RSI Oversold AO - Long IndicatorRSI Oversold AO DCA — Long Indicator
🔷 What it does:
This is a signal-only indicator that mirrors a dual-RSI-gated long DCA workflow. It tracks one virtual long position at a time, opened only on a lower-timeframe RSI cross-down into oversold, and averages the position with up to four safety orders on an aggressive 2× × 2× ladder — but each safety order requires the RSI to still be below 25 at the moment of fill. No falling-knife averaging into recovering momentum. Exit is a fixed Take Profit at 3% above average entry. Every event emits a webhook-ready JSON payload for a DCA Bot.
- Dual RSI gating: cross-down 30 entry trigger AND static less-than-25 continuation filter on every safety order.
- Aggressive 2× × 2× safety-order ladder: deviations 1.00%, 3.00%, 7.00%, 15.00%; sizes 60, 120, 240, 480 USDT.
- Fixed Take Profit: 3% above running average entry, no trailing.
- Honest virtual bookkeeping: total cost and qty updated incrementally on every fill — avg entry and open PnL displayed live.
- Six discrete events per cycle (entry + 4 AO fills + TP), each with its own webhook payload.
🔷 Who is it for:
- Swing traders running a DCA Bot on crypto pairs that frequently overshoot into oversold readings.
- Bot operators who want a chart-driven signal source that emits per-event JSON ready for a DCA Bot.
- Traders who want averaging gated by momentum continuation, not just price levels — the "no falling knives" guard prevents loading further when momentum has already reversed.
- Traders who want to monitor an evolving DCA position — base entry, owned AO levels, deployed capital, open PnL, live RSI readings — directly on the chart without the strategy-tester overhead.
🔷 How does it work:
Entry RSI Filter (Oversold Cross Down): A 15-minute RSI(7) is sampled via request.security with lookahead disabled. The entry gate fires when RSI crosses down through 30 — momentum has just entered oversold territory. At host-bar close, if the indicator is flat and the cross is fresh, the virtual long position opens.
Safety Order Ladder (Dual Gate): After entry, the indicator monitors two conditions in parallel for each pending safety order: price deviation downward against the position AND a static RSI continuation filter. The k-th safety order fires only when close ≤ base entry × (1 − cumulative deviation) AND the 15-minute RSI(7) is still below 25. Cumulative deviation grows by the step multiplier (default 2×): 1.00%, 3.00%, 7.00%, 15.00%. Each safety order's virtual size grows by 2×: 60, 120, 240, 480 USDT.
Why the AO Gate Matters: A pure price-ladder DCA blindly averages into any decline. The RSI < 25 gate stops the averaging if momentum has reversed back above 25 — the asset is no longer oversold by the indicator's definition, and adding to the position would mean buying a recovery, not a dip. This filter trades off some averaging frequency for materially higher average-entry quality.
Honest Virtual Bookkeeping: Total cost and qty are updated incrementally on every fill, so the avg entry, deployed capital, and open 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 3% above the running average entry. When close hits the TP target, the close webhook fires and the virtual position resets.
🔷 Why it's unique:
- Dual RSI Gating: Most DCA indicators gate only the entry. This indicator gates both the entry (cross-down momentum trigger) and the continuation of averaging (static oversold filter on every safety order).
- Aggressive 2× × 2× Ladder: Most published DCA tools use mild 1.05–1.25× compounding. This one doubles both the deviation step and the size each rung — the position scales fast if all safety orders fill, but only inside a confirmed oversold regime.
- 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.
- Per-Event Webhook Ledger: Six 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 on 1h–2h ranges. Default thresholds are calibrated for DOGEUSDT 1h. Different pairs may need RSI threshold and deviation ladder tuning.
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.
Aggressive Compounding: The 2× × 2× ladder is more aggressive than typical published DCAs. If all four safety orders fill, the position scales from 100 USDT base to 1,000 USDT total. Match the indicator's per-slot allocation to your bot's grid configuration to keep the avg-entry display honest.
No Stop Loss: There is no exit signal on adverse moves beyond the 4-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.
RSI Oversold Continuation: The AO gate uses a static RSI < 25 check, not a cross. If RSI dips to 20 and stays there for multiple bars while price drops further, all four AOs can fill in succession. Conversely, a sharp RSI recovery above 25 freezes the ladder mid-position.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester. For performance metrics over a 4-month sample (~44 closed trades, 77.27% win rate, 0.96% max drawdown, profit factor 5.791, +1.26% net return), use the companion strategy version on identical parameters. The 44-trade sample is below the typical ≥100 floor for statistical confidence — re-run on a 12+ month window for a more robust validation.
🔷 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 AO gate RSI filter, the 4-AO ladder parameters, and the Take Profit percentage. Defaults are calibrated for DOGEUSDT 1h — recalibrate per asset before deploying.
🔸 Set Base Order Size and AO sizes to match your bot's grid 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_DOGE).
🔸 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 safety 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 safety orders per cycle (default 4).
First AO Size (USDT): Virtual size of the first safety 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 safety order's USDT size.
Entry RSI Timeframe / Length / Level: Lower-timeframe RSI cross-down filter for the base entry.
AO Trigger RSI Timeframe / Length / Less Than: Lower-timeframe RSI continuation filter for each safety order.
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.
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.
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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
Indicator
RSI Oversold AO - Long StrategyRSI Oversold AO — Long Strategy
🔷 What it does:
This is a long-only DCA strategy that buys oversold dips and continues averaging into them only while the asset stays in the oversold zone. A long entry opens on a lower-timeframe RSI crossing down through 30. Four safety orders then average the position on an aggressive 2× deviation × 2× size ladder — but each one fires only if the lower-timeframe RSI is still below 25 at that moment. No falling-knife averaging into recovering momentum. Exit is a fixed 3% Take Profit from average entry. No trailing, no Stop Loss.
- Single base order with up to four safety orders on a 2× × 2× ladder.
- Dual RSI gating: cross-down entry trigger AND static oversold continuation filter.
- Aggressive size compounding: 60 / 120 / 240 / 480 USDT margins on the four safety orders.
- Fixed Take Profit: 3% above average entry, no trailing.
- Every entry, safety order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
🔷 Who is it for:
- Swing traders looking for systematic long exposure on crypto pairs that frequently sweep liquidity into oversold readings.
- DCA-style traders who want averaging gated by momentum continuation, not just price levels — the "no falling knives" guard prevents loading further when momentum has already reversed.
- Bot operators who want to drive a DCA Bot via webhook with per-event JSON payloads tagged for each base / safety order / exit action.
- Traders comfortable with deploying up to ~10% of equity per trade in exchange for a wider 3% profit target.
🔷 How does it work:
Entry RSI Filter (Oversold Cross Down): A 15-minute RSI(7) is sampled via request.security with lookahead disabled. The entry gate fires when RSI crosses down through 30 — momentum has just entered oversold territory. At host-bar close, if no position is open and the cross is fresh, the strategy opens the base order.
Base Order: Sized at 100 USDT default (1% of 10k capital). Configurable as Market (default) or Limit at the bar's close.
Safety Order Ladder (Dual Gate): After the base fill, the strategy monitors two conditions in parallel for each pending safety order: price deviation downward against the position AND a static RSI continuation filter. The k-th safety order fires only when close ≤ base entry × (1 − cumulative deviation) AND the 15-minute RSI(7) is still below 25. Cumulative deviation grows by the step multiplier (default 2×): 1.00%, 3.00%, 7.00%, 15.00%. Each safety order's size grows by the size multiplier (default 2×): 60, 120, 240, 480 USDT.
Why the AO Gate Matters: A pure price-ladder DCA blindly averages into any decline. The RSI < 25 gate stops the averaging if momentum has reversed back above 25 — the asset is no longer oversold by the strategy's definition, and adding to the position would mean buying a recovery, not a dip. This filter trades off some averaging frequency for materially higher average-entry quality.
Exit: A fixed Take Profit at 3% above the running average entry. The strategy closes the moment close ≥ TP target. No trailing, no scaling out, no second-guessing.
🔷 Why it's unique:
- Dual RSI Gating: Most DCA tools gate only the base entry. This strategy gates both the entry (cross-down momentum trigger) and the continuation of averaging (static oversold filter on each safety order).
- Aggressive 2× × 2× Ladder: Most published DCAs use mild 1.05–1.25× compounding. This one doubles both the deviation step and the size each rung — the position gets large fast if all safety orders fill, but only inside a confirmed oversold regime.
- Wide Take Profit (3%): Most scalp DCAs use tight 0.5–1.0% TPs. The 3% target lets the strategy ride the oversold reversal further before locking in, capturing more of the mean-reversion move.
- DCA Bot Integration: Every event (base, AO 1–4, 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:DOGEUSDT spot on 1h. The dual-RSI logic is portable to other liquid crypto pairs that frequently overshoot oversold, but RSI thresholds and the deviation ladder should be reviewed before redeployment.
Sample Size: The 4-month backtest produced 44 closed trades — below the ≥100 floor typically used for statistical confidence. The strategy generates roughly 11 closed trades per month at default settings, so extending the test window to 12+ months would yield ~130 trades and a more robust sample. The 77.27% win rate and 5.791 profit factor are encouraging but should be re-validated on a longer test period before live deployment.
Commission Calibration: The default 0.18% commission was set conservatively above Binance spot taker rates (~0.1%). Live performance with realistic Binance fees should be modestly better than the published numbers. Update the commission input to match your fee tier for accurate forward expectations.
Strong Downtrends: Like any oversold-buying setup, this strategy is positioned for mean reversions, not waterfall declines. In sustained downtrends the strategy will keep filling the ladder while RSI < 25, then hold the position once RSI recovers. The dual RSI filter limits exposure compared to pure price-ladder DCAs, but a regime shift to sustained selling still produces extended underwater hold time.
Aggressive Compounding: The 2× × 2× ladder is more aggressive than typical published DCAs. If all four safety orders fill, the position scales from 100 USDT base to 1,000 USDT total = 10% of equity at default settings. This is right at the upper edge of PulseWire's typical 5–10% per-trade band — comfortable, but no further headroom. Scale base + AO sizes down to dial position risk lower.
No Stop Loss Justification: There is no exit on adverse moves beyond the 4-AO ladder. Per-trade risk is structurally capped by the bounded position-size ladder — at defaults that is 1,000 USDT max deployed = 10% of equity, at the upper edge of the conventional 5–10% per-trade band. If a hard exchange-side stop is required, layer it on the bot directly.
RSI Oversold Continuation: The AO gate uses a static RSI < 25 check, not a cross. This means averaging continues as long as RSI stays below 25 — if RSI dips to 20 and stays there for multiple bars while price drops further, all four AOs can fill in succession. Conversely, a sharp RSI recovery above 25 freezes the ladder mid-position. Test the strategy's behavior on your target asset before live deployment.
Demo Testing: Always demo-test before going live. Past results do not guarantee future performance, especially on a strategy whose profitability hinges on the asset reaching the 3% TP target while still recovering from an oversold print.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:DOGEUSDT (Spot)
Timeframe: 1H
Test Period: February 1, 2026 — May 28, 2026 (~4 months).
Initial Capital: 10,000 USDT.
Order Size per Trade: 1% of Capital base + 4 safety orders at 2× progression.
Max Capital Deployed: 1,000 USDT per trade (~10% of equity, upper edge of 5–10% band).
Commission: 0.18% per trade.
Slippage: 3 ticks.
Margin for Long Positions: 100%.
Indicator Settings: Default Configuration.
Base Order: 100 USDT, Market by default (Limit toggle available).
Take Profit: 3.0% above average entry (no trailing).
Stop Loss: None — bounded position size is the structural risk cap.
Entry Filter: 15m RSI(7) Crossing Down 30.
AO Gate: 15m RSI(7) Less Than 25 (static continuation filter).
Safety Orders: 4, Deviation 1.0%, Deviation Step 2.0×, Size Multiplier 2.0×.
Strategy: Long Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +126.22 USDT (+1.26%)
Max Equity Drawdown: 96.05 USDT (0.96%)
Total Closed Trades: 44
Percent Profitable: 77.27% (34 / 44)
Profit Factor: 5.791
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, the entry RSI filter (timeframe / length / level), the AO gate RSI filter, the 4-AO ladder parameters, and the Take Profit percentage. Defaults are calibrated for DOGEUSDT 2h — 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). 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 safety 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 safety orders per deal (default 4).
First AO Size (USDT): USDT size of the first safety 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 safety order's USDT size.
Entry RSI Timeframe / Length / Level: Lower-timeframe RSI filter that gates the base entry on cross down.
AO Trigger RSI Timeframe / Length / Less Than: Lower-timeframe RSI continuation filter that gates each safety order.
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
WAVE TIME ORGAN FORCE🌊 WAVE TIME ORGAN FORCE
WAVE TIME ORGAN FORCE is a multi-timeframe market flow and synchronization engine designed to combine organ-based market pressure analysis, EMA-smoothed visual flow, timeframe force propagation, and cinematic wave-style visualization into one clean and powerful trading system.
The indicator was built with two main goals:
1. To measure how market pressure behaves internally.
2. To visualize how that pressure propagates through multiple timeframe layers.
Instead of functioning as a simple oscillator or signal generator, WAVE TIME ORGAN FORCE focuses on market rhythm, synchronization, pressure quality, and directional propagation.
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THE MAIN PHILOSOPHY
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Most traditional indicators analyze only one dimension of the market.
Examples:
• RSI measures momentum strength.
• MACD measures moving average relationship.
• ATR measures volatility.
• OBV measures volume pressure.
WAVE TIME ORGAN FORCE combines several internal market behaviors into one synchronized system.
The indicator tries to answer questions such as:
Is the current movement supported by volume?
Is volatility supporting expansion?
Are multiple timeframes aligned together?
Is momentum propagating upward through the timeframe stack?
Is the market synchronized or internally conflicted?
Is the current structure smooth or chaotic?
The goal is not only to identify direction, but to understand the internal quality of market movement.
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ORGAN ENGINE
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The internal core is based on the “Organ Engine” concept.
The market is treated like a living structure composed of multiple organs.
The engine currently includes:
Trend Organ
Momentum Organ
Volume Organ
Volatility Organ
Each organ measures a different type of market behavior.
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TREND ORGAN
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The Trend Organ measures directional pressure using EMA slope behavior.
Instead of only checking whether price is above or below a moving average, the system measures how aggressively the trend itself is moving.
This allows the engine to detect acceleration and directional force more naturally.
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MOMENTUM ORGAN
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The Momentum Organ measures the speed and force of price movement using ROC-based calculations.
This helps the system determine whether the market movement is weak, expanding, slowing down, or accelerating.
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VOLUME ORGAN
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The Volume Organ uses OBV-style pressure calculations to determine whether volume supports the current market movement.
A bullish move without volume support is considered weaker than a move supported by synchronized volume behavior.
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VOLATILITY ORGAN
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The Volatility Organ uses ATR-based directional behavior.
This layer helps the system detect:
Expansion
Compression
Directional volatility pressure
The volatility component is important because strong trends usually expand volatility while weak or exhausted movements often compress.
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RAW ORGAN VALUE
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All organ layers are normalized and merged into a single internal value called the Raw Organ.
The Raw Organ represents the true internal market pressure.
This raw value is preserved internally and is not destroyed by visual smoothing.
This is extremely important.
The calculation engine remains mathematically intact while the visualization becomes smoother and easier to read.
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EMA-SMOOTHED ORGAN FLOW
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The visual Organ Flow is created by applying EMA smoothing to the Raw Organ.
This creates a flowing wave appearance instead of a sharp mechanical oscillator.
The smoothing exists for visual clarity and wave behavior representation.
The purpose is not to manipulate signals.
The result is a more natural energy-flow appearance where the market behaves like a living wave system rather than disconnected candles.
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TIMEFRAME FORCE ENGINE
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One of the most important parts of WAVE TIME ORGAN FORCE is the Timeframe Force Engine.
The system reads multiple timeframe layers simultaneously.
Instead of asking:
“Is the market bullish?”
the engine asks:
“Is bullish pressure propagating successfully through multiple timeframes?”
This creates a propagation-based analysis system rather than a simple trend filter.
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TIMEFRAME PROPAGATION
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Lower timeframe movement alone is often unreliable.
The system therefore checks whether momentum and directional pressure are successfully spreading into higher timeframe layers.
This creates a more stable and higher-quality directional environment.
The indicator measures:
Bullish Layer Count
Bearish Layer Count
Timeframe Alignment
Directional Force
Cascade Conditions
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CASCADE STRUCTURE
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A cascade occurs when all timeframe layers align in the same direction.
Bull Cascade:
All timeframe layers are synchronized bullish.
Bear Cascade:
All timeframe layers are synchronized bearish.
Mixed Wave:
The timeframe stack is not fully aligned.
The cascade system is important because strong directional moves often occur when multiple timeframe layers begin moving together.
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QUALITY CROSS ENGINE
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The indicator uses a cross relationship between:
Organ Flow EMA
Signal EMA
A bullish quality condition forms when:
• Organ Flow crosses above the signal line
• Organ Flow is above zero
• Timeframe Force is bullish
• Multiple timeframe layers support the movement
A bearish quality condition forms when:
• Organ Flow crosses below the signal line
• Organ Flow is below zero
• Timeframe Force is bearish
• Multiple timeframe layers support the movement
This creates a cleaner confirmation structure than simple crossover systems.
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WAVE STACK VISUALIZATION
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The indicator visualizes multiple timeframe layers as a stacked wave structure.
Each layer represents a different market rhythm.
Lower timeframe waves react faster.
Higher timeframe waves react slower and represent larger directional force.
The stacked structure creates a living market-flow appearance.
The purpose is to help the user visually understand:
Market rhythm
Directional depth
Synchronization
Pressure propagation
Wave expansion
Flow behavior
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GLOW & AURA SYSTEM
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The indicator uses cinematic glow and aura layers to improve readability and create a premium visual structure.
Glow layers emphasize:
Main Organ Flow
Timeframe Force
Wave Expansion
Cascade Conditions
Aura fills help visualize the relationship between:
Organ Flow
Signal Flow
Timeframe Force
Wave Stack Layers
The goal is to create a visually alive chart environment rather than a static indicator appearance.
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MAIN CHART CANDLE COLORING
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The indicator can color candles directly on the main chart.
This allows the user to visually identify stronger conditions without cluttering the chart with excessive BUY/SELL labels.
Yellow:
Higher-quality bullish condition.
Orange:
Higher-quality bearish condition.
Lime:
Bullish force dominance.
Red:
Bearish force dominance.
Gray:
Mixed or uncertain conditions.
The candle system is designed to communicate market state visually while keeping the chart clean.
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PANEL SYSTEM
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The premium panel acts as a live market cockpit.
It displays:
Current Market State
Organ Flow EMA
Raw Organ Value
Timeframe Force
Bullish Layer Count
Bearish Layer Count
Cross Quality
Signal State
The panel is designed to help the trader understand WHY the current condition exists instead of only displaying random numbers.
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MARKET STATES
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The indicator can display different structural conditions:
Bull Cascade
Bear Cascade
Bull Force
Bear Force
Mixed Wave
This allows the user to read the market as a living structure instead of reducing everything to simple buy and sell labels.
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WHY THIS INDICATOR IS DIFFERENT
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WAVE TIME ORGAN FORCE is not a traditional oscillator.
It combines:
Organ-based market pressure
EMA-smoothed visual flow
Multi-timeframe propagation analysis
Wave-stack visualization
Cascade synchronization
Cinematic glow and aura effects
Candle-state coloring
Premium panel guidance
The purpose is not simply to generate signals.
The purpose is to visualize market behavior, synchronization, and pressure flow.
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IMPORTANT NOTE
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This indicator does not predict the future.
It is a market structure and flow visualization engine.
It should always be used together with:
Risk management
Support and resistance
Volume analysis
Higher timeframe structure
Personal trading strategy
Market context
No indicator should be treated as a guaranteed prediction system.
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SUMMARY
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WAVE TIME ORGAN FORCE is designed to visualize how market pressure behaves and propagates across multiple timeframe layers.
The indicator combines organ-based internal pressure analysis with smooth wave-style visual presentation.
The result is a cinematic market-flow system focused on:
Direction
Force
Synchronization
Timeframe Propagation
Wave Behavior
Cascade Structure
Market Rhythm
Pressure Quality
Visual Clarity
The system is built for traders who want to understand the internal rhythm and synchronization of the market instead of relying only on traditional buy/sell indicators.
Indicator
True Trend Oscillator + Price EnvelopeTrue Trend Oscillator + Price Envelope is a Pine v6 rebuild and expanded interpretation of the original True Trend Oscillator concept by wbburgin.
The original idea is simple but powerful:
• Convert ATR into a stochastic volatility / trend-energy reading
• Smooth that Stoch ATR reading with a Rational Quadratic Kernel
• Use RSI as the directional pressure input
• Build separate Bull Trend and Bear Trend lines from that shared volatility engine
In this rebuild, I kept the original spirit of the oscillator but expanded it into a fuller trend-energy framework with automatic timeframe-aware settings, cleaner visual controls, price-pane candles, and a chart-side ATR envelope.
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Core Idea
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The oscillator is built from two main pieces:
1. Volatility / trend energy
ATR is normalized through a stochastic calculation, then smoothed with a Rational Quadratic Kernel. This creates the “energy” side of the oscillator.
2. Directional pressure
RSI supplies the directional side of the model.
The two final oscillator lines are:
Bull Trend = sqrt(RSI × Smoothed Stoch ATR)
Bear Trend = sqrt((100 - RSI) × Smoothed Stoch ATR)
That means the Bull and Bear lines are both connected to the same volatility / trend-energy source, but RSI determines which side has more directional pressure.
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How to Read the Oscillator
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The oscillator has two main lines:
• Bull Trend line
• Bear Trend line
The leading line shows which side currently has control.
A few practical reads:
• Bull above Bear
Bull pressure is leading.
• Bear above Bull
Bear pressure is leading.
• Both lines rising together
Trend energy is expanding.
• Both lines falling together
Trend energy is cooling, compressing, or losing force.
• Both lines collapsing near zero
The market is moving into a low-energy / compression state.
This is one of the more important parts of the script. The oscillator is not only asking which side is leading but whether the move has enough volatility energy behind it to matter.
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Active Trend Threshold
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The active threshold is used to separate trend conditions from low-energy / range conditions.
A trend is only treated as active when the weaker side of the oscillator is above the active threshold.
In plain terms:
• Bull can be above Bear, but if both lines are too weak, the script treats the market as range / low energy.
• Bear can be above Bull, but if volatility energy is collapsing, the script does not force a strong trend read.
• When both sides clear the threshold, the leading side becomes more meaningful.
This helps reduce the “every crossover is a signal” problem that many simple oscillators can have.
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Extreme Readings
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The script includes an upper guide at 80. When the Bull Trend line pushes above 80, the script can highlight that as an extreme bull-energy condition. When the Bear Trend line pushes above 80, the script can highlight that as an extreme bear-energy condition.
By default:
• Bull extreme = orange
• Bear extreme = purple
These colors can also carry into the price candles and envelope visuals, making strong directional energy easier to spot without needing to stare only at the oscillator pane.
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Auto / Manual Engine
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The script includes an Auto / Manual engine profile.
Auto mode adjusts the main calculation settings based on the chart timeframe, including:
• ATR length
• Stochastic length
• RSI length
• Stoch smoothing
• Kernel lookback
• Kernel weighting
• Active range threshold
Manual mode unlocks the user-defined settings. When Auto mode is active, the manual inputs are grayed out so the settings panel stays easier to understand.
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Price Candle Overlay
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This rebuild includes a price-pane candle overlay using plotcandle() and force_overlay.
The candle overlay keeps the real OHLC candle shape intact, but recolors the body, wick, and border based on the active True Trend state.
The candle colors can represent:
• Bull trend
• Bear trend
• Range / low-energy
• Bull extreme
• Bear extreme
Body, wick, and border transparency are controlled separately, so the candle overlay can be made bold or subtle depending on the chart style.
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True Trend Price Envelope
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The script also includes a True Trend Price Envelope projected onto the main chart.
The envelope is built from:
• EMA(HLC3) basis
• ATR-based width
• True Trend strength expansion
As oscillator strength increases, the envelope can widen. This creates a chart-side visual map of how the oscillator’s trend-energy state is interacting with price.
The envelope behavior is designed around support / resistance style context:
• Bull-side pressure fills the upper half of the envelope
• Bear-side pressure fills the lower half of the envelope
• Bull pressure can plot the lower band as a support-style trail
• Bear pressure can plot the upper band as a resistance-style trail
• Neutral conditions can optionally show a soft neutral envelope or basis trail
This helps connect the oscillator pane back to price instead of leaving the oscillator isolated below the chart.
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How I Use It
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I use this script as a trend-energy and compression map.
A few practical ways to read it:
• When Bull is above Bear and both lines are rising, bull pressure is expanding with energy.
• When Bear is above Bull and both lines are rising, bear pressure is expanding with energy.
• When the leading side is still on top but both lines are falling, the move may be cooling or losing force.
• When both lines collapse toward zero, the market may be compressing or moving through a lower-energy phase.
• When price is holding the envelope trail in the same direction as the oscillator state, the price chart is confirming the oscillator pressure more cleanly.
• When oscillator pressure and price-envelope behavior disagree, that disagreement can be useful information by itself because it may point to chop, transition, or fading momentum.
• Extreme colors can help identify when directional energy is stretched rather than simply trending.
This is not meant to be a standalone buy/sell signal machine. It is a visual context tool designed to help organize trend direction, volatility energy, compression, and price confirmation.
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Attribution
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This script is a Pine v6 rebuild and expanded interpretation of the original True Trend Oscillator concept by wbburgin.
Original author / concept:
• © wbburgin
• Original PulseWire script:
This version adds my own Pine v6 structure, Auto / Manual timeframe behavior, expanded visuals, price-pane plotcandles, extreme-state coloring, and the True Trend Price Envelope.
Special thanks to jdehorty for the KernelFunctions library used for the Rational Quadratic Kernel smoothing.
As always, this script is a visual context tool. It is not financial advice and is not meant to replace risk management, market structure, support/resistance, volume analysis, or a complete trading plan.
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Chart Examples
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Indicator
Adaptive Tail Risk MonitorAdaptive Tail Risk Monitor (ATRM)
What It Is
The Adaptive Tail Risk Monitor (ATRM) is a real-time statistical framework designed to map the changing architecture of asset return distributions. Most traditional indicators measure momentum, trend, or simple volatility. ATRM measures something deeper: the structural asymmetry and tail behavior of recent returns.
By calculating the 3rd moment (Skewness) and 4th moment (Kurtosis) of the return distribution and processing them through a rolling percentile framework, ATRM normalizes this advanced data against an asset’s own historical footprint. The result is a dynamic, self-calibrating view of market risk that automatically adapts to any financial instrument or timeframe.
Why It Was Built
Standard technical tools are largely blind to distributional shifts. A market can trend calmly while quietly accumulating statistical instability long before price confirmation becomes visually obvious. Hidden anomalies—such as fat tails, negative skew, and rising kurtosis—frequently precede major market regime transitions.
ATRM was built to surface these hidden conditions. By combining rolling central moment (skewness and kurtosis) estimation with adaptive percentile ranking, it converts abstract mathematical concepts into a highly interpretable visual dashboard. It tells you not just what the market is doing, but what kind of statistical regime you are operating in.
Core Concepts
🧠 Adaptive Percentile Framework
ATRM operates without static thresholds.
Instead, Skewness and Kurtosis are continuously evaluated relative to their own historical distributions using rolling percentile ranking.
This adaptive approach allows the framework to:
• Normalize behavior across asset classes
• Adapt across timeframes
• Remain responsive to structural market shifts
• Improve regime consistency
Key Takeaway:
Percentile levels represent relative statistical positioning unique to that specific asset’s history, rather than arbitrary fixed values.
1. Skewness — Asymmetric Return Conditions
Skewness is directional, measuring whether the return distribution is becoming positively or negatively imbalanced. It defines which side of the distribution carries the greater tail concentration.
Positive Skewness:
• Upside returns dominate
• Positive outliers become more frequent
• Bullish expansion conditions may be developing
Negative Skewness:
• Downside returns dominate
• Negative outliers increase
• Bearish asymmetry may be emerging
🟩 Skewness Color Mapping
The skewness line dynamically changes color according to its historical percentile state:
🟩 Extreme Positive Asymmetry: ≥ 90th percentile
🍏 Positive Asymmetry: 65th–90th percentile
⬜ Neutral Symmetry: 35th–65th percentile
🍎 Negative Asymmetry: 10th–35th percentile
🟥 Extreme Negative Asymmetry: < 10th percentile
2. Kurtosis — Extreme Return Conditions (Tail Risk)
Kurtosis measures the concentration and extremity of outliers (the thickness of the tails). Excess kurtosis is non-directional; it flags the probability of extreme price shocks regardless of sign. Elevated kurtosis tells you that the tails are getting fat, extreme returns are becoming more frequent, while Skewness provides the directional context.
