash/spot index has no real volume. "Volume Mode" auto-detects this, and you can borrow a traded-volume series from a related futures contract; the "Data" row shows the active mode.
**Notes**
All signals and divergence confirm on closed pivots and do not repaint. Divergence labels appear "Pivot Right" bars after the turn, which is inherent to honest pivot detection.
**Disclaimer**
For education and information only. This is not financial, investment, or trading advice and guarantees no outcome. Signals describe current and past conditions; they do not predict the future. The calibration figures describe past behaviour only — they are not a backtest or a probability of future results. Volume-based readings depend on the data feed and are unreliable on instruments without real volume. Trading carries substantial risk of loss; you are solely responsible for your own decisions and risk management. Consider consulting a licensed professional.
Indicator
SAR/ATR Trend-Extension OscillatorSAR/ATR Trend-Extension Oscillator
WHAT THIS INDICATOR IS
The SAR/ATR Trend-Extension Oscillator measures, in a single line, how far price has stretched away from its Parabolic SAR trailing reference, and it expresses that distance in units of volatility rather than raw price. The output is a signed oscillator: it rises into positive (green) territory as an uptrend extends and falls into negative (red) territory as a downtrend extends. The further the value sits from the zero line, the more stretched the current move is relative to its own recent volatility.
It is built as ONE coherent reading. Parabolic SAR and Average True Range (ATR) are not plotted side by side; they are fused mathematically into the oscillator value. Three further elements - a rolling statistical standardization, an ADX regime filter and a higher-timeframe trend filter - qualify and contextualize that value rather than adding separate indicators to the pane.
WHY THESE COMPONENTS ARE COMBINED (and how they work together)
Each ingredient is included to solve a specific weakness of the one before it.
1) Parabolic SAR provides trend direction and a trailing stop level, but on its own it only tells you which side of the trend you are on. The raw gap between price and SAR is measured in price points, which cannot be compared between a low-priced stock and a high-valued index, or between a quiet and a volatile session. So SAR alone cannot answer "how stretched is this move."
2) ATR answers that. By dividing the SAR-to-price gap by ATR, the distance becomes volatility-relative: "price is X average true ranges beyond its SAR." This SAR-divided-by-ATR step is the core of the indicator and produces information that neither Parabolic SAR nor ATR shows alone - a bounded, cross-market measure of trend extension that reads consistently across symbols and timeframes.
3) Rolling standardization (Z-Score, or robust median/MAD) fixes a subtler problem: even an ATR-normalized value has a distribution that drifts over time, so one fixed threshold means different things in different conditions. Standardizing the value over a lookback window rescales it so the +/-2 and +/-3 reference levels keep a stable statistical meaning. A "Raw" mode (the plain volatility-normalized value, no rescaling) is also available.
4) ADX regime filter. Parabolic SAR is prone to repeated false flips in sideways markets. ADX measures trend strength, so the indicator suppresses buy/sell flags whenever ADX is below a user threshold (a ranging market) and shades the background to show it. ADX is never drawn on the oscillator; it only gates the signals.
5) Higher-timeframe filter. The same SAR direction is read from a higher, confirmed timeframe and used to filter out crossings that fight the dominant trend. It is the identical calculation applied to a larger context, not a different indicator.
6) Divergence. Because the oscillator is a measure of trend extension, a price high paired with a lower oscillator high (or a price low paired with a higher oscillator low) indicates the trend is extending less forcefully. Regular and hidden divergences are detected from confirmed pivots and drawn with connecting lines and labels.
Putting it together, the plotted value is one number: sign(SAR trend) x (SAR-to-price gap / ATR), optionally standardized and clamped to limit single-bar spikes.
A buy or sell flag is raised only when that oscillator crosses the Signal level AND the ADX regime AND the higher-timeframe direction agree. Everything feeds one question: is price extending, in a genuine trend, in line with the larger trend?
WHAT MAKES IT ORIGINAL
This is not Parabolic SAR with an ATR drawn next to it. It transforms the SAR trailing stop into a continuous, signed, volatility-normalized and statistically standardized extension oscillator, then wraps that single value in regime and higher-timeframe gating plus divergence logic. The resulting "how stretched is this trend, on a comparable scale" reading does not exist in either source indicator.
HOW TO USE IT
- Choose a normalization mode: Raw, Z-Score, or Robust (median/MAD, least sensitive to spikes).
- Read color and distance: green = uptrend extension, red = downtrend extension; the further from zero, the more extended. The Signal, Warning and Extreme levels mark progressively stretched zones.
- Treat the triangle markers (a Signal-level cross that agrees with the ADX regime and the higher-timeframe bias) as points to investigate, not as automatic entries.
- Use divergences as early warning that extension is fading, and the on-pane dashboard for trend, regime, higher-timeframe bias and ATR-based stop/target context. The stop and target figures are reference levels only.
- All parameters - SAR step and maximum, ATR period and smoothing type, the standardization window, every threshold, the ADX threshold and the higher timeframe - are adjustable.
REPAINTING
Signals confirm on bar close by default and do not repaint. The higher-timeframe filter reads the previous closed higher-timeframe bar, so it does not look ahead. Divergence labels appear a few bars after the pivot they confirm; that lag is inherent to honest pivot detection and is expected behavior.
ATTRIBUTION
This implementation builds on the original concept of combining Parabolic SAR with ATR. The volatility normalization, statistical standardization, regime and higher-timeframe filtering, divergence detection and alerting described above are part of this independent implementation.
DISCLAIMER
This script is provided for research and educational purposes only. It is not financial advice and makes no guarantee of profitability or accuracy. Indicators describe past and present price behavior; they do not predict future prices, and no indicator works in all conditions. Trading involves substantial risk of loss. Always test on historical and out-of-sample data and make your own independent decisions. The author accepts no liability for any use of this script.
Indicator
Lumina Adaptive Momentum Oscillator [Pineify]Lumina Adaptive Momentum Oscillator
This oscillator measures price momentum through a double-smoothed triangular moving average, then overlays a Kaufman-style Adaptive Moving Average as a signal line that accelerates in trending conditions and slows in ranging ones. The result is a histogram that stays cleaner than a simple ROC or MACD while still catching real directional shifts — buy and sell signals fire only when momentum crosses the adaptive signal while on the "wrong" side of zero, filtering out crosses that occur mid-trend.
Key Features
Triangular MA momentum — double SMA smoothing cuts through noise that a single-period momentum calculation amplifies
Kaufman Adaptive Moving Average signal line — efficiency-ratio scaling means the signal line tracks fast when price has clear direction and lags conservatively during chop
Polarity-colored histogram — bars flip between bull and bear colors on the zero line, making directional bias readable at a glance
Counter-trend signal filter — buy signals require momentum to be below zero; sell signals require it above, so the oscillator only flags reversals, not trend continuation pulses
Configurable alerts for buy and sell conditions (uncomment the alertcondition lines to enable)
How It Works
Triangular momentum : A triangular moving average is the SMA of an SMA — ta.sma(ta.sma(close, length), length) . This double pass heavily weights the middle of the lookback window, producing a line that barely reacts to individual candle spikes. Momentum is then the change in this average over length bars, equivalent to asking: "how much has the ultra-smooth baseline shifted over the period?"
Adaptive signal line (AMA) : The signal applies a Kaufman Adaptive Moving Average to the momentum values. Each bar, an Efficiency Ratio is computed as the absolute cumulative price change divided by the sum of bar-by-bar absolute changes over the window. A high ER (price moving steadily in one direction) produces a fast smoothing constant; a low ER (lots of back-and-forth) produces a slow one. The smoothing constant is squared before application — squaring compresses near-zero values toward zero and pushes higher values closer to one, amplifying the contrast between ranging and trending states.
Signals : A buy condition fires when the momentum histogram crosses above the signal line from below zero. A sell condition fires when momentum crosses below the signal line from above zero. Both plotshape and alertcondition calls are included but commented out by default, so the chart stays clean unless signals are explicitly enabled.
How the Components Work Together
The triangular MA reduces the raw momentum noise that trips up standard crossover strategies. A plain ta.change(close, length) signal line would fire constantly in sideways markets because individual candle closes swing around. By first anchoring momentum to a doubly-smoothed baseline, the histogram only moves when an actual directional shift is underway in price.
The AMA signal line then adapts to how directional that momentum itself is. When momentum is trending (e.g., steadily falling through a corrective move), the AMA tracks it closely, keeping the histogram-to-signal gap narrow and the crossover conditions quiet. When momentum flips abruptly — the scenario a reversal trader wants — the ER spikes, the smoothing constant rises, and the signal line catches up quickly enough to generate a timely cross.
The zero-side filter adds the final constraint: only counter-trend crosses matter. A bullish cross above zero would typically mean momentum is already positive and the trend is continuing, not reversing — those are excluded. This makes the signals less frequent but more aligned with actual turning points.
Trading Ideas and Insights
Use on the daily or 4H chart during confirmed trending markets. Wait for pullbacks that drive momentum negative, then watch for a histogram-crosses-signal event below zero as an early re-entry cue. Confirmation from price action (e.g., a higher low or a break of the short-term descending channel) reduces false positives.
On intraday charts, the double smoothing introduces noticeable lag — roughly 2× the period in bars. For a 14-bar setting this means signals may appear 3-5 candles after the actual reversal candle. Consider reducing length to 7-9 on lower timeframes to recover responsiveness.
The signal line (currently commented out) can be uncommented as an additional visual layer. When the histogram bars are shrinking toward zero while the signal line is still diverging, it often indicates momentum exhaustion before the actual cross occurs, giving a heads-up for limit orders.
Unique Aspects
Most MACD-style oscillators apply EMA smoothing to raw price; this one applies double-SMA smoothing before differencing, which produces a different noise profile — more immune to single-bar wicks but slower to react to sharp moves
Applying the Kaufman AMA to momentum values (rather than price) is less common. The efficiency ratio reflects momentum's own trendiness, not price's, so the adaptive behavior is tuned to the oscillator's dynamic rather than borrowed from a price-following MA
The zero-side signal filter is built in rather than left to the trader to configure — the indicator makes an explicit methodological choice that these signals represent reversals only
How to Use
Add the indicator to any chart. The default length of 14 suits daily and 4H charts; adjust lower for faster timeframes.
Watch the histogram color: sustained green bars above zero indicate positive momentum; sustained red bars below zero indicate negative momentum.
For signals: uncomment the two plotshape lines in the source to display BUY/SELL labels, or uncomment the alertcondition lines and create alerts via PulseWire's alert panel.
A BUY label appears when the histogram crosses above the signal line while below zero — a potential momentum reversal from bearish territory.
A SELL label appears when the histogram crosses below the signal line while above zero — a potential momentum reversal from bullish territory.
Combine with a higher-timeframe trend filter (e.g., price above/below a 200 EMA) to take only signals aligned with the prevailing trend.
Customization
Data Length (default: 14) — Controls the period for both the triangular MA and the adaptive signal line. Higher values produce smoother output with more lag; lower values react faster but generate more noise. Typical range: 7–21.
Bullish Color (default: green) — Color of histogram bars when momentum is positive.
Bearish Color (default: red) — Color of histogram bars when momentum is negative.
Conclusion
The Lumina Adaptive Momentum Oscillator combines triangular-MA momentum with a Kaufman-adaptive signal line to surface genuine reversal pressure rather than routine oscillations. The built-in zero-side signal filter keeps the indicator focused on counter-trend setups, making it most useful as a timing tool within a larger trend-following framework. Past patterns do not guarantee future results — use alongside price structure and volume confirmation.
Indicator
PI Radius Energy (PRE)# PI Radius Energy (PRE)
PI Radius Energy (PRE) is a momentum and volatility fusion engine designed to transform traditional ATR data into a dynamic circular energy model.
Instead of treating ATR as a simple volatility measurement, PRE interprets ATR as a radius and converts it into an energy field using the mathematical relationship of a circle:
π × r²
This approach allows market volatility to be expressed as an expanding or contracting energy field rather than a linear value. The resulting energy is then combined with OBV momentum flow, creating a unique representation of market participation, pressure, and directional strength.
The core objective of PRE is not to chase trends after they have already developed, but to identify the moments when energy begins to build beneath the surface. By combining circular volatility expansion, volume flow acceleration, squeeze detection, and momentum confirmation, PRE attempts to highlight areas where market energy is transitioning from compression to expansion.
### Main Components
• PI Radius Engine (πr² volatility model)
• OBV Momentum Flow Integration
• Dynamic Energy Normalization
• Squeeze Compression Detection
• Energy Trend EMA Filter
• ATR Rank & Volume Rank Validation
• Momentum Z-Score Filtering
• 3D Aura Visualization
• Early Bottom Detection Pills
• Bullish Confirmation Signals
### How to Read PRE
**Green Aura**
* Energy is above its average.
* Market pressure is expanding.
* Bullish conditions are strengthening.
**Red Aura**
* Energy is below its average.
* Market pressure is weakening.
* Bearish conditions are dominant.
**Green Pills**
* Early signs of energy expansion.
* Potential transition from compression to movement.
* Designed to appear before major momentum phases whenever possible.
**Yellow Confirmation Pills**
* Additional confirmation that energy has crossed into a stronger bullish state.
**Purple Energy Trend Line**
* Long-term energy trend.
* Helps distinguish temporary spikes from sustained energy expansion.
### Philosophy Behind PRE
Most indicators measure price.
Some indicators measure volume.
PRE attempts to measure something different:
**Market Energy.**
By transforming volatility into a circular energy field and combining it with volume-driven momentum, PRE seeks to provide a different perspective on trend development, accumulation, expansion phases, and emerging directional pressure.
PRE is not intended to predict the future. Instead, it is designed to visualize how market energy evolves, contracts, and expands over time, helping traders identify potential opportunities before they become obvious to the broader market.
Indicator
Indicator
Modern Adaptive MACD [GBB]The MACD is half a century old. Gerald Appel published it in 1979 for daily charts of US equities, and the 12/26/9 default has been copied from one trading textbook to the next ever since. Nobody asks anymore why those three numbers should be the right ones for Bitcoin five-minute charts in 2026.
This is a rebuild. Four modernizations, each independently toggleable, all measured before being added. With every layer at default, the output is the textbook MACD. Switch them on one at a time to see what each one does on your own chart.
Layer 1: Adaptive periods
Instead of hard-coding 12 and 26, the indicator measures the market's dominant cycle in real time with an Ehlers homodyne discriminator and tunes the periods to it. In slow trends the periods widen and the indicator stops chopping you up with false crosses. When volatility picks up, periods tighten and it stays responsive.
Layer 2: Signal speedup
Classic MACD has two layers of lag. One in the EMAs that build the MACD line, another in the signal line on top of that. Most of the lag people complain about lives in the second smoother.
The first version of this layer used a zero-lag EMA. It didn't work. The zero-lag transform overshoots, and on strong moves the signal ends up ahead of the MACD, inverting the histogram color exactly when you most need the cross to be honest.
What shipped is the boring fix: a multiplier on the signal length. 1.0 keeps the classic 9-bar signal. Lower values speed it up. I measured the trade across 24 months of Bitcoin perpetual data. At a multiplier of 0.5, the indicator confirms a swing roughly 4 bars earlier and catches about 25% more swings than the classic. The cost is that the false-signal rate, whipsaw crosses with no real swing attached, roughly doubles, from 6% to 12.5% of all crosses. Whether that trade is worth it depends on what you do with the indicator. Pick the multiplier accordingly.
Layer 3: Normalization
A raw MACD reading of 15 means nothing on its own. On gold at $4500 it's small. On a penny stock it's enormous. Two normalization modes are available. "Percent of price" expresses the MACD as a percent of current price, which makes the reading comparable across instruments. "Z-Score" expresses it as standard deviations from its own recent average. Both are off by default. Turn one on if you trade more than one market, or if you want thresholds that don't need re-tuning every time you switch symbols.
Layer 4: Divergences
Regular and hidden divergences are detected automatically on confirmed pivots. Confirmed means they do not repaint. The line shows up a few bars after the pivot it marks, which is the honest cost of non-repainting confirmation. If anyone shows you a divergence indicator that draws lines in real time at the exact low, check what happens to those lines after the next few candles close.
Small triangles mark every MACD/Signal cross at the crossing point. Teal for bullish, red for bearish. Useful on busy charts where the cross moment is otherwise ambiguous.
What this is, and what it isn't
I tested every configuration of this indicator as a standalone trading system on 24 months of Bitcoin one-hour data. Always in market, long on bullish cross, flip on bearish. Every configuration lost money. Profit factor below 1 across the board. Negative Sharpe. Nothing statistically significant, before or after multiple-comparison correction.
This is what happens to any oscillator cross strategy run without a filter. The classic MACD shows the same result on the same test.
This is not a system. It's a timing tool. It tells you when momentum is shifting, earlier and more cleanly than the classic. Your job is to combine that with whatever else you trade on: higher-timeframe trend, market structure, key levels, your own setup logic. Without that filter, the cross alone is noise.
Settings
Source: close by default.
Classic periods: 12/26/9. Used when Adaptive is off.
Layer 1 (Adaptive): on by default. Min and max cycle bounds and the fast/signal ratios are exposed if you want to tune them.
Layer 2 (Signal speedup): multiplier 0.3 to 1.0. Default 1.0. Try 0.5 first.
Layer 3 (Normalize): None / Percent of price / Z-Score. Off by default. Z-Score has its own lookback length.
Layer 4 (Divergences): on by default, regular divergences only. Hidden divergences are off by default to keep the chart clean. Pivot left/right bars control how strict the swing detection is.
Display: cross markers on by default.
Alerts are wired for every cross (MACD/signal and zero-line) and every divergence type (regular and hidden, bullish and bearish).
Free. No paywall, no subscription, no gated features. If you find a configuration that works well on a specific instrument or timeframe, drop a comment.
Open-source script
In true PulseWire spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
GoodBadBitcoin
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Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by Indicator
Gold Toolkit 22 [MatsukazeAlgo]🇬🇧 ENGLISH
A modular indicator that consolidates 22 Gold-specialized analysis tools into a single script. Each module can be toggled independently — enable one or two at a time for focused analysis. The shared infrastructure provides session awareness, Dollar Index correlation, and psychological price level detection across every module. Designed exclusively for XAUUSD on intraday timeframes.
Concepts
Modular Architecture -- Most indicators serve a single purpose: one trend filter, one oscillator, one pattern detector. For Gold traders who use multiple tools, this means loading 5–10 separate indicators, each consuming chart resources and requiring independent configuration. A modular architecture solves this by housing all tools within a single script, sharing a common infrastructure layer. Each module runs its own logic but inherits the same session detection, DXY feed, and psychological level engine. The result is consistent behavior across all tools without duplicate calculations.
Session-Dependent Behavior -- Gold does not trade the same way at all hours. The Asia session (19:00–03:00 ET) is characterized by tight ranges and stop runs that reverse at the London open. The London session (03:00–09:00 ET) produces directional breakouts driven by European institutional flow. The New York session (09:00–17:00 ET) carries the highest volume and tends to either continue the London move or reverse it sharply. An indicator that applies the same parameters across all three sessions is ignoring 60% of the context. Every module in this toolkit reads the current session and adjusts its signal thresholds accordingly. Asia signals require stronger confirmation. London signals favor trend continuation. NY signals weight volume more heavily.
Inverse Dollar Correlation -- Gold is priced in US Dollars. When the Dollar strengthens, Gold tends to fall. When the Dollar weakens, Gold tends to rise. This inverse relationship is not perfect on every bar, but over any meaningful sample it dominates. The toolkit reads TVC:DXY (US Dollar Index) daily data on every bar. Bull signals across all modules require a weak Dollar context (DXY close below open). Bear signals require a strong Dollar context. This single filter eliminates a substantial number of false signals that would otherwise fire against the macro trend.
Psychological Price Levels -- Gold reacts consistently at $50 and $100 round numbers. Institutional orders cluster at $4,500, $4,550, $4,600, and similar levels. When price approaches these levels, the toolkit tightens sensitivity and marks signals with a ★ indicator. A Stop Run Reversal scoring 85/100 at $4,550 is qualitatively different from the same score at $4,537 — the psychological level adds an independent layer of institutional confluence.
Modules
The 22 modules are organized into five categories. Each module is a complete analysis tool.
Trend Modules
01 ML Supertrend — A Supertrend variant with a session-learning engine. Tracks flip outcomes per session and adjusts the band multiplier over time. Sessions with low win rates get wider bands (fewer signals). Sessions with high win rates get tighter bands (more signals). Volume surge filter and RSI confirmation prevent signals in thin markets. The dashboard shows per-session win rates, current adapted multiplier, and learning state.
04 Parabolic SAR — Standard SAR calculation with two additions: age-based transparency fading and momentum scoring. Fresh SAR dots are fully opaque. As the trend ages, dots fade toward transparency, giving a visual read on trend maturity without cluttering the chart. The momentum score measures the distance between price and SAR relative to ATR. A high score means price is accelerating away from the SAR. A collapsing score warns of an impending flip. Multi-timeframe alignment check confirms whether the higher timeframe SAR agrees.
05 ACN Trend — An adaptive coral noise filter that outputs a smoothed trend line with risk zones above and below. The noise score quantifies how choppy the current market is. When noise exceeds the threshold, the background shades as a warning to avoid trading. The conviction meter is the inverse of noise — a high conviction reading means clean trend conditions. Bull/Bear signal counts per session track which sessions produce the most reliable signals for your timeframe.
09 Anchored Channels — A dual-layer channel system. Macro channels connect confirmed swing pivots and project forward with band widths derived from maximum deviation. Micro channels fit a short-term linear regression to the most recent bars. When price breaks the macro channel, it is classified as BRK (breakout). When price returns to the channel boundary, it is PB (pullback). When the micro channel aligns with the macro direction, it is CONT (continuation). The MTF screener checks two higher timeframes for directional agreement. A status badge labels the overall trend bias.
18 Asymmetric Trend — Uses different thresholds for entering and exiting a trend. The entry threshold is tight — price must move strongly to flip the trend. The exit threshold is wide — the trend persists through normal retracements. This asymmetry reduces whipsaws in ranging markets while catching genuine trend changes quickly. Gradient fill between the trend line and price shows acceleration visually. Reversal diamond markers appear at flip points with session tags and trend age.
Reversal Modules
02 Stop Run Reversal — Detects when price pierces a range boundary (liquidity grab) and reverses. Each event is scored 0–100 based on wick ratio, penetration depth, volume spike, DXY alignment, and session context. Zone boxes mark the reversal area with reference, invalidation, and target lines. A pending state tracker monitors setups that have not yet confirmed, preventing premature signals. Session and DXY tags on each label provide immediate context.
06 Arc Momentum — A non-linear RSI oscillator. Instead of plotting RSI as a flat line, the oscillator curves toward price in an arc. When the arc flips direction, a signal fires. Divergence detection compares RSI pivot extremes against price pivot extremes and flags when they disagree. The momentum zone classification (Overbought / Bull / Neutral / Bear / Oversold) shades the background for a quick visual read on the current state.
11 Harmonic Patterns — Scans for five harmonic patterns: Bat, Gartley, Butterfly, Crab, and Shark. Both bullish (XABCD with D at bottom) and bearish (XABCD with D at top) configurations are detected. Each pattern is scored based on session quality, DXY alignment, and proximity to psychological levels. Fibonacci projection levels are drawn at the PRZ (Potential Reversal Zone) showing 0.382, 0.618, 1.0, 1.272, and 1.618 targets. The tolerance parameter controls how strictly the Fibonacci ratios must match the textbook definitions.
16 RSI Swing Structure — Uses RSI overbought and oversold zones to define swing points. When RSI enters OB and price makes a high, that high is labeled. When RSI enters OS and price makes a low, that low is labeled. Each swing point is classified as HH (Higher High), HL (Higher Low), LH (Lower High), or LL (Lower Low). When the classification sequence breaks — for example, a HH followed by a LL — the indicator labels it as CHoCH (Change of Character). When the sequence continues — HH followed by another HH — it labels BOS (Break of Structure). Swing connecting lines visually link the pivots. RSI value appears on each label.
Structure Modules
03 EMA Inversion — Three EMAs (21, 55, 200) with ribbon fill. The indicator tracks Fair Value Gaps that form during trend moves. When an FVG is subsequently filled from the opposite direction (inverse FVG flip), a signal fires. Built-in SL/TP management uses the most recent swing high/low for stop placement and projects a 1:1 target. A cooldown timer prevents re-entry immediately after a stop-out. The trade state label shows whether the indicator considers the current position LONG, SHORT, or FLAT.
08 SwingRegress — Anchors linear regression channels to swing pivot confirmations. When a CHoCH occurs (price breaks the previous swing extreme), a new channel begins from the most recent opposite pivot. The channel slope and deviation are calculated from all bars within the segment. Band 1 and Band 2 at configurable standard deviations define the channel width. A linefill between the bands makes the channel body visible. Psychological price levels within the channel are drawn as dotted gold lines. A Bollinger/Keltner squeeze detector highlights when volatility compresses inside the channel — often a precursor to the next directional move.
10 S/R Zones — Builds support and resistance zones from volume-weighted pivot clustering. Nearby pivots are merged into zones. Each zone receives a strength score based on the number of touches, volume at touch, and recency. When price breaks through a zone, it is flagged. When price returns to a broken zone from the other side, it is flagged as a retest. Ghost zones keep broken levels visible with faded opacity. Star ratings provide a quick strength summary. An age-based decay ensures old, untested zones gradually disappear.
12 FVG Wave — Tracks Fair Value Gaps across the chart with session-colored rendering. Asia FVGs are rose, London FVGs are teal, NY FVGs are sky blue. Each FVG has a POC (midpoint) dotted line. When price touches the POC, a detection event fires. Age-based opacity fading dims old FVGs. Mitigation tracking removes FVGs that have been completely filled. Ghost mode optionally keeps mitigated FVGs visible in muted colors for reference.
17 OB Zone Study — Detects order blocks at displacement candles that follow swing pivots. Each OB is scored with a breakdown showing trend alignment, location quality, session, DXY confluence, and psychological level proximity. Mitigation tracking monitors whether price returns to the OB. Once mitigated, the OB is removed. Age-based opacity fading gradually dims unmitigated OBs that have been on the chart for a long time.
19 Vector SMC — Smart Money Concepts with a volume gate. FVGs and order blocks are only detected when the candle's volume exceeds the average by a configurable multiplier. This filters out structural patterns formed on low participation. OBs extend forward and are automatically invalidated when price closes through them. Sweep labels mark liquidity grabs at swing highs and lows where volume confirms institutional activity.
Session Modules
13 Session Range — Tracks the OHLC of Asia, London, and NY sessions in real time. A candle panel visualizes each session's range as a mini candlestick. 25% retracement lines for the London range identify the level where NY price action tends to react. H/M/L/O reference lines project key session levels forward. Regime classification analyzes the session structure pattern (e.g., London Partial Up, London Full Range). Asia sweep detection identifies whether the Asia high or low was taken during London. A stats table shows historical percentages for session behavior patterns.
15 Session Killzones — Draws boxes for Asia, London, NY AM, and NY PM killzone periods. When a killzone closes, its high and low are recorded as levels. These levels extend forward as dashed lines until price sweeps through them. Anticipation bars project the levels further for planning. When a sweep occurs, a detection label marks the bar. Session name labels identify each killzone box.
20 AlgoPath — Plots previous day high and low as horizontal lines. The equilibrium level (midpoint of PDH and PDL) is drawn as a dashed line. London session open and NY session open are drawn when each session begins. New day background shading marks the daily boundary. Whale candle detection flags abnormally large candles — those with body size exceeding a configurable ATR multiple — with session-colored labels showing the session name and exact time.
Volume and Correlation Modules
07 Minicharts — Displays Silver (XAG/USD), Dollar Index (DXY), and Gold Futures (GC1!) in a correlation panel. Each symbol shows EMA position (above/below). SMT (Smart Money Technique) divergence detection flags when Gold moves in the opposite direction to a correlated asset — a potential early warning of reversal.
14 Institutional Volume — Identifies accumulation and distribution phases using volume clustering analysis. When multiple high-volume candles with consistent directional bias appear within a lookback window, the indicator flags the zone. Climax volume detection identifies bars where volume × range reaches the highest level in the lookback period. Zone boxes mark the accumulation or distribution area on the chart.
21 Swing TPO — Builds Time Price Opportunity distributions anchored to swing points. The price range between swing pivots is divided into bins, and each TPO period assigns a letter to every visited bin. Gradient-colored boxes range from cool (low activity) to warm (high activity). The POC (Point of Control) line marks the highest-activity price. Psychological level detection flags when the POC lands near a $50/$100 round number.
22 VWAP — Dual-anchor Volume Weighted Average Price. The primary anchor resets on Session, Week, or Month boundaries. An optional second anchor provides a longer-term VWAP for confluence. Standard deviation bands at 1σ and 2σ show statistical extremes. Previous period VWAP, VAH (Value Area High), and VAL (Value Area Low) levels persist as reference lines with price labels. Band touch signals flag when price reaches the 2σ extreme. Slope direction indicates whether the VWAP is rising, falling, or flat.
How to Use
1. Open indicator settings. Under "Module Select," enable 1–2 modules.
2. Configure "Gold Settings" for session filtering, DXY, and psychological levels.
3. Apply to XAUUSD on your preferred intraday timeframe (5m–4h recommended).
4. Use the Style tab to show/hide individual signal shapes.
5. The module panel (top right) shows all 22 modules with the active one highlighted in gold.
Shared Infrastructure
Session Detection — Automatically identifies Asia (19:00–03:00 ET), London (03:00–09:00 ET), and New York (09:00–17:00 ET). Each module reads the current session for parameter adjustment and signal filtering.
DXY Feed — Pulls TVC:DXY daily open and close. Determines whether the Dollar is strengthening or weakening on the day. All modules use this for macro alignment.
ATR Normalization — All distance calculations (band widths, displacement thresholds, target projections) are normalized to the 14-period ATR. This ensures consistent behavior across timeframes and volatility regimes.
Psychological Level Engine — Configurable interval ($25, $50, or $100). Detects proximity to round numbers and flags signals near these levels with ★ markers. Multiple modules use this for confluence scoring.
Signal Bus — When any active module generates a Buy or Sell signal, it writes to a shared signal bus. The unified output shapes fire from this bus, providing a consistent visual regardless of which module produced the signal.
Module Panel — The top-right panel lists all 22 modules. The active module is highlighted in gold. Inactive modules are dimmed. Session, DXY, and daily range are displayed in the header and footer.
Input Reference
Module Select — 22 boolean toggles, one per module. Default: Module 01 ON, all others OFF.
Gold Settings — Session Filter (ON), Asia Signals (OFF), London Signals (ON), NY Signals (ON), Show DXY (ON), Psych $50/$100 (ON), Psych Interval (50), Show Panel (ON).
Each module has its own parameter group accessible when that module is enabled.
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🇯🇵 日本語
22のゴールド専用分析モジュールを1つのインジケーターに統合したモジュラー型ツール。各モジュールは設定パネルから個別にON/OFF可能 — 1〜2個ずつ有効にして使用。共通インフラがセッション認識、ドルインデックス相関、心理的価格帯検出を全モジュールに提供。XAUUSD日中足専用設計。
コンセプト
モジュラーアーキテクチャ -- 多くのインジケーターは単一目的。複数ツールを使うゴールドトレーダーは5〜10個のインジを個別にロードする必要がある。モジュラーアーキテクチャはすべてのツールを単一スクリプトに収容し、共通インフラ層を共有することで解決。各モジュールは独自ロジックを実行しつつ、同一のセッション検出、DXYフィード、心理的価格帯エンジンを継承。
セッション依存型動作 -- ゴールドは時間帯によって異なる動きをする。アジア（19:00–03:00 ET）はタイトレンジとストップラン。ロンドン（03:00–09:00 ET）は欧州機関投資家フローによる方向性ブレイクアウト。ニューヨーク（09:00–17:00 ET）は最大ボリュームでロンドンの継続か急反転。全セッションに同じパラメータを適用するインジケーターは文脈の60%を無視している。本ツールキットの全モジュールは現在のセッションを読み取り、シグナル閾値を調整。
ドル逆相関 -- ゴールドはUSドル建て。ドル高→ゴールド下落、ドル安→ゴールド上昇の逆相関が支配的。TVC:DXY日足データを毎バー読み取り、Bullシグナルはドル安文脈、Bearシグナルはドル高文脈を要求。このフィルターだけでマクロトレンドに逆行する偽シグナルの大部分を排除。
心理的価格帯 -- ゴールドは$50/$100刻みのラウンドナンバーで一貫して反応。機関投資家の注文が$4,500、$4,550、$4,600等に集中。価格がこれらのレベルに接近すると感度を引き締め、★マーカーでシグナルを強調。
モジュール一覧
トレンド系 — 01 ML Supertrend：セッション学習エンジン搭載、勝率追跡・自動調整。04 Parabolic SAR：経過時間フェード、モメンタムスコア、MTFアライメント。05 ACN Trend：適応型コーラルノイズフィルター、ノイズスコア、コンビクションメーター。09 Anchored Channels：マクロ+マイクロ二層チャネル、BRK/PB/CONT分類、MTFスクリーナー。18 Asymmetric Trend：非対称閾値フィルター、グラデーション塗り、リバーサルダイヤ。
リバーサル系 — 02 Stop Run Reversal：流動性奪取検出、0–100スコアリング、ゾーンボックス。06 Arc Momentum：非線形アーク型RSI、ダイバージェンス検出、ゾーン背景表示。11 Harmonic Patterns：5種パターン（Bull+Bear）、フィボナッチ投影。16 RSI Swing Structure：HH/HL/LH/LL分類、CHoCH/BOS検出。
ストラクチャー系 — 03 EMA Inversion：3本EMAリボン+FVG追跡+iFVGフリップ。08 SwingRegress：ピボット固定LRC、CHoCH/BOS、スクイーズ検出。10 S/R Zones：出来高加重クラスタリング、強度スコア、リテスト追跡。12 FVG Wave：セッション色分けFVG、POC、ミティゲーション追跡。17 OB Zone Study：OB検出+スコア内訳+経過フェード。19 Vector SMC：出来高ゲート付きSMC。
セッション系 — 13 Session Range：Asia/London/NY OHLC、キャンドルパネル、25%ライン、レジーム分類。15 Session Killzones：キルゾーンボックス+未スイープレベル追跡。20 AlgoPath：前日高安、イクイリブリアム、ホエールキャンドル。
ボリューム・相関系 — 07 Minicharts：Silver/DXY/GC相関パネル、SMT検出。14 Institutional Volume：蓄積/分配検出、クライマックス出来高。21 Swing TPO：グラデーションTPO分布、POC。22 VWAP：デュアルアンカー、σバンド、前期間レベル。
使い方
1. 設定の「Module Select」で1〜2個を有効化。
2. 「Gold Settings」でセッションフィルター、DXY、心理的価格帯を設定。
3. XAUUSD日中足（5分〜4時間推奨）に適用。
4. 右上のモジュールパネルで全22モジュールの状態を確認。有効モジュールはゴールドで表示。
共通インフラ — セッション検出（Asia/London/NY自動識別）、DXYフィード（$の強弱判定）、ATR正規化、心理的価格帯エンジン（$25/$50/$100）、シグナルバス（統一Buy/Sell出力）、モジュールパネル（全22モジュール一覧表示）。 Indicator
Indicator
Candle Pressure Flip Engine [trade_w_samet]🎯 Candle Pressure Flip Engine
Candle Pressure Flip Engine is a professional candle-pressure reversal and trade-visualization indicator designed to help traders study potential pressure-shift conditions directly on the price chart.
This script combines:
🔥 candle pressure analysis
⚡ exhaustion move detection
🕯️ rejection wick logic
📍 close-location pressure
📊 volume burst confirmation
🧭 RSI momentum flip confirmation
🧠 Auto Best optimizer logic
🎯 target / risk projection boxes
🏷️ BULLISH / BEARISH flip labels
🏁 WIN / LOSS result stamps
🩸 Crimson Spine + Echo + Fill visual system
🚨 professional alert messages
🎨 multiple visual themes
📦 historical target/risk visual tracking
The goal of Candle Pressure Flip Engine is not to predict the future or provide guaranteed buy/sell instructions.
Its purpose is to help users visually study:
⚡ exhaustion after aggressive moves
🕯️ candle rejection behavior
📍 where price closes inside the candle range
📊 whether volume expanded during the reaction
🧭 whether RSI momentum started turning
🎯 projected target and risk areas
🏁 visual target/risk outcomes
🩸 price-following pressure visuals
🚨 alert-based chart monitoring
Candle Pressure Flip Engine should be treated as a structured chart-analysis and educational decision-support tool.
It is not financial advice.
It is not an automated trading system.
It does not guarantee profitable results.
It does not place broker orders.
It does not remove the need for personal analysis, risk management, or trade validation.
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📌 OVERVIEW
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At a high level, Candle Pressure Flip Engine does the following:
🔥 Measures the size of the prior price move using ATR-based exhaustion logic.
🕯️ Checks whether the signal candle shows meaningful rejection wick pressure.
📍 Evaluates where the candle closes inside its own range.
📊 Optionally confirms the move with volume expansion.
🧭 Optionally confirms momentum change using RSI behavior.
🧠 Runs a background optimizer to compare internal setup combinations.
🎯 Draws a single target zone and risk zone after confirmed signals.
📦 Keeps historical target/risk boxes on the chart.
🏁 Tracks whether target or risk was reached first.
🏷️ Prints clean BULLISH FLIP ▲ and BEARISH FLIP ▼ labels.
🩸 Displays a premium Crimson Spine + Echo + Fill visual trail around price.
🚨 Provides professional human-readable and JSON-style dynamic alerts.
This makes the script more than a simple signal-label indicator.
It is designed as a complete candle-pressure review environment that combines candle behavior, exhaustion context, rejection, momentum, volume, visual planning, and alerts.
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🧠 CORE IDEA
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The core idea behind Candle Pressure Flip Engine is that a potential reversal should not be judged from a single isolated condition.
A candle can look strong, but without context it may not mean much.
For that reason, this script combines several layers:
🔥 exhaustion move context
🕯️ rejection wick behavior
📍 close-position pressure
📊 volume burst confirmation
🧭 RSI momentum turn
🧠 optimizer-based internal comparison
🎯 target/risk visualization
🩸 visual price-following pressure trail
The script does not attempt to catch every reversal.
It attempts to highlight moments where the internal candle-pressure model detects a possible shift after price has already moved aggressively in one direction.
The purpose is not to create more signals.
The purpose is to make potential pressure-flip conditions easier to identify, review, and compare on the chart.
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🧩 WHY THIS SCRIPT IS NOT A SIMPLE BUY/SELL INDICATOR
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Candle Pressure Flip Engine is not intended to behave like a basic “buy here / sell here” script.
It is built as a structured workflow:
Exhaustion Move
→ Candle Rejection
→ Close Pressure
→ Volume Burst
→ Momentum Flip
→ Score Requirement
→ Optional Auto Best Selection
→ BULLISH / BEARISH Flip Label
→ Target / Risk Projection
→ Result Tracking
→ Crimson Spine Visual Context
→ Alerts
Each part has a specific role.
🔥 The exhaustion engine checks whether price has moved enough before a flip is considered.
🕯️ The wick engine checks whether the candle rejected a level strongly enough.
📍 The close-pressure engine checks where the candle closed inside its range.
📊 The volume module checks whether the signal candle has volume expansion.
🧭 The momentum module checks whether RSI is turning in the expected direction.
🧠 The optimizer compares internal parameter combinations in the background.
🎯 The target/risk module draws visual planning zones.
🩸 The Crimson Spine module adds a premium price-following visual layer.
🚨 The alert module helps monitor signals and results without constantly watching the chart.
This makes the script a complete visual review framework, not a one-condition signal tool.
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⚙️ HOW THE SCRIPT WORKS
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🔥 EXHAUSTION MOVE ENGINE
The script first checks whether price has made a meaningful move over a selected lookback period.
This is done using:
• Exhaustion Lookback
• Minimum Exhaustion Move ATR
• Minimum Directional Bars
• ATR-based move measurement
A bullish flip can only appear after bearish exhaustion conditions are detected.
A bearish flip can only appear after bullish exhaustion conditions are detected.
This means the script is designed to look for possible pressure flips after directional movement, not random candles in the middle of neutral price action.
For bullish setups, the script looks for prior downside pressure.
For bearish setups, the script looks for prior upside pressure.
This creates the first layer of context.
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🕯️ REJECTION WICK ENGINE
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After exhaustion is detected, the script checks the signal candle itself.
For a bullish flip, the script evaluates the lower wick.
For a bearish flip, the script evaluates the upper wick.
The purpose is to identify whether price rejected one side of the candle range.
The main setting is:
Minimum Rejection Wick %
A larger rejection wick requirement makes the script more selective.
A smaller rejection wick requirement allows more potential signals.
The wick condition does not guarantee that price will reverse.
It only means that the candle showed rejection behavior according to the script’s internal model.
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📍 CLOSE-PRESSURE ENGINE
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The script also evaluates where the candle closes inside its own range.
This is important because a rejection wick alone is not always enough.
For bullish flips, the script prefers candles that close closer to the upper part of the candle range.
For bearish flips, the script prefers candles that close closer to the lower part of the candle range.
This is controlled by:
Close Pressure Threshold %
Example:
If the threshold is 65%, a bullish candle must close relatively high in its candle range.
For bearish flips, the inverse logic is used.
This helps the script avoid weak candles that reject but fail to close with enough pressure.
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📏 BODY PRESSURE ENGINE
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The script also checks the body size of the signal candle.
This is controlled by:
Minimum Reversal Body %
The candle body is measured as a percentage of the full candle range.
This helps avoid extremely weak candles where the wick may be large but the body does not show enough directional pressure.
A higher value makes the script more selective.
A lower value allows more signals.
This does not mean a larger candle body is always better.
It simply gives the model a minimum candle-strength requirement.
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📊 VOLUME BURST CONFIRMATION
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Candle Pressure Flip Engine includes an optional Volume Burst filter.
When enabled, the script compares current volume to its moving average.
The main settings are:
📊 Use Volume Burst
📊 Volume MA Length
📊 Minimum Volume Multiplier
Example:
A Minimum Volume Multiplier of 1.10 means the current volume must be at least 10% above its average.
The purpose is to check whether the pressure-flip candle appeared with above-average participation.
This can be useful on markets where volume data is meaningful.
Important note:
Some symbols, brokers, CFDs, forex feeds, or synthetic markets may have limited or less reliable volume data.
Users can disable this filter if volume is not useful for their selected market.
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🧭 RSI MOMENTUM FLIP CONFIRMATION
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The script includes an optional RSI Momentum Flip module.
This does not use RSI as a classic overbought/oversold signal.
Instead, the script checks whether RSI is turning in the expected direction.
Main settings:
🧭 Use Momentum Flip
🧭 RSI Length
🧭 RSI Turn Lookback
🧭 Bullish RSI Max After Flip
🧭 Bearish RSI Min After Flip
For bullish flips, RSI should start turning upward without already being too extended.
For bearish flips, RSI should start turning downward without already being too extended.
This is designed to help filter signals where candle pressure appears but momentum has not started shifting yet.
RSI confirmation is only one part of the model.
It does not guarantee future price movement.
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🧠 AUTO BEST OPTIMIZER
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Candle Pressure Flip Engine includes a background optimizer.
The optimizer compares controlled internal combinations of:
• Exhaustion move requirement
• Rejection wick requirement
• Signal score requirement
• Risk/reward target
The optimizer can be set to:
Light 27
Full 81
Light mode tests fewer combinations.
Full mode tests a deeper combination set.
The script can automatically use the best internal combination after enough closed virtual outcomes are collected.
This is controlled by:
🧠 Use Background Optimizer
🧠 Auto Use Best Optimizer Combo
🧠 Optimizer Grid Depth
🧠 Best Combination Ranking
🧠 Minimum Trades For Best Combo
Important note:
The optimizer is an internal visual-analysis feature.
It is not the same as PulseWire Strategy Tester.
It does not include broker execution, spread, slippage, commissions, order delay, partial fills, or real trade management.
It should be treated as a chart-based adaptive review tool, not as a guarantee of improved future performance.
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🎯 TARGET / RISK VISUAL SYSTEM
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When a valid candle pressure flip appears, the script can draw a projected trade plan.
The chart can show:
🎯 Target Zone
⚠️ Risk Zone
📍 Entry Zone
📈 Target line
🛑 Risk line
🏁 WIN / LOSS result stamp
The system uses a single target model.
There are no TP1 / TP2 / TP3 levels in this script.
The default target is based on the selected Risk Reward value.
Default:
Target Risk Reward = 2.0R
The risk distance can be calculated using:
Signal Wick
ATR
Hybrid
The current default risk mode is ATR.
The ATR multiplier used in the model is fixed internally at 4.0.
This creates a consistent risk projection structure.
Important note:
The target and risk boxes are visual projections only.
They are not broker orders.
They do not execute trades.
They do not guarantee that the displayed target or risk will be reached in a profitable way.
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🛡️ RISK MODE EXPLANATION
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The script includes three risk modes:
Signal Wick
ATR
Hybrid
Signal Wick mode uses the candle wick area as the risk reference.
ATR mode uses ATR-based distance.
Hybrid mode uses a wider protective logic between wick-based and ATR-based risk.
The purpose of these modes is to give users flexibility in how projected risk zones are visually drawn.
Risk settings affect the chart projection.
They should not be treated as trade recommendations.
Users should always apply their own risk management and validation.
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⚠️ SAME-CANDLE TARGET/RISK HANDLING
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If both target and risk are touched on the same candle, the true intrabar sequence cannot be known from standard OHLC chart data.
The script includes a setting for this situation:
If Target and Risk Hit Same Bar
Available options:
SL First
TP First
The default is SL First.
This is a conservative assumption.
It helps avoid overly optimistic historical visual results when the true intrabar order is unknown.
Users should understand that this is still an assumption based on available bar data.
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🏁 RESULT TRACKING
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The script can track whether a projected setup reaches target or risk first.
Possible result labels:
WIN | TARGET HIT
LOSS | RISK HIT
A WIN label means the projected target zone was reached first according to the script’s bar-based logic.
A LOSS label means the projected risk zone was reached first according to the script’s bar-based logic.
These labels are visual summaries only.
They do not represent broker execution.
They do not include slippage, spread, commissions, order delay, partial fills, liquidity issues, or real entry conditions.
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🗂️ HISTORICAL TARGET / RISK BOXES
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Candle Pressure Flip Engine can keep previous target and risk boxes on the chart.
This helps users visually review past projected setups.
The script includes a maximum historical trade-plan limit.
This is important because PulseWire has object limits.
Historical visuals may include:
🎯 previous target boxes
⚠️ previous risk boxes
📍 previous entry lines
🏁 previous result labels
🏷️ previous target/risk price tags
Users can reduce the historical object limit if the chart becomes crowded or performance slows down.
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🏷️ SIGNAL LABELS
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The script displays professional signal labels:
BULLISH FLIP ▲
BEARISH FLIP ▼
A BULLISH FLIP label appears when the script detects a possible bullish candle-pressure shift.
A BEARISH FLIP label appears when the script detects a possible bearish candle-pressure shift.
The arrow icon is included to make direction easier to identify visually.
These labels do not mean the future outcome is guaranteed.
They only mean the script’s internal conditions aligned at that candle.
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🩸 CRIMSON SPINE + ECHO + FILL
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Candle Pressure Flip Engine includes a premium visual system called:
Crimson Spine + Echo + Fill
This is not a signal by itself.
It is a visual price-following layer designed to create a clean pressure-aura effect around price.
The system includes:
🩸 one central Crimson Spine
🩸 multiple upper echo layers
🩸 multiple lower echo layers
🩸 soft crimson fill clouds
🩸 optional pulse effect
🩸 adaptive spread based on internal pressure intensity
The purpose of the Crimson Spine system is to enhance chart readability and create a premium visual structure around price.
It can help users visually track price flow, pressure compression, and expansion.
Important note:
The Crimson Spine visual is not a standalone entry signal.
It should not be used by itself as a buy/sell system.
It is a supporting visual layer.
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🎨 VISUAL THEME SYSTEM
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The script includes multiple visual themes:
Midnight Pro
Ice Minimal
Black Gold
Red Carbon
The theme system affects:
🎨 BULLISH / BEARISH label colors
🎨 Target zone colors
🎨 Risk zone colors
🎨 Result stamp colors
🎨 Entry / target / risk tags
🎨 Candle highlight color
🎨 Glow effects
The script uses a modern chart-first visual style.
It does not include a classic dashboard.
It does not include a large statistics panel.
The goal is to keep the chart clean while still providing strong visual feedback.
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🚨 PROFESSIONAL ALERT SYSTEM
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Candle Pressure Flip Engine includes two alert layers:
1. Standard alertcondition() events
2. Dynamic alert() messages
Standard alert conditions are included for compatibility with PulseWire’s normal alert interface.
Dynamic alerts can include more detailed information such as:
🚨 symbol
🚨 timeframe
🚨 direction
🚨 score
🚨 entry
🚨 risk
🚨 target
🚨 RR
🚨 Auto Best state
🚨 result
🚨 Net R
The alert system can be configured using:
🚨 Enable Dynamic Alerts
🚨 Alert Bullish Flips
🚨 Alert Bearish Flips
🚨 Alert Trade Results
🚨 Alert Payload Format
🚨 Include Entry / Risk / Target
🚨 Include Auto Best State
🚨 Alert Tag
Available payload formats:
Human
JSON
Human format is easier to read.
JSON format is more suitable for webhook workflows.
Important note:
Alerts are monitoring tools only.
They are not trade execution instructions.
They do not place orders.
Users must confirm all alerts with their own analysis and risk management.
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🔔 HOW TO USE ALERTS
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A practical alert workflow:
1. Add Candle Pressure Flip Engine to your chart.
2. Open PulseWire’s alert window.
3. Select the indicator as the alert condition.
4. Choose the desired alert type.
5. For dynamic alert() messages, use “Any alert() function call” if needed.
6. Select alert frequency according to your preference.
7. Use alerts for monitoring only.
8. Confirm each alert manually before making any trading decision.
Alerts may behave differently depending on chart timeframe, symbol, session, and real-time bar updates.
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🧪 HOW TO USE THE INDICATOR
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A practical workflow:
1. Add Candle Pressure Flip Engine to your chart.
2. Start with the default settings.
3. Review whether the chart is trending, ranging, or highly volatile.
4. Wait for a BULLISH FLIP ▲ or BEARISH FLIP ▼ label.
5. Review the candle that created the signal.
6. Check whether the move before the signal was extended.
7. Check whether the rejection wick is meaningful.
8. Check whether the candle closed with pressure.
9. Review the target and risk boxes.
10. Review the Crimson Spine visual context.
11. Use alerts if you want automatic monitoring.
12. Validate the signal with your own market structure, liquidity, trend, session, and risk-management rules.
This indicator is best used as a structured visual review tool.
It should not be used as a blind execution system.
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⚙️ SETTINGS REFERENCE
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⚙️ General
Signal Mode
Controls how selective the signal engine is.
Available modes:
Aggressive
Balanced
Conservative
Aggressive allows more signals.
Balanced is the default middle-ground profile.
Conservative requires stricter conditions.
Only One Active Trade
When enabled, the script waits until the active projection reaches target or risk before allowing a new signal.
Signal Cooldown Bars
Controls how many bars must pass between confirmed signals.
Show BULLISH / BEARISH Labels
Shows or hides the main signal labels.
Max Signal Labels
Limits how many signal labels remain visible on the chart.
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🔥 Candle Pressure Flip Engine
Exhaustion Lookback
Defines how many bars are used to evaluate the prior aggressive move.
Minimum Exhaustion Move ATR
Defines how large the prior move must be, measured in ATR.
Minimum Directional Bars
Requires a minimum number of bars inside the lookback to support the exhaustion direction.
Minimum Reversal Body %
Controls the minimum candle body size of the signal candle.
Minimum Rejection Wick %
Controls the minimum rejection wick percentage.
Close Pressure Threshold %
Controls where the candle must close inside its range.
Minimum Signal Score
Defines the minimum internal score required for a signal.
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📊 Volume Burst
Use Volume Burst
Enables or disables volume confirmation.
Volume MA Length
Defines the moving average length used for volume comparison.
Minimum Volume Multiplier
Defines how much larger current volume must be compared to average volume.
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🧭 Momentum Flip
Use Momentum Flip
Enables or disables RSI momentum confirmation.
RSI Length
Defines the RSI calculation length.
RSI Turn Lookback
Defines how many bars back RSI is compared.
Bullish RSI Max After Flip
Prevents bullish signals from appearing when RSI is already too extended upward.
Bearish RSI Min After Flip
Prevents bearish signals from appearing when RSI is already too extended downward.
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🎯 Target / Risk Result Engine
Show Target / Risk Boxes
Shows projected target and risk zones.
Show Entry / Risk / Target Lines
Shows entry, risk, and target lines.
Show Only Last Trade Plan
Removes older visual trade plans and keeps only the newest one.
Keep Historical Target / Risk Boxes
Keeps previous target/risk projections on the chart.
Max Historical Trade Plans
Controls the maximum number of historical visual plans.
Track Win / Loss Result
Enables visual result tracking.
Default Target Risk Reward
Defines the default projected RR value.
Risk Mode
Controls whether risk is based on signal wick, ATR, or hybrid logic.
ATR Length
Defines the ATR length used for risk calculations.
Risk Buffer Ticks
Adds a small tick buffer to wick-based risk calculations.
Trade Box Extend Bars
Controls how far target/risk boxes extend to the right.
If Target and Risk Hit Same Bar
Controls the same-candle assumption.
Max Result Stamps
Limits the number of WIN / LOSS result labels.
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🧠 Background Optimizer
Use Background Optimizer
Enables the internal optimizer engine.
Auto Use Best Optimizer Combo
Allows the script to automatically apply the best internal combination after enough closed virtual outcomes are collected.
Optimizer Grid Depth
Controls whether the optimizer uses Light 27 or Full 81 testing depth.
Best Combination Ranking
Controls whether combinations are ranked by wins first or win rate first.
Minimum Trades For Best Combo
Defines how many closed virtual trades are required before a combination can become eligible.
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🎨 Visual Pro Design
Visual Theme
Controls the main chart color theme.
Visual Intensity
Controls glow and line emphasis.
Label Size
Controls signal/result label size.
Target / Risk Box Transparency
Controls how transparent projected boxes appear.
Show Signal Glow
Shows or hides the signal candle glow.
Show WIN / LOSS Stamps
Shows or hides result labels.
Show Compact Price Tags
Shows or hides ENTRY ZONE, TARGET ZONE, and RISK ZONE tags.
Candle Highlight Mode
Controls candle coloring on signal/result bars.
Max Signal Glow Objects
Limits signal glow objects for chart performance.
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🚨 Professional Alerts
Enable Dynamic Alerts
Turns dynamic alert() messages on or off.
Alert Bullish Flips
Enables alerts for bullish flip signals.
Alert Bearish Flips
Enables alerts for bearish flip signals.
Alert Trade Results
Enables alerts for target/risk results.
Alert Payload Format
Choose Human or JSON.
Include Entry / Risk / Target
Adds projected price levels into alerts.
Include Auto Best State
Adds Auto Best status into signal alerts.
Alert Tag
Custom text tag included in alert messages.
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🩸 Crimson Spine + Echo
Show Crimson Spine System
Shows or hides the Crimson Spine visual layer.
Spine Source
Defines the source price used by the spine.
Spine EMA Length
Controls the central spine smoothing.
Echo Spacing ATR
Controls how far echo layers are spaced from the central spine.
Adaptive Echo Spread
Expands or compresses the echo cloud based on internal pressure intensity.
Spine Line Width
Controls line thickness.
Core Line Transparency
Controls the transparency of the central spine.
Echo Transparency Step
Controls how quickly outer echo layers become transparent.
Crimson Fill Transparency
Controls the fill cloud transparency.
Spine Pulse Effect
Adds a subtle pulsing visual effect.
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🧠 WHAT MAKES THIS SCRIPT ORIGINAL
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Candle Pressure Flip Engine uses familiar concepts such as:
🔥 candle body analysis
🕯️ wick rejection
📍 close-location pressure
📊 volume comparison
🧭 RSI momentum
📏 ATR-based risk projection
🎯 target/risk boxes
🚨 alerts
These concepts are not unique by themselves.
The originality of the script lies in how they are organized into one workflow:
Exhaustion Move
→ Rejection Wick
→ Close Pressure
→ Volume Burst
→ Momentum Flip
→ Internal Score
→ Auto Best Optimizer
→ BULLISH / BEARISH Flip Label
→ Target / Risk Projection
→ Result Tracking
→ Crimson Spine Visual Layer
→ Professional Alerts
This structure is designed to give users a clearer way to review potential candle-pressure reversal conditions.
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⚠️ IMPORTANT PRACTICAL NOTES
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The script’s behavior depends heavily on settings.
Signal frequency and visual output may change based on:
🎛️ signal mode
🔥 exhaustion lookback
📏 ATR settings
🕯️ wick requirement
📍 close-pressure threshold
📊 volume settings
🧭 RSI settings
🧠 optimizer settings
🎯 target/risk settings
⏱️ timeframe
📊 symbol volatility
🌐 market session
📚 available historical bars
A configuration that looks clean on one symbol may behave differently on another.
A setting that appears useful on one timeframe may not be useful on another.
Users should test the script on the exact markets and timeframes they personally study.
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⚠️ LIMITATIONS AND SHORTCOMINGS
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This script has important limitations:
❌ It does not guarantee profitable trades.
❌ It does not predict future price movement.
❌ It does not replace risk management.
❌ It does not execute trades.
❌ It does not place broker orders.
❌ It does not include broker slippage.
❌ It does not include commissions.
❌ It does not include spreads.
❌ It does not include order delay.
❌ It does not include partial fills.
❌ It uses bar-based chart data.
❌ Same-candle target/risk order cannot be known from standard OHLC data.
❌ Internal optimizer results are not official Strategy Tester results.
❌ Target/risk boxes are visual projections only.
❌ Result labels are visual outcomes only.
❌ Crimson Spine visuals are not standalone signals.
❌ Alerts are monitoring tools only.
❌ Historical behavior does not ensure future behavior.
For these reasons, Candle Pressure Flip Engine should be used as an educational decision-support and chart-analysis tool, not as a standalone trading strategy.
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👤 WHO THIS SCRIPT MAY BE USEFUL FOR
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This script may be useful for traders who:
✅ study candle-pressure behavior
✅ study reversal conditions after extended moves
✅ want structured candle rejection confirmation
✅ want volume and momentum context
✅ want clean target/risk visual planning
✅ want historical visual projection review
✅ want premium chart visuals without a large dashboard
✅ want alert-based monitoring
✅ want a structured educational analysis tool
✅ prefer chart-first visual design
It may be less suitable for users who:
❌ want guaranteed buy/sell signals
❌ want a fully automated trading bot
❌ do not use technical analysis
❌ do not want chart visuals
❌ expect one setting to work on every market
❌ expect alerts to execute trades
❌ expect visual projections to match broker execution
❌ want an indicator that replaces personal decision-making
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🧭 BEST PRACTICE SUGGESTIONS
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For cleaner review:
✅ Start with the default settings.
✅ Use Balanced mode first.
✅ Review signals together with market structure.
✅ Check whether the signal appears after a meaningful move.
✅ Review rejection wick quality.
✅ Review candle close position.
✅ Use target/risk boxes as visual planning tools only.
✅ Do not treat every signal as a trade.
✅ Review the Crimson Spine as a supporting visual layer, not as a standalone signal.
✅ Use alerts for monitoring, not automatic execution.
✅ Test the indicator on the symbols and timeframes you actually study.
✅ Combine the tool with independent analysis and risk management.
✅ Keep expectations realistic.
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🔓 PUBLICATION NOTE
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Candle Pressure Flip Engine is published as an educational and visual market-analysis tool.
The purpose of this description is to explain:
✅ what the script does
✅ how the main logic works
✅ how signals are created
✅ how candle pressure is evaluated
✅ how target/risk boxes are drawn
✅ how result labels work
✅ what the Crimson Spine visual means
✅ what the alert system does
✅ what the limitations are
✅ how the indicator should and should not be used
The script is designed to support structured analysis.
It does not promise profitable results.
It does not remove market risk.
It does not execute trades.
It should not be used as a blind buy/sell system.
It is best used as a visual framework for reviewing candle-pressure reversal conditions, target/risk projection behavior, and alert-based monitoring.
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🛡️ DISCLAIMER
━━━━━━━━━━━━━━━━━━━━━━
Candle Pressure Flip Engine is provided for educational and informational purposes only.
It does not constitute financial, investment, or trading advice.
No indicator can guarantee future results.
Markets are uncertain, conditions change, and historical behavior does not ensure future performance.
Every user is responsible for their own analysis, validation, risk management, position sizing, and trading decisions.
The target/risk boxes, BULLISH / BEARISH labels, WIN / LOSS result stamps, Crimson Spine visuals, optimizer behavior, and alerts are visual analysis tools only.
Use this script as a structured decision-support and visual review framework, not as a promise of profitability.
Indicator
MACD Pressure Zones | Alpha S+MACD Pressure Zones
MACD Pressure Zones is a normalized MACD histogram oscillator designed to show momentum pressure on a 0 to 100 scale.
Instead of displaying the raw MACD histogram around a zero line, this script normalizes the histogram over a selected lookback period and maps it into a bounded oscillator range. This allows users to compare MACD histogram pressure across different market conditions with fixed reference zones such as 90, 85, 50, 15, and 10.
The script does not provide entry or exit recommendations. Its purpose is to help users study momentum pressure, extended momentum areas, neutral pressure, and cooling or heating behavior inside a simplified MACD-based zone structure.
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Core Concept
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The standard MACD histogram shows the distance between the MACD line and the signal line.
When the histogram expands, momentum pressure is increasing.
When the histogram contracts, momentum pressure is weakening.
This script takes that MACD histogram value and normalizes it into a 0 to 100 range.
The normalized structure uses five main reference levels:
• 90: Extreme upper momentum pressure
• 85: Upper pressure zone
• 50: Neutral pressure level
• 15: Lower pressure zone
• 10: Extreme lower momentum pressure
The red line is a smoothed version of the normalized MACD histogram. It helps users read the broader momentum pressure curve rather than reacting to every individual histogram bar.
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What This Script Shows
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The script can display:
• normalized MACD histogram columns
• smoothed MACD pressure line
• 90 and 85 upper pressure levels
• 50 neutral pressure level
• 15 and 10 lower pressure levels
• upper and lower zone background highlights
• histogram expansion or contraction state
• current pressure zone
• momentum heating or cooling state
• positive or negative pressure bias
• number of bars spent inside upper or lower pressure zones
• optional status panel
These elements are designed to help users identify whether MACD histogram pressure is extended, recovering, cooling, expanding, or returning toward neutral.
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How It Works
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1. The script calculates the MACD line using the selected fast and slow EMA lengths.
2. The signal line is calculated from the MACD line.
3. The MACD histogram is calculated as MACD minus signal.
4. The histogram is normalized over the selected lookback period.
5. The normalized value is mapped into a 0 to 100 oscillator range.
6. A smoothed red pressure line is calculated from the normalized oscillator.
7. The script compares the pressure line with the 90, 85, 50, 15, and 10 reference levels.
8. Zone background highlights appear when the pressure line enters upper or lower pressure areas.
9. Histogram columns become visually stronger or weaker depending on expansion or contraction.
10. The status panel summarizes current pressure, zone, momentum state, bias, zone duration, and histogram condition.
This structure converts MACD histogram behavior into a cleaner zone-based momentum pressure map.
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Inputs And Customization
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Users can adjust:
• MACD fast length
• MACD slow length
• MACD signal length
• source price
• normalization lookback
• red line smoothing length
• 0 to 100 clamping
• extreme upper pressure level
• upper pressure level
• neutral pressure level
• lower pressure level
• extreme lower pressure level
• zone background visibility
• histogram visibility
• red line visibility
• status panel visibility
• panel position
• panel text size
• histogram colors
• red line color
• reference level color
• panel background color
The default levels are designed around a 90 / 85 / 50 / 15 / 10 pressure-zone framework.
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Visual Elements
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The script includes:
• normalized histogram columns
• smoothed red pressure line
• horizontal reference levels
• upper pressure background
• lower pressure background
• status panel
The histogram columns show the normalized MACD histogram value.
The red line smooths the normalized histogram and makes the pressure cycle easier to read.
The 50 level acts as the neutral pressure reference.
The 85 and 90 levels mark upper momentum pressure zones.
The 15 and 10 levels mark lower momentum pressure zones.
The panel summarizes the current state without adding directional trade labels to the chart.
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Reference States
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Extreme Upper Pressure:
The smoothed pressure line is at or above the upper extreme level.
Upper Pressure:
The smoothed pressure line is inside the upper pressure zone.
Positive Pressure:
The pressure line is above the neutral level but below the upper pressure zone.
Neutral Pressure:
The pressure line is near the neutral reference level.
Negative Pressure:
The pressure line is below the neutral level but above the lower pressure zone.
Lower Pressure:
The smoothed pressure line is inside the lower pressure zone.
Extreme Lower Pressure:
The smoothed pressure line is at or below the lower extreme level.
Heating:
The smoothed pressure line is rising.
Cooling:
The smoothed pressure line is falling.
Expanding:
The normalized histogram is increasing compared with the prior bar.
Contracting:
The normalized histogram is decreasing compared with the prior bar.
These states are informational and should not be interpreted as trading instructions.
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How To Use
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Use this script as a MACD histogram pressure and momentum-zone viewer.
General interpretation examples:
• When the red line is above 85, MACD histogram pressure is in an upper extended area.
• When the red line is above 90, the upper pressure condition is more extreme.
• When the red line moves down from the upper pressure zone, momentum pressure may be cooling.
• When the red line is near 50, MACD histogram pressure is closer to neutral.
• When the red line is below 15, MACD histogram pressure is in a lower extended area.
• When the red line is below 10, the lower pressure condition is more extreme.
• When the red line rises from the lower pressure zone, momentum pressure may be heating.
• Zone Bars can help users see how long the pressure line has remained in an upper or lower pressure zone.
• Histogram expansion can show strengthening pressure, while contraction can show fading pressure.
This script is best reviewed together with price action, trend structure, volatility, support and resistance, and higher-timeframe context.
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Confirmation And Repainting Notes
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The script calculates MACD, the histogram, normalization range, and the smoothed pressure line from available chart data.
On realtime candles, values can change before the candle closes because the MACD histogram and normalization values can update intrabar.
For more conservative analysis, users should review the oscillator after candle confirmation.
The script does not use future price data to predict market direction.
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Limitations
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This script does not predict future price movement.
It does not provide entry or exit recommendations.
A high pressure reading does not guarantee a reversal.
A low pressure reading does not guarantee a rebound.
MACD histogram behavior can remain extended during strong trends.
Normalization depends on the selected lookback period, so readings may change when the lookback setting changes.
Different symbols and timeframes may require different settings.
This script should not be used as a standalone trading system.
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Disclaimer
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This publication is for educational and informational chart analysis only.
It does not constitute financial advice, investment advice, or a recommendation to trade any financial instrument.
All trading and investment decisions are the responsibility of the user.
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MACD Pressure Zones
MACD Pressure Zones는 MACD 히스토그램을 0~100 범위로 정규화하여 모멘텀 압력 구간을 보여주는 오실레이터형 지표입니다.
일반 MACD 히스토그램을 0선 중심으로 표시하는 대신, 이 스크립트는 선택한 lookback 구간 안에서 히스토그램 값을 정규화하고 이를 고정된 오실레이터 범위로 변환합니다. 이를 통해 90, 85, 50, 15, 10과 같은 기준 구간을 사용해 다양한 시장 상황의 MACD 히스토그램 압력을 비교할 수 있습니다.
이 지표는 진입 또는 청산 추천을 제공하지 않습니다. 목적은 모멘텀 압력, 확장된 모멘텀 구간, 중립 압력, cooling 또는 heating 상태를 단순한 MACD 기반 구간 구조 안에서 분석하는 것입니다.
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핵심 개념
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일반 MACD 히스토그램은 MACD 라인과 시그널 라인 사이의 거리를 보여줍니다.
히스토그램이 확장되면 모멘텀 압력이 증가하는 상태로 볼 수 있습니다.
히스토그램이 수축되면 모멘텀 압력이 약해지는 상태로 볼 수 있습니다.
이 스크립트는 MACD 히스토그램 값을 0~100 범위로 정규화합니다.
정규화된 구조는 다섯 개의 주요 기준선을 사용합니다.
• 90: 극단적 상단 모멘텀 압력
• 85: 상단 압력 구간
• 50: 중립 압력 기준선
• 15: 하단 압력 구간
• 10: 극단적 하단 모멘텀 압력
빨간선은 정규화된 MACD 히스토그램을 평활화한 값입니다. 개별 히스토그램 막대보다 넓은 모멘텀 압력 곡선을 읽는 데 도움을 줍니다.
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이 스크립트가 보여주는 것
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이 스크립트는 다음 요소를 표시할 수 있습니다.
• 정규화된 MACD 히스토그램 막대
• 평활화된 MACD 압력선
• 90 및 85 상단 압력 기준선
• 50 중립 압력 기준선
• 15 및 10 하단 압력 기준선
• 상단 및 하단 구간 배경 강조
• 히스토그램 확장 또는 수축 상태
• 현재 압력 구간
• 모멘텀 heating 또는 cooling 상태
• positive 또는 negative 압력 방향
• 상단 또는 하단 압력 구간 체류 봉 수
• 선택 가능한 상태 패널
이 요소들은 MACD 히스토그램 압력이 확장, 회복, 둔화, 확장 지속, 또는 중립 회귀 중 어디에 가까운지 확인하는 데 도움을 줍니다.
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작동 방식
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1. 선택한 fast EMA와 slow EMA 길이를 사용해 MACD 라인을 계산합니다.
2. MACD 라인에서 시그널 라인을 계산합니다.
3. MACD에서 시그널을 뺀 값으로 MACD 히스토그램을 계산합니다.
4. 선택한 lookback 구간에서 히스토그램을 정규화합니다.
5. 정규화된 값을 0~100 오실레이터 범위로 변환합니다.
6. 정규화 오실레이터에서 평활화된 빨간 압력선을 계산합니다.
7. 압력선을 90, 85, 50, 15, 10 기준선과 비교합니다.
8. 압력선이 상단 또는 하단 압력 구간에 진입하면 배경이 강조됩니다.
9. 히스토그램 막대는 확장 또는 수축 여부에 따라 다르게 표시됩니다.
10. 상태 패널은 현재 압력, 구간, 모멘텀 상태, 방향성, 구간 체류 시간, 히스토그램 상태를 요약합니다.
이 구조는 MACD 히스토그램 행동을 더 깔끔한 구간 기반 모멘텀 압력 맵으로 변환합니다.
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입력값 및 설정
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사용자는 다음 항목을 조정할 수 있습니다.
• MACD fast length
• MACD slow length
• MACD signal length
• source price
• normalization lookback
• red line smoothing length
• 0 to 100 clamping
• extreme upper pressure level
• upper pressure level
• neutral pressure level
• lower pressure level
• extreme lower pressure level
• zone background visibility
• histogram visibility
• red line visibility
• status panel visibility
• panel position
• panel text size
• histogram colors
• red line color
• reference level color
• panel background color
기본 기준선은 90 / 85 / 50 / 15 / 10 압력 구간 구조를 중심으로 설계되어 있습니다.
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시각 요소
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이 스크립트는 다음 시각 요소를 포함합니다.
• 정규화 히스토그램 막대
• 평활화된 빨간 압력선
• 수평 기준선
• 상단 압력 배경
• 하단 압력 배경
• 상태 패널
히스토그램 막대는 정규화된 MACD 히스토그램 값을 보여줍니다.
빨간선은 정규화된 히스토그램을 평활화하여 압력 사이클을 더 쉽게 읽게 해줍니다.
50선은 중립 압력 기준선 역할을 합니다.
85와 90은 상단 모멘텀 압력 구간을 표시합니다.
15와 10은 하단 모멘텀 압력 구간을 표시합니다.
패널은 차트에 방향성 매매 라벨을 추가하지 않고도 현재 상태를 요약합니다.
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참고 상태
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Extreme Upper Pressure:
평활화된 압력선이 상단 극단 기준선 이상에 있는 상태입니다.
Upper Pressure:
평활화된 압력선이 상단 압력 구간에 있는 상태입니다.
Positive Pressure:
압력선이 중립 기준선 위에 있지만 상단 압력 구간 아래에 있는 상태입니다.
Neutral Pressure:
압력선이 중립 기준선 부근에 있는 상태입니다.
Negative Pressure:
압력선이 중립 기준선 아래에 있지만 하단 압력 구간 위에 있는 상태입니다.
Lower Pressure:
평활화된 압력선이 하단 압력 구간에 있는 상태입니다.
Extreme Lower Pressure:
평활화된 압력선이 하단 극단 기준선 이하에 있는 상태입니다.
Heating:
평활화된 압력선이 상승 중인 상태입니다.
Cooling:
평활화된 압력선이 하락 중인 상태입니다.
Expanding:
정규화된 히스토그램이 직전 봉보다 증가하는 상태입니다.
Contracting:
정규화된 히스토그램이 직전 봉보다 감소하는 상태입니다.
이 상태들은 정보 제공용이며, 매매 지시로 해석해서는 안 됩니다.
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사용 방법
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이 스크립트는 MACD 히스토그램 압력 및 모멘텀 구간 확인 도구로 사용하는 것이 적절합니다.
일반적인 해석 예시는 다음과 같습니다.
• 빨간선이 85 위에 있으면 MACD 히스토그램 압력이 상단 확장 구간에 있는 상태로 볼 수 있습니다.
• 빨간선이 90 위에 있으면 더 극단적인 상단 압력 상태로 볼 수 있습니다.
• 빨간선이 상단 압력 구간에서 하락하면 모멘텀 압력이 cooling 되는 과정일 수 있습니다.
• 빨간선이 50 부근에 있으면 MACD 히스토그램 압력이 중립에 가까운 상태입니다.
• 빨간선이 15 아래에 있으면 MACD 히스토그램 압력이 하단 확장 구간에 있는 상태로 볼 수 있습니다.
• 빨간선이 10 아래에 있으면 더 극단적인 하단 압력 상태로 볼 수 있습니다.
• 빨간선이 하단 압력 구간에서 상승하면 모멘텀 압력이 heating 되는 과정일 수 있습니다.
• Zone Bars는 압력선이 상단 또는 하단 압력 구간에 얼마나 오래 머물렀는지 확인하는 데 사용할 수 있습니다.
• Histogram expansion은 압력 강화, contraction은 압력 둔화를 보여줄 수 있습니다.
이 스크립트는 가격 행동, 추세 구조, 변동성, 지지와 저항, 상위 시간대 컨텍스트와 함께 검토하는 것이 좋습니다.
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확인봉 및 리페인트 안내
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이 스크립트는 사용 가능한 차트 데이터를 기준으로 MACD, 히스토그램, 정규화 범위, 평활화된 압력선을 계산합니다.
실시간 캔들에서는 MACD 히스토그램과 정규화 값이 봉 마감 전까지 변경될 수 있으므로 값이 변할 수 있습니다.
보다 보수적인 분석을 원한다면 봉 마감 이후 오실레이터를 검토하는 것이 적절합니다.
이 스크립트는 미래 가격 데이터를 사용해 시장 방향을 예측하지 않습니다.
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한계
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이 스크립트는 미래 가격 움직임을 예측하지 않습니다.
진입 또는 청산 추천을 제공하지 않습니다.
높은 압력 수치가 반전을 보장하지 않습니다.
낮은 압력 수치가 반등을 보장하지 않습니다.
강한 추세에서는 MACD 히스토그램 압력이 오랜 시간 확장 구간에 머무를 수 있습니다.
정규화 값은 선택한 lookback period에 따라 달라질 수 있습니다.
종목과 시간대에 따라 적절한 설정값이 달라질 수 있습니다.
이 스크립트를 단독 매매 시스템으로 사용해서는 안 됩니다.
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중요 고지
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본 게시물은 교육 및 정보 제공 목적의 차트 분석 자료입니다.
투자 자문, 특정 금융상품 거래 권유, 또는 수익 보장을 의미하지 않습니다.
모든 투자 판단과 그 결과에 대한 책임은 이용자 본인에게 있습니다.
Indicator
RSI-T (RSI + Time)
RSI-T
RSI with Time Parameter
Technical White Paper & User Guide
Dimitrios Kataliakos
May 2026
Based on the theory: "Market as Expanding Dough"
(Agora os Diogkoumeno Zymari)
Table of Contents
Table of Contents 1
1. Executive Summary 1
2. Theoretical Foundation 1
2.1 The Market as Expanding Dough 1
2.2 Time as a Curvature Factor 1
2.3 Regime Classification 1
3. Mathematical Definition 1
3.1 Core Formula 1
3.2 Parameters 1
3.3 Derived Metrics 1
4. Timeframe Analysis 1
4.1 Timeframe Weight 1
4.2 Recommended Settings by Timeframe 1
4.3 Multi-Timeframe Confluence 1
5. User Guide 1
5.1 Installation (PulseWire) 1
5.2 Reading the Indicator 1
5.3 Trading Rules 1
Rule 1: Regime Identification First 1
Rule 2: Do Not Short Persistent Bull 1
Rule 3: Do Not Buy Persistent Bear 1
Rule 4: Momentum Zone is Decision Zone 1
Rule 5: Watch the Divergence 1
5.4 Practical Examples 1
6. Backtest Strategy 1
6.1 Strategy Logic 1
6.2 Risk Management 1
6.3 Pine Script Strategy 1
6.4 Metrics to Evaluate 1
7. Limitations & Future Work 1
7.1 Known Limitations 1
7.2 Future Development 1
8. Appendix 1
8.1 Files Included 1
8.2 Version History 1
1. Executive Summary
The RSI-T (RSI with Time) is a technical indicator that extends the classic Wilder RSI by adding a third parameter: the duration of time price action remains in an extreme zone. While the standard RSI measures the magnitude of recent price changes, it fails to capture the persistence of momentum regimes. The RSI-T solves this by quantifying how long the RSI stays above or below threshold levels, providing traders with a tool that distinguishes between transient spikes and sustained directional moves.
The indicator is derived from the economic theory of markets as expanding systems, where price does not tend toward equilibrium but rather expands unevenly, creating zones of compression and expansion. The RSI-T operationalizes this concept by treating the time spent in extreme RSI territory as a measure of regime strength.
2. Theoretical Foundation
2.1 The Market as Expanding Dough
Traditional economic theory assumes markets tend toward equilibrium. The theory underlying RSI-T proposes an alternative model: the market behaves like expanding dough, where nominal prices continuously inflate, but the expansion is uneven across time and sectors. This creates regions of rapid expansion (bubbles, momentum regimes) and compression (consolidations, mean-reversion zones).
The three analytical layers of this model are:
• Geometry (Curvature): How price curves in space, measured through momentum and convexity. This corresponds to the RSI dimension of the indicator.
• Temperature (Volatility): The thermal energy of the market, measured through implied and realized volatility. This informs the threshold sensitivity.
• Cohesion (Liquidity): The structural integrity of price action, related to order flow and market microstructure. This provides context for regime classification.
2.2 Time as a Curvature Factor
The critical insight of RSI-T is that time spent at extremes is itself information. When the RSI remains above 70 for one bar, it may be a transient spike. When it remains above 70 for eight consecutive bars, the market has entered a different regime entirely. Standard RSI treats both situations identically. RSI-T does not.
In the dough metaphor, this corresponds to a region that is not just expanded, but has been expanding for a sustained period. The longer the expansion persists, the more the local structure of the market has reorganized around the new price level, and the less likely a simple mean-reversion is to occur.
This is consistent with empirical findings in momentum literature: assets that have been trending tend to continue trending, and the duration of the trend is a stronger predictor of continuation than the magnitude alone.
2.3 Regime Classification
The RSI-T framework classifies market states into distinct regimes based on the combination of RSI level and time at extreme:
Regime RSI Condition Time Condition
NEUTRAL Between oversold and overbought Counter = 0
MOMENTUM_BULL RSI > Overbought threshold 2 to N-1 bars
MOMENTUM_BEAR RSI < Oversold threshold 2 to N-1 bars
PERSISTENT_BULL RSI > Overbought threshold N or more bars
PERSISTENT_BEAR RSI < Oversold threshold N or more bars
Where N is the persistence threshold (default: 5 bars). In the persistent regimes, traditional mean-reversion signals (e.g., sell when RSI > 70) are weakened or inverted.
3. Mathematical Definition
3.1 Core Formula
The RSI-T value is calculated as:
RSI_T = clamp( RSI + (bars_at_extreme × time_weight × direction), 0, 100 )
Where:
• RSI = Standard Wilder RSI(close, period)
• bars_at_extreme = consecutive bars where RSI > threshold_OB or RSI < threshold_OS
• time_weight (α) = scaling factor per bar of persistence (default: 1.2)
• direction = +1 if RSI > threshold_OB, -1 if RSI < threshold_OS, 0 otherwise
• clamp() = constrains result to
3.2 Parameters
Parameter Default Range Description
period 14 5 – 50 RSI lookback period (Wilder smoothing)
threshold 70 / 30 55–90 / 10–45 Overbought / Oversold boundary
time_weight (α) 1.2 0.0 – 5.0 Signal boost per bar at extreme
max_boost 20 5 – 40 Maximum cumulative boost (cap)
persist_bars (N) 5 2 – 20 Bars required for persistent regime
3.3 Derived Metrics
• Divergence = RSI_T − RSI: Measures the total impact of the time parameter. When divergence is zero, RSI-T equals classic RSI. When divergence is large, the time dimension is providing significant additional information.
• Time Counter (bars_extreme): The raw number of consecutive bars spent above/below the threshold. This is the primary regime classifier.
• Regime Label: Categorical classification (NEUTRAL, MOMENTUM_BULL, MOMENTUM_BEAR, PERSISTENT_BULL, PERSISTENT_BEAR) derived from the combination of RSI level and time counter.
4. Timeframe Analysis
The RSI-T works across all timeframes, but its interpretation changes because the time counter has different weight depending on bar duration.
4.1 Timeframe Weight
Timeframe 1 Bar = 5 Bars (Persistent) = Interpretation
1 minute 1 minute 5 minutes Micro-momentum, scalping noise common
5 minutes 5 minutes 25 minutes Intraday momentum phases
15 minutes 15 minutes 1.25 hours Session-level regime shifts
1 hour 1 hour 5 hours Intraday trend confirmation
4 hours 4 hours 20 hours Multi-session directional bias
Daily 1 day 1 week Swing-level regime classification
Weekly 1 week 5 weeks (~1 month) Position-level trend strength
Monthly 1 month 5 months Macro regime identification
4.2 Recommended Settings by Timeframe
Timeframe Period Time Weight Persist Bars
1–5 min 14 0.5 – 0.8 8 – 12
15–60 min 14 0.8 – 1.2 5 – 8
4H / Daily 14 1.0 – 1.5 4 – 6
Weekly 14 1.5 – 2.0 3 – 5
Monthly 14 2.0 – 3.0 3 – 4
The general principle: shorter timeframes need more bars to confirm persistence (more noise to filter), while longer timeframes establish regimes faster because each bar carries more weight.
4.3 Multi-Timeframe Confluence
The highest-conviction signals occur when multiple timeframes agree. For example, if the daily RSI-T shows PERSISTENT_BULL and the weekly RSI-T enters MOMENTUM_BULL, this represents a multi-timeframe momentum alignment that significantly increases the probability of trend continuation.
Conversely, if the daily is in PERSISTENT_BULL but the weekly RSI-T is declining from a recent extreme, this divergence between timeframes suggests the persistent regime may be nearing exhaustion.
5. User Guide
5.1 Installation (PulseWire)
1. Open PulseWire and navigate to the chart of your chosen instrument.
2. Click Pine Editor at the bottom of the screen.
3. Click New and select New indicator.
4. Delete all existing code and paste the RSI-T Pine Script (v6) code.
5. Click Add to chart. The RSI-T panel appears below the price chart.
6. Adjust parameters via the Settings gear icon on the indicator.
5.2 Reading the Indicator
Blue line: Classic RSI. This is the baseline reference.
Orange/Red line: RSI-T. When this diverges from the blue line, the time parameter is active and providing additional information.
Histogram (bottom): Scaled time counter showing the number of bars spent at the extreme zone.
Green background: Persistent bull regime. The RSI has been above the overbought threshold for N or more bars.
Red/orange background: Persistent bear regime (red) or momentum bear/bull (orange/blue).
Blue background: Momentum bull. RSI above overbought for 2 to N-1 bars. Early-stage momentum zone.
5.3 Trading Rules
Rule 1: Regime Identification First
Before making any trading decision, identify the current regime from the background color. In NEUTRAL regime, traditional RSI-based mean-reversion strategies apply normally. In MOMENTUM or PERSISTENT regimes, mean-reversion signals are weakened or inverted.
Rule 2: Do Not Short Persistent Bull
When the RSI-T shows persistent bull (green background), do not initiate short positions based on overbought readings. The persistence signal indicates that the market has reorganized around the uptrend and further upside is more likely than immediate reversal. Wait for the regime to reset (counter returns to zero) before considering mean-reversion trades.
Rule 3: Do Not Buy Persistent Bear
The inverse of Rule 2. When persistent bear is active (red background), do not buy dips based on oversold readings. The selling pressure has established itself as a regime, not a transient condition.
Rule 4: Momentum Zone is Decision Zone
The blue/orange background (momentum zone, 2 to N-1 bars) is where decisions are made. This is the transitional phase where the market is testing whether it will establish a persistent regime or revert. Tighter stops and smaller positions are appropriate here.
Rule 5: Watch the Divergence
When RSI-T diverges significantly from classic RSI (large divergence value), the time dimension is dominating. A sudden collapse of this divergence (counter drops to zero) often precedes sharp reversals, as the accumulated time pressure releases.
5.4 Practical Examples
Scenario RSI-T Reading Action
RSI at 75, counter = 1 Momentum bull (blue bg) Standard caution, normal position sizing
RSI at 75, counter = 7 Persistent bull (green bg) Do NOT short. Trailing stop on existing longs
RSI at 42, counter = 0 Neutral Normal analysis applies. No regime signal
RSI at 25, counter = 6 Persistent bear (red bg) Do NOT buy dips. Wait for regime exit
RSI at 72, counter drops from 5 to 0 Regime exit Alert: potential reversal. Tighten stops
6. Backtest Strategy
6.1 Strategy Logic
The RSI-T Strategy for backtesting converts the indicator into actionable entries and exits. The core logic uses regime transitions as signals:
Long Entry:
• RSI-T crosses above the overbought threshold AND the time counter reaches the momentum threshold (2 bars), confirming directional commitment.
• Alternative: Enter when the regime transitions from NEUTRAL to MOMENTUM_BULL (catching the early phase of a potential persistent move).
Long Exit:
• The time counter resets to zero after being in persistent bull (regime exit signal).
• Alternative: RSI-T crosses below the midline (50) from above.
Short Entry:
• RSI-T crosses below the oversold threshold AND the time counter reaches the momentum threshold.
Short Exit:
• Time counter resets to zero after persistent bear, or RSI-T crosses above midline.
6.2 Risk Management
• Position size: 10% of equity per trade (adjustable in strategy settings).
• Stop loss: Based on ATR multiplier (default 2x ATR-14) to account for regime volatility.
• Trailing stop: Activates once position reaches 1.5x risk in profit.
• No pyramiding by default (can be enabled for persistent regime continuation).
6.3 Pine Script Strategy
A complete Pine Script v6 strategy file (rsi_t_strategy_v6.pine) is provided alongside this document. The strategy includes configurable parameters for entry/exit rules, position sizing, stop-loss, and trailing stop. It can be applied to any instrument and timeframe in PulseWire for historical backtesting.
6.4 Metrics to Evaluate
When backtesting the RSI-T strategy, focus on the following metrics to validate the theoretical framework:
• Win Rate in Persistent vs. Momentum vs. Neutral regimes (the theory predicts higher win rates in persistent regimes for trend-following entries).
• Average trade duration across regimes (persistent regime trades should be longer and more profitable).
• False signal rate: How often does momentum (blue background) fail to convert to persistent (green background)?
• Regime exit accuracy: What percentage of regime exits (counter reset) are followed by actual reversals within N bars?
• Comparison vs. classic RSI strategy (same entry rules without the time parameter) to isolate the value added by the time dimension.
7. Limitations & Future Work
7.1 Known Limitations
• The RSI-T is a lagging indicator by nature. The time counter requires bars to accumulate before signaling persistence, meaning the earliest phase of a move is not captured.
• In choppy or range-bound markets, the counter may produce false starts, briefly entering momentum zone before resetting. The persist_bars threshold helps filter these but cannot eliminate them entirely.
• The linear time_weight model (each bar adds the same boost) may not be optimal. Markets may exhibit non-linear acceleration, where the 10th bar at extreme is more significant than the 3rd.
• The indicator does not incorporate volume, volatility, or cross-asset information. It is purely price-derived.
7.2 Future Development
• Non-linear time weighting: Exponential or logarithmic boost curves that better reflect the accelerating nature of regime establishment.
• Volatility-adjusted thresholds: Dynamic overbought/oversold levels that adjust based on current implied volatility (high-vol environments may require wider thresholds).
• Fast/Slow RSI divergence: Comparing RSI-T across different periods (e.g., RSI-T(7) vs RSI-T(21)) to measure regime acceleration, as described in the original theory.
• Cross-asset regime correlation: Using the RSI-T regime of correlated assets (e.g., SPX for individual stocks) as a confirmation layer.
• Machine learning optimization: Using historical data to optimize time_weight and persist_bars parameters per asset class and market regime.
8. Appendix
8.1 Files Included
File Description
rsi_t_v6.pine RSI-T indicator for PulseWire (Pine Script v6)
rsi_t_strategy_v6.pine RSI-T backtest strategy for PulseWire (Pine Script v6)
rsi_t_indicator.py RSI-T Python implementation for custom backtesting
8.2 Version History
Version Date Changes
1.0 May 2026 Initial release: RSI-T indicator, strategy, white paper
Copyright © 2026 Dimitrios Kataliakos. All rights reserved.
This document and the associated indicator code are proprietary work based on the original theory of markets as expanding systems.
Indicator
RSI-T (RSI + Time)
RSI-T
RSI with Time Parameter
Technical White Paper & User Guide
Dimitrios Kataliakos
May 2026
Based on the theory: "Market as Expanding Dough"
(Agora os Diogkoumeno Zymari)
Table of Contents
Table of Contents 1
1. Executive Summary 1
2. Theoretical Foundation 1
2.1 The Market as Expanding Dough 1
2.2 Time as a Curvature Factor 1
2.3 Regime Classification 1
3. Mathematical Definition 1
3.1 Core Formula 1
3.2 Parameters 1
3.3 Derived Metrics 1
4. Timeframe Analysis 1
4.1 Timeframe Weight 1
4.2 Recommended Settings by Timeframe 1
4.3 Multi-Timeframe Confluence 1
5. User Guide 1
5.1 Installation (PulseWire) 1
5.2 Reading the Indicator 1
5.3 Trading Rules 1
Rule 1: Regime Identification First 1
Rule 2: Do Not Short Persistent Bull 1
Rule 3: Do Not Buy Persistent Bear 1
Rule 4: Momentum Zone is Decision Zone 1
Rule 5: Watch the Divergence 1
5.4 Practical Examples 1
6. Backtest Strategy 1
6.1 Strategy Logic 1
6.2 Risk Management 1
6.3 Pine Script Strategy 1
6.4 Metrics to Evaluate 1
7. Limitations & Future Work 1
7.1 Known Limitations 1
7.2 Future Development 1
8. Appendix 1
8.1 Files Included 1
8.2 Version History 1
1. Executive Summary
The RSI-T (RSI with Time) is a technical indicator that extends the classic Wilder RSI by adding a third parameter: the duration of time price action remains in an extreme zone. While the standard RSI measures the magnitude of recent price changes, it fails to capture the persistence of momentum regimes. The RSI-T solves this by quantifying how long the RSI stays above or below threshold levels, providing traders with a tool that distinguishes between transient spikes and sustained directional moves.
The indicator is derived from the economic theory of markets as expanding systems, where price does not tend toward equilibrium but rather expands unevenly, creating zones of compression and expansion. The RSI-T operationalizes this concept by treating the time spent in extreme RSI territory as a measure of regime strength.
2. Theoretical Foundation
2.1 The Market as Expanding Dough
Traditional economic theory assumes markets tend toward equilibrium. The theory underlying RSI-T proposes an alternative model: the market behaves like expanding dough, where nominal prices continuously inflate, but the expansion is uneven across time and sectors. This creates regions of rapid expansion (bubbles, momentum regimes) and compression (consolidations, mean-reversion zones).
The three analytical layers of this model are:
• Geometry (Curvature): How price curves in space, measured through momentum and convexity. This corresponds to the RSI dimension of the indicator.
• Temperature (Volatility): The thermal energy of the market, measured through implied and realized volatility. This informs the threshold sensitivity.
• Cohesion (Liquidity): The structural integrity of price action, related to order flow and market microstructure. This provides context for regime classification.
2.2 Time as a Curvature Factor
The critical insight of RSI-T is that time spent at extremes is itself information. When the RSI remains above 70 for one bar, it may be a transient spike. When it remains above 70 for eight consecutive bars, the market has entered a different regime entirely. Standard RSI treats both situations identically. RSI-T does not.
In the dough metaphor, this corresponds to a region that is not just expanded, but has been expanding for a sustained period. The longer the expansion persists, the more the local structure of the market has reorganized around the new price level, and the less likely a simple mean-reversion is to occur.
This is consistent with empirical findings in momentum literature: assets that have been trending tend to continue trending, and the duration of the trend is a stronger predictor of continuation than the magnitude alone.
2.3 Regime Classification
The RSI-T framework classifies market states into distinct regimes based on the combination of RSI level and time at extreme:
Regime RSI Condition Time Condition
NEUTRAL Between oversold and overbought Counter = 0
MOMENTUM_BULL RSI > Overbought threshold 2 to N-1 bars
MOMENTUM_BEAR RSI < Oversold threshold 2 to N-1 bars
PERSISTENT_BULL RSI > Overbought threshold N or more bars
PERSISTENT_BEAR RSI < Oversold threshold N or more bars
Where N is the persistence threshold (default: 5 bars). In the persistent regimes, traditional mean-reversion signals (e.g., sell when RSI > 70) are weakened or inverted.
3. Mathematical Definition
3.1 Core Formula
The RSI-T value is calculated as:
RSI_T = clamp( RSI + (bars_at_extreme × time_weight × direction), 0, 100 )
Where:
• RSI = Standard Wilder RSI(close, period)
• bars_at_extreme = consecutive bars where RSI > threshold_OB or RSI < threshold_OS
• time_weight (α) = scaling factor per bar of persistence (default: 1.2)
• direction = +1 if RSI > threshold_OB, -1 if RSI < threshold_OS, 0 otherwise
• clamp() = constrains result to
3.2 Parameters
Parameter Default Range Description
period 14 5 – 50 RSI lookback period (Wilder smoothing)
threshold 70 / 30 55–90 / 10–45 Overbought / Oversold boundary
time_weight (α) 1.2 0.0 – 5.0 Signal boost per bar at extreme
max_boost 20 5 – 40 Maximum cumulative boost (cap)
persist_bars (N) 5 2 – 20 Bars required for persistent regime
3.3 Derived Metrics
• Divergence = RSI_T − RSI: Measures the total impact of the time parameter. When divergence is zero, RSI-T equals classic RSI. When divergence is large, the time dimension is providing significant additional information.
• Time Counter (bars_extreme): The raw number of consecutive bars spent above/below the threshold. This is the primary regime classifier.
• Regime Label: Categorical classification (NEUTRAL, MOMENTUM_BULL, MOMENTUM_BEAR, PERSISTENT_BULL, PERSISTENT_BEAR) derived from the combination of RSI level and time counter.
4. Timeframe Analysis
The RSI-T works across all timeframes, but its interpretation changes because the time counter has different weight depending on bar duration.
4.1 Timeframe Weight
Timeframe 1 Bar = 5 Bars (Persistent) = Interpretation
1 minute 1 minute 5 minutes Micro-momentum, scalping noise common
5 minutes 5 minutes 25 minutes Intraday momentum phases
15 minutes 15 minutes 1.25 hours Session-level regime shifts
1 hour 1 hour 5 hours Intraday trend confirmation
4 hours 4 hours 20 hours Multi-session directional bias
Daily 1 day 1 week Swing-level regime classification
Weekly 1 week 5 weeks (~1 month) Position-level trend strength
Monthly 1 month 5 months Macro regime identification
4.2 Recommended Settings by Timeframe
Timeframe Period Time Weight Persist Bars
1–5 min 14 0.5 – 0.8 8 – 12
15–60 min 14 0.8 – 1.2 5 – 8
4H / Daily 14 1.0 – 1.5 4 – 6
Weekly 14 1.5 – 2.0 3 – 5
Monthly 14 2.0 – 3.0 3 – 4
The general principle: shorter timeframes need more bars to confirm persistence (more noise to filter), while longer timeframes establish regimes faster because each bar carries more weight.
4.3 Multi-Timeframe Confluence
The highest-conviction signals occur when multiple timeframes agree. For example, if the daily RSI-T shows PERSISTENT_BULL and the weekly RSI-T enters MOMENTUM_BULL, this represents a multi-timeframe momentum alignment that significantly increases the probability of trend continuation.
Conversely, if the daily is in PERSISTENT_BULL but the weekly RSI-T is declining from a recent extreme, this divergence between timeframes suggests the persistent regime may be nearing exhaustion.
5. User Guide
5.1 Installation (PulseWire)
1. Open PulseWire and navigate to the chart of your chosen instrument.
2. Click Pine Editor at the bottom of the screen.
3. Click New and select New indicator.
4. Delete all existing code and paste the RSI-T Pine Script (v6) code.
5. Click Add to chart. The RSI-T panel appears below the price chart.
6. Adjust parameters via the Settings gear icon on the indicator.
5.2 Reading the Indicator
Blue line: Classic RSI. This is the baseline reference.
Orange/Red line: RSI-T. When this diverges from the blue line, the time parameter is active and providing additional information.
Histogram (bottom): Scaled time counter showing the number of bars spent at the extreme zone.
Green background: Persistent bull regime. The RSI has been above the overbought threshold for N or more bars.
Red/orange background: Persistent bear regime (red) or momentum bear/bull (orange/blue).
Blue background: Momentum bull. RSI above overbought for 2 to N-1 bars. Early-stage momentum zone.
5.3 Trading Rules
Rule 1: Regime Identification First
Before making any trading decision, identify the current regime from the background color. In NEUTRAL regime, traditional RSI-based mean-reversion strategies apply normally. In MOMENTUM or PERSISTENT regimes, mean-reversion signals are weakened or inverted.
Rule 2: Do Not Short Persistent Bull
When the RSI-T shows persistent bull (green background), do not initiate short positions based on overbought readings. The persistence signal indicates that the market has reorganized around the uptrend and further upside is more likely than immediate reversal. Wait for the regime to reset (counter returns to zero) before considering mean-reversion trades.
Rule 3: Do Not Buy Persistent Bear
The inverse of Rule 2. When persistent bear is active (red background), do not buy dips based on oversold readings. The selling pressure has established itself as a regime, not a transient condition.
Rule 4: Momentum Zone is Decision Zone
The blue/orange background (momentum zone, 2 to N-1 bars) is where decisions are made. This is the transitional phase where the market is testing whether it will establish a persistent regime or revert. Tighter stops and smaller positions are appropriate here.
Rule 5: Watch the Divergence
When RSI-T diverges significantly from classic RSI (large divergence value), the time dimension is dominating. A sudden collapse of this divergence (counter drops to zero) often precedes sharp reversals, as the accumulated time pressure releases.
5.4 Practical Examples
Scenario RSI-T Reading Action
RSI at 75, counter = 1 Momentum bull (blue bg) Standard caution, normal position sizing
RSI at 75, counter = 7 Persistent bull (green bg) Do NOT short. Trailing stop on existing longs
RSI at 42, counter = 0 Neutral Normal analysis applies. No regime signal
RSI at 25, counter = 6 Persistent bear (red bg) Do NOT buy dips. Wait for regime exit
RSI at 72, counter drops from 5 to 0 Regime exit Alert: potential reversal. Tighten stops
6. Backtest Strategy
6.1 Strategy Logic
The RSI-T Strategy for backtesting converts the indicator into actionable entries and exits. The core logic uses regime transitions as signals:
Long Entry:
• RSI-T crosses above the overbought threshold AND the time counter reaches the momentum threshold (2 bars), confirming directional commitment.
• Alternative: Enter when the regime transitions from NEUTRAL to MOMENTUM_BULL (catching the early phase of a potential persistent move).
Long Exit:
• The time counter resets to zero after being in persistent bull (regime exit signal).
• Alternative: RSI-T crosses below the midline (50) from above.
Short Entry:
• RSI-T crosses below the oversold threshold AND the time counter reaches the momentum threshold.
Short Exit:
• Time counter resets to zero after persistent bear, or RSI-T crosses above midline.
6.2 Risk Management
• Position size: 10% of equity per trade (adjustable in strategy settings).
• Stop loss: Based on ATR multiplier (default 2x ATR-14) to account for regime volatility.
• Trailing stop: Activates once position reaches 1.5x risk in profit.
• No pyramiding by default (can be enabled for persistent regime continuation).
6.3 Pine Script Strategy
A complete Pine Script v6 strategy file (rsi_t_strategy_v6.pine) is provided alongside this document. The strategy includes configurable parameters for entry/exit rules, position sizing, stop-loss, and trailing stop. It can be applied to any instrument and timeframe in PulseWire for historical backtesting.
6.4 Metrics to Evaluate
When backtesting the RSI-T strategy, focus on the following metrics to validate the theoretical framework:
• Win Rate in Persistent vs. Momentum vs. Neutral regimes (the theory predicts higher win rates in persistent regimes for trend-following entries).
• Average trade duration across regimes (persistent regime trades should be longer and more profitable).
• False signal rate: How often does momentum (blue background) fail to convert to persistent (green background)?
• Regime exit accuracy: What percentage of regime exits (counter reset) are followed by actual reversals within N bars?
• Comparison vs. classic RSI strategy (same entry rules without the time parameter) to isolate the value added by the time dimension.
7. Limitations & Future Work
7.1 Known Limitations
• The RSI-T is a lagging indicator by nature. The time counter requires bars to accumulate before signaling persistence, meaning the earliest phase of a move is not captured.
• In choppy or range-bound markets, the counter may produce false starts, briefly entering momentum zone before resetting. The persist_bars threshold helps filter these but cannot eliminate them entirely.
• The linear time_weight model (each bar adds the same boost) may not be optimal. Markets may exhibit non-linear acceleration, where the 10th bar at extreme is more significant than the 3rd.
• The indicator does not incorporate volume, volatility, or cross-asset information. It is purely price-derived.
7.2 Future Development
• Non-linear time weighting: Exponential or logarithmic boost curves that better reflect the accelerating nature of regime establishment.
• Volatility-adjusted thresholds: Dynamic overbought/oversold levels that adjust based on current implied volatility (high-vol environments may require wider thresholds).
• Fast/Slow RSI divergence: Comparing RSI-T across different periods (e.g., RSI-T(7) vs RSI-T(21)) to measure regime acceleration, as described in the original theory.
• Cross-asset regime correlation: Using the RSI-T regime of correlated assets (e.g., SPX for individual stocks) as a confirmation layer.
• Machine learning optimization: Using historical data to optimize time_weight and persist_bars parameters per asset class and market regime.
8. Appendix
8.1 Files Included
File Description
rsi_t_v6.pine RSI-T indicator for PulseWire (Pine Script v6)
rsi_t_strategy_v6.pine RSI-T backtest strategy for PulseWire (Pine Script v6)
rsi_t_indicator.py RSI-T Python implementation for custom backtesting
8.2 Version History
Version Date Changes
1.0 May 2026 Initial release: RSI-T indicator, strategy, white paper
Copyright © 2026 Dimitrios Kataliakos. All rights reserved.
This document and the associated indicator code are proprietary work based on the original theory of markets as expanding systems.
Indicator
SOL RSI DCA - Long IndicatorSOL RSI DCA - Long Indicator
🔷 What it does:
This is a signal-only indicator that mirrors a long-only DCA workflow on SOL. It tracks one virtual long position at a time, opened while higher-timeframe momentum is depressed, then averages the position down on a measured geometric price-deviation ladder with up to three averaging orders. The base entry arms whenever the 1-hour RSI(14) sits below a configurable level (default 44). Averaging is price-driven only — no extra momentum gate — matching the source bot configuration. Exit is a fixed Take Profit at 2.4% above average entry. Every event emits a webhook-ready JSON payload for a DCA Bot.
- HTF RSI entry gate: base order arms while 1h RSI(14) is below the threshold (Less Than condition).
- Geometric averaging ladder: deviations −2.50%, −5.75%, −9.98%; sizes 87.5, 109.4, 136.7 USDT on a 1.3× deviation step × 1.25× size step.
- Fixed Take Profit: 2.4% above running average entry, no trailing.
- Honest virtual bookkeeping: total cost and qty updated incrementally on every fill — avg entry, deployed capital, open PnL, and cumulative realized PnL displayed live.
- Five discrete events per cycle (entry + 3 AO fills + TP), each with its own webhook payload.
🔷 Who is it for:
- Swing traders running a DCA Bot on SOL who want systematic long exposure when momentum is soft, scaling in if the dip deepens.
- Bot operators who want a chart-driven signal source that emits per-event JSON ready for a DCA Bot.
- DCA-style traders who prefer a measured geometric ladder over an aggressive doubling schedule.
- Traders who want to monitor an evolving DCA position — base entry, owned AO levels, deployed capital, open PnL, realized PnL, live RSI reading — directly on the chart without the strategy-tester overhead.
🔷 How does it work:
Entry RSI Filter (HTF Oversold): A 1-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The base order arms whenever this RSI is below the configured level (default 44). At host-bar close, if the indicator is flat, the virtual long position opens.
Averaging Order Ladder (Price-Driven): After the base fill, the indicator watches price deviation against the position. The k-th averaging order fires when close ≤ base entry × (1 − cumulative deviation). Cumulative deviation grows by the 1.3× step multiplier: 2.50%, 5.75%, 9.98%. Each averaging order's virtual size grows by the 1.25× size multiplier: 87.5, 109.4, 136.7 USDT. Averaging is gated by price only — no extra RSI condition, matching the source bot configuration.
Honest Virtual Bookkeeping: Total cost and qty are updated incrementally on every fill, so the avg entry, deployed capital, open PnL, and cumulative realized PnL displayed in the status table reflect the actual broker-equivalent position state — no shortcut from base entry, no synthetic averaging.
Exit: A fixed Take Profit at 2.4% above the running average entry. When close hits the TP target, the close webhook fires, the realized PnL accumulator banks the gain, and the virtual position resets.
🔷 Why it's unique:
- HTF RSI Entry Gate: The base order keys off a 1-hour RSI(14) rather than the chart timeframe, so entries are anchored to the higher-timeframe momentum picture instead of intrabar noise.
- Measured Geometric Ladder: A 1.3× deviation step paired with a 1.25× size step keeps the average entry compounding controlled — the position deepens gradually rather than ballooning, which keeps maximum deployment near 5% of equity.
- Fill-by-Fill Avg Entry: The orange avg-entry line is derived from running totals updated on every event — what you see is what the broker-equivalent position would actually have.
- Realized PnL Readout: The status table shows cumulative realized PnL banked across closed cycles, so the chart reflects how the workflow has performed over the visible history, not just the open position.
- Per-Event Webhook Ledger: Five distinct events per cycle, each with its own JSON alert payload. The indicator drives a DCA Bot end-to-end through a single PulseWire alert.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Designed for liquid crypto pairs. Default thresholds are calibrated for BINANCE:SOLUSDT spot, with the RSI filter on 1h. Run on a 1h chart (or lower for finer averaging-order fills). Different pairs may need RSI level and deviation ladder tuning.
Entry Is a Level, Not a Cross: The base order uses a Less Than condition (RSI < 44), matching the source bot. After a Take Profit, if RSI is still below 44 the indicator can immediately reopen a new virtual deal. This produces more frequent re-entries than a cross-down trigger — intended behavior, but review it against your risk appetite.
Cross Detection Granularity: Entries and AO fills are evaluated on bar close. A bar that spikes through a level and returns within the same bar may be missed by design — this matches realistic polling behavior and avoids over-signaling on intra-bar wicks.
Live vs Historical State: The virtual position state is rebuilt from chart history each time the indicator is recompiled. If the indicator is added mid-deployment or the live bot diverges from the signal stream (manual interventions, partial fills), the indicator state may not match the live bot. Toggle the indicator off and on to reset.
Capital Deployment: If all three averaging orders fill, the virtual position scales from 200 USDT base to ~534 USDT total. Match the indicator's per-order allocation to your bot's configuration to keep the avg-entry display honest.
No Stop Loss: There is no exit signal on adverse moves beyond the 3-AO ladder. Risk is structurally capped on the bot side by the bounded position-size ladder. If a hard exchange-side stop is required, configure it on the bot directly.
Strong Downtrends: Like any dip-buying setup, this is positioned for mean reversions, not waterfall declines. In a sustained downtrend the ladder fills out and the position holds underwater until price recovers to the 2.4% TP above average. The bounded ladder limits the size of that exposure, but underwater hold time can still extend.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester. For performance metrics over a ~3.5-month sample (29 closed trades, 86.21% win rate, 0.63% max drawdown, profit factor 22.256, +0.83% net return), use the companion strategy version on identical parameters. The 29-trade sample is well below the typical ≥100 floor for statistical confidence, and the high-win/low-frequency profile rests on a fixed 2.4% TP being hit most of the time — re-run on a 12+ month window for a more robust validation before drawing firm conclusions.
🔷 How to Use It:
🔸 Add the indicator to a 1h chart on the crypto pair you want to trade.
🔸 Review the entry RSI filter (timeframe / length / level), the 3-AO ladder parameters, and the Take Profit percentage. Defaults are calibrated for SOLUSDT 1h — recalibrate per asset before deploying.
🔸 Set Base Order Size and AO sizes to match your bot's configuration (the indicator's avg-entry display becomes meaningful when virtual sizing matches real sizing).
🔸 In the DCA Bot Webhook group, paste the Bot ID, Email Token, and Pair (QUOTE_BASE format, e.g., USDT_SOL).
🔸 Create an alert on the indicator with "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field. The indicator will emit JSON payloads for entry, each averaging order, and TP exit — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): Virtual order size for the avg-entry / open-PnL computation.
Averaging Orders per Trade: Maximum number of averaging orders per cycle (default 3).
First AO Size (USDT): Virtual size of the first averaging order; subsequent AOs scale by the Size Multiplier.
Deviation to First AO (%): Distance from base entry at which AO1 becomes eligible.
Deviation Step Multiplier: Ladder factor that widens each subsequent deviation step.
Order Size Multiplier: Factor that grows each subsequent averaging order's USDT size.
Entry RSI Timeframe / Length / Level: Higher-timeframe RSI filter that arms the base entry (Less Than condition).
Take Profit (%): Fixed distance above the running average entry where the virtual long closes.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle AO Ladder, Avg / TP plot lines, fill labels, signal triangles, status table (including cumulative realized PnL).
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Indicator
Machine Learning RSI | AI Classification & Ranking (Zeiierman)█ Overview
The Machine Learning RSI | AI Classification & Ranking (Zeiierman) is an adaptive RSI intelligence system that combines momentum analysis, historical analog recognition, machine learning classification, confidence scoring, and dynamic trend management into a single framework.
Rather than interpreting RSI solely through traditional overbought and oversold thresholds, the indicator examines how similar RSI environments have behaved historically and uses those observations to classify current market conditions.
The script transforms RSI into a multi-dimensional feature space, stores historical market behavior, identifies the closest historical analogs, and allows those analogs to vote on future directional bias.
An adaptive feature-optimization engine then continuously learns which RSI characteristics provide the greatest predictive value under current market conditions.
The result is a hybrid system that blends:
• Multi-dimensional RSI analysis
• Historical analog matching
• Machine learning classification
• Adaptive feature weighting
• Rank & confidence scoring
• AI-driven trend management
█ Why is this one unique
This is not a normal RSI. It is a full analog classification engine built in Pine Script v6. It turns RSI behavior into an 8-feature market fingerprint, stores historical examples, labels them by future outcome, finds the closest past situations, lets those analogs vote, then converts the result into an adaptive ML RSI, rank/confidence scores, signals, and an ML-modulated Supertrend.
⚪ What it does
At a high level:
1. Builds 8 RSI-derived features
It does not only use the RSI value. It models:
RSI level, slope, acceleration, distance from 50, percentile rank, RSI volatility, fast/slow RSI spread, and smoothed RSI regime.
That means each bar becomes a multi-dimensional “state” of momentum, not just “RSI is 63.”
2. Creates a memory bank
Each confirmed bar is stored with its feature snapshot and a future outcome label. The label is based on whether price moved up or down after a fixed horizon, scaled by ATR. That is the learning dataset.
3. Uses K-nearest-neighbor analog matching
For the current bar, the script scans the historical bank and finds the closest past examples. It uses a Lorentzian-style compressed distance:
log(1 + abs(feature difference))
That is good because it reduces the impact of outliers. Huge feature mismatches do not completely dominate the model.
4. Lets analogs vote
Nearest neighbors vote bull or bear, weighted by distance. Closer matches matter more. The output becomes: analogScore, bias direction, agreement fraction, and gap tightness.
5. Auto-optimizes feature weights
This is one of the most sophisticated parts. The script uses a Fisher-discriminant-style calculation to determine which RSI features currently best separate bullish vs. bearish outcomes. Then it rescales those weights and smooths them over time.
So the model can learn that, for example, RSI slope matters more on one instrument, while RSI percentile or regime matters more on another.
6. Builds rank and confidence
Signals are not triggered just because the model flips bullish or bearish. They must pass a quality system:
Rank blends agreement, distance tightness, trend alignment, volatility health, regime fit, slope fit, smoothness, persistence, and penalties for chop or early flips.
Confidence focuses more on analog agreement, tightness, persistence, and slope fit.
This is much better than a simple buy/sell oscillator because it asks: “Is this setup actually supported?”
7. Adds adaptive Supertrend
The Supertrend is not static. Its band width changes based on ML conviction. High conviction tightens the trailing stop. Low conviction or chop widens it. That makes the trend system responsive without being blindly reactive.
⚪ Why it is good
The strongest part is that it combines machine learning logic, technical architecture, and trade-quality filtering into a single system.
Most PulseWire indicators are fixed formulas: RSI crosses 30, MACD crosses, Supertrend flips, moving average slope changes. This code differs because it creates a small local learning model directly in Pine.
The unique edge is the combination of:
• Feature engineering: RSI is transformed into 8 separate behavioral dimensions.
• Historical analog learning: Current market conditions are compared to past similar conditions.
• Distance-weighted voting: Closer historical examples have more influence.
• Auto feature weighting: The system adapts which features matter most.
• ATR-based outcome labeling: Learning is normalized by volatility, not just raw price movement.
• Quality scoring: Signals require both rank and confidence.
• Adaptive trend logic: The ML engine not only generates oscillator signals but also modifies Supertrend behavior.
That combination is rare in Pine Script. PulseWire supports advanced data structures such as arrays, matrices, and user-defined types, but many public scripts still use simpler procedural indicator logic. This script uses those advanced structures as a true modeling framework.
⚪ What makes it sophisticated
The code actually implements an AI-style classification workflow:
Input features → labeled memory → nearest-neighbor search → weighted classification → confidence scoring → adaptive output.
That is a real machine-learning pattern.
But this script goes further than a basic KNN signal tool because it adds:
• Auto-optimized feature weights using class separation.
• Rank/confidence gates instead of raw prediction signals.
• Chop, volatility, and trend filters to reduce bad market conditions.
• ML-driven Supertrend adaptivity rather than using ML only for arrows.
• Non-repainting signal discipline by firing on confirmed bars only.
⚪ Why It’s Marketable
Most RSI indicators treat every reading the same. This tool takes a different approach by analyzing how similar RSI conditions performed in the past and evaluating the current setup against those historical patterns. It only generates signals when multiple factors align, including confidence, trend direction, volatility, and market structure.
What makes it valuable is that it transforms RSI from a simple momentum oscillator into a context-aware decision framework. Rather than reacting to fixed overbought and oversold levels, it identifies recurring market behaviors, measures the similarity of current conditions to historical examples, and assigns a quality score to each opportunity. It then filters out low-probability environments and dynamically adjusts its trend management based on the strength of the model's conviction.
The result is a more selective, adaptive, and intelligent signal engine that helps traders focus on higher-quality setups instead of every RSI fluctuation. This moves well beyond the capabilities of a conventional PulseWire RSI indicator.
⚪ Main weakness
It is not deep learning, and it does not train a neural network. It is an online analog classifier. That is still legitimate AI-style logic. Also, because it learns from historical analogs inside the chart, performance depends heavily on market regime, symbol, timeframe, memory depth, and filters.
█ How It Works
⚪ Machine Learning Feature Engine
Most RSI indicators analyze a single value.
The Machine Learning RSI transforms RSI into a complete momentum fingerprint, consisting of eight independent characteristics that describe how momentum behaves beneath the surface.
The model analyzes:
• RSI Value
• RSI Slope
• RSI Acceleration
• Distance From Neutral (50)
• RSI Percentile Rank
• RSI Volatility
• Fast vs Slow RSI Spread
• RSI Regime Structure
Features cur = Features.new(
rOsc / 100.0,
scale01(rOsc - rOsc , winLen),
scale01(rOsc - rOsc -
(rOsc - rOsc ), winLen),
math.abs(rOsc - 50.0) / 50.0,
ta.percentrank(rOsc, winLen) / 100.0,
scale01(ta.stdev(rOsc, 14), winLen),
scale01(rOscF - rOscS, winLen),
scale01(ta.ema(rOsc, 20) - 50.0, winLen)
)
Together these features create a much richer representation of market behavior than traditional RSI calculations.
Instead of asking:
“Where is RSI?”
The model asks:
“What type of momentum behavior is currently occurring?”
⚪ Historical Analog Memory
The indicator continuously builds a memory bank of historical market behavior.
Every confirmed bar is stored together with its RSI fingerprint and the future outcome that followed.
row = array.from(
fVal, fSlp, fAcc, fMid,
fPct, fChn, fSpr, fReg,
float(outcome)
)
bank.add_row(0, row)
Over time the model accumulates hundreds or even thousands of historical observations.
Each observation becomes a real market example the system can reference later.
Rather than relying entirely on fixed formulas, the indicator learns from historical market behavior.
⚪ AI Classification Engine
Once the memory bank has been built, the Machine Learning RSI begins searching for historical situations that closely resemble the current market.
The comparison is performed across all eight RSI features simultaneously.
g = cur.gapTo(row, wts)
Similarity is measured using a weighted Lorentzian distance function.
compress(float d) =>
math.log(1.0 + math.abs(d))
Unlike traditional distance calculations, logarithmic compression reduces the influence of extreme outliers and prevents a single feature from dominating the comparison process.
This creates a more stable and robust analog matching system.
The objective is not to find identical charts.
The objective is to find historical momentum environments that behaved similarly.
⚪ Historical Analog Voting
After locating the closest historical matches, the system allows them to vote on the current market direction.
Closer analogs receive greater influence while weaker matches contribute less.
float w = 1.0 / (1.0 + n.gap)
v.score := v.score + n.cls * w
The weighted votes are combined into a final classification score.
eng.analogScore :=
vote.total > 0
? vote.score / vote.total
: 0.0
This process produces:
• Directional Bias
• Analog Agreement
• Classification Strength
• Similarity Quality
• Market Conviction
Rather than attempting to predict the future directly, the model asks:
“How did the most similar momentum environments behave when they occurred previously?”
⚪ Adaptive Feature Optimizer
Markets are constantly changing.
Features that are highly predictive in one environment may become less useful in another.
To solve this problem, the Machine Learning RSI includes an adaptive feature optimization engine.
The model continuously evaluates which RSI characteristics are doing the best job separating bullish outcomes from bearish outcomes.
float f =
math.pow(mB - mBe, 2)
/
(vB + vBe + 1e-6)
This process is based on Fisher Discriminant Analysis.
Features that consistently separate winning conditions from losing conditions receive larger weights.
Features that lose predictive power gradually receive less influence.
wts.value := wAuto.get(0)
wts.slope := wAuto.get(1)
wts.accel := wAuto.get(2)
wts.mid := wAuto.get(3)
This allows the model to adapt automatically to changing market conditions without requiring constant manual optimization.
⚪ Rank & Confidence Engine
Most indicators generate signals immediately after a condition is met.
The Machine Learning RSI goes several steps further. Every setup receives two independent evaluations.
• Rank → Measures setup quality.
• Confidence → Measures model conviction.
Rank evaluates:
• Historical agreement
• Analog quality
• Trend alignment
• Volatility conditions
• Regime structure
• Momentum consistency
• Market stability
Confidence evaluates:
• Historical consensus
• Analog clustering
• Directional consistency
• Signal persistence
• Structural confirmation
setup.rank := rankScore(…)
setup.conf := confScore(…)
Signals are only generated once both quality and confidence requirements have been satisfied.
This helps filter weaker market conditions while prioritizing stronger opportunities.
⚪ AI-Driven Learning System
The Machine Learning RSI does not simply memorize historical outcomes.
It learns what constitutes a meaningful outcome.
Each historical observation is classified based on future movement relative to current volatility.
outcome =
moveFwd > 2 * bandFwd ? 3 :
moveFwd > bandFwd ? 2 :
moveFwd > 0 ? 1 :
moveFwd < -2 * bandFwd ? -3 :
moveFwd < -bandFwd ? -2 :
moveFwd < 0 ? -1 : 0
• Large bullish moves receive stronger bullish labels.
• Large bearish moves receive stronger bearish labels.
• Small movements receive weaker classifications.
This allows the model to distinguish meaningful market behavior from ordinary noise.
⚪ ML Supertrend System
The indicator includes an adaptive Machine Learning Supertrend that responds to model conviction.
Unlike traditional Supertrends that rely on a fixed ATR multiplier, the ML Supertrend dynamically adjusts its sensitivity based on classification strength.
mlDrive =
math.abs(convSmoothed) * 0.5 +
eng.gapTight * 0.3 +
eng.agreeFrac * 0.2
As conviction increases:
• Bands tighten
• Trend changes become faster
• Stops become more responsive
As conviction decreases:
• Bands widen
• Noise tolerance increases
• Whipsaws are reduced
adaptMult =
stMultBase *
(1.0 + stMlResp * (1.0 - mlDrive))
This creates a trend-following system that adapts to the strength of the model’s conviction rather than relying solely on volatility.
█ How To Use
⚪ Reading The ML RSI
The Machine Learning RSI ranges from 0 to 100.
• Values above 50 suggest bullish momentum conditions dominate the market.
• Values below 50 suggest bearish momentum conditions dominate the market.
• Readings above 70 typically indicate strong bullish conditions, while readings below 30 suggest strong bearish pressure.
⚪ Reading The Signals
The Machine Learning RSI generates signals when the model detects a meaningful shift in market conditions and that shift passes both its quality and confidence requirements.
• Long signals indicate that the classification engine has identified a bullish market environment supported by historical analog agreement, trend structure, and market conditions.
• Short signals indicate that the classification engine has identified a bearish market environment supported by historical analog agreement, trend structure, and market conditions.
⚪ Using The ML Supertrend
The ML Supertrend acts as both a trend filter and a dynamic trailing stop.
• When the Supertrend flips bullish, the model considers the market to be operating in an uptrend regime.
• When the Supertrend flips bearish, the model considers the market to be operating in a downtrend regime.
█ Settings
Price Source: controls the price data used to build every RSI feature inside the learning engine.
Base RSI Length: controls the main RSI period used to create the ML RSI and its feature set.
Memory Depth: controls how many historical bars the model stores and searches when looking for similar market conditions.
Analog Count (k): controls how many closest historical matches are allowed to vote on the current market direction.
Show Signal Markers: toggles the Long and Short signal markers on the chart.
Candle Coloring: colors candles based on the current ML Supertrend regime.
Min Rank to Signal: controls the minimum setup-quality score required before a signal can appear.
Min Confidence to Signal: controls the minimum model conviction required before a signal can appear.
Trend Gate: requires signals to align with the ML Supertrend direction.
Volatility Band: filters signals so they only appear in healthier volatility conditions.
Min Vol Rank: controls the lower volatility threshold required for signals.
Chop Filter: blocks signals during choppy, range-bound market conditions.
Learning Sensitivity: controls how large a future move must be before the model treats it as a meaningful historical outcome.
Auto-Optimize Weights: allows the model to automatically learn which RSI features are most important.
Adaptation Speed: controls how quickly the learned feature weights adjust to changing market behavior.
Feature Weights: manually control the importance of each RSI feature when Auto-Optimize Weights is disabled.
Show ML Supertrend: toggles the adaptive ML Supertrend line, cloud, and trend visuals.
Supertrend Source: controls the price source used to build the ML Supertrend bands.
ATR Multiplier: controls the base distance of the ML Supertrend from price.
ML Band Adaptivity: controls how strongly model conviction adjusts the Supertrend band width.
RSI Signal Line Type: selects the moving average style displayed on the ML RSI.
RSI Signal Line Length: controls the smoothing length of the RSI signal line.
BB StdDev: controls the Bollinger Band width when using SMA + Bollinger Bands.
Colors: customize signal markers, candle coloring, ML RSI colors, Supertrend colors, cloud colors, and signal line visuals.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
SOL RSI DCA - Long StrategySOL RSI DCA - Long Strategy
🔷 What it does:
This is a long-only DCA strategy that opens a base long while SOL's higher-timeframe momentum is depressed, then averages down on a geometric price-deviation ladder if the dip extends. A long entry arms whenever the 1-hour RSI(14) sits below a configurable level (default 44). Up to three averaging orders ladder the position deeper on widening deviation steps and growing order sizes. Exit is a fixed Take Profit from the running average entry. No trailing, no Stop Loss.
- Single base order with up to three averaging orders on a geometric deviation × geometric size ladder.
- HTF RSI entry gate: base order arms while 1h RSI(14) is below the threshold (Less Than condition).
- Deviation ladder grows by a 1.3× step multiplier; order sizes grow by a 1.25× size multiplier.
- Fixed Take Profit: 2.4% above average entry, no trailing.
- Every entry, averaging order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
🔷 Who is it for:
- Swing traders who want systematic long exposure on SOL when momentum is soft, scaling in if the dip deepens.
- DCA-style traders who prefer a measured geometric ladder over an aggressive doubling schedule.
- Bot operators who want to drive a DCA Bot via webhook with per-event JSON payloads tagged for each base / averaging order / exit action.
- Range and mean-reversion traders comfortable with a moderate per-trade capital footprint (~5% of equity at default settings).
🔷 How does it work:
Entry RSI Filter (HTF Oversold): A 1-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The base order arms whenever this RSI is below the configured level (default 44). At host-bar close, if no position is open, the strategy opens the base order at market.
Base Order: Sized at 200 USDT default (2% of 10k capital). Configurable as Market (default) or Limit at the bar's close.
Averaging Order Ladder (Price-Driven): After the base fill, the strategy watches price deviation against the position. The k-th averaging order fires when close ≤ base entry × (1 − cumulative deviation). Cumulative deviation grows by the 1.3× step multiplier: 2.50%, 5.75%, 9.98%. Each averaging order's size grows by the 1.25× size multiplier: 87.5, 109.4, 136.7 USDT. Averaging is gated by price only — no extra RSI condition, matching the source bot configuration.
Exit: A fixed Take Profit at 2.4% above the running average entry. The strategy closes the moment close ≥ TP target. No trailing, no scaling out.
🔷 Why it's unique:
- HTF RSI Entry Gate: The base order keys off a 1-hour RSI(14) rather than the chart timeframe, so entries are anchored to the higher-timeframe momentum picture instead of intrabar noise.
- Measured Geometric Ladder: A 1.3× deviation step paired with a 1.25× size step keeps the average entry compounding controlled — the position deepens gradually rather than ballooning, which keeps maximum deployment near 5% of equity.
- Honest Position Bookkeeping: The avg-entry line, TP line, and status table all reflect the actual broker-equivalent position state derived from fill-by-fill order tracking — no synthetic averaging.
- DCA Bot Integration: Every event (base, AO 1–3, exit) emits a fully-formed JSON alert payload. Connect one alert to a DCA Bot's webhook URL and the strategy drives the bot end-to-end without any glue layer.
🔷 Considerations Before Using the Strategy:
Market & Timeframe: Defaults are calibrated for BINANCE:SOLUSDT spot, with the RSI filter on 1h. Run the strategy on a 1h chart (or lower for finer averaging-order fills). The logic is portable to other liquid pairs, but the RSI level and the deviation ladder should be reviewed before redeployment.
Entry Is a Level, Not a Cross: The base order uses a Less Than condition (RSI < 44), matching the source bot. This means after a Take Profit, if RSI is still below 44 the strategy can immediately reopen a new deal. This produces more frequent re-entries than a cross-down trigger — intended behavior, but review it against your risk appetite.
Capital Deployment: If all three averaging orders fill, the position scales from 200 USDT base to ~534 USDT total ≈ 5.3% of equity at default settings — comfortably inside PulseWire's 5–10% per-trade band. Scale base + AO sizes down to dial position risk lower.
No Stop Loss Justification: There is no exit on adverse moves beyond the 3-AO ladder. Per-trade risk is structurally capped by the bounded position-size ladder — at defaults that is ~534 USDT max deployed ≈ 5.3% of equity, well inside the conventional 5–10% per-trade band. If a hard exchange-side stop is required, layer it on the bot directly.
Strong Downtrends: Like any dip-buying setup, this strategy is positioned for mean reversions, not waterfall declines. In a sustained downtrend the ladder fills out and the position holds underwater until price recovers to the 2.4% TP above average. The bounded ladder limits the size of that exposure, but underwater hold time can still extend.
Commission Calibration: The default 0.1% commission matches Binance spot taker conditions. Update the commission input to match your fee tier for accurate forward expectations.
Sample Size: The ~3.5-month backtest produced 29 closed trades — below the ≥100 floor typically used for statistical confidence. The 86.21% win rate and the very high 22.256 profit factor are encouraging but rest on a small sample and a high-win/low-frequency profile (a fixed 2.4% TP that is hit most of the time). Extend the test window to 12+ months and re-validate before drawing firm conclusions or deploying live.
Demo Testing: Always demo-test before going live. Past results do not guarantee future performance.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:SOLUSDT (Spot)
Timeframe: 1H (recommended; RSI filter sampled on 1h).
Test Period: February 16, 2026 — June 1, 2026 (~3.5 months).
Initial Capital: 10,000 USDT.
Order Size per Trade: 2% of Capital base + 3 averaging orders on a 1.25× size ladder.
Max Capital Deployed: ~534 USDT per trade (~5.3% of equity).
Commission: 0.1% per trade.
Slippage: 3 ticks.
Margin for Long Positions: 100%.
Indicator Settings: Default Configuration.
Base Order: 200 USDT, Market by default (Limit toggle available).
Take Profit: 2.4% above average entry (no trailing).
Stop Loss: None — bounded position size is the structural risk cap.
Entry Filter: 1h RSI(14) Less Than 44.
Averaging Orders: 3, Deviation 2.5%, Deviation Step 1.3×, Size Multiplier 1.25× (cumulative −2.5% / −5.75% / −9.98%).
Strategy: Long Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +82.90 USDT (+0.83%)
Max Equity Drawdown: 63.27 USDT (0.63%)
Total Closed Trades: 29
Percent Profitable: 86.21% (25 / 29)
Profit Factor: 22.256
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, the entry RSI filter (timeframe / length / level), the 3-AO ladder parameters, and the Take Profit percentage. Defaults are calibrated for SOLUSDT on 1h — recalibrate per asset before deploying.
🔸 Results Review: Run a full-period backtest and confirm Max Drawdown stays inside your personal risk band. Validate that the closed-trade count is statistically meaningful (≥ 100 is a reasonable floor; extend the test window if needed). Update commission and slippage to match your exchange's actual conditions.
🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The strategy will emit JSON payloads for entry, each averaging order, and exit — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): USDT amount opened on the long entry.
Use LIMIT for Base: Toggle between Market (default) and Limit at bar close.
Averaging Orders per Trade: Maximum number of averaging orders per deal (default 3).
First AO Size (USDT): USDT size of the first averaging order; subsequent AOs scale by the Size Multiplier.
Deviation to First AO (%): Distance from base entry at which AO1 becomes eligible.
Deviation Step Multiplier: Ladder factor that widens each subsequent deviation step.
Order Size Multiplier: Factor that grows each subsequent averaging order's USDT size.
Entry RSI Timeframe / Length / Level: Higher-timeframe RSI filter that arms the base entry (Less Than condition).
Take Profit (%): Fixed distance above average entry where the long closes for profit.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle AO Ladder, Avg / TP plot lines, fill labels, status table.
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Strategy
Indicator
Hamppu - Flow EngineHamppu - Flow Engine is an open-source crypto intraday context engine built in Pine Script v6.
It is designed to help read market context, not to provide standalone buy/sell signals.
The script combines multi-layer RSI regime logic, RSI compression/release, WaveTrend-style stretch reclaim/reject context, liquidity sweep quality scoring, displacement after sweep, HTF with-flow / counter-flow classification and a dynamic MTF Flow Stack.
The goal is transparency. Markers are not magic signals. They are context events that help show when momentum, liquidity and higher-timeframe flow may be interacting.
Core features:
- Multi-layer RSI momentum regime
- RSI compression and directional release
- WaveTrend-style stretch reclaim/reject context
- Liquidity sweep quality scoring
- Displacement after sweep
- HTF with-flow / counter-flow classification
- MTF Flow Stack with selectable 3–6 timeframe slots
- Curated profiles: Balanced, Degen Fast, Conservative, Research and Custom
- Optional source labels for studying RSI / WaveTrend / Degen Fast marker sources
Visual language:
- Background color shows local RSI regime.
- Marker color shows HTF alignment.
- MTF Flow Stack shows broader multi-timeframe momentum context.
Marker guide:
- Triangle = early momentum reclaim/reject context
- Circle = momentum release after RSI compression
- X = compression release / compression ended
- Heart = Flow Context: sweep + displacement + momentum
- Orange marker = counter-flow / HTF disagreement
Profiles:
Balanced is the default public profile.
Degen Fast is a faster 5m/15m profile with early reclaim behavior.
Conservative is stricter and produces fewer context events.
Research is a looser exploration profile.
Custom is for manual tuning.
Important:
Balanced, Degen Fast, Conservative and Research are curated presets. These presets may override selected sensitivity controls internally, including sweep thresholds, cooldowns, compression tightness and confirmed/live behavior.
Use Profile = Custom if you want manual control over the visible sensitivity inputs.
Suggested workflow:
1. Start with Balanced.
2. Read the background regime first.
3. Check marker color for HTF alignment.
4. Use the MTF Flow Stack to understand broader context.
5. Treat markers as context events, not automatic entries.
6. Use your own price action, risk management and invalidation.
Alerts:
Alerts focus on main context events and with-flow reclaim/reject events. Not every visual marker has a separate alert. For more stable alerts, use bar-close alert settings.
Stability note:
When confirmed HTF is active, HTF Bias uses the previous closed HTF candle. Current chart timeframe values can still update while the active candle is open.
License: MIT.
This script is published for educational/open-source purposes. It does not provide financial advice. Indicator
Edo Control Edo Control — Structural Market Context from Williams %R and ADX, with State-Classified Control Candles, an Intensity Heatmap and Integrated Multi-Timeframe Reading
Williams %R, introduced by Larry Williams, measures on each bar where price closes inside its recent range and translates that into an overbought and oversold scale. ADX and the DMI directional system, developed by J. Welles Wilder in 1978, measure something different and complementary: how much strength the move has and which way it leans. Each one answers its own question well, but separately they leave gaps. Williams %R tells you whether price is stretched, not whether the trend has strength. ADX tells you whether there is strength, not where in the range price sits. And neither one, on its own, tells you whether what is happening on the current chart is consistent with the higher timeframes.
Edo Control was built to close those gaps without giving up the classic logic. Instead of reading %R and ADX as two loose oscillators, it crosses them bar by bar into a single state matrix that colors every candle, condenses them into an intensity layer, and projects the same reading onto three timeframes at once. The result is not a buy or sell signal: it is a framework of structural context that answers a question prior to any trade, the question of whether current market conditions even justify considering an entry.
It is worth saying what it is not. Edo Control does not generate entry or exit signals, does not predict direction and does not automate decisions. It describes the state of the market; the decision remains the trader's.
WHAT THE INDICATOR DOES
Edo Control organizes price information into three coordinated visual layers that share a single calculation logic. The Control Candles classify each candle into a structural state according to the interaction between Williams %R and directional strength. The Heatmap translates the intensity and health of the move into a background color layer, in three reading modes. The multi-timeframe module replicates the same state reading across three simultaneous timeframes to assess agreement or conflict between frames. The three layers are independent: each one can be turned on or off separately, so the trader has full control over the visual load of the chart.
CONCEPTUAL CALCULATION BASIS
The core of the indicator combines two classic measurements. The first is position in the range: Williams %R over a period of 40 places the close inside the recent high-low range relative to the equilibrium level at −50. The second is directional strength: the DMI/ADX system, with length 7, measures the intensity of the move and which direction dominates, comparing +DI against −DI. From there, a context score integrates both dimensions conceptually: how far price moves away from the equilibrium of the range, modulated by the strength with which it is moving. A stretched move without strength, and a contained move with growing strength, produce different readings. That same score feeds the three layers —the candle classification, the Heatmap color and the multi-timeframe values—, so everything seen on the chart comes from a single coherent source.
THE CONTROL CANDLES
Each candle is assigned a state based on three combined checks: which side of the −50 Williams %R level it sits on, the bullish or bearish zone of the range, and how far; whether %R is accelerating or decelerating versus the previous bar; and whether directional strength is rising or fading versus the previous bar. The combination of those three checks produces a map of up to twelve color states grouped into four reading families.
The impulse and continuation family gathers the states where price advances with a dominant body and growing strength in the direction of the move. The rejection and change family captures the %R crosses over the −50 level that mark a possible bias shift, bullish to bearish or the reverse. The decision and transition family groups medium strength or mixed sequences, where the move neither confirms nor exhausts clearly. And the reference and extreme family covers strong continuation states and the extreme zones of the range that serve as structural anchors.
This classification does not predict the next candle: it translates its internal structure into a color, so the trader reads at a glance whether recent activity is impulse, rejection, indecision or reference, without analyzing candle by candle. The system works only with confirmed data, so the state of a closed candle is not redrawn.
THE HEATMAP, AN INTENSITY LAYER
The Heatmap paints the chart background according to the context score, with three selectable modes. The Multicolor mode is a three-point gradient running from trend exhaustion (MIN) to stable trend (MID) and maximum acceleration (MAX); it is the richest reading, because it shows the health of the move and not just its direction. The Bicolor mode resolves four directional strength states by combining DMI direction with intensity: high or low bullish strength and high or low bearish strength. The Hybrid mode simplifies the reading to two states, healthy trend or warning and exhaustion.
The Heatmap opacity is configurable, 70% by default, so it does not cover the candles. The intensity layer is historical context of how price has been moving, never a support or resistance zone nor a prediction of future volatility.
MULTI-TIMEFRAME
The multi-timeframe module computes the same context score on three timeframes at once and displays them as three column bars with their normalized value, from 0 to 1, and labels to the right of the chart. The timeframes are assigned automatically according to the chosen trading profile, ensuring coherence between the operating horizon and the context frames: the Scalper profile works on 1m, 3m and 5m; Intraday on 5m, 15m and 1h; Swing on 1h, 4h and Daily; and Long Term on Daily, Weekly and Monthly. When the three timeframes point the same way a confluence occurs; when they diverge, the market is in transition. Confluence is context information, not an entry trigger.
INFORMATION PANEL
Edo Control includes legend panels that can be toggled independently, positionable in the four corners and with two sizes and Dark or Light mode. The Last TF Candle Monitor shows the context value of the latest candle on the three timeframes. The Candles Guide is the legend of the Control Candle states with their color and description. The Heatmap Guide describes the active Heatmap mode and updates when the mode changes. The legend is available in English and Spanish.
LEARNING MODE
An educational option displays over the historical candles the internal state numbering, from 0 to 11, and explanatory tooltips on hover, to study how each combination of %R and directional strength translates into a state. It is meant for the first familiarization sessions; it is best disabled during live trading to reduce visual load. The depth of history, from 50 to 400 bars, is configurable.
ALERTS
Although Edo Control's philosophy is to offer context rather than entry or exit signals, it includes a set of six alert conditions consistent with that nature, configurable from the standard PulseWire dialog. They warn of context transitions, not of buy or sell orders. Two of them watch the Heatmap: the score entering the exhaustion zone (MIN), the first sign that the move is losing strength, and entering the maximum acceleration zone (MAX), when the move extends with strength. Another two watch the rejection candles: Williams %R crossing above the −50 level, which points to a possible bearish-to-bullish turn, and the cross below, which points to the opposite turn. The last two watch multi-timeframe confluence: when the three timeframes of the profile place %R above −50 at once, or below at once.
The multi-timeframe confluence is evaluated on the −50 axis of Williams %R, the same one that classifies the rejection candles, and not on the numeric value of the score, which measures context intensity and is directionally neutral.
HOW TO READ IT
A clean reading follows a sequence from higher to lower timeframe. Start with the macro context, the value and color of the latest candle on the higher timeframe, which sets the backdrop. Then check the intermediate context, to see whether the middle timeframe confirms or contradicts the higher frame. Then drop to the current situation: the type of recent Control Candles and the active Heatmap zone. And integrate the three layers into a synthesis.
Some reading patterns are common. In a healthy continuation, impulse candles chain together, the Heatmap stays in MID or MAX in the direction of the move and multi-timeframe confluence points the same way. In an exhaustion, the Heatmap migrates toward MIN while price still advances and decision or rejection candles appear. In a possible turn, a rejection candle coincides with a sign change in directional strength and the loss of confluence between frames. And in an indecision, decision candles dominate, the Heatmap turns neutral and the timeframes conflict: the context offers no clear structural edge.
ORIGINALITY AND JUSTIFICATION
Williams %R and ADX/DMI are classic, public-domain indicators; Edo Control neither reinvents nor renames them. What it adds is the coordination: instead of reading two oscillators in separate panes, it integrates both into a single twelve-state matrix that colors each candle directly, derives from them an intensity layer with three reading modes, and replicates that same reading across three timeframes coherent with the operating horizon. The combination answers something neither one resolves separately: reading position in the range, strength of the move and coherence between frames at a single glance and under a common logic. That integration, and not the components themselves, is the indicator's own method.
CONFIGURATION
Multi-timeframe: trading profile selection (Scalper, Intraday, Swing or Long Term) and visibility of the multi-TF bars. Core settings: enable the Control Candles, enable the Heatmap, Heatmap mode (Multicolor, Bicolor or Hybrid) and Heatmap opacity, from 10 to 100% with 70 by default. Legends: enable the Last TF Candle Monitor, the Candles Guide and the Heatmap Guide, position in any of the four corners, opacity, size and language, English or Spanish. Learning: enable learning mode, tooltips, history depth of 50, 100, 200 or 300 bars with an option to force 400, and label size and opacity. Style and visibility: colors and visibility per timeframe from the standard PulseWire tabs.
OPEN SOURCE
Edo Control is published as an open source and free indicator. The full Pine Script is publicly available on PulseWire for study, adaptation and integration into any workflow.
This indicator is a technical analysis tool intended exclusively for educational and informational purposes. It does not generate automatic buy or sell signals and should not be considered financial advice. Trading in financial markets carries a significant risk of capital loss. Past results do not guarantee future results. Always use proper risk management. Indicator
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