Indicator
Everex Lite (Effort vs Result Participation)Everex Lite is a streamlined Effort vs Result participation indicator inspired by the original RedK Everex concept.
The indicator measures the relationship between market participation (effort) and price movement (result) to help traders visualize how efficiently price is moving through the auction.
Rather than focusing solely on volume or momentum, Everex Lite evaluates whether price progress is being supported by participation. This can help identify conditions such as:
• Strong participation supporting directional movement
• Absorption and stalled auctions
• Weakening momentum
• Thin liquidity moves
• Potential shifts in participation strength
Everex Lite intentionally removes several components from the original implementation to create a cleaner and easier-to-read display. The result is a lightweight tool that focuses on the core Rate of Flow (ROF) model and Signal Line while reducing visual clutter.
Features:
• Simplified Rate of Flow (ROF) calculation
• Optional Line or Histogram display modes
• Configurable Signal Line
• Multiple moving average types (WMA, EMA, SMA, HMA, RMA)
• Optional participation levels
• Clean, lightweight design
This indicator is best used alongside market structure, VWAP, volume profile, support/resistance levels, and Auction Market Theory concepts.
Everex Lite is not designed as a standalone buy or sell signal. Instead, it provides additional context regarding participation and price efficiency to help traders better understand the auction taking place beneath the chart.
Credits:
This indicator is a simplified derivative of the original RedK Everex indicator. Full credit for the original Effort vs Result implementation belongs to RedK.
If you find the indicator useful, please leave a like and share your feedback. Indicator
MTF MA & MACD & StochRSI (pro)Multi-Timeframe MA & MACD & StochRSI (Pro)
The Multi-Timeframe MA & MACD & StochRSI (Pro) is a professional multi-timeframe confluence dashboard built to help traders quickly identify trend direction, momentum strength, and cross-timeframe alignment in one clean visual layout.
This tool combines Moving Averages, MACD logic, and StochRSI cross conditions across multiple timeframes, allowing traders to reduce chart clutter and improve decision-making without constantly switching between charts.
Designed for traders who rely on confluence, top-down analysis, and momentum confirmation.
Core Purpose
This indicator answers one key trading question:
Are my moving averages, momentum, and oscillator signals aligned across multiple timeframes?
By tracking multiple confirmations together, traders can identify stronger trend setups while filtering weaker or conflicting market conditions.
Multi-Timeframe Dashboard
The dashboard scans and displays data across:
1 Minute
5 Minute
15 Minute
1 Hour
4 Hour
1 Day
1 Week
This provides both short-term and higher-timeframe market alignment.
Core Features
1) Multi-Timeframe Moving Average Analysis
The indicator tracks:
20 EMA
50 EMA
For each timeframe it checks whether price is:
Above EMA → Bullish bias
Below EMA → Bearish bias
This gives a quick directional read of market structure.
2) MACD Confirmation Logic (Enhanced)
Unlike a basic MACD crossover, this version uses stricter logic for stronger confirmation.
Buy Condition
Histogram > 0
MACD Line > 0
Signal Line > 0
Sell Condition
Histogram ≤ 0
MACD Line ≤ 0
Signal Line ≤ 0
Neutral
If momentum is mixed, the dashboard displays Neutral.
This helps remove weaker crossover noise and improves momentum quality.
3) StochRSI Cross Confirmation
The dashboard tracks StochRSI cross alignment using:
RSI calculation
Stochastic range
Smoothed %K line
Smoothed %D line
Buy
%K > %D
Sell
%K < %D
Neutral
Flat or undefined conditions
This adds momentum confirmation beyond moving averages.
4) Non-Repainting Multi-Timeframe Logic
The script uses stable request.security() calls with completed timeframe bars to reduce repainting behaviour and improve consistency.
Useful for traders who want cleaner higher-timeframe confirmation.
5) On-Chart Moving Average Overlay
In addition to the dashboard, the indicator plots:
Current timeframe 20 EMA
Current timeframe 50 EMA
These allow traders to visually track trend support/resistance directly on price.
6) Weekly MA Overlay
Optional higher-timeframe moving averages can also be shown directly on the active chart:
Weekly 20 EMA
Weekly 50 EMA
This helps identify:
Macro trend direction
Dynamic support/resistance
Higher timeframe bias
Confluence zones
Can be toggled ON/OFF in settings.
7) Adjustable Table Text Size
The dashboard supports text scaling for cleaner viewing:
Tiny
Small
Normal
Large
Huge
Useful for different monitor sizes and chart layouts.
Colour Logic
Green
Bullish / Buy
Price above EMA
Positive MACD alignment
StochRSI Buy condition
Red
Bearish / Sell
Price below EMA
Negative MACD alignment
StochRSI Sell condition
Grey
Neutral / Mixed
No strong directional bias
This allows fast visual scanning across all timeframes.
Best Used For
This indicator is ideal for:
Multi-timeframe trend analysis
Momentum confirmation
Confluence trading
Swing trading
Intraday trading
Scalping
Breakout confirmation
Trend-following systems
Works well on:
Crypto
Forex
Indices
Stocks
Commodities
How to Use It
Step 1 – Check EMA Alignment
Look for price above or below the 20 and 50 EMA across multiple timeframes.
Step 2 – Confirm MACD Strength
Check whether MACD is fully aligned (not just crossing).
Step 3 – Confirm StochRSI Direction
Look for %K vs %D agreement.
Step 4 – Find Confluence
The strongest setups often occur when:
MA structure aligns
MACD aligns
StochRSI aligns
Higher timeframe bias supports the trade
Trading Framework Example
A strong bullish setup might show:
Price above 20 EMA
Price above 50 EMA
MACD Buy
StochRSI Buy
Weekly MA acting as support
A strong bearish setup may show the inverse.
Summary
Multi-Timeframe MA & MACD & StochRSI (Pro) is a high-confluence dashboard built for traders who want cleaner multi-timeframe trend analysis, stronger momentum confirmation, and faster market alignment in one professional workflow. Indicator
Volatility Rotation Compass [ZOM]Volatility Rotation Compass is a lower-pane regime and momentum-rotation tool built from a combination of Vortex directional spread, Choppiness Index, and normalized volume z-score. The goal is to separate directional expansion from low-quality chop instead of treating every oscillator move through zero as equally useful.
The core calculation starts with the Vortex Indicator. The script compares positive and negative Vortex movement to estimate which side is controlling directional flow. That directional spread is then scaled by a trendiness factor derived from Choppiness Index: lower chop values give more weight to directional movement, while higher chop compresses the compass score. A normalized volume z-score is used as a participation filter so stronger readings are favored when volume is above its recent baseline.
The main compass oscillator is plotted around a zero line. Teal/green histogram pressure represents bullish expansion, rose/crimson pressure represents bearish expansion, and amber/gray behavior represents indecision, chop, or weakening participation. Subtle background shading shows the active regime so the lower pane can be read quickly without turning the chart into clutter.
Bull rotation markers appear when the compass pushes above the bullish threshold while chop falls and volume confirms participation. Bear rotation markers appear when the compass pushes below the bearish threshold under similar trend and participation conditions. Exhaustion dots identify stretched readings where the compass is extended but chop begins to rise, which can warn that momentum is becoming less efficient.
I use this as a regime filter and timing aid, not as a standalone entry system. A bullish rotation is more useful when it aligns with higher-timeframe structure, a reclaim, or clean continuation candles. A bearish rotation is stronger when price is failing below structure, rejecting supply, or continuing after a breakdown. Exhaustion dots are not automatic reversal calls; they are warnings to reduce confidence in chasing late movement.