High Kurtosis typically flags:
• Volatility expansion
• Large price movements
• Panic or euphoric phases
• Unstable regime transitions
Low Kurtosis reflects:
• Stable, balanced conditions
• Mean-reverting environments
• Limited tail expansion
🔵 Kurtosis Color Mapping
The kurtosis plot dynamically shifts color to indicate tail expansion intensity:
🔵 Extreme Expansion: ≥ 90th percentile
🔹 Elevated Expansion: 75th–90th percentile
⚪ Baseline Conditions: < 75th percentile
🖥️ Market Condition Framework
The indicator synthesizes both Skewness and Kurtosis states into a unified classification system, painting the chart background when critical structural transitions occur.
🟩 Bright Green — Positive Returns Dominant
Skewness ≥ 90th percentile & Kurtosis ≥ 90th percentile
🍏 Light Green — Positive Returns More Frequent
Skewness 65th–90th percentile & Kurtosis ≥ 75th percentile
🟦 Blue — Neutral Expansion
Skewness 35th–65th percentile & Kurtosis ≥ 75th percentile
🍎 Light Red — Negative Returns More Frequent
Skewness 10th–35th percentile & Kurtosis ≥ 75th percentile
🟥 Bright Red — Negative Returns Dominant
Skewness < 10th percentile & Kurtosis ≥ 90th percentile
⬛ Baseline Conditions
Kurtosis < 75th percentile
(Stable, low-dispersion environment)
This framework allows traders to quickly assess whether market conditions are becoming increasingly directional, increasingly unstable, or returning toward equilibrium.
🛠️ User Settings & Customization
Rolling Window
Controls the initial Skewness and Kurtosis estimation lookback.
• Shorter windows increase responsiveness
• Longer windows increase statistical stability
Minimum recommended: Intraday/Daily 63+, Weekly 52+, Monthly 36+.
Percentile Window
Sets the lookback for historical percentile ranking. For statistical integrity, this window must exceed the Rolling Window length for Skewness and Kurtosis.
Minimum recommended: Intraday/Daily 126+, Weekly 52+, Monthly 36+. Longer windows produce more stable percentile ranks
EMA Smoothing
Applies exponential smoothing to reduce noise on raw statistical estimates.
• 3–5 = higher responsiveness
• 8–13 = greater stability
Higher values improve stability but increase lag during regime transitions.
Display Style Flexibility
Users can independently switch display formats (Line, Columns, Histogram, or Area) for both Kurtosis and Skewness via the native PulseWire Style menu.
Visibility Controls & Legends
Fully customize or toggle:
• Percentile bands
• Background colors
• Legend tables
⚙️ Multi-Panel Configuration Note
For maximum clarity, consider loading ATRM twice as separate indicator panes:
• One configured to display only Skewness
• One configured to display only Kurtosis
⚠️ CRITICAL REQUIREMENT: When stacking multiple ATRM instances across separate panes, maintain identical Rolling Window lengths to keep percentile states synchronized.
Different lookback windows create independent historical distributions, which may lead to desynchronized percentile states and inconsistent regime classification between panels.
📈 Application Examples & Strategy Filters
1. ATRM + RSI — Filtering False Reversals
RSI is designed to identify overbought and oversold conditions but cannot evaluate whether the surrounding market environment supports stable mean reversion or continued directional expansion. ATRM fills that gap by providing distributional context around the signal.
The Oversold Trap — Avoiding False Reversals
The Setup
RSI overbought/oversold signals perform best during mean-reverting environments but often struggle during sustained trends or market dislocation phases. A common trap is buying a deeply oversold RSI reading during an aggressive market decline. The RSI signal looks like a reversal opportunity but the market continues lower.
The Filter
If RSI flashes an oversold signal while ATRM Skewness is firmly in its lower percentiles (< 35th percentile) and Kurtosis is elevated (> 75th percentile), the return distribution remains heavily negatively skewed with elevated tail expansion. Avoid mean-reversion longs in this environment. Wait for Skewness to recover toward the neutral zone before attempting reversal entries.
The Confirmed Reversal — High-Confidence Mean Reversion
The Setup
Following a period of market stress, RSI moves into oversold territory while distributional conditions begin to stabilize. The question is whether the signal reflects genuine mean-reversion potential or another false recovery.
The Filter
When Kurtosis is below the 75th percentile and Skewness is neutral, the market is operating in a more stable, symmetric environment where RSI reversal signals carry higher confidence.
2. ATRM + MACD — Confirming Breakouts & Avoiding Whipsaws
Standard indicators like RSI, MACD, or Moving Averages track trend and momentum but cannot detect the underlying shape of the return distribution. ATRM acts as a distributional condition filter—helping determine whether a strategy's signals are operating in a favorable or unstable statistical environment.
The Breakout Confirmation — Filtering False Crossovers
The Setup
MACD crossovers frequently generate false signals during choppy, low-conviction markets. Look for periods where Kurtosis is compressed near the bottom of its historical range, indicating a low-dispersion environment where crossover signals should be treated with skepticism.
The Filter
When a fresh MACD crossover occurs simultaneously with Kurtosis breaking upward through the 75th percentile, it confirms the return distribution is expanding to support a genuine directional move. The MACD provides the directional entry; ATRM confirms the structural conditions support it.
The Exhaustion Warning — Avoiding Late-Stage Exposure
The Setup
A bullish MACD crossover occurs after a prolonged advance, potentially pulling in late buyers near the late-stage extension point of a structural move.
The Filter
If the crossover occurs while Kurtosis is already above the 90th percentile and Skewness remains highly positive, the distribution is statistically stretched. Reduce position sizing or trail stops aggressively rather than initiating fresh exposure at that stage.
3. ATRM + Moving Average Crossovers — Filtering Trend Whipsaws
Moving average crossovers are designed to capture shifting trends but have no built-in mechanism to evaluate whether the market environment actually supports a sustained directional move. ATRM fills that gap by providing the distributional context the crossover itself cannot see.
The Squeeze and Launch — High-Probability Breakouts
The Setup
During sideways, range-bound markets, moving averages flatten and cross repeatedly in both directions, generating false signals. Look for periods where the averages are tangled while ATRM Kurtosis is flat near the bottom of its historical range — this is a compressed, low-dispersion environment where breakout signals should be treated with skepticism.
The Filter
Do not trade minor crossovers while Kurtosis remains compressed. Wait for the bar where a fresh MA crossover coincides with Kurtosis breaking upward through the 75th percentile. This indicates the return distribution is beginning to expand, which is consistent with a genuine directional move emerging from the consolidation. The crossover gives direction; ATRM confirms the distributional conditions have shifted to support it.
The Climax Trap — Avoiding Late-Stage Entries
The Setup
An asset enters a strong, sustained advance. A lagging moving average crossover finally triggers a bullish signal after price has already moved significantly, pulling in late trend-followers near the exhaustion point.
The Filter
If the crossover occurs while Kurtosis is already above the 90th percentile and Skewness is in the upper percentiles, the distribution is statistically extended. This does not guarantee reversal, but it indicates the market is in a high-dispersion, asymmetric state that is less favorable for new long entries. Use this condition to trail existing stops aggressively rather than initiating fresh positions.
The Dead Cat Bounce — Identifying False Recoveries
The Setup
Following a sharp decline, price bounces and shorter-term moving averages cross back to the upside, creating the appearance of a trend reversal. This pattern frequently traps traders who interpret the crossover as confirmation that the worst is over.
The Filter
If the bullish crossover occurs while ATRM Skewness remains below the 10th percentile, the return distribution is still heavily negatively skewed. The underlying conditions that drove the decline have not resolved. Treat the crossover as a potential continuation pattern rather than a confirmed reversal, and approach any long signal with significantly reduced conviction until skewness recovers toward the neutral zone.
📌Important note: ATRM is not a standalone entry/exit signal. Use it as a market condition filter layered over your existing strategy — tighten risk or reduce exposure when tail risk is accumulating, increase exposure when distributional conditions are favorable.
Disclaimer
ATRM is an analytical framework developed for educational and research purposes. It does not constitute financial or investment advice.
All trading involves substantial financial risk. Indicator
EMA 40 Pullback Pyramid StrategyEMA 40 Pullback Pyramid Strategy
EMA 40 Pullback Pyramid Strategy is an educational trend-following strategy designed to study long-side entries around a rising 40-period Exponential Moving Average, with optional pullback re-entry logic, ADX trend-strength filtering, and EMA cross-based entry/exit conditions.
This is a strategy script, not a prediction tool and not financial advice. It is intended for research, backtesting, and forward-testing only. Historical results are hypothetical and can differ significantly from live trading due to slippage, commissions, liquidity, order execution, symbol behavior, timeframe selection, and market regime changes.
What the strategy does
The strategy uses the 40-period EMA as its main directional reference.
The EMA color changes according to its slope:
- Green EMA: the EMA is rising.
- Red EMA: the EMA is falling.
- Gray EMA: the EMA is flat or unchanged.
The strategy can enter long positions when selected bullish conditions occur and can close positions when selected bearish or exit conditions occur.
Core logic
1. EMA 40 trend direction
The strategy calculates a fast EMA using the selected EMA length. The default value is 40.
A bullish trend condition exists when the EMA is rising. A bearish condition exists when the EMA is falling.
The original base entry occurs when the EMA changes from not rising to rising, and ADX is above the selected minimum threshold.
2. ADX trend-strength filter
The strategy uses DMI / ADX to filter weak trend conditions.
A trade can qualify only when ADX is above the selected ADX threshold. The default threshold is 20.
This filter is intended to reduce entries during weak or sideways market conditions, but it does not eliminate false signals.
3. Pullback re-entry logic
When enabled, the pullback module looks for price to retrace toward the EMA by a selected ATR-based distance and then recover above the EMA.
The pullback condition uses:
- ATR length.
- Pullback distance multiplied by ATR.
- Recovery candle logic, where the candle closes above the EMA and closes above its open.
This feature is designed to study additional entries during an existing upward EMA trend. Because pyramiding is enabled, these pullback signals can add to an existing long position depending on the strategy settings.
4. EMA 40 cross signals
The strategy includes optional EMA cross buy/sell logic.
The cross detection mode can be:
- Close mode: uses close crossing above or below the EMA.
- Wick mode: uses wick interaction with the EMA followed by a close on the opposite side.
When “Use EMA cross signals in strategy orders” is enabled, these signals can participate in actual strategy entries and exits. When disabled, they can be used only as visual reference signals.
5. Minimum bars between entries
The strategy includes a minimum-bars-between-entries setting. This helps reduce immediate repeated entries and gives users control over signal spacing.
6. Pyramiding
The strategy uses pyramiding to allow multiple long entries when qualifying conditions appear. This is mainly intended to study whether adding into a trend after pullbacks improves or worsens the tested behavior.
Users should review this setting carefully. Pyramiding increases exposure and can materially increase both potential returns and potential drawdowns.
Default strategy properties
The script uses the following default strategy properties:
- Initial capital: 1,000
- Position sizing: percent of equity
- Default order size: 33% of equity
- Pyramiding: 3
- Commission: 0.1%
- Slippage: defined in the strategy settings
- Bar magnifier: disabled
- Calculate on every tick: disabled
- Process orders on close: disabled
These settings are included for testing purposes only. They may not be suitable for every market, timeframe, or trader. Users should adjust position sizing, commission, slippage, pyramiding, and test date range to reflect realistic conditions for the instrument being tested.
Important backtesting note
PulseWire strategy results are simulations based on historical bar data. They are not live trading results.
Backtest results can change significantly depending on:
- Symbol
- Timeframe
- Date range
- Commission
- Slippage
- Liquidity
- Spread
- EMA length
- ADX threshold
- ATR length
- Pullback multiplier
- Minimum bars between entries
- EMA cross mode
- Whether EMA cross signals are used for orders
- Pyramiding setting
- Market regime
Users should test the strategy on a sufficiently large sample of trades and across different market conditions before drawing conclusions. A small number of trades is not enough to evaluate a strategy reliably.
How to use it
A practical workflow is:
1. Select the symbol and timeframe to test.
2. Use a realistic date range that includes different market conditions.
3. Review whether the strategy produces a sufficient number of trades.
4. Adjust commission and slippage to match the market being tested.
5. Review the impact of position size and pyramiding on drawdown.
6. Compare results with and without pullback re-entry.
7. Compare results with and without EMA cross signals being used for strategy orders.
8. Forward-test before considering any real-world use.
Inputs
Date Range
- Start Date: first date included in the test.
- End Date: last date included in the test.
Moving Average
- Fast EMA Length: controls the EMA used for trend direction, pullbacks, and cross signals.
DMI / ADX
- DI Length: DMI calculation period.
- ADX Smoothing: smoothing period for ADX.
- ADX minimum to trade: minimum ADX value required for qualifying trend entries.
Pullback Re-entry
- Enable pullback re-entry: enables or disables ATR-based pullback entries.
- Pullback distance × ATR: controls how close price must pull back toward the EMA.
- ATR Length: ATR period used for pullback distance.
Signal Control
- Minimum bars between entries: controls spacing between entries.
EMA 40 Cross Signals
- Use EMA 40 cross buy/sell signals: enables visual EMA cross signals.
- EMA cross detection mode: chooses Close mode or Wick mode.
- Use EMA cross signals in strategy orders: determines whether EMA cross signals affect actual strategy orders.
Visual elements
The script plots:
- The EMA line, colored by slope.
- Base entry markers.
- Pullback add-entry markers.
- Optional EMA cross buy/sell markers.
- Hidden ADX and ADX threshold plots available for reference.
Limitations
This strategy is long-side focused and does not create independent short positions.
The strategy can underperform during sideways or choppy market conditions, even with the ADX filter.
EMA-based systems are inherently lagging because moving averages react to prior price data.
ADX can confirm trend strength but does not determine trade direction by itself.
Pullback and pyramiding logic can increase exposure and may increase drawdown.
No strategy setting can guarantee profitability or future performance.
Recommended use
This strategy is best used as an educational framework for testing EMA trend continuation, ATR-based pullback re-entry, ADX trend-strength filtering, and pyramiding behavior.
It should be used with realistic backtesting assumptions, conservative risk controls, and additional independent analysis before any trading decision. Strategy
Confluence Flow OscillatorConfluence Flow Oscillator
Confluence Flow Oscillator is an educational momentum, pressure, and volume-flow indicator designed to help traders evaluate whether current market movement is supported by directional pressure, bar-close behavior, and volume-weighted participation.
This script is an indicator, not a trading strategy. It does not place trades, does not simulate orders, and does not provide backtested performance results. Any signal markers are optional and disabled by default. The indicator should be used as a research and decision-support tool, not as financial advice or an automatic trading system.
What the script measures
The indicator creates a composite oscillator called Flow Score. The Flow Score is calculated from three separate components:
1. Close Location Value / CLV
CLV measures where the candle closes within its own high-low range.
When the close is near the high of the candle, CLV is positive.
When the close is near the low of the candle, CLV is negative.
When the close is near the middle of the candle, CLV is closer to neutral.
This helps measure intrabar buying or selling pressure.
2. RSI Distance From 50
The script uses RSI as a momentum component, but instead of displaying the standard RSI scale, it re-centers RSI around a zero line.
RSI values above 50 contribute positively to the Flow Score.
RSI values below 50 contribute negatively to the Flow Score.
This allows RSI momentum to be blended into a zero-centered oscillator.
3. Chaikin Money Flow / CMF
CMF measures volume-weighted accumulation or distribution over the selected lookback period.
Positive CMF values suggest that volume is more associated with buying pressure.
Negative CMF values suggest that volume is more associated with selling pressure.
The script scales CMF so it can be blended with the other oscillator components.
How the Flow Score is calculated
The Flow Score is a weighted blend of:
- Smoothed CLV × 100.
- RSI distance from 50.
- CMF × 100.
Users can adjust the weight of each component. For example, increasing the CMF weight gives more influence to volume-based flow. Setting a component weight to zero removes that component from the composite calculation.
The final result is plotted as a zero-centered oscillator:
- Positive values suggest bullish pressure.
- Negative values suggest bearish pressure.
- Readings above the bullish threshold suggest stronger upside flow.
- Readings below the bearish threshold suggest stronger downside flow.
Originality and usefulness
This indicator is designed as a confluence-based flow oscillator rather than a simple single-input momentum tool.
The purpose of combining CLV, RSI distance, and CMF is to evaluate three different aspects of market behavior in one normalized view:
- CLV shows where candles close within their own range.
- RSI distance from 50 shows directional momentum relative to a neutral momentum level.
- CMF shows whether volume is supporting accumulation or distribution.
The script also includes optional confirmation filters so that signals are not based only on a threshold cross. These filters can require volume conviction, recent pivot structure, and exhaustion protection before a signal marker is allowed.
This makes the indicator useful for traders who want to study whether directional movement is supported by price location, momentum, and volume flow together.
Signal logic
The script can optionally display signal markers, but they are disabled by default.
A bullish signal can occur when the Flow Score crosses above the bullish threshold and the selected confirmation filters are satisfied.
A bearish signal can occur when the Flow Score crosses below the bearish threshold and the selected confirmation filters are satisfied.
A long-exit marker can occur when the Flow Score crosses below the bearish threshold while the script’s internal long-state is active.
These markers are informational only. They are not guaranteed entries or exits, and they should not be used without additional analysis, risk management, and testing.
Confirmation filters
The script includes several optional filters:
1. Volume Conviction Filter
When enabled, the signal requires current volume to be at or above a selected percentile of recent volume. This is intended to reduce signals that occur during low-participation conditions.
2. Pivot Structure Filter
When enabled, bullish signals require a recent confirmed pivot low, and bearish signals require a recent confirmed pivot high. This helps connect oscillator signals to recent market structure.
Because pivot confirmation requires bars to close after the pivot point, pivot-based logic can appear with delay. This is a normal characteristic of confirmed pivot calculations.
3. Exhaustion Guards
When enabled, the script attempts to avoid buying into overbought conditions and avoid selling into oversold conditions.
The exhaustion guard can block bullish signals when RSI is already above the selected overbought block level, and it can block bearish signals when RSI is already below the selected oversold block level.
It also checks whether an opposite-side flow regime existed recently before allowing a new signal. This helps reduce signals that occur after an extended one-sided move without prior regime context.
How to use it
A practical workflow is:
1. Use the zero line to identify whether flow is generally bullish or bearish.
2. Use the bullish and bearish threshold lines to identify stronger flow conditions.
3. Review whether the Flow Score is rising, falling, or flattening.
4. Enable optional signal markers only if you want visual threshold-cross markers.
5. Use the volume, pivot, and exhaustion filters to make signals more selective.
6. Confirm any setup with your own market structure, trend context, support/resistance, higher timeframe analysis, and risk rules.
Main settings
Core Periods
- RSI Length: controls the RSI momentum lookback.
- CMF Length: controls the Chaikin Money Flow lookback.
- CLV Smoothing: smooths the Close Location Value component.
Component Weights
- CLV Weight: controls the influence of candle close-location pressure.
- RSI Distance Weight: controls the influence of RSI momentum.
- CMF Weight: controls the influence of volume-weighted money flow.
Signal Logic
- Long Entry Threshold: bullish Flow Score threshold.
- Short/Exit Threshold: bearish Flow Score threshold.
- Show Short Signals: enables bearish short markers. Disabled by default.
Volume Conviction
- Require Volume Conviction: requires above-percentile volume before signals are shown.
- Volume Percentile: sets the required volume percentile.
- Volume Window: sets the lookback used for volume percentile calculation.
Pivot Structure
- Require Recent Pivot: requires recent pivot confirmation before signals.
- Pivot Left Bars: controls the left-side pivot confirmation.
- Pivot Right Bars: controls the right-side pivot confirmation.
- Max Pivot Age: controls how recent a pivot must be to qualify.
Exhaustion Guards
- Use Exhaustion Guards: enables overbought/oversold and regime-context filters.
- RSI Oversold Block: blocks bearish signals when RSI is too low.
- RSI Overbought Block: blocks bullish signals when RSI is too high.
- Regime Confirmation Window: checks whether a prior opposite-side flow regime existed.
Visuals
- Shade Bullish/Bearish Zones: shades the oscillator area above or below zero.
- Show Threshold Lines: displays bullish and bearish threshold lines.
- Show Buy/Sell Signal Markers: enables optional signal markers in the oscillator pane.
- Plot Signal Arrows on Price: displays optional markers on the main price chart when signal markers are enabled.
Alerts
The script includes alert conditions for:
- Bullish Signal.
- Bearish Signal.
- Long Exit.
Alerts only trigger when signal markers are enabled. They are intended as informational alerts, not automated trading instructions.
Important limitations
This indicator does not predict future price movement.
A positive Flow Score does not guarantee price will continue upward.
A negative Flow Score does not guarantee price will continue downward.
A bullish or bearish marker does not guarantee a profitable trade.
The Flow Score can behave differently across symbols, timeframes, sessions, and market conditions. Volume-based components may be less reliable on instruments where volume data is limited, synthetic, or inconsistent.
Users should test the indicator across multiple symbols and timeframes before relying on it in any decision-making process.
Recommended use
Confluence Flow Oscillator is used as a supporting oscillator for studying momentum, candle pressure, and volume participation together. It is designed to complement, not replace, a complete trading plan. Indicator
AetherEdge - Adaptive Smart RSI🖊️ Overview
AE-ASRSI is a next-generation RSI that online-learns each instrument's truly effective overbought/oversold levels, rather than judging by fixed 70/30 lines. It transplants the core idea of Q-learning — learning action values from experience — to dynamically select the highest-performing line from a set of candidate thresholds. With its color changing the instant BUY/SELL signals are emitted, it is intuitive even for beginners.
🔶 Key Features
Dynamic OB/OS: Q-learning chooses the optimal level from candidate thresholds (60–80 / 40–20)
Color-flip signals: RSI turns red/green the moment it enters a zone, with BUY/SELL bubbles
Intuitive visuals: zone entry also tints the background — "color changed = signal" at a glance
Adaptive lines: OB/OS levels move automatically based on instrument and market regime
ε-greedy exploration: occasionally samples weaker thresholds to avoid lock-in to local optima
Neon-glow RSI plot with a refined red/green palette
Integrated HUD showing learned levels and each zone's success rate
Built-in BUY/SELL alerts
🧠 Technical Architecture
A full Q-learning implementation is too heavy for Pine, but its core idea — learn action values from experience, prefer high-value actions — is reproduced online. Five candidate thresholds each are kept for OB (60/65/70/75/80) and OS (40/35/30/25/20), with a Q-value (0–1) per candidate. When RSI crosses a candidate, its context is buffered; after the outcome horizon, a reward is generated from whether a real reaction (an ATR-scaled move against the cross direction) actually occurred, and Q is updated via Q ← Q + α(r − Q). The displayed threshold is the argmax candidate, while ε-greedy occasionally samples others to maintain exploration. Plot color flips instantly on zone detection, serving as the visual signal.
⚙️ Recommended Settings & Tuning Guide
Tuned with crypto in mind. RSI Length 14 and Smoothing ~2 are a starting point. Outcome Horizon is the bar count for evaluating reactions — 5–10 for intraday, 15–25 for swing. Reaction Threshold (ATR) sets how large a reaction counts as success; for strictness, raise to 1.5–2.0. Exploration (ε) defaults to 0.1 — higher increases exploration, lower stabilizes.
💡 How to Use in Practice
The simplest use is "trade the color flip." When RSI turns green with a BUY bubble, consider a long fading oversold; turning red with a SELL bubble, consider a short fading overbought. The HUD's learned OB/OS levels indicate the bounds actually working on this instrument — more precise than judging by fixed 70/30. If the zone success rate stably exceeds 50%, the learning is functioning. Counter-trend accuracy degrades in trending markets, so pair with trend tools and rely on this most in ranging conditions.
⚠️ Important Notes
This tool is Q-learning-inspired, not a full reinforcement-learning agent; within Pine's constraints it reproduces the core idea as online threshold selection. Learning requires accumulated data, so on new instruments or short windows the Q-values remain near initial values and behavior approaches the default thresholds. Static success rates in the HUD signal insufficient learning data. RSI is fundamentally a counter-trend tool that excels in ranges; in strong trends, signals can fire repeatedly without working well.
🚨 Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial or investment advice. No signal guarantees future profit, and past performance does not indicate future results. All trading decisions are made at your own risk. Indicator
Indicator
Strategy
Ichimoku Trend Oscillator [Gabremoku]Ichimoku Trend Oscillator is a custom trend-following oscillator that transforms core Ichimoku components into a normalized trend force model, designed to make bullish and bearish pressure easier to read in a single lower-panel view.
Instead of plotting the full traditional Ichimoku Cloud on price, this script converts the relationship between Tenkan, Kijun, Kumo structure, and price location vs cloud into a smoothed oscillator with:
a central zero line
trend force scoring
histogram confirmation
momentum shift detection
optional Tenkan force overlay on the main chart
The Ichimoku framework is commonly used to evaluate trend, momentum, and support/resistance at a glance, especially through the relationship between price and cloud position, plus the Tenkan/Kijun structure.
What it shows
📉 Trend Force Line — the main oscillator line represents a normalized force score derived from:
Tenkan vs Kijun spread
price location relative to the cloud
bullish or bearish cloud structure
📊 Histogram — visualizes the difference between the force line and its signal line, helping show momentum acceleration or deceleration.
🌈 Soft Gradient Fill — the oscillator fill changes intensity depending on how far trend force is from zero.
📍 Tenkan Force Overlay — optionally plots the Tenkan line on the main chart with dynamic color logic tied to trend condition.
🚦 Signals — the script can display:
LONG on bullish zero-line cross
SHORT on bearish zero-line cross
SHIFT markers when momentum changes sharply without a fresh zero cross
🪧 Dashboard — displays state, force value, trend bias, Tenkan/Kijun relation, price vs Kumo position, and momentum-shift status.
Core logic
The script compresses several Ichimoku readings into one oscillator.
It combines:
Tenkan/Kijun directional spread
price above / inside / below cloud
cloud directional structure
ATR-based normalization
and smoothing for cleaner force transitions
This matters because in standard Ichimoku interpretation:
price above the cloud is usually read as bullish context
price below the cloud is usually read as bearish context
Tenkan above Kijun supports bullish alignment, while the opposite supports bearish alignment
By translating those conditions into a normalized oscillator, the script gives traders a faster way to read trend quality and directional pressure without plotting the full classic system every time.
State model
The oscillator classifies the market into states such as:
Bullish Expansion
Bullish Pressure
Bearish Expansion
Bearish Pressure
Neutral
This is useful because it separates simple directional bias from stronger “expansion” conditions where multiple Ichimoku elements are aligned.
For example:
force above zero suggests bullish pressure
force below zero suggests bearish pressure
stronger positive or negative readings reflect stronger directional alignment
SHIFT signals are used to highlight sudden changes in momentum before a full regime flip
How to use
A practical workflow is:
Use the zero line as the primary directional divider.
Use the force line to judge strength.
Use the histogram to evaluate acceleration or fading momentum.
Watch for SHIFT markers when force changes quickly.
Use the Tenkan overlay on the main chart as an additional structure guide.
In general:
cross above zero = bullish transition
cross below zero = bearish transition
force staying far from zero = stronger trend persistence
shift signals = possible early momentum change without full bias reversal yet
Features
✅ Ichimoku-based lower-panel oscillator
✅ Trend force model built from Tenkan, Kijun, Kumo, and price/cloud relationship
✅ ATR-normalized force engine
✅ Smoothed force line
✅ Signal line and histogram
✅ Soft gradient fill around zero
✅ LONG / SHORT zero-cross signals
✅ Bullish / bearish momentum shift markers
✅ Optional Tenkan force overlay on the main chart
✅ Live dashboard with state and bias information
Notes
This indicator is designed to turn Ichimoku structure into a more compact trend momentum oscillator, not to replace full discretionary Ichimoku analysis. It works best as a directional filter or timing aid when combined with price structure, support/resistance, or a broader trend framework.
Author: Gabremoku
Pine Script v6 Indicator
Indicator
SVEA - Smart Valuation & Analysis [Gabremoku]SVEA - Smart Valuation & Analysis is a multi-layer technical analysis framework designed to combine adaptive RSI overbought/oversold logic, multi-timeframe confluence, ADX volatility zones, and smart signal visualization into one single chart overlay.
At its core, SVEA uses RSI as the primary valuation engine for detecting overbought and oversold conditions, then expands that logic with adaptive thresholds, asset-specific presets, multi-timeframe confirmation, and ADX-based dynamic price zones. RSI is widely used to spot momentum extremes, but it is often more effective when combined with broader context such as trend strength, volatility, and higher-timeframe confirmation.
The result is a flexible decision-support tool built for traders who want more than a plain oscillator — a full environment for reading exhaustion, confluence, volatility expansion, and reversal potential directly on the chart.
What it shows
📊 Adaptive OB/OS Engine — SVEA uses RSI as the core oscillator and can switch between:
Adaptive thresholds
Auto-detected presets
Equity / Crypto / Forex / 15m presets
Custom levels
Because RSI thresholds often behave differently across instruments and timeframes, adaptive or asset-specific levels can provide more context than rigid 70/30 defaults.
🎯 OB/OS Price Zones — instead of showing only RSI values, the script projects overbought and oversold conditions into visual price bands and event boxes on the chart.
🧠 Multi-Timeframe Confluence — RSI values from the current timeframe plus two higher timeframes are compared in a confluence table, making it easier to identify when conditions align across chart scales. Multi-timeframe RSI is commonly used to improve timing and filter noise.
⚡ ADX Volatility Zones — SVEA combines ADX with Bollinger Band expansion logic to create dynamic top and bottom zones, then generates ADX-based zone-entry signals. ADX is a trend-strength tool, while Bollinger Bands help frame volatility expansion and statistical stretch.
🔺 Adaptive Buy/Sell Signals — buy/sell markers are triggered when RSI exits oversold or overbought conditions, optionally filtered by ADX strength and multi-timeframe confirmation.
🎨 Theme System — choose between a classic look or the Gabremoku visual identity.
Core logic
SVEA is built around four layers:
📉 RSI exhaustion logic — overbought and oversold detection
🧠 adaptive thresholds — levels that adjust with RSI behavior over time
🕒 multi-timeframe confluence — confirmation from higher timeframes
📈 ADX + BB zones — volatility-adjusted structural areas for signal visualization
This is important because RSI alone can remain overbought or oversold for a long time during strong trends, so combining it with ADX and higher-timeframe context helps reduce low-quality reversal signals. RSI is often strongest in ranging environments, while ADX helps identify whether trend conditions are too strong for mean-reversion logic to work cleanly.
Features
✅ RSI-based overbought/oversold framework
✅ Adaptive OB/OS thresholds based on RSI mean and standard deviation
✅ Auto preset detection by asset class and timeframe
✅ Presets for Equity, Crypto, Forex, and 15m charts
✅ Custom OB/OS levels
✅ Continuous or event-based OB/OS price zones
✅ Multi-timeframe RSI confluence table
✅ ADX + Bollinger Band dynamic top/bottom zones
✅ ADX-Buy and ADX-Sell zone-entry signals
✅ Adaptive Buy/Sell signals from RSI exit conditions
✅ Optional ADX confirmation filter
✅ Optional multi-timeframe confirmation filter
✅ Divergence framework inputs and styling foundation
✅ Theme switch between Classic and Gabremoku
✅ Integrated alerts for OB/OS, MTF confluence, and ADX zone signals
How to use
A practical workflow with SVEA is:
🔎 Start with the OB/OS state — determine whether RSI is entering an extreme zone.
🕒 Check the MTF confluence table — if current and higher timeframes align, the setup has stronger context. Multi-timeframe alignment is commonly used to reduce false single-timeframe signals.
📈 Look at ADX conditions — if ADX is high, the market may still be trending strongly, meaning raw RSI reversals can be less reliable. ADX above 25 is often used as a sign of strong trend conditions.
🎯 Use the adaptive buy/sell markers as transition signals when price exits an extreme area rather than blindly reacting to the first OB/OS touch.
Operational suggestion
💡 Suggested trading logic
🔵 Bullish mean-reversion setup: stronger when RSI is oversold, higher timeframes are also oversold or supportive, and price enters the bottom ADX zone. This creates a layered reversal context rather than a single-indicator trigger.
🟨 Bearish mean-reversion setup: stronger when RSI is overbought, higher timeframes confirm the stretch, and price enters the top ADX zone.
⚠️ Strong-trend caution: when ADX is elevated, do not assume every RSI extreme will reverse immediately. A strong ADX often means the current directional move still has strength behind it.
🧠 Best use case: use SVEA as a confluence engine, not as a stand-alone auto-entry tool.
A practical rule:
RSI gives you exhaustion
MTF gives you context
ADX gives you trend strength
Zones give you location
That combination is exactly what makes this script more robust than a standard RSI overlay.
Notes
This script is best described as a technical confluence framework rather than a single-indicator oscillator. It is especially useful for traders who want to visualize when price is statistically stretched, whether that stretch is confirmed across timeframes, and whether trend strength supports or weakens the case for reversal. Confluence-based tools are commonly used to improve selectivity by requiring several conditions to align before acting.
Author: Gabremoku Indicator
AetherEdge - Hypercube Heatmap (Horizon Field)🖊️ Overview
AE-HYPE2 is a heatmap engine that embeds multiple market features into a latent energy and projects it across the chart as horizontal energy bands by price level. It dynamically weights feature importance with attention and modulates band brightness with a Bayesian-style uncertainty. Brighter bands mark price levels where energy concentrates, intuitively conveying where market force accumulates. It expresses the CoinGlass-style horizontal-band aesthetic through a unique "market energy" lens rather than liquidations.
🔶 Key Features
Price-level energy field: projects multi-feature latent energy into horizontal bands by price
Latent embedding: five features (momentum, volatility, volume, trend, RSI) compressed into latent energy
Dynamic attention: softmax real-time weighting of each feature's importance
Uncertainty estimation: a Bayesian-style estimate from feature dispersion, darkening uncertain bands
Smooth gradient field via vertical smoothing
Viridis palette (purple→teal→green→yellow) reproducing the CoinGlass aesthetic
Hotspot glow and an integrated HUD showing total energy, uncertainty, and the focused feature
🧠 Technical Architecture
Within Pine — which has no autodiff, external libraries, or animation — this reproduces the mathematical core of deep embedding and attention in static form. A softmax over five standardized features yields attention weights, and their weighted sum is the latent energy. Uncertainty is a Bayesian-style estimate from the standard deviation among features. In rendering, for each past bar, the latent energy (attenuated by uncertainty) is accumulated into the price row that bar's price occupied, so levels where energy concentrates emerge as bright horizontal bands. Vertical smoothing diffuses energy into neighboring bands for a smooth gradient field. Color is the Viridis spectrum, with brightness encoding energy magnitude.
⚙️ Recommended Settings & Tuning Guide
Tuned with crypto in mind. Price Resolution 48 and Lookback Width ~250 are a starting point. Attention Temperature sets the embedding's character — below 1 focuses sharply on the strongest feature, above 1 blends multiple. Vertical Range adjusts field height, Color Intensity overall opacity. Enabling Apply Uncertainty Softening darkens uncertain price levels so confident bands stand out. Raising Price Resolution makes finer bands but watch the drawing-object limit (up to ~120).
💡 How to Use in Practice
Bright bands are price levels where market energy concentrates, marking levels that historically drew large interest (volume, momentum, volatility). These tend to act as support/resistance, and moments where price approaches them are worth attention. Dark, blurred-looking bands indicate high uncertainty and lower confidence. The HUD's focused feature reveals what currently drives the market. Used together with AE-LIQ (the liquidation heatmap), you can find levels where liquidation bands and energy bands coincide — doubly significant levels.
⚠️ Important Notes
This tool is inspired by deep learning and attention, not a true backprop-trained neural network. External libraries like NeuraLib, and animation/particle/blur effects, are impossible in Pine and are not included. Energy bands are a visualization of market state, not predictions. The heatmap rebuilds only on the last bar and does not repaint confirmed history. Pushing Price Resolution too high may hit the drawing-object limit and break the display.
🚨 Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial or investment advice. No output guarantees future prices, and past performance does not indicate future results. All trading decisions are made at your own risk. Indicator
AetherEdge - Adaptive Liquidation Heatmap🖊️ Overview
AE-LIQ is a liquidation-level estimation engine in the spirit of CoinGlass-style liquidation heatmaps. It estimates the price levels where leveraged liquidation orders cluster and renders them as bright horizontal bands — the "magnets" price tends to be drawn toward. Real liquidation maps use exchange position data, but since Pine can only access price and volume, this tool estimates from those by back-solving liquidation prices for several leverage tiers, emphasizing the bands that work via adaptive learning.
🔶 Key Features
Liquidation-band estimation: back-solves liquidation prices for 5×/10×/25×/50×/100× leverage
Volume weighting: each bar's volume serves as a position-size proxy for band intensity
Swept decay: bands price has already traded through are decayed, emphasizing un-swept bands (remaining liquidity)
Long/short selection: long liquidations (below) and short liquidations (above) can be shown separately
Adaptive tier reliability: online-learns whether price reaching each tier's bands actually reacted, emphasizing the effective ones
Viridis palette (purple→teal→green→yellow) reproducing the CoinGlass aesthetic
Integrated HUD showing the strongest leverage tier and each tier's reliability
🧠 Technical Architecture
Liquidation distance is approximated by the inverse of leverage (≈10% for 10×, ≈4% for 25×). From each bar's price, liquidation prices are back-solved for every enabled leverage tier, and a volume-based weight is added to the row (price bin) that price occupies. Higher leverage produces tighter, more crowded bands weighted more heavily. The accumulated row energy is normalized, bands price recently swept are decayed by the configured amount ("liquidated"), and un-swept bands remain bright. The AI layer checks whether, historically, price reaching each tier's liquidation distance actually produced an ATR-scaled reaction, updating per-tier reliability via an exponentially-weighted average. More reliable tiers gain band weight and visual emphasis. Rendering uses per-row horizontal box transparency grading, with Viridis-spectrum brightness encoding energy magnitude.⚙️ Recommended Settings & Tuning Guide
Tuned with crypto in mind. Price Resolution 60 and Accumulation Lookback ~250 are a starting point. On high-volatility instruments, raise Vertical Range to cover a wider price span. Swept-Band Decay controls how much traded-through bands are erased — higher leaves only the un-swept bands vivid, like CoinGlass. If cluttered, turn off unneeded tiers or restrict to one side (long/short).
💡 How to Use in Practice
Bright yellow bands read as price levels where heavy liquidations sleep — magnets that attract price. Price often moves toward such bands, and reaching them tends to trigger large volatility (liquidation cascades). The brightest bands above and below current price offer references for short-term targets and risk management. The HUD's strongest tier shows which leverage layer actually functions as a magnet on this instrument, guiding which bands to prioritize. Pairing with other structure analysis and favoring levels where liquidation bands align with support/resistance is effective.
⚠️ Important Notes
This tool is Estimated and differs from a real CoinGlass liquidation map. Exchange open-interest and leverage-distribution data cannot be accessed in Pine, so this is an approximation back-solved from price and volume, and may diverge from the actual distribution of liquidation orders. Liquidation bands are probabilistic estimates, not certain price targets. The heatmap rebuilds only on the last bar and does not repaint confirmed history. The AI reliability learning requires accumulated data.
🚨 Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial or investment advice. No output guarantees future prices, and past performance does not indicate future results. All trading decisions are made at your own risk. Indicator
MTF RSI Synchrony | Rainbow MatrixGENERAL OVERVIEW
The MTF RSI Synchrony is a multi-timeframe RSI fusion oscillator that aggregates five independent RSI readings — one per Fibonacci-spaced timeframe — into a single weighted Master Line. Each per-timeframe RSI is also plotted as a "ghost line" that fades by distance to the Master: when the five timeframes align, the rainbow renders solid; when they diverge, the ghost lines spread visibly across the pane, making synchrony itself a visible density property rather than a number to compute.
The main goal of this indicator is to give traders a single integrated read of RSI across multiple horizons — without flipping between charts, mentally averaging values, or guessing which timeframe's RSI matters at the current decision point. Every line, color, and divergence event on the pane was derived from real RSI calculations on each native timeframe, not approximated from the current chart's resolution.
It computes the Master Line from five timeframes via Fibonacci-proportioned weights (peak weight on the macro middle TFs), classifies the result through an adaptive Fibonacci channel that builds Z-Breathing / Z-Alert / Z-Exhaustion / Black Swan zones around the Master, and runs a classic price↔RSI divergence engine on each of the 5 TFs plus the Master line independently. A 5-column MTF Legend Table surfaces every TF's state at a glance, with an antenna marker (📡) flagging the row whose timeframe matches the chart's native resolution.
This indicator was developed for traders who already understand RSI and divergence concepts and want to see them across multiple timeframes in a single visual, with automatic synchrony detection and an integrated classic divergence layer.
WHAT IS THE THEORY BEHIND THIS INDICATOR?
Most RSI implementations on PulseWire operate on a single timeframe. They show you a value between 0 and 100 for the current chart and leave the multi-timeframe assessment to manual work — flipping between charts, sketching trendlines, or stacking multiple instances of the indicator on different intervals. This treats each timeframe as an isolated decision space.
The problem: institutional momentum is not isolated to one timeframe. The participants operating on the daily horizon see different RSI conditions than those operating on the weekly or 4-hour horizon. When the 15-minute RSI flips above 70 but the daily RSI is still neutral, the overbought signal is local — likely a counter-trend bounce. When the 15-minute RSI flips above 70 and the daily RSI also approaches the upper zone, the overbought signal is structurally agreed across horizons — far more likely to mark a multi-horizon exhaustion.
This indicator addresses that by extracting RSI from five user-configured timeframes simultaneously via request.security, fusing them via canonical Fibonacci weights (peak weight on the macro middle TFs), and rendering both the integrated Master signal and each contributing TF's individual reading on the same pane. The math of the per-TF extraction is standard RSI on the native bars — what makes it useful is doing it across five timeframes at once, weighting them by structural significance, and surfacing both the alignment and the per-TF divergences in a single visual.
The classic divergence layer addresses a parallel problem: textbook regular divergence (price↔RSI on the same timeframe) is a well-known reversal cue, but traders typically watch it on one timeframe at a time. By running pivot-based divergence detection independently on each of the 5 TFs and on the Master line, the indicator surfaces local divergences (on fast TFs — often noise) versus structural divergences (on slow TFs — often precede major reversals) in the same table view, with the Master line acting as the integrated read drawn directly on the chart.
MTF RSI SYNCHRONY FEATURES
The indicator includes 7 main features:
◇ Multi-Timeframe RSI Fusion Engine
◇ Adaptive Fibonacci Channel (Master Volatility Envelope)
◇ Hybrid Black Swan Zone (static or dynamic)
◇ Classic Divergence Detection Engine (per-TF + Master)
◇ MTF Legend Table with antenna marker
◇ Per-Timeframe RSI Length Customization
◇ Multilingual interface (5 languages) and full visual customization
MULTI-TIMEFRAME RSI FUSION ENGINE
🔹 What It Does
The core of the indicator. For each of the five configured timeframes, an independent RSI reading is extracted at its native resolution. The five readings are then fused into a single Master Line via canonical Fibonacci-proportioned weights.
🔹 Method
The extraction runs via request.security with lookahead=barmerge.lookahead_off to prevent repainting. Per-timeframe RSI uses Wilder's standard formulation. The Master is computed as a weighted average with the following Fibonacci weights:
◇ TF1 (Trigger, default 5m): 0.15
◇ TF2 (Intraday, default 15m): 0.20
◇ TF3 (Macro 1, default 60m): 0.25 (peak weight)
◇ TF4 (Macro 2, default 240m): 0.25 (peak weight)
◇ TF5 (Base, default Daily): 0.15
The peak weight sits on the macro middle TFs (TF3 + TF4), where institutional decisions consolidate. The Master is clamped to the 0–100 RSI range.
🔹 Ghost Line Rendering
Each per-timeframe RSI is plotted as a ghost line with transparency inversely proportional to its absolute distance from the Master. The fade sensitivity is configurable (default 3.5): at distance 0 the line is solid (transparency 20), at ~20 RSI points away it becomes effectively invisible. Synchrony emerges as a visible density property — when the five lines collapse toward the Master, the rainbow is solid; when they spread, the pane fills with translucent ghosts.
ADAPTIVE FIBONACCI CHANNEL
🔹 What It Does
The Master Line is wrapped in an adaptive volatility channel built from its own highest/lowest over a configurable lookback (default 50), EMA-smoothed (default 10). From the channel envelope, four Fibonacci-proportioned zones are derived above and below the channel midpoint:
◇ Z-Breathing (1.50σ proportion) — yellow (high) / green (low)
◇ Z-Alert (1.85σ anchor) — orange (high) / teal (low)
◇ Z-Exhaustion (2.75σ proportion) — red (high) / blue (low)
◇ Black Swan (3.85σ proportion) — purple (high) / aqua (low)
🔹 Why It Matters
The 30/50/70 lines of classic RSI are static — they don't adapt to the volatility regime of the current instrument or timeframe. The Fibonacci channel does. In a low-volatility regime, the Z-Exhaustion zone tightens and the script flags exhaustion at lower thresholds; in a high-volatility regime, the channel widens and only genuine outliers reach the extreme zones. The Master's position within the channel — color-coded continuously — is a regime-aware read on momentum saturation that the fixed 30/70 lines cannot provide.
HYBRID BLACK SWAN ZONE
🔹 What It Does
The Black Swan threshold operates in hybrid mode:
◇ OFF (default): classic 80/20 RSI extremes — the conventional Wilder oversold/overbought boundaries.
◇ ON: dynamic Fibonacci 3.85σ proportion of the Master channel — adapts to current volatility.
🔹 Method
When dynamic mode is enabled, the Black Swan High becomes osc_up4 = dyn_mid + (dist_up × 3.85/1.85), and the Low becomes dyn_mid − (dist_dn × 3.85/1.85). Both are clamped to . The threshold breathes with the channel — wider in volatile regimes, tighter in calm ones.
🔹 Visual Design
Black Swan zones render as a line + proximity-based glow only — NO fill is drawn underneath, by design. This is a hard rule of the indicator's visual grammar: every other zone (Breathing, Alert, Exhaustion) has a fill; Black Swan is line + glow only, making the extreme zone visually distinct from the gradient zones below it.
CLASSIC DIVERGENCE DETECTION ENGINE
🔹 What It Does
Regular divergence (price↔RSI on the same timeframe) is detected independently on each of the 5 timeframes and on the Master line:
◇ Bear divergence (top): price made higher high + RSI made lower high — momentum failing to confirm the new price peak; exhaustion warning.
◇ Bull divergence (bottom): price made lower low + RSI made higher low — momentum failing to confirm the new price trough; accumulation signal.
🔹 Method
Pivot detection runs via ta.pivothigh and ta.pivotlow with a configurable lookback (default 5 bars before and after). For each timeframe, the previous pivot and current pivot are compared on both price and RSI. A divergence is flagged when price and RSI move in opposite directions across the two pivots, gated by na guards to handle cold-start conditions.
🔹 Two Layers of Output
The detection produces two complementary outputs:
◇ Per-TF divergence flags are rendered in the Legend Table 'Div' column (🔺 bull / 🔻 bear / — none, color-coded). This gives granular per-horizon insight: which exact timeframe is showing divergence right now.
◇ Master divergence — the integrated MTF signal — is additionally drawn on the indicator pane as a line connecting the two pivots, with a "🔺 Bull Div Master" or "🔻 Bear Div Master" label at the second pivot. An alert is available (toggleable, ON by default).
🔹 Why Two Layers
Per-TF divergences answer "where is the divergence forming?" — fast TFs (TF1, TF2) often catch local noise; slow TFs (TF4, TF5) catch structurally significant turns. Master divergence answers "is the integrated MTF view showing exhaustion?" — Master fuses all five TFs into one signal weighted by significance, so its divergence is the consolidated read. The strongest setups occur when both layers agree: Master divergence drawn on the chart + multiple Legend Table 'Div' cells lighting up in the same direction.
MTF LEGEND TABLE
🔹 What It Shows
A compact 5-column table renders inside the indicator pane (force_overlay=false for mobile readability), with 8 rows:
◇ Row 0: title header (multilingual)
◇ Rows 1–5: per-timeframe data — color-coded RSI value, timeframe resolution, trend arrow (▲ rising / ▼ falling / ▬ flat with ±0.5 RSI point deadzone to avoid flicker), and classic divergence cell (🔺/🔻/—)
◇ Row 6: Master row — displays "🌈 Master (~XhYm)" where XhYm is the geometric weighted mean of the 5 active timeframes (e.g. ~1h11m for the default 5/15/60/240/D set), with the Master's RSI value, trend arrow, and divergence state
◇ Row 7: MTF Divergence status row — tracks RSI alignment between TF1 and TF5
🔹 Antenna Marker
An antenna marker (📡) appears at the end of the timeframe label on the row whose timeframe matches the chart's native resolution. Start the read at the antenna row — that's your chart's RSI — then scan up to faster TFs and down to slower TFs to see whether they confirm or contradict the current read.
🔹 MTF Divergence Status Row (TF1 ↔ TF5)
Separate from the classic per-TF divergence: the status row at the bottom tracks RSI alignment between the fastest and slowest configured timeframes:
◇ Aligned (TF1 and TF5 in the same zone): trend continuation, no MTF divergence.
◇ Strong Divergence (TF1 ≥ 70 vs TF5 ≤ 30, or mirrored): fast and slow timeframes telling completely opposite stories. Common at major turning points.
◇ Moderate Divergence (TF1 ≥ 65 vs TF5 ≤ 40, or mirrored): partial misalignment between fast and slow.
PER-TIMEFRAME RSI LENGTH CUSTOMIZATION
🔹 What It Does
RSI period defaults to 14 globally — Wilder's canonical setting. Each of the 5 timeframes has an optional length override: zero means inherit the global default, any positive integer means use that period for that timeframe only.
🔹 Why It Helps
Real-world strategies often want different RSI sensitivities at different horizons. Scalpers use 7-9 on the trigger TF for fast signals while keeping 14 on slower TFs for stability. Swing traders use 14-21 on intraday TFs and 21+ on the daily for smoother reads. Connors-style strategies use 2 on the trigger for mean-reversion. The hybrid pattern keeps the settings panel clean for casual users (one input controls all) while letting power users specialize per TF when needed.
MULTILINGUAL INTERFACE
The indicator supports five languages for the HUD display, Legend Table headers, and alert messages: English (default), Português, Español, Русский, and 中文 (Chinese). Code, comments, and configuration tooltips remain in English regardless of the selected language. Tech abbreviations (RSI, MTF, HTF, TF) stay Latin in all language contexts — they are universally recognized in trading and translation would add noise.
For reference, the multilingual coverage includes:
◇ HUD title and all row labels
◇ Trend arrows (universal: ▲▼▬)
◇ Divergence cells (universal: 🔺🔻—)
◇ MTF Divergence status row (Aligned / Strong / Moderate, with Top/Bottom directional labeling)
◇ All alert messages including the new classic divergence alerts
HOW TO USE
This indicator is not a signal generator. It is a structural map: it tells you where RSI sits across multiple horizons, how aligned (or divergent) those horizons are, and where classic price↔RSI divergence is forming.
🔹 Reading the Rainbow
◇ Solid rainbow + Master near equilibrium (30–70 zone): no clear signal. Trending behavior absent.
◇ Solid rainbow + Master in Z-Alert (orange/teal): trend in motion across all horizons. Look for follow-through confirmation.
◇ Solid rainbow + Master in Z-Exhaustion (red/blue): elevated probability of mean reversion. Multiple horizons agreeing on saturation.
◇ Master touches Black Swan (purple/aqua glow): statistically rare overshoot. High-probability reversal setup, especially when the MTF Divergence row also fires Strong.
◇ Ghost lines visibly spread far from Master: synchrony breakdown. Wait for re-convergence before high-conviction entries.
🔹 Reading the Legend Table
◇ Antenna row (📡): your chart's native TF. Start there.
◇ Scan above the antenna: faster TFs. If they're in extremes opposite to the antenna, the local signal is conflicted.
◇ Scan below the antenna: slower TFs. If they're aligned with the antenna, the structural bias confirms.
◇ Master row: the integrated read. The "~XhYm" label tells you where Master sits in the TF spectrum.
🔹 Reading the Classic Divergence Layer
◇ Single TF lit up (e.g. only TF2 shows 🔻): local divergence. Often noise on fast TFs.
◇ Multiple TFs lit up in the same direction: structurally significant. Confluence of divergence across horizons.
◇ Master divergence drawn on chart + 2 or more TFs in same direction: high-conviction reversal setup. The strongest signal this indicator produces.
◇ Divergence appearing on slow TFs (TF4 / TF5) while fast TFs are quiet: often precedes major reversals — slow-horizon participants are pulling away before fast-horizon ones notice.
🔹 Tactical Reading
◇ Master in Z-Alert + MTF status Aligned: with-trend continuation setup.
◇ Master in Z-Exhaustion + Bear Div drawn on chart + 2 TFs 🔻: short setup with multi-horizon confirmation.
◇ Master at Black Swan Low + Bull Div drawn on chart + Strong MTF Divergence (TF1 ≤ 30 vs TF5 ≥ 70 mirrored): rare confluence of multiple exhaustion signals.
INPUTS EXPLAINED
🔹 System Language
Display language for the HUD and alert messages. Options: English (default), Português, Español, Русский, 中文 (Chinese).
🔹 Multi-Timeframe (TF1 to TF5)
Configure each of the five timeframes to scan. Defaults: 5m / 15m / 60m / 240m / Daily. Plus AI Auto-Sync option that adjusts the 5 TFs based on chart resolution.
🔹 Default RSI Length + 5 Per-TF Overrides
Default 14 applied globally; per-TF override is 0 by default (inherit). Set override > 0 to specialize per TF.
🔹 Dynamic Black Swan Mode
OFF (default): static 80/20 thresholds. ON: dynamic Fibonacci 3.85σ proportion of the Master channel.
🔹 Dynamic Channel Lookback + Smoothing
Lookback for highest/lowest of Master (default 50). EMA smoothing applied to the channel envelope (default 10).
🔹 Divergence Pivot Lookback
Lookback (bars before/after) for the classic divergence pivot detection. Default 5 — matches most community divergence indicators.
🔹 TF Colors + Show/Hide Toggles
Color and visibility for each of the 5 ghost lines. Hiding a TF does NOT remove it from the Master fusion — the calculation continues; visibility is purely visual.
🔹 Ghost Fade Sensitivity
Higher = ghost lines fade more aggressively as they diverge from the Master. Default 3.5 (invisible at ~20 RSI points apart).
🔹 Show Master Line / Fills / Black Swan / Channel / Legend Table / Static Levels / Div Column / Div Chart Line
Independent toggles for each visual layer.
🔹 Legend Table Position + Font Sizes
Position of the table (four corners) and separate font sizes for data rows and label rows.
🔹 Alert Toggles
Master crosses Black Swan High / Low — fires when Master crosses the threshold.
Strong MTF Divergence — fires when TF1 vs TF5 enter opposite extremes.
Master enters Z-Exhaustion — fires when Master enters the red/blue zone (OFF by default to avoid overlap with Black Swan alerts).
Master Classic Divergence — fires when classic bear or bull divergence is detected on the Master line (ON by default).
IMPORTANT NOTES
The MTF RSI Synchrony works on any timeframe. The default radar configuration (5m/15m/60m/240m/D) is calibrated for intraday and swing trading on liquid instruments. For position trading or scalping, the radar timeframes can be reconfigured to scan longer or shorter horizons respectively, or AI Auto-Sync can be enabled to let the engine pick automatically.
The script makes 10 request.security calls in total (5 for the RSI extraction + 5 for the per-TF divergence detection). On low-volatility chart resolutions or weaker hardware, chart load may take a moment longer than for a single-TF RSI; this is expected and normal.
Alerts fire once per confirmed bar (alert.freq_once_per_bar + barstate.isconfirmed gating). Historical bars never repaint after they close. The live bar updates intra-bar as expected for a real-time indicator.
The Fibonacci channel calibration (ratios 1.50 / 1.85 / 2.75 / 3.85) is the canonical Rainbow Matrix ratio set, also used in other portfolio scripts for consistency.
Pine Script v6. Open-source under Mozilla Public License 2.0.
UNIQUENESS
The MTF RSI Synchrony is unique in three ways. First, it performs RSI extraction across five timeframes simultaneously via request.security with Fibonacci-proportioned weights — the integrated Master Line is not a smoothed version of one TF but a true weighted fusion of five independent RSIs, with peak weight on the macro middle TFs where institutional decisions consolidate. Second, the per-timeframe RSIs are rendered as fade-by-distance ghost lines around the Master, transforming synchrony itself into a visible density property — when the timeframes align the rainbow is solid, when they diverge the ghost lines spread visibly across the pane, without requiring the trader to read numbers. Third, the classic divergence detection runs in parallel on each of the 5 timeframes plus the Master line, producing two complementary outputs: a per-TF Legend Table column for granular per-horizon insight and a Master-line chart visual (line connecting pivots + label) for the integrated MTF signal. The combination of weighted multi-timeframe fusion, density-based synchrony visualization, and two-layer divergence detection produces a structural map of RSI behavior that single-timeframe RSI indicators cannot provide — particularly at decision points where multiple horizons converge or where slow-horizon divergences emerge before they reach fast-horizon attention. Indicator
AetherEdge - Generative Flow Synthesizer🖊️ Overview
The Generative Flow Synthesizer is a path-synthesis engine inspired by the principles of a Variational Autoencoder (VAE), learning the market's "generative distribution." It compresses past price action into a low-dimensional latent distribution, samples latent variables via the reparameterization trick, and synthesizes multiple future price paths from them. Unlike conventional tools that draw a single forecast line, it renders the very spread of plausible futures as a stream of generated samples flowing forward like particles.
🔶 Key Features
VAE-inspired generative model: encode (latent compression) → sample (reparameterization) → decode (path expansion)
Reparameterization trick: latent sampling via z = μ + σ·ε (identical math to a real VAE)
Central predicted flow: a deterministic mean path generated from the latent mean
Multiple generated sample paths: stochastic draws from the latent distribution stream forward like particles
Generative confidence band: a ±σ uncertainty envelope widening each step
Online-learned latent distribution: drift, volatility, and autocorrelation adapt via EWMA
Sampling temperature: control future spread from conservative to bold
Mean-reversion strength: tune from pure random walk to convergent paths
Generative/fluid palettes (Plasma Flow et al.) with particle fade toward the horizon
🧠 Technical Architecture
This tool is a translation that realizes the VAE's mathematical core within Pine, which lacks autodiff. The encoder extracts sufficient statistics from log returns — drift (mean), volatility (standard deviation), and autocorrelation (persistence) — and online-learns the latent distribution parameters (μ, logσ²) via EWMA, a Pine realization of the posterior an encoder network would learn.
The sampling stage is identical to a real VAE, drawing latent variables through the reparameterization trick z = μ + σ·ε (ε a standard normal via Box–Muller). The decoder expands each latent sample into a forward price path through a mean-reverting stochastic process r_t = z + φ·(r_{t-1} − z) + σ·temp·ε_t. Because each path uses its own random sequence, they diversify like particles. The central predicted flow is the deterministic mean path with the noise term removed; the confidence band is the ±σ envelope built from accumulated step variance.
⚙️ Recommended Settings & Tuning Guide
Tuned with crypto in mind. On BTC and ETH, Encoder Window 60 and Generation Horizon ~24 are a starting point. Sampling Temperature is the generative core — below 1 yields narrow, conservative futures; above 1, wide, bold exploration. In trends, lower Mean-Reversion Strength for freer paths; in ranges, raise it for convergent paths, matching the possibility distribution to market character. Number of Sample Paths trades visual richness against compute; ~12 is a good balance.
💡 How to Use in Practice
The central predicted flow serves as the model's most average future trajectory for reading trend bias. The spread of the sample paths (particle scatter) expresses uncertainty itself — tight scatter signals clear direction, wide scatter a hard-to-predict regime. The confidence band width offers an objective reference for stop placement and target setting. For multi-timeframe trading, pair a higher-timeframe generative flow with a lower timeframe for timing.
⚠️ Important Notes
This tool is VAE-inspired, not a true backprop-trained neural-network VAE; within Pine's constraints it reproduces the VAE's core principles in a feasible form. Generated paths are samples from a learned distribution, not predictions of the future — purely a visualization of the spread of possibilities. Generation occurs only on the last bar and does not repaint confirmed history. Learning the latent distribution requires accumulated data and cannot overcome the fundamental constraint of market predictability.
🚨 Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial or investment advice. No generated path guarantees future prices, and past performance does not indicate future results. All trading decisions are made at your own risk. Indicator
Impulse RSI - TobbySimardOverview
Impulse RSI is a custom oscillator that combines two classical concepts — momentum and the Relative Strength Index — into a single, unified reading. Rather than applying RSI to raw price as traditionally done, this indicator applies RSI mathematics directly to price momentum, creating a smoother and more context-aware measure of trend strength and direction. The result is a 0–100 bounded oscillator that tells you not just whether price is moving, but how much conviction sits behind that move.
How It Works
The calculation happens in three stages. First, raw momentum is measured by subtracting the price N bars ago from the current price, capturing how far price has traveled over your chosen lookback window. Second, the bar-to-bar acceleration of that momentum is computed — essentially measuring whether momentum is speeding up or slowing down. Third, Wilder's smoothing (RMA) is applied to the gains and losses of that acceleration, exactly as a standard RSI would, producing a normalized value between 0 and 100. That raw value is then smoothed with an EMA to create the final signal line you see plotted on the chart.
The key distinction from a traditional RSI is that this indicator measures the strength of momentum change, not price change. This makes it particularly sensitive to trend shifts and sustained directional moves.
The 50 Line & Direction
The 50 level is the central axis of the indicator and the most important reference point. When the signal is above 50, the indicator considers the market to be in a bullish state. When below 50, bearish. This binary directional read is also available in the Data Window as the Direction value, outputting 1 for bullish, -1 for bearish, and 0 when exactly at the midline.
Zone System
The oscillator is divided into four distinct zones, each with its own color, giving you an immediate visual read of where strength currently sits.
Zone 1 (30–40) — Red represents weak or deteriorating bearish momentum. Zone 2 (40–50) — Blue is the bearish side but showing signs of hesitation or recovery. Zone 3 (50–60) — Green is the bullish side with moderate strength. Zone 4 (60–70) — Orange reflects elevated bullish momentum and stronger conviction.
These zones are filled directly on the oscillator panel, and if bar coloring is enabled, the chart candles themselves will reflect whichever zone the signal currently occupies, giving you an at-a-glance trend context directly on your price chart without needing to look down at the indicator.
Entry Signal
Beyond simple directional bias, the indicator includes a rising signal confirmation layer. A long entry is only highlighted when two conditions are simultaneously true — the signal must be above 50 (bullish direction), and it must be higher now than it was N bars ago, confirming that the signal is actively climbing rather than simply sitting above the midline. This filters out flat or stalling bullish conditions and focuses attention on moments where momentum is genuinely building. The lookback period for this confirmation is fully adjustable, allowing you to require either a short-term or long-term rising confirmation depending on your trading style.
When enabled, these entry conditions are highlighted directly on your price chart as a background color, making them easy to spot without any manual analysis.
Alerts
A comprehensive set of alerts is built in to support both discretionary and automated trading workflows. You can be notified when the signal crosses above or below 50 for general directional conditions, when a confirmed long entry triggers, when the signal crosses into any of the four zones, and when the signal recovers from a lower zone or pulls back from a higher one. This covers the full spectrum of scenarios from trend initiation to zone transitions.
Settings
All key parameters are adjustable. The Momentum Length controls how far back the raw price momentum is measured. The RSI Length controls the smoothing applied to the acceleration gains and losses. The Signal Length controls the EMA smoothing on the final output. The Signal Lookback in the Rising Signal group controls how many bars back the indicator looks when confirming the signal is rising. Zone colors, bar coloring, and entry highlighting are all fully customizable to fit your chart setup. Indicator
Indicator
Wyckoff Pattern Indicator-AlmostPerfectWyckoff Pattern Indicator — Accumulation & Distribution Phase Tracker
Overview
This indicator automatically identifies **Wyckoff market phases** in real time and plots **BUY, SELL, and HOLD signals** directly on the chart. It works on all timeframes and all instruments (stocks, indices, crypto, forex, commodities).
The Wyckoff Method, developed by Richard Wyckoff in the early 1900s, is one of the most enduring frameworks in technical analysis. It describes how large institutional operators ("Composite Operator") accumulate or distribute positions within a trading range before the next major price move. This indicator brings that logic into a structured, automated form.
How It Works
#### Phase Detection
Every bar is scored across six independent factors:
| Factor | Favours Accumulation | Favours Distribution |
|---|---|---|
| Price position in range | Lower 35% | Upper 65% |
| Long-term trend (EMA 50 vs 200) | Below EMA 200 | Above EMA 200 |
| Consolidation (low realised volatility) | In range | In range |
| Volume dry-up inside range | Yes | Yes |
| RSI | Below 50 | Above 50 |
| MACD histogram slope | Rising | Falling |
A 3-bar consecutive confirmation is required before the phase is declared. This debounce prevents single-bar RSI or MACD wobbles from flipping the phase flag and causing false signals.
Wyckoff Schematic Events Detected
| Label | Event | What it means |
|---|---|---|
| **SC** | Selling Climax | Wide bearish bar on high volume at period low — panic selling exhausted |
| **BC** | Buying Climax | Wide bullish bar on high volume at period high — euphoric buying exhausted |
| **SP** | Spring | Price dips below support then snaps back — a trap for weak hands |
| **UTAD** | Upthrust After Distribution | Price pierces resistance then fails — a bull trap |
| **SOS** | Sign of Strength | Wide up-bar on rising volume breaking short-term resistance |
| **SOW** | Sign of Weakness | Wide down-bar on rising volume breaking short-term support |
| **LPS** | Last Point of Support | Low-volume pullback during mark-up — healthy retest |
| **LPSY** | Last Point of Supply | Low-volume rally during mark-down — weak bounce |
Phase Progression (A → E)
Accumulation Phases
- **Phase A** — Stopping the downtrend (SC, Preliminary Support)
- **Phase B** — Building a cause (secondary tests, range establishing)
- **Phase C** — The spring / shakeout test (potential final trap)
- **Phase D** — Mark-up begins (SOS, LPS sequence)
- **Phase E** — Trending higher out of the trading range
**Distribution Phases**
- **Phase A** — Stopping the uptrend (BC, Preliminary Supply)
- **Phase B** — Building a cause for decline (secondary tests)
- **Phase C** — UTAD / upthrust test (bull trap)
- **Phase D** — Mark-down begins (SOW, LPSY sequence)
- **Phase E** — Trending lower out of the trading range
A label appears **once on the chart at the exact bar the phase transitions** — not on every bar — so the chart stays clean.
Signals
Signals fire only on the **first bar of a new signal state**, not continuously. They will never contradict the phase:
- **▲ BUY** (green) — Fires during Accumulation Phase C or D, on a Spring, or on an LPS. **Completely suppressed during Distribution.**
- **▼ SELL** (red) — Fires during Distribution Phase C or D, on a UTAD, or on an LPSY. **Completely suppressed during Accumulation.**
- **◆ HOLD** (yellow) — Fires when entering Phase B consolidation on either side, or when the range is ambiguous. Means: wait for confirmation.
Supply & Demand Zones
Two shaded bands track the current phase's trading range in real time:
- **Red band (Supply Zone)** — upper boundary of the current phase range
- **Green band (Demand Zone)** — lower boundary of the current phase range
The bands use `plot()` + `fill()` (not static boxes) so they move correctly with any chart pan, zoom, or scroll on all scale modes.
Info Table (top-right)
A live dashboard shows:
- Current major phase (Accumulation / Distribution / Neutral)
- Sub-phase (A through E)
- Active signal
- Volume condition (Climax / Dry-Up / Normal)
- Long-term trend
- RSI reading
- Consolidation / Trending status
- Raw Accumulation and Distribution scores
Settings
| Setting | Default | Description |
|---|---|---|
| Lookback Period | 50 | Bars used to define the trading range high/low |
| Volume Climax Multiplier | 1.8× | How many times avg volume = climax |
| RSI Length | 14 | RSI period |
| Phase Background | On | Blue/red background shading per phase |
| Show Wyckoff Events | On | SC, BC, SP, UTAD, SOS, SOW markers |
| Show Buy/Sell Signals | On | BUY / SELL / HOLD labels |
| Show Phase Labels | On | Phase transition labels on candles |
| Show Supply/Demand Zones | On | Red/green zone bands |
| Show EMAs | On | EMA 20 / 50 / 200 |
Alerts
Nine alert conditions are built in:
- Wyckoff BUY / SELL / HOLD
- Spring detected
- UTAD detected
- Selling Climax / Buying Climax
- Sign of Strength / Sign of Weakness
Important Notes
- This indicator is based on **pattern recognition and scoring**, not exact Wyckoff schematic fitting. It is a decision-support tool, not a mechanical trading system.
- Always confirm signals with **volume context** and **broader market structure** before trading.
- On lower timeframes (1m–5m), increase the Lookback Period to reduce noise.
- On higher timeframes (Daily+), the phase transitions are more reliable and slower-moving.
---
*Based on the Wyckoff Market Cycle framework developed by Richard D. Wyckoff (1873–1934).*
Indicator
RSI Dip + EMA Trend Long DCA - IndicatorRSI Dip + EMA Trend Long DCA — Leveraged Indicator
🔷 What it does:
This is a signal-only indicator that mirrors a leveraged dip-buying DCA workflow on crypto perpetuals. It tracks one virtual long position at a time, opened only when an oversold dip and an uptrend confirmation align across two lower timeframes. The indicator manages up to four safety orders as price ladders lower, and exits via three independent paths: take profit with trailing, hard stop loss, or a forced close after a maximum holding period. Every event emits a webhook-ready JSON payload tailored for a DCA Bot configured for leveraged futures.
- Dual confirmation entry: RSI(12) crossing down 35 on 5m AND EMA(50) > EMA(100) on 15m.
- Soft-compounding safety ladder: 4 SOs at 1.05× margin progression, deviations 1.00%, 2.20%, 3.64%, 5.37%.
- Three-exit architecture: 1.0% Take Profit with 0.1% trailing, 9% hard Stop Loss, 3-day Max Hold timeout.
- Default leverage 25×, configurable from 1× upward.
- Honest virtual bookkeeping: total notional and qty updated per fill, avg entry / open PnL displayed live.
🔷 Who is it for:
- Active traders running a DCA Bot on leveraged crypto perpetuals who want a systematic dip-buying engine.
- Bot operators who want a chart-driven signal source with per-event JSON ready for a DCA Bot.
- Traders who want to monitor an evolving leveraged position — base entry, owned SO levels, deployed notional, open PnL, time-to-max-hold — directly on the chart.
- Operators comfortable with portfolio-level drawdowns in the 15–20% range in exchange for accelerated returns.
🔷 How does it work:
Entry RSI Filter (Oversold Dip): A 5-minute RSI(12) is sampled via request.security with lookahead disabled. The dip gate fires when RSI crosses down through 35 — momentum has rolled over into oversold.
EMA Trend Filter: A 15-minute EMA(50) and EMA(100) are sampled in parallel. The trend gate is satisfied only while Fast EMA > Slow EMA — broader trend is up. When the EMA cross flips, the dip signal alone cannot open a virtual position.
Entry: When both gates align at host-bar close, the indicator marks a virtual long entry, captures the base entry price, seeds the cost-basis ledger with base margin × leverage notional, and fires the entry webhook payload.
Safety Order Ladder: After base fill, the indicator monitors close price downward against the position. When close reaches base entry × (1 − cumulative deviation), the k-th SO is marked filled, cost-basis is updated, and the SO webhook payload is fired. No additional gating on the SO ladder — pure price.
Honest Virtual Bookkeeping: Total notional and qty are updated incrementally on every event, so the avg entry, deployed notional, and open PnL displayed in the status table reflect the actual broker-equivalent position state — no shortcut from base entry, no synthetic averaging.
Exit Priority: Three exits evaluated in order on each bar: (1) Stop Loss at 9% below average entry, (2) Maximum Hold timeout from base entry, (3) Take Profit at 1.0% above average entry with 0.1% trailing — once price reaches the TP target, the position closes only after a 0.1% retrace from the in-favor peak.
🔷 Why it's unique:
- Two-Layer Confirmation: RSI dip on 5m for timing, EMA stack on 15m for trend bias. The two filters operate on different scales — momentum exhaustion alone cannot fire a signal against a confirmed downtrend, and trend alignment alone cannot fire outside a tactical entry window.
- Three-Exit Architecture: Most DCA tools use one or two exit conditions. This indicator handles all three failure modes explicitly — hard tail-risk stop, stuck-trade timeout release, and momentum-trailing winner exit.
- Leverage-Aware Sizing: Margin and leverage are independent inputs. The virtual ledger tracks notional position, so the avg-entry line and open PnL reflect the leveraged broker state, not unleveraged cash-only math.
- Per-Event Webhook Ledger: Up to seven distinct events per cycle (entry + 4 SO fills + close + max-hold/SL), 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 perpetuals on 15m. Default thresholds are calibrated for XMRUSDT.P 15m. Different pairs may need EMA period and RSI threshold tuning.
Leverage Warning: The default 25× leverage is aggressive. The companion strategy's backtest at default settings produced 18.01% maximum drawdown — substantially above the 5–10% per-trade band, although that figure reflects portfolio-level accumulation across 779 trades, not single-trade risk. Lower the leverage input to dial down portfolio-level drawdown proportionally.
Cross Detection Granularity: Entries and SO 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.
No SO Condition: Safety orders fire on pure price ladder with no momentum gate — averaging continues unconditionally as price drops, until SL, MaxHold, or price reversal. Higher average-entry quality in shallow dips; greater unrealized exposure on sharp drops.
Maximum Hold Timeout: The 3-day forced close exists to release capital from stuck trades. The indicator dispatches a close webhook the moment the timeout fires — verify the receiving DCA Bot accepts unconditional close commands.
Funding Rates (Perpetuals): The indicator does not account for perpetual funding rates. Sustained negative funding improves live performance for this long strategy; sustained positive funding degrades it. Review the historical funding pattern before live deployment.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester. For performance metrics over a 14-month sample (~779 closed trades, 74.07% win rate, 18.01% max drawdown, profit factor 1.313, +30.79% net return), use the companion strategy version on identical parameters.
🔷 How to Use It:
🔸 Add the indicator to a 15m chart on the leveraged perpetual pair you want to trade.
🔸 Review the entry filters (RSI on 5m, EMA stack on 15m), the 4-SO ladder, and the three exit conditions. Defaults are calibrated for XMRUSDT.P 15m at 25× leverage — recalibrate per asset and per risk tolerance before deploying.
🔸 Set leverage and base margin to match your exchange and account configuration. Lower leverage scales portfolio-level drawdown proportionally.
🔸 In the DCA Bot Webhook group, paste the Bot ID, Email Token, and Pair (QUOTE_BASE format, e.g., USDT_XMR).
🔸 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 safety order, and all three close types — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Margin (USDT): Margin per base trade. Notional = Margin × Leverage. Used for the virtual avg-entry / open-PnL computation.
Leverage (×): Exchange leverage. Default 25×.
Max Safety Orders: Maximum number of safety orders per cycle (default 4).
First SO Margin (USDT): USDT margin of the first safety order; subsequent SOs scale by the Size Multiplier.
Step to First SO (%): Distance from base entry at which SO1 becomes eligible.
Step Multiplier: Ladder factor that widens each subsequent deviation step.
Size Multiplier: Factor that grows each subsequent safety order's USDT margin.
Entry RSI Timeframe / Length / Level: Lower-timeframe RSI oversold-dip filter.
EMA Timeframe / Fast / Slow: Higher-timeframe trend confirmation filter.
Take Profit (%) / Trailing Deviation (%): TP target above avg entry and trailing buffer.
Stop Loss (%): Hard stop below avg entry.
Force Close After Max Hold / Max Hold (seconds): Timeout for forced market close.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle SO Ladder, Avg / TP / SL plot lines, fill labels, signal triangles, 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. Indicator
RSI Dip + EMA Trend Long DCA - StrategyRSI Dip + EMA Trend Long DCA — Leveraged Strategy
🔷 What it does:
This is a long-only DCA strategy on leveraged crypto perpetuals that buys oversold dips inside confirmed uptrends. A long entry opens only when the lower-timeframe RSI crosses down into oversold territory AND a higher-timeframe EMA cross confirms the larger trend is up. Four safety orders form a pure-price deviation ladder. Exit is a tight Take Profit with trailing, OR a hard Stop Loss, OR a forced close after a maximum holding period.
- Single base order with up to four safety orders, soft 1.05× size compounding.
- Dual confirmation entry: RSI(12) crossing down 35 on 5m AND EMA(50) > EMA(100) on 15m.
- Three exit paths: 1.0% Take Profit with 0.1% trailing, 9% hard Stop Loss, or forced market close after 3 days max hold.
- Default leverage 25× — per-trade realized risk ~7.17% of equity (inside the 5–10% band).
- Every entry, safety order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
🔷 Who is it for:
- Active traders comfortable with leveraged crypto perpetuals who want a systematic dip-buying engine inside confirmed uptrends.
- Bot operators who want a chart-driven signal source with per-event JSON ready for a DCA Bot configured for leveraged futures.
- Traders looking to combine momentum exhaustion (RSI dip) with trend confirmation (EMA stack) for higher-confidence entries.
- Portfolio operators who can absorb a 15–20% maximum drawdown in exchange for ~30% trailing returns over comparable periods.
🔷 How does it work:
Entry RSI Filter (Oversold Dip): A 5-minute RSI(12) is sampled via request.security with lookahead disabled. The dip gate fires when RSI crosses down through 35 — momentum has rolled over into oversold, which on a confirmed uptrend often marks a tactical bounce point.
EMA Trend Filter: A 15-minute EMA(50) and EMA(100) are sampled in parallel. The trend gate is satisfied only while Fast EMA > Slow EMA — the broader trend is up. When the EMA cross flips, the dip signal alone cannot open a trade.
Entry: When both gates align at host-bar close, a long position opens. Base order is configurable as Market (default) or Limit. With default 25× leverage, base margin × leverage = notional position size.
Safety Order Ladder: After base fill, the strategy monitors price deviation downward against the position. No additional gating — pure price ladder. The k-th safety order fires when close ≤ base entry × (1 − cumulative deviation), where cumulative deviation grows by the step multiplier (default 1.2): 1.00%, 2.20%, 3.64%, 5.37%. Each safety order's USDT margin grows by 1.05× — soft compounding.
Exit Priority: Three exit paths evaluated in order on each bar: (1) Stop Loss at 9% below average entry, (2) Maximum Hold timeout at 3 days from base entry, (3) Take Profit at 1% above average entry with 0.1% trailing — once price reaches the TP target, the position closes only after a 0.1% retrace from the in-favor peak.
🔷 Why it's unique:
- Two-Layer Confirmation: RSI(12) dip on 5m for entry timing, EMA(50/100) on 15m for trend bias. The two filters operate on different scales — momentum exhaustion alone cannot open a trade against a confirmed downtrend, and trend alignment alone cannot open a trade outside a tactical entry window.
- Three-Exit Architecture: Hard Stop Loss for tail-risk protection, Maximum Hold timeout for stuck trades that don't reach either bound, and Take Profit with trailing for letting winners run. Most DCA strategies use one or two exits; this one explicitly handles all three failure modes.
- Leverage-Aware Sizing: Base margin and leverage are independent inputs. Margin sets the per-trade capital commitment; leverage sets the notional exposure. Per-trade risk at SL = base + SO margins × SL% — bounded and predictable.
- DCA Bot Integration: Every event (base, SO 1–4, TP/SL/MaxHold close) 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.
🔷 Considerations Before Using the Strategy:
Market & Timeframe: Defaults are calibrated for BYBIT:XMRUSDT perpetual on 15m. The dip-buying-in-uptrend logic is portable to other liquid crypto perpetuals with clear directional regimes, but the EMA periods and RSI thresholds should be reviewed before redeployment.
Leverage Warning: The default 25× leverage is aggressive. A 9% adverse price move at 25× leverage equals 225% of base margin — the Stop Loss closes the position at full margin loss before liquidation. The per-trade realized risk at SL is approximately 7.17% of equity at default base margin (60 USDT). Lower the leverage input or reduce base margin to dial down per-trade exposure.
Drawdown Profile: The backtest produced a 18.01% maximum equity drawdown over a 14-month sample with 779 closed trades. This is above PulseWire's typical 5–10% per-trade band — but the figure reflects portfolio-level accumulation of losing trades across an adverse period, not single-trade risk. Per-trade risk remains inside the 5–10% band; the portfolio-level DD reflects the leveraged compounding and should be sized accordingly within a diversified strategy mix.
No SO Condition: Safety orders fire on pure price ladder with no momentum gate. This means averaging continues unconditionally as price drops, until either SL fires or the price reverses. The trade-off: higher average-entry quality if the dip continues, but greater unrealized loss exposure during sharp drops.
Maximum Hold Period: The 3-day forced close exists to release capital from stuck trades that haven't reached TP or SL. On a 15m chart, this is approximately 288 bars. Adjust the timeout to match your strategy rotation cadence.
Funding Rates (Perpetuals): Backtests do not account for perpetual funding rates. Sustained negative funding (shorts pay longs) improves live performance for this long strategy; sustained positive funding degrades it. Review the historical funding pattern before live deployment.
Demo Testing: Always demo-test before going live. Past results do not guarantee future performance, especially on leveraged strategies where small parameter changes materially affect risk.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:XMRUSDT.P (Perpetual)
Timeframe: 15M
Test Period: April 1, 2025 — May 26, 2026 (~14 months).
Initial Capital: 10,000 USDT.
Order Size per Trade: 60 USDT margin × 25× leverage = 1,500 USDT notional base + 4 safety orders at 1.05× progression.
Max Capital Deployed (Margin): ~318.6 USDT per trade across base + 4 SOs.
Max Realized Loss per Trade: ~717 USDT at full ladder + SL (~7.17% of equity).
Commission: 0.05% per trade.
Slippage: 3 ticks.
Leverage: 25× (configurable).
Margin for Long Positions: 100%.
Indicator Settings: Default Configuration.
Base Order: 60 USDT margin, Market by default (Limit toggle available).
Take Profit: 1.0% above average entry with 0.1% trailing.
Stop Loss: 9% below average entry (hard close).
Max Hold: 3 days (259,200 seconds) — forced market close.
Entry Filter: 5m RSI(12) Crossing Down 35 AND 15m EMA(50) > EMA(100).
Safety Orders: 4, Deviation 1.0%, Deviation Step 1.2×, Size Multiplier 1.05×.
Strategy: Long Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +3,078.80 USDT (+30.79%)
Max Equity Drawdown: 2,013.77 USDT (18.01%)
Total Closed Trades: 779
Percent Profitable: 74.07% (577 / 779)
Profit Factor: 1.313
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Margin, Leverage, entry filter (RSI level on 5m, EMA periods on 15m), the 4-SO ladder, and the three exit conditions. Defaults are calibrated for XMRUSDT.P 15m at 25× leverage — recalibrate per asset and per risk profile before deploying.
🔸 Results Review: Run a full-period backtest and confirm Max Drawdown stays inside your personal risk band. The 18% DD at default settings reflects 25× leverage — lower the leverage input to scale risk down proportionally. Validate the closed-trade count (≥ 100 minimum is a comfortable statistical floor).
🔸 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 safety order, and all three exit types — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Margin (USDT): Margin per base trade. Notional = Margin × Leverage.
Leverage (×): Exchange leverage. Default 25× — adjust to match your account configuration.
Use LIMIT for Base: Toggle between Market (default) and Limit at bar close.
Max Safety Orders: Maximum number of safety orders per deal (default 4).
First SO Margin (USDT): USDT margin of the first safety order; subsequent SOs scale by the Size Multiplier.
Step to First SO (%): Distance from base entry at which SO1 becomes eligible.
Step Multiplier: Ladder factor that widens each subsequent deviation step.
Size Multiplier: Factor that grows each subsequent safety order's USDT margin.
Entry RSI Timeframe / Length / Level: Lower-timeframe RSI oversold-dip filter.
EMA Timeframe / Fast / Slow: Higher-timeframe trend confirmation filter.
Take Profit (%) / Trailing Deviation (%): TP target above avg entry and trailing buffer.
Stop Loss (%): Hard stop below avg entry.
Force Close After Max Hold / Max Hold (seconds): Timeout for forced market close.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle SO Ladder, Avg / TP / SL 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.
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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