Key inputs include Vortex length, Choppiness length, volume z-score length, smoothing, signal visibility, exhaustion dot visibility, dashboard position, and palette colors. Shorter lengths make the compass faster but noisier. Longer lengths make it slower but more stable. The dashboard summarizes regime, direction, volume z-score, chop reading, trend score, and compass value so traders can see why the current state is being plotted.
This script intentionally uses standard plots, histograms, background color, markers, and tables instead of static projected drawings. That keeps the visuals anchored to the chart across scrolling and timeframe changes.
Open-source script for educational use only. Not financial advice. Indicator
RSI + ZC COG Candles + Buy SignalThis script combines a normalized Center of Gravity (ZC COG) candle view with an RSI color regime and a context‑aware buy signal filter.
The RSI block builds a three‑state background:
Green when RSI trades above an adaptive band around its SMA (strong momentum zone).
Yellow when price is neither strongly oversold nor strongly overbought (neutral / transition zone).
Red when RSI drops below a forced level or below the lower band (downtrending / risk zone).
On top of that regime, the script plots ZC COG candles, where price is transformed into a normalized oscillator:
COG is centered, scaled to a fixed half‑range, optionally quantized, then drawn as synthetic candles with body and wick.
This gives a clean visual of swings and turning points, independent of the raw price scale.
The buy signal layer is designed to look for potential mean‑reversion moves out of recent red RSI zones, while trying to avoid most obvious bad contexts:
Candles must close positively in the COG space.
A configurable number of bars back (default: 5) is optionally checked to ensure the current candle is closing below a previous reference candle.
The RSI must be above a minimum level and above an offset‑adjusted RSI SMA, so you can allow a small margin under the SMA if needed.
A “recent red zone” filter requires that a red RSI regime occurred within a user‑defined lookback window, to focus on bounce‑type setups rather than chasing extended trends.
This indicator is meant to be used together with a standard RSI 14 for divergence work:
The buy markers highlight structural contexts where a bounce could make sense.
The separate RSI 14 helps you confirm bullish divergences and filter out false signals.
Without that divergence layer, you should expect more noise and more traps around earnings, gaps, and fast news moves.
How to use it
Apply this script and a classic RSI 14 on your chart.
Use the colored background and COG candles to understand the current regime and local swings.
Treat the buy signals as potential bounce zones, not guaranteed entries.
Confirm using RSI 14 divergences, higher‑timeframe structure, and your own risk management rules.
Disclaimer
This script is provided for educational purposes only.
It does not constitute financial advice, trade recommendations, or a solicitation to buy or sell any security or instrument.
Markets can react unexpectedly to:earnings releases, macro events, company‑specific news, liquidity shocks, and overnight gaps.
No indicator, including this one, can fully protect you from those events, and there is always a risk of loss when trading or investing.
Past performance and historical patterns do not guarantee future results.
Always do your own research, adapt parameters to your own strategy, and consult a qualified financial professional if you need personalized advice. Your capital is at risk and you remain fully responsible for your decisions. Indicator
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Adaptive Support & Resistance Pro with EMA Momentum Filter## Description
This indicator is an advanced tool designed to identify adaptive Support and Resistance (S/R) zones and combine them with an Exponential Moving Average (EMA) momentum filter. Unlike static S/R lines, this script uses a combination of momentum oscillators and dynamic pivot calculations to find high-probability reversal zones on higher or current timeframes.
The core philosophy of this indicator is to prevent "knife-catching." Instead of firing a signal immediately when a support or resistance level is formed, it waits for the price to confirm a change in momentum by crossing the EMA line in the direction of the trade.
---
## How It Works (Under the Hood)
### 1. Support & Resistance Detection
The script uses a multi-layered filter to detect true pivot points:
* **Legacy RSI & Modified RSI:** It evaluates overbought (>75) and oversold (<25) conditions using a 9-period Relative Strength Index.
* **Chande Momentum Oscillator (CMO) based on HMA:** It applies a 1-period CMO logic over Hull Moving Averages (HMA 5 and HMA 12) to detect immediate shifts in market velocity.
* **Close Pivots:** It uses deviation-free highest/lowest calculations (`ta.highest` and `ta.lowest`) combined with `ta.valuewhen` to fetch precise structural levels.
A **Support Zone** is formed only when the RSI is oversold, the CMO shows an upward momentum shift (>50), and a local low pivot is confirmed.
A **Resistance Zone** is formed when the RSI is overbought, the CMO shows a downward shift (<-50), and a local high pivot is confirmed.
### 2. S/R Timeframe Flexibility
Through the `request.security` function, users can plot these adaptive levels from higher timeframes (HTF) onto their current chart. To prevent **repainting** and back-shifting signals, the script strictly uses `barmerge.lookahead_off`.
### 3. EMA Momentum Trigger (The Confirmation Filter)
To filter out false breakouts and premature entries during heavy trend extensions, an EMA filter is introduced:
* **BUY Signal:** Triggered only when a new Support level has been established AND the price successfully closes above the EMA (`ta.crossover`).
* **SELL Signal:** Triggered only when a new Resistance level has been established AND the price successfully closes below the EMA (`ta.crossunder`).
**Strict Discipline:** The script uses an internal state machine (`waitForBuyBreak` / `waitForSellBreak`) ensuring that **only ONE signal** is fired per newly created S/R level. This completely eliminates the "whipsaw" effect (multiple false signals) when the price is consolidating or chopping around the moving average.
---
## Settings & Customization
* **Line Width / Colors:** Fully customize the visual thickness and color styling of your Support and Resistance zones.
* **S/R Timeframe:** Leave it blank for the current chart timeframe, or select higher timeframes (e.g., 4H or 1D) for macro level analysis.
* **Enable EMA Filter:** Toggle this option ON to use the momentum confirmation logic, or OFF to see signals immediately upon S/R level creation.
* **EMA Length:** Adjust the period of the confirmation line (Default is 50, but can be set to 20 for faster entries or 200 for macro trend-following).
---
## Alerts
The script includes three built-in alert conditions for automation:
1. `New S/R line` - Triggers whenever a new support or resistance level is plotted.
2. `BUY Signal` - Triggers when the EMA crossover confirms the support bounce.
3. `SELL Signal` - Triggers when the EMA crossunder confirms the resistance rejection.
## Disclaimer
This indicator is meant for educational and analytical purposes only. Past performance does not guarantee future results. Always practice proper risk management. Indicator
POL RSI Long Indicator [3Commas]POL RSI Long Indicator
🔷 What it does:
This is a signal-only indicator that mirrors a POL dip-buying workflow with a scaling safety-order ladder. It tracks one virtual long position at a time, opened only when POL prints a deep oversold reading on 4-hour RSI. Five safety orders fire at fixed deviations from base entry (−2%, −5%, −9.5%, −16%, −25%) with sizes scaling 1.8× on every rung. Exit is a fixed 3% Take Profit from average entry. The indicator computes running average entry, deployed capital, open PnL, and lifetime realized PnL — all derived from honest fill-by-fill bookkeeping. Every event emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
- Selective oversold entry: 4h RSI < 28.
- Non-uniform fixed-deviation safety ladder: −2%, −5%, −9.5%, −16%, −25% from base entry.
- 1.8× scaling safety-order sizes: 900 / 1,620 / 2,916 / 5,249 / 9,448 USDT from a $500 base.
- Tight 3% Take Profit from the averaged-down entry — quick deal close once price stabilizes.
- Honest virtual bookkeeping: Open PnL and lifetime Total PnL displayed live on the chart.
🔷 Who is it for:
- Swing traders running a DCA Bot on POL who want to buy deep oversold dips.
- DCA-style traders who want a disciplined averaging ladder that only deepens on serious adverse moves.
- Bot operators who want a chart-driven signal source that emits per-event JSON ready for a DCA Bot.
- Traders comfortable with a scaling martingale ladder deploying up to ~20.6% of equity per trade in exchange for a high deal-close rate.
🔷 How does it work:
Entry Filter: A 4-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The entry gate fires when RSI is below 28 (deep oversold) at host-bar close, filtering out shallow dips.
Base Entry: When the gate is satisfied, the indicator marks a virtual long entry, captures the base entry price, and seeds the cost-basis ledger with the configured base order size (default 500 USDT).
Safety Order Ladder (Fixed Deviations, 1.8× Sizes): After base fill, the indicator monitors price deviation against the base entry. Each safety order has its own fixed deviation from base — not a cumulative ladder. AO1 fills at close ≤ base × 0.98 (−2%); AO2 at −5%; AO3 at −9.5%; AO4 at −16%; AO5 at −25%. USDT sizes scale 1.8× from a 900 first AO: 900 / 1,620 / 2,916 / 5,249 / 9,448. Each fill updates the running cost-basis and dispatches its own webhook payload.
Honest Virtual Bookkeeping: Total cost and qty are updated incrementally on every event, so the avg entry, deployed capital, Open PnL, and Total PnL displayed in the status table reflect the actual broker-equivalent position state — no shortcut from base entry, no synthetic averaging.
Lifetime Total PnL: When the position closes for profit, the realized PnL from that cycle accumulates into a lifetime counter. The status table displays both Open PnL (current cycle, resets on exit) and Total PnL (lifetime, persists across the chart history).
Exit: A fixed 3% Take Profit above the running average entry. When close hits the TP target, the close webhook fires, realized PnL accumulates, and the virtual position resets.
🔷 Why it's unique:
- Selective Oversold Entry: The deal opens only on a deep 4h RSI < 28 print, so capital is committed at genuinely stretched conditions rather than on every dip.
- Non-Uniform Fixed-Deviation Ladder: Most published DCA tools use formula-based ladders (step × multiplier). This one exposes each AO deviation as a direct input, allowing an asymmetric ladder (2% / 5% / 9.5% / 16% / 25%) where deeper safety orders trigger only on serious adverse moves.
- 1.8× Scaling (Not Doubling): The 1 / 1.8 / 3.24 / 5.83 / 10.5 size progression is softer than a 2× doubling martingale — it still concentrates size in the deeper rungs but caps maximum deployment at ~20.6% of equity.
- Lifetime PnL Tracking: Open PnL and Total PnL are displayed live on the chart — Open resets per cycle, Total persists across the entire chart history. The indicator gives strategy-tester-equivalent insight without running a backtest.
- Per-Event Webhook Ledger: Up to seven discrete events per cycle (entry + 5 AO fills + TP), each with its own JSON alert payload. One PulseWire alert with "Any alert() function call" drives a DCA Bot end-to-end.
🔷 Considerations Before Using the Indicator:
Sample Size: The companion strategy's backtest produced 72 closed trades over a ~21-month window — below the ≥100 floor typically used for statistical confidence. The high win rate and profit factor reflect favorable conditions and the averaging mechanic, not a deterministic edge. Treat them as indicative, not a forward-performance guarantee.
Aggressive Capital Deployment: If all five safety orders fill, total deployed capital reaches ~$20,633 = ~20.6% of the default reference equity. The scaling ladder amplifies both upside on recovery and risk if the lower bound breaks. Match the indicator's per-AO allocation to your bot's configuration to keep the avg-entry display honest.
No Stop Loss: There is no exit signal on adverse moves below AO5 (−25% from base). If price keeps falling, the virtual position holds unhedged until either price recovers to the 3% TP target or the user intervenes. Risk is structurally capped on the bot side by the bounded position ladder; if a hard exchange-side stop is required, configure it on the bot directly.
Martingale Tail Risk: A ladder that bottoms out at −25% is built for mean-reverting moves. POL is a high-volatility asset; a sustained directional collapse below −25% leaves the full virtual position open with no further averaging available — the single largest risk in any martingale DCA.
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.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester — but the live Total PnL counter in the status table gives a running approximation. For full metrics over a ~21-month sample (72 closed trades, 72.22% win rate, 0.94% max drawdown, profit factor 7.9, +3.58% net return), use the companion strategy version on identical parameters.
🔷 How to Use It:
🔸 Add the indicator to a 4h POL / USDT chart.
🔸 Review the RSI entry level, the five AO deviations and sizes, and the Take Profit percentage. Defaults are calibrated for POL 4h — recalibrate when the asset's volatility regime shifts.
🔸 Set Base Order Size and AO sizes to match your bot's configuration (the indicator's avg-entry display becomes meaningful when virtual sizing matches real sizing).
🔸 In the DCA Bot Webhook group, paste the Bot ID, Email Token, and Pair (QUOTE_BASE format, e.g., USDT_POL).
🔸 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.
AO1–AO5 Deviation (%): Fixed distance from base entry where each safety order becomes eligible. Non-uniform by design, reaching −25% at AO5.
AO1–AO5 Size (USDT): Virtual USDT amount of each safety order. Scales 1.8× per rung by default.
RSI Timeframe / Length / Less Than: 4h RSI filter for the base entry.
Take Profit (%): Fixed distance above the running average entry where the virtual long closes.
Active Window: Optional date filter — when ON, the indicator only fires signals between From and To dates.
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
POL RSI Long Strategy [3Commas]POL RSI Long Strategy
🔷 What it does:
This is a long-only DCA strategy with a selective oversold entry and a scaling safety-order ladder. A long entry opens only when the 4-hour RSI falls below 28 (deep oversold). Five safety orders then fire at fixed deviations from base entry (−2%, −5%, −9.5%, −16%, −25%) with sizes scaling 1.8× on every rung ($900 → $1,620 → $2,916 → $5,249 → $9,448 from a $500 base). Exit is a fixed 3% Take Profit from average entry. No trailing, no Stop Loss.
- Single base order with up to five safety orders on a non-uniform fixed-deviation ladder reaching −25% below base.
- Size scaling 1.8× per rung — aggressive enough to pull the average down hard, softer than a 2× doubling martingale.
- Tight 3% Take Profit from average entry — the averaging ladder pulls the average down so a small recovery closes the deal in profit.
- Single entry filter: deeply oversold 4h RSI — a clean, selective trigger.
- 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 long exposure on POL when it prints deep oversold readings on the 4h.
- DCA-style traders who want a disciplined averaging ladder that only deepens on serious adverse moves.
- 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 a scaling martingale ladder deploying up to ~20.6% of equity per trade in exchange for a high deal-close rate.
🔷 How does it work:
Entry Filter: A 4-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The entry gate fires when RSI is below 28 (deep oversold) at host-bar close, filtering out shallow dips.
Base Order: Sized at 500 USDT default (0.5% of 100k capital). Configurable as Market (default) or Limit at the bar's close.
Safety Order Ladder (Fixed Deviations, 1.8× Sizes): After the base fill, the strategy monitors price deviation against the base entry. Each safety order has its own fixed deviation from base — not a cumulative ladder. AO1 fires when close ≤ base × 0.98 (−2%); AO2 at −5%; AO3 at −9.5%; AO4 at −16%; AO5 at −25%. Sizes scale 1.8× from a 900 USDT first AO: 900 / 1,620 / 2,916 / 5,249 / 9,448.
Exit: A fixed 3% Take Profit above the running average entry. When close hits the TP target, the position closes at market. No trailing, no Stop Loss.
Why the Ladder Works: Each scaling safety order weights the average entry toward the lowest fills. After several rungs fill, the average sits well below base, so a modest 3% bounce off the lows is enough to close the whole deal in profit — the core mechanic of a DCA bot.
🔷 Why it's unique:
- Selective Oversold Entry: The deal opens only on a deep 4h RSI < 28 print, so capital is committed at genuinely stretched conditions rather than on every dip.
- Non-Uniform Fixed-Deviation Ladder: Most published DCAs use formula-based ladders (step × multiplier). This one exposes each AO deviation as a direct input, allowing an asymmetric ladder (2% / 5% / 9.5% / 16% / 25%) where deeper safety orders trigger only on serious adverse moves and the lowest rung sits a full 25% below base.
- 1.8× Scaling (Not Doubling): The 1 / 1.8 / 3.24 / 5.83 / 10.5 size progression is softer than a 2× doubling martingale — it still concentrates size in the deeper rungs but caps maximum deployment at ~20.6% of equity rather than ~31%.
- Tight Recovery Target: The 3% Take Profit on the averaged-down entry closes deals quickly once price stabilizes, keeping the win rate high and holding times short relative to the depth of the ladder.
- DCA Bot Integration: Every event (base, AO 1–5, 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:
Sample Size: The backtest produced 72 closed trades — below the ≥100 floor typically used for statistical confidence. The 72.22% win rate and high profit factor reflect favorable conditions over the test window and the averaging mechanic, not a deterministic edge. Treat these numbers as indicative of how the ladder behaves, not a forward-performance guarantee. Extend the test window or run the strategy across multiple assets to build a larger sample before committing capital.
Aggressive Capital Deployment: If all five safety orders fill, total deployed capital reaches ~$20,633 = ~20.6% of default 100k equity — above PulseWire's typical 5–10% per-trade band. Size the base and AO inputs down to dial per-trade risk into a safer range. The scaling ladder amplifies both upside (when price recovers) and risk (if the lower bound breaks).
No Stop Loss: There is no exit on adverse moves below the −25% AO5. If price keeps falling below the lowest safety order, the position holds unhedged until either price recovers to the 3% TP target or the user intervenes. The structural risk cap is the bounded 5-rung position ladder; if a hard exchange-side stop is required, layer it on the bot directly.
Martingale Tail Risk: A ladder that bottoms out at −25% is built for mean-reverting moves. POL is a high-volatility asset; a sustained directional collapse below −25% leaves the full position open with no further averaging available — the single largest risk in any martingale DCA. Choose regimes where deep-but-recoverable dips are the norm.
Commission Calibration: The default 0.06% commission is calibrated for perpetual taker conditions. Match it to your exchange's actual fees.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:POLUSDT.P (Perpetual) — portable to any POL / USDT pair.
Timeframe: 4H
Test Period: September 13, 2024 — June 24, 2026 (~21 months).
Initial Capital: 100,000 USDT.
Order Size per Trade: 0.5% of Capital base + 5 safety orders with 1.8× size scaling.
Max Capital Deployed: ~$20,633 per trade (~20.6% of equity).
Commission: 0.06% per trade.
Slippage: 3 ticks.
Margin for Long Positions: 100%.
Indicator Settings: Default Configuration.
Base Order: 500 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: 4h RSI(14) Less Than 28.
Safety Orders: 5 with fixed deviations −2% / −5% / −9.5% / −16% / −25% from base entry; sizes 900 / 1,620 / 2,916 / 5,249 / 9,448 USDT (1.8× scaling).
Strategy: Long Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +3,583.76 USDT (+3.58%)
Max Equity Drawdown: 944.08 USDT (0.94%)
Total Closed Trades: 72
Percent Profitable: 72.22% (52 / 72)
Profit Factor: 7.9
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, the five AO deviations and sizes, the RSI entry level, and the Take Profit percentage. Defaults are calibrated for POL 4h — recalibrate when the asset's volatility regime shifts.
🔸 Results Review: The backtest produced 72 closed trades over ~21 months — below the ~100-trade floor for statistical relevance. Treat the metrics as indicative of the ladder's behavior; a larger sample increases confidence. Confirm that the trade frequency and the ladder's max deployment fit your risk tolerance before deploying capital.
🔸 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.
AO1–AO5 Deviation (%): Fixed distance from base entry where each safety order becomes eligible. Non-uniform by design, reaching −25% at AO5.
AO1–AO5 Size (USDT): USDT amount of each safety order. Scales 1.8× per rung by default.
RSI Timeframe / Length / Less Than: 4h RSI filter for the base entry.
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.
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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
CVD Flow EngineCVD Flow Engine
CVD Flow Engine is an advanced order-flow analysis framework that combines Cumulative Volume Delta (CVD), structural flow analysis, retention-style candles, trend detection, strength signals, and divergences into a single indicator.
Unlike traditional CVD indicators that focus only on cumulative delta, CVD Flow Engine attempts to classify the quality and persistence of buying and selling pressure by analyzing both trend and structure.
Key Features
• CVD Profiles
Builds a profile from cumulative delta activity, allowing traders to identify areas where buying and selling pressure have accumulated over time.
• Retention-Style CVD Candles
Transforms CVD Balance, CVD Delta, or CVD Acceleration into candle structures where each candle opens from the previous value. This provides a clearer visualization of participation and flow persistence than a traditional line plot.
• Structural Flow Analysis
Instead of relying solely on EMA position, the engine evaluates whether order flow is improving or deteriorating through market structure.
The candle coloring system identifies:
* Strong Bull Flow: CVD above trend and maintaining bullish momentum.
* Bullish Recovery: CVD remains below trend but begins producing Higher Highs and Higher Lows, indicating improving participation.
* Strong Bear Flow: CVD below trend and maintaining bearish momentum.
* Bearish Weakness: CVD remains above trend but begins producing Lower Highs and Lower Lows, suggesting deterioration in buying pressure.
This allows traders to identify improving flow conditions before traditional trend filters react.
• Dynamic Trend Engine
A CVD EMA is used to classify the prevailing order-flow regime. EMA slope analysis helps distinguish bullish, bearish, and transitional environments.
• Strong Bull / Strong Bear Signals
The indicator identifies periods where trend, momentum, and flow retention align. Compact markers highlight these states without cluttering the chart.
• Divergence Detection
Bullish and bearish divergences compare price structure against order-flow structure.
Bullish Divergence:
* Price makes a Lower Low.
* CVD makes a Higher Low.
Bearish Divergence:
* Price makes a Higher High.
* CVD makes a Lower High.
These conditions may indicate weakening participation behind the current move.
How To Use
Bullish Environment:
* Retention candles are predominantly green.
* Higher High and Higher Low structures continue to form.
* Strong Bull signals appear.
* Bullish divergences can identify pullback opportunities.
Bearish Environment:
* Retention candles transition into bearish structure.
* Lower High and Lower Low sequences develop.
* Strong Bear signals appear.
* Bearish divergences can identify weakening rallies.
Transition Environment:
* EMA slope flattens.
* Structure begins shifting before trend confirmation.
* Recovery or deterioration states emerge.
* Divergences become more frequent.
The objective of CVD Flow Engine is not to predict future price movement but to provide a structured view of whether order flow is strengthening, weakening, recovering, or deteriorating beneath the surface of price action.
By combining cumulative delta, structural analysis, trend classification, and divergence detection, the indicator helps traders evaluate whether participation is supporting the current market move or signaling a potential transition.
Indicator
Value-Distribution OscillatorValue-Distribution Oscillator
Overview
A volume-by-price value map expressed as a bounded pane oscillator. It rolls a decaying volume distribution of recent trade, finds the Point of Control (most-traded price) and the Value Area, then plots where price sits inside that value structure on a fixed −50 / +50 scale: 0 = at the POC (fair value), ±25 = the value-area edges (VAH / VAL), ±50 = stretched beyond the developed range. It is a study of acceptance and location — not a directional signal.
Why these parts are ONE tool (mashup rationale)
A volume profile is an overlay that shows where value is; it can't give you, as a single number, how far price has travelled from value or whether that travel reverts. This chains: a decaying distribution builds the map → a position transform turns price into one bounded location reading → a fade flag fires only when price is stretched into the tails and turning back → a calibration harness tests whether stretched-and-reverting readings actually return toward the POC on your instrument. Remove a part and the chain breaks: a profile is just a picture, the transform alone is just a number, the fade alone is an untested claim.
How it works
Each confirmed bar's volume is distributed across a price grid (body weighted heavier than wicks) and the whole grid decays geometrically, so the map tracks recent trade and re-anchors when price leaves its range. The POC is the heaviest level; the Value Area grows outward from the POC to the chosen volume share; the transform maps price piecewise-linearly (POC→0, VAH/VAL→±25, extremes→±50). The harness logs each stretched fade and checks a ≥ k×ATR move back toward the POC a fixed horizon later.
How to use
Read location: near 0 = fair value; the ±25 band = the edge of value; beyond ±40 = stretched into the tails, where reversion setups have context and breakouts that hold signal value migration. Then read the Edge row — fades in the tails only earn their keep if they beat the base rate. Context, never a standalone trigger.
Originality
The POC / Value-Area concept is public (credited below); the original work is the assembly — a decaying-grid distribution, the price-into-value position transform that turns a profile into a series, and the forward base-rate calibration. It's the pane-oscillator counterpart to a volume profile, not a re-skin of one.
Concept credit
Market / Volume Profile, Point of Control and Value-Area framing — J. Peter Steidlmayer and the CBOT Market Profile tradition; value-area / acceptance reading developed further by practitioners such as James Dalton. Implementation, transform and harness are this script's own.
Honesty / limitations
The distribution uses bar ranges, not exchange price-by-price prints or tick data — a probabilistic approximation. The grid decays, so it's a recent-trade view, not a session-anchored profile. Edge figures are in-sample, close-to-close, overlapping windows, no costs — descriptive context, not a backtest. Nothing here predicts direction.
Disclaimer
Research / educational only. NOT financial advice; no guarantee of profitability. Indicators describe past behaviour. Trading carries risk of loss. Test out-of-sample. The author accepts no liability. Indicator
Flow Pressure OscillatorFlow Pressure Oscillator visualizes directional market pressure, trend alignment, regime quality, pullback pressure, and extended pressure conditions in a separate oscillator pane.
The tool is built to help traders read whether market pressure is leaning bullish, bearish, or neutral. It combines trend structure, EMA alignment, ATR-normalized movement, ADX, directional efficiency, volatility behavior, and volume participation into a bounded flow reading between -100 and +100.
The main Flow Trail shows the current pressure direction and strength. Positive readings indicate bullish pressure, negative readings indicate bearish pressure, and values near the zero line suggest a more neutral or mixed environment.
Regime Dots show the internal market regime state. Upper dots represent bullish regime pressure, lower dots represent bearish regime pressure, and neutral readings show that no strong directional regime is active.
The Pullback Reload Line is designed to highlight pullback pressure inside an existing bullish or bearish regime. It is not an entry signal by itself. It is meant to be used as context together with the Flow Trail, regime state, and the user’s own chart analysis.
The oscillator also highlights expansion and exhaustion-style pressure conditions. These areas can help identify when pressure is becoming stretched, accelerating, or losing momentum. They should be treated as market-context readings, not as guaranteed reversal or continuation points.
Core components
Flow Trail:
The main pressure line. It reacts to trend pressure, momentum slope, acceleration, structure alignment, volatility, and volume participation.
Zero Line:
A neutral reference level. Readings above zero show bullish pressure dominance. Readings below zero show bearish pressure dominance.
Regime Dots:
A visual regime filter for bullish, bearish, or neutral pressure conditions.
Pullback Reload Line:
A secondary pressure line designed to show pullback or reload behavior inside an active regime.
Pressure Fill:
A visual fill between the Flow Trail and the zero line to make pressure direction easier to read.
Extreme Pressure Coloring:
Highlights expanded, stretched, or exhaustion-style pressure states.
A simple way to use the oscillator is:
- Flow Trail above zero = bullish pressure is dominant;
- Flow Trail below zero = bearish pressure is dominant;
- Rising Flow Trail = pressure is strengthening;
- Falling Flow Trail = pressure is weakening;
- Regime Dots help confirm whether the broader pressure environment supports the current flow direction;
- Reload Line can help identify pullback pressure during an existing bullish or bearish regime;
- Extreme pressure areas should be used for awareness, not as automatic trade signals.
Important notes
Flow Pressure Oscillator is a market-pressure visualization tool only. It does not provide financial advice, trade recommendations, profit targets, stop losses, win-rate calculations, or performance guarantees.
The script should be used together with the trader’s own market structure, support and resistance, risk management, and confirmation process. No single oscillator should be used as a complete trading system. Indicator
Trend Persistence OscillatorTrend Persistence Oscillator
OVERVIEW
Most oscillators answer "is price stretched?" This one answers the prior question almost everyone skips: "is the market even in a state where a stretch should snap back?" It plots a rolling persistence exponent of price around the 0.5 line. ~0.5 is a random walk; above 0.5 the series is persistent (moves tend to continue → trending); below 0.5 it is anti-persistent (moves tend to reverse → mean-reverting). It is an analytical study of market state — not a directional signal and not a strategy.
WHY THESE COMPONENTS BELONG IN ONE SCRIPT (mashup rationale)
Three parts that chain into one testable idea — is a reversion likely here, and has that held before?
The persistence exponent classifies the regime (trending / random / reverting). Research finds price reverts to its mean significantly faster when the local exponent is anti-persistent, so a low reading is a green light for fades and a high reading is a warning that a reversion will likely fail.
A stretch z-score measures how far price sits from its rolling mean — the "is it extended?" half a regime read alone can't supply.
A fade flag arms only when both agree (anti-persistent regime and stretched), turning the research claim into a concrete, located event.
The calibration harness proves or disproves the claim on your instrument: it logs each fade and checks, a fixed horizon later, whether price actually reverted — reporting Edge versus the unconditional base rate.
A regime read without a stretch is just a state label; a stretch without the regime is a naive fade; either without calibration is an untested assertion. Chained, they answer one question end to end. Remove a part and the chain breaks.
HOW IT WORKS
The exponent is estimated by the structure-function (generalized-Hurst) method: for several lags, the windowed mean of |log-price(t) − log-price(t−lag)| scales like lag^H, so the exponent is the slope of log(mean|Δ|) against log(lag). The first-moment (absolute) form is used deliberately because it is the variant most robust to the heavy tails of financial returns — Monte-Carlo studies find the generalized-Hurst approach gives the lowest bias and variance of the common estimators on heavy-tailed data.
A short optional smoothing tames the noise inherent to short-window local estimates (very short windows are known to produce volatile readings and false alarms).
A stretch z-score and the regime thresholds combine into the fade flag.
The harness logs each fade and, a fixed horizon later, checks a ≥ k × ATR reversion.
HOW TO USE
Read the line for regime: in the green (reverting) zone, mean-reversion / fade setups have the wind behind them; in the gold (trending) zone, expect continuation and treat reversion setups with suspicion; near 0.5 the tape is effectively random. The fade dots mark reverting-and-stretched moments. Then read the Edge row — a regime filter only earns its keep if fades taken inside it beat the unconditional base rate. Context, never a standalone trigger.
Three visual styles are provided (Gradient area + glow / Histogram / Line).
UNIVERSAL ACROSS MARKETS
The price source is an input, so the engine runs on any instrument and timeframe. Defaults target intraday index futures (e.g. NSE NIFTY); change the source for any other market. The reading is self-normalising around 0.5, so the same regime bands work everywhere.
ORIGINALITY
The exponent itself is a standard public statistic, credited below. The original work is the assembly: a structure-function persistence estimator chosen for heavy-tail robustness and smoothed against short-window noise, gated against a stretch z-score into a located fade event, and tied to a forward base-rate calibration so the regime claim is tested on each instrument rather than asserted. It is a regime and validation tool, not a plain exponent plot. No third-party Pine code is reused.
CONCEPT CREDIT
The scaling exponent and rescaled-range analysis — Harold E. Hurst (1951). Fractional / self-similar processes and the generalized exponent — Benoit Mandelbrot. The structure-function (generalized-Hurst) estimator is the variant most robust to heavy-tailed financial data. The anti-persistence-anticipates-reversion application follows recent local-exponent mean-reversion research (2024). Not affiliated with, nor endorsed by, any third party.
HONESTY / LIMITATIONS
The exponent is an estimate from a finite window — it is noisy and lags, and short windows can raise false alarms (which is why a smoothing control is provided, on by default). A low reading is context, not a trigger. The Edge figures are in-sample, close-to-close, with overlapping forward windows and no costs — descriptive context, not a verified backtest. An Edge near zero or negative is the harness honestly reporting that the regime read isn't helping here; do not tune until it turns green — that is curve-fitting. Nothing here predicts direction.
DISCLAIMER
Research and educational tool only. NOT financial advice and NO guarantee of profitability or accuracy. Indicators describe past behaviour; they do not predict the future. Trading carries risk of loss. Test out-of-sample and make your own decisions. The author accepts no liability for any use of this script. Indicator
Lead-Lag Information FlowLead-Lag Information Flow
OVERVIEW
Correlation tells you two instruments move together. It cannot tell you who moves first. This indicator answers that question directly: it measures the net directional information flow between a reference symbol and the chart using transfer entropy — how much knowing the reference's last move reduces uncertainty about the chart's next move, beyond what the chart's own history already says, minus the same quantity in the other direction.
The result plots around zero. Positive = the reference leads the chart; negative = the chart leads the reference. A regime read (is the follower trending or chopping?) sits alongside it, because a lead is only worth acting on when the follower is in a state that lets the move pay off.
WHY THESE COMPONENTS BELONG IN ONE SCRIPT (mashup rationale)
Three parts, one question — is there exploitable lead-lag right now, and which way? Each closes a gap the others leave open:
Transfer entropy (net, in bits) answers the DIRECTION of information — who leads. It is model-free and captures nonlinear lead-lag that a correlation or linear regression misses, and netting the two directions cancels much of the small-sample bias that distorts raw entropy estimates.
The Hurst regime read answers whether a lead is tradeable: information flowing into a persistent (trending) follower is far more actionable than into a mean-reverting chop. The same lead means different things in different regimes.
The calibration harness answers whether it has actually worked here: it logs each lead-and-follow setup and, a fixed horizon later, checks whether the chart moved with the leader by at least k × ATR, reporting Hit %, Base %, and Edge.
Direction without a regime filter fires into noise; a regime read without direction is just a Hurst line; either without calibration is an untested assertion. Together they form one decision — lead exists (entropy) and the follower can run (regime) and it has paid before (Edge). Remove any one and the question is answered less completely.
HOW IT WORKS
Each series' bar-to-bar move is reduced to an up/down state.
Over a rolling window, state-transition frequencies estimate the transfer entropy in each direction (Schreiber's estimator); the plotted line is the net (reference→chart minus chart→reference), in bits. An optional Miller-Madow finite-sample correction subtracts the small-sample bias raw entropy estimates carry on short windows — a streaming-feasible step toward effective transfer entropy.
A Hurst exponent (a structure-function estimate around the 0.5 line) classifies the follower's regime as trending or reverting.
A follow setup arms when net flow says the reference leads and the reference has just moved; the calibration harness then measures whether the chart followed.
HOW TO USE
Read the line for direction — above the upper threshold, the reference leads; below the lower threshold, the chart leads — and read the dashboard for regime and the Edge row. A lead into a trending follower with a positive, matured Edge is the context this tool is built to surface. A lead into a reverting follower, or one where Edge sits near zero, is the engine telling you the lead-lag is not exploitable on this pair and timeframe. The background tints faintly green when the reference leads decisively and red when the chart leads. Treat all of this as context, never a standalone trigger.
Three visual styles are provided (Gradient area + glow / Histogram / Line); the gradient area's intensity scales with how strong the net flow is.
UNIVERSAL ACROSS MARKETS
The chart is the follower; the Reference symbol is the candidate leader — both are inputs, so the engine runs on any related pair in any market: cash index vs its futures, an index vs a lead constituent, an asset vs its dominant driver. Defaults pair NSE:NIFTY (cash) as the candidate leader against a NIFTY-futures chart; change the reference for any other pair. Use it on the timeframe at which you expect the lead-lag to operate.
ORIGINALITY
The techniques are public and credited below. The original work is the integration: a streaming two-state transfer-entropy estimator that nets the two directions and applies a Miller-Madow finite-sample correction to approximate effective transfer entropy (the documented fix for small-sample bias) without the shuffle step that a streaming script can't perform, gated by a Hurst regime classifier so a lead is only surfaced where the follower can act on it, and tied to a forward base-rate calibration so every follow setup reports its own realized Edge rather than an asserted one. No third-party Pine code is reused.
CONCEPT CREDIT
Transfer entropy — Thomas Schreiber (2000); effective transfer entropy and small-sample bias correction — Marschinski & Kantz (2002). Finite-sample entropy correction — Miller (1955) / Madow. Information entropy — Claude E. Shannon (1948). Hurst exponent — Harold E. Hurst (1951); long-memory framing — Benoit Mandelbrot. Not affiliated with, nor endorsed by, any third party.
HONESTY / LIMITATIONS
This is a coarse, two-state, windowed estimator. The finite-sample (Miller-Madow) correction and the netting of the two directions together approximate effective transfer entropy — they reduce the small-sample bias raw TE carries — but they are not a full surrogate-shuffle effective TE with significance testing (which requires reshuffling that isn't possible in a streaming script). The Edge figures are in-sample, close-to-close, with overlapping forward windows and no costs — descriptive context, not a verified backtest. An Edge near zero or negative is the harness honestly reporting that the lead-lag is not exploitable here; do not tune until it turns green — that is curve-fitting. The reference must be a genuinely related instrument for the read to mean anything. Nothing here predicts price.
DISCLAIMER
Research and educational tool only. NOT financial advice and NO guarantee of profitability or accuracy. Indicators describe past behaviour; they do not predict the future. Trading carries risk of loss. Test out-of-sample and make your own decisions. The author accepts no liability for any use of this script. Indicator
BCH RSI Indicator [3Commas]BCH RSI Indicator
🔷 What it does:
This is the signal-only companion to the BCH RSI Short strategy — it fires alerts without running a backtest engine. It tracks one virtual short at a time, opened when the RSI(9) — sampled on the 5-minute timeframe — crosses back DOWN through 80. The indicator itself runs on the 15-minute chart, which acts as the execution/confirmation layer: signals are evaluated at 15m bar close while the trigger reads the lower-timeframe RSI. Up to three averaging orders stack at +1%, +2%, and +3% above entry (equal size). The deal closes on a 1.3% Take Profit from the average with a 0.3% trailing lock, or a hard 8% Stop Loss. Running average entry, deployed capital, open PnL, and lifetime realized PnL are kept from honest fill-by-fill bookkeeping, and every event emits a webhook-ready JSON payload for a DCA Bot.
- RSI trigger on 5m; indicator run on the 15m chart (higher timeframe = confirmation).
- Uniform averaging ladder above entry: +1% / +2% / +3%.
- 1.3% Take Profit with a 0.3% trailing lock, plus a hard 8% Stop Loss.
- Live Open PnL and lifetime Total PnL on the chart.
🔷 Who is it for:
- Intraday traders fading overbought spikes on BCH with a multi-timeframe filter.
- Bot operators wiring PulseWire alerts straight into a DCA Bot via per-event JSON.
- Traders who want a defined-risk short signal — averaging with a stop, not a stopless martingale.
- Operators who want to watch the virtual deal state (entry, fills, exit) directly on the chart.
🔷 How does it work:
Timeframe Setup: Add the indicator to a 15-minute chart. The RSI is pulled from the 5-minute timeframe via request.security with lookahead disabled (no repaint). The entry signal is driven by 5m RSI dynamics, while the execution clock — when entries, averaging orders, and exits are evaluated — is the 15m bar close. The higher 15m timeframe therefore acts as a confirmation/execution layer over the faster 5m trigger.
Entry Trigger: The base short opens when the 5m RSI(9) was ≥ 80 on its prior close and drops below it — the overbought-to-neutral rollover.
Base Entry: On the trigger, the indicator marks a virtual short, records the entry, and seeds the cost-basis ledger with the base order size (default 500 USDT).
Averaging Ladder (uniform): Three safety orders at fixed +1% / +2% / +3% above base, 250 USDT each. Each fill updates the running cost-basis and dispatches its own webhook, raising the virtual average entry.
Honest Bookkeeping: Cost and quantity update on every event, so the average entry, deployed capital, Open PnL, and Total PnL in the status table reflect the true broker-equivalent state.
Exit (TP + Trailing): At 1.3% below the running average, a trailing exit arms; the indicator tracks the in-favor low and signals a close on a 0.3% retrace off it.
Stop Loss: A hard 8% stop above the average fires the close webhook, banks realized PnL, and resets the virtual position.
Lifetime Total PnL: Each closed cycle's realized PnL accumulates into a lifetime counter shown alongside the current-cycle Open PnL.
🔷 Why it's unique:
- Multi-Timeframe Filter: A 5m RSI rollover trigger executed on the 15m chart blends a fast signal with a slower execution cadence — the 15m close acts as a confirmation gate that reduces reaction to 5m noise.
- Stop-Bounded Averaging: A compact 3-rung ladder plus an explicit 8% stop keeps the worst-case loss known up front.
- Trailing Profit Lock: The 1.3% target arms a 0.3% trail, banking the snap-back while letting an extended drop run.
- Lifetime PnL Tracking: Open and lifetime Total PnL on the chart give strategy-tester-equivalent insight without a backtest.
- Plug-and-Play Webhooks: Base, each AO, and the exit each emit a complete JSON alert; one "Any alert() function call" alert drives a DCA Bot end-to-end.
🔷 Considerations Before Using the Indicator:
Sample Size: The companion strategy's backtest produced 131 closed trades — above the ~100-trade floor commonly used for statistical relevance. Still a single test window, so treat the metrics as indicative.
Timeframe Pairing: This setup samples a LOWER timeframe (5m) than the chart it runs on (15m); the indicator only acts at 15m closes, filtering some intra-15m 5m crosses — that is the intended "confirmation" behavior. Keep the chart on 15m to reproduce the companion strategy's results.
Short Execution Venue: This signals shorts. Live shorting of BCH requires a margin or perpetual venue — it cannot run on a spot account.
Stop Loss Discipline: The 8% stop is the core risk control. Base plus three AOs deploy at most ~1,250 USDT (12.5% of the default reference equity); an 8% stop on that caps the worst case near ~1% of equity. Keep the stop on.
Trend Risk: Fading strength suits ranges and choppy tape. In a relentless uptrend the short can be stopped out repeatedly; the rollover trigger reduces, but does not remove, that risk.
Cross Detection Granularity: Entries, AO fills, and exits evaluate on bar close. A spike-and-revert within a single bar may be missed by design — matching realistic polling and avoiding intra-bar over-signaling.
Live vs Historical State: The virtual state is rebuilt from chart history on each recompile. If added mid-deployment or if the live bot diverges (manual interventions, partial fills), states may differ. Toggle the indicator off and on to reset.
Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester — but the live Total PnL counter gives a running approximation. For full metrics over a ~13.7-month sample (131 closed trades, 87.79% win rate, 1.73% max drawdown, profit factor 2.821, +4.63% net return), use the companion strategy version on identical parameters.
🔷 How to Use It:
🔸 Add the indicator to a 15-minute BCH / USDT chart (the RSI input stays on 5m — this is the intended pairing).
🔸 Review the RSI trigger level/timeframe, the averaging-order count/deviation/size, the Take Profit, Trailing, and Stop Loss percentages. Defaults mirror the source strategy.
🔸 Set Base Order Size and AO sizes to match your bot's configuration (the 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_BCH).
🔸 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 emits JSON for entry, each averaging order, and the TP/SL exit.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): Virtual order size for the avg-entry / open-PnL computation.
Averaging Orders per Trade: Number of safety orders (default 3).
First AO Size (USDT): Virtual size of each averaging order (uniform by default).
Deviation to First AO (%) / Deviation Step Multiplier: Spacing of the AO ladder above base entry. Defaults to uniform +1% steps.
Order Size Multiplier: Per-rung size scaling (1.0 = uniform).
RSI Timeframe / Length / Crossing Down Level: The RSI(9) crossing-down trigger — default 5m, run on the 15m chart.
Take Profit (%) / Trailing (%): TP distance below average entry and the trailing retrace that closes the position.
Stop Loss (%): Hard stop above average entry.
Active Window: Optional date filter — when ON, the indicator only fires signals between From and To dates.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle DCA 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.
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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
BCH RSI Strategy [3Commas]BCH RSI Strategy
🔷 What it does:
A short-only, momentum-fade DCA system for Bitcoin Cash. The deal arms the moment a fast push higher exhausts itself: the RSI(9) — sampled on the 5-minute timeframe — must cross back DOWN through 80. The strategy itself runs on the 15-minute chart, which acts as the execution/confirmation layer: signals are evaluated and orders fire at 15m bar close, while the trigger reads the lower-timeframe RSI. From the base short, up to three averaging orders stack at +1%, +2%, and +3% above entry (equal size). The position closes on a 1.3% Take Profit from the average with a 0.3% trailing lock, and a hard 8% Stop Loss caps the downside.
- RSI trigger on 5m; strategy executed on the 15m chart (higher timeframe = confirmation).
- One base short plus a 3-rung uniform averaging ladder placed above entry.
- Take Profit at −1.3% from average with a 0.3% trailing retrace to extend winners.
- Hard 8% Stop Loss — a real, bounded per-trade risk rather than an open-ended martingale.
- Every base fill, averaging order, and exit emits a webhook-ready JSON payload for a DCA Bot.
🔷 Who is it for:
- Intraday traders who fade overbought spikes on BCH with a multi-timeframe filter.
- Bot operators wiring PulseWire alerts straight into a DCA Bot via per-event JSON.
- Traders who want averaging with a stop attached, not a stopless grind.
- Portfolio builders adding a high-win-rate short-side sleeve with capped risk.
🔷 How does it work:
Timeframe Setup: Add the strategy to a 15-minute chart. The RSI is pulled from the 5-minute timeframe via request.security with lookahead disabled (no repaint). So the entry signal is driven by 5m RSI dynamics, while the execution clock — when entries, averaging orders, and exits are evaluated — is the 15m bar close. The higher 15m timeframe therefore acts as a confirmation/execution layer over the faster 5m trigger.
Entry Trigger: The base short opens when the 5m RSI(9) was ≥ 80 on its prior close and drops below it — the overbought-to-neutral rollover.
Base Order: 500 USDT default (5% of 10k capital), placed Limit at the signal bar's close (a Market toggle is available).
Averaging Ladder (uniform): Three safety orders sit at fixed +1% / +2% / +3% above the base, each 250 USDT (half the base). They average the short up if price keeps climbing, shrinking the bounce needed to reach target.
Exit (TP + Trailing): Once price reaches 1.3% below the running average, a trailing exit arms; the strategy then tracks the in-favor low and closes on a 0.3% retrace off it.
Stop Loss: A hard 8% stop above the average closes the deal at market if the short keeps running against the position.
🔷 Why it's unique:
- Multi-Timeframe Filter: A 5m RSI rollover trigger executed on the 15m chart blends a fast signal with a slower execution cadence — the 15m close acts as a confirmation gate that reduces reaction to 5m noise.
- Stop-Bounded Averaging: A compact 3-rung ladder plus an explicit 8% stop keeps the worst-case loss known up front, unlike classic stopless martingale shorts.
- Trailing Profit Lock: The 1.3% target arms a 0.3% trail, banking the snap-back while still letting an extended drop run.
- Plug-and-Play Webhooks: Base, each AO, and the exit each emit a complete JSON alert; one "Any alert() function call" alert drives a DCA Bot end-to-end.
🔷 Considerations Before Using the Strategy:
Sample Size: The backtest produced 131 closed trades — above the ~100-trade floor commonly used for statistical relevance. The 87.79% win rate and 2.821 profit factor still reflect a single test window, so treat them as indicative and broaden the test (longer period or more assets) before sizing up.
Timeframe Pairing: This setup samples a LOWER timeframe (5m) than the chart it runs on (15m). The strategy only acts at 15m closes, so some intra-15m 5m crosses are effectively filtered — that is the intended "confirmation" behavior. If you change the chart timeframe, the signal cadence changes; keep the chart on 15m to reproduce these results.
Stop Loss Discipline: The 8% Stop Loss is the defining risk control. With the base plus three averaging orders, maximum deployed capital is ~1,250 USDT (12.5% of default equity); an 8% stop on that bounds the worst-case loss to roughly 1% of equity. Keep the stop enabled.
Trend Risk: Fading overbought conditions works best in ranges and choppy regimes. In a strong, sustained uptrend the short can hit the 8% stop repeatedly. The RSI-crossing-down trigger reduces but does not eliminate this.
Commission Calibration: The default 0.06% commission is calibrated for Bybit perpetual taker conditions. Match it to your venue's actual fees.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:BCHUSDT.P (Perpetual) — portable to any BCH / USDT pair.
Timeframe: 15M chart, with the RSI trigger sampled from 5M (higher timeframe acts as confirmation).
Test Period: May 1, 2025 — June 23, 2026 (~13.7 months).
Initial Capital: 10,000 USDT.
Order Size: 500 USDT base (5%) + 3 averaging orders of 250 USDT each (uniform).
Max Capital Deployed: ~1,250 USDT per trade (~12.5% of equity).
Commission: 0.06% per trade.
Slippage: 3 ticks.
Margin for Short Positions: 100% (1× leverage, Isolated in source config).
Indicator Settings: Default Configuration.
Base Order: 500 USDT, Limit by default (Market toggle available).
Entry Trigger: 5m RSI(9) Crossing Down 80 (evaluated on the 15m chart).
Averaging Orders: 3 with fixed deviations +1% / +2% / +3% above base entry; uniform 250 USDT sizing.
Take Profit: 1.3% below average entry, with 0.3% trailing.
Stop Loss: 8% above average entry (hard close).
Strategy: Short Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +462.89 USDT (+4.63%)
Max Equity Drawdown: 173.62 USDT (1.73%)
Total Closed Trades: 131
Percent Profitable: 87.79% (115 / 131)
Profit Factor: 2.821
🔷 How to Use It:
🔸 Add the strategy to a 15-minute BCH / USDT chart (the RSI input stays on 5m — this is the intended pairing).
🔸 Adjust Settings: Review the Base Order Size, the AO count/deviation/size, the RSI trigger level/timeframe, the Take Profit/Trailing, and the Stop Loss. Defaults mirror the source DCA Bot configuration.
🔸 Results Review: 131 closed trades clears the ~100-trade floor; still validate across a longer window or more assets, and confirm drawdown and trade frequency fit your tolerance before going live.
🔸 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. The strategy emits JSON for entry, each averaging order, and exit.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): USDT amount opened on the initial short.
Use LIMIT for Base: Toggle between Limit (default) and Market entry.
Averaging Orders per Trade: Number of safety orders (default 3).
First AO Size (USDT): Size of each averaging order (uniform by default).
Deviation to First AO (%) / Deviation Step Multiplier: Spacing of the AO ladder above base entry. Defaults to uniform +1% steps.
Order Size Multiplier: Per-rung size scaling (1.0 = uniform).
RSI Timeframe / Length / Crossing Down Level: The RSI(9) crossing-down trigger — default 5m, run on the 15m chart.
Take Profit (%) / Trailing (%): TP distance below average entry and the trailing retrace that closes the position.
Stop Loss (%): Hard stop above average entry.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle DCA 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
RSI Divergence (Bull/Bear) RSI Divergence (Bull/Bear) is an advanced momentum analysis indicator that automatically detects bullish and bearish RSI divergence between price action and the Relative Strength Index (RSI). These divergence signals can help traders identify potential market reversals, trend exhaustion, and high-probability trading opportunities across multiple financial markets.
The indicator continuously analyzes swing highs and swing lows in both price and RSI, highlighting areas where momentum no longer confirms the current price movement. These conditions often appear before significant trend reversals or corrective moves.
Features
• Automatic Bullish RSI Divergence Detection
• Automatic Bearish RSI Divergence Detection
• Swing High & Swing Low Analysis
• Visual Buy & Sell Signal Labels
• Divergence Confirmation Zones
• Optional RSI Sensitivity Settings
• Clean & Lightweight Chart Layout
• Multi-Timeframe Compatible
• Non-Repainting Divergence Detection
• Customizable Signal Display
How It Works
The indicator monitors price swings alongside RSI momentum.
When price forms a **Lower Low** while RSI forms a **Higher Low**, a **Bullish Divergence** is detected, suggesting weakening selling pressure and a possible bullish reversal.
When price forms a **Higher High** while RSI forms a **Lower High**, a **Bearish Divergence** is detected, indicating weakening buying momentum and a potential bearish reversal Signals are displayed directly on the chart, allowing traders to quickly identify possible turning points.
Signal Types
🟢 Bullish Divergence
• Price makes a Lower Low
• RSI makes a Higher Low
• Possible bullish reversal
• Momentum strengthening
🔴 Bearish Divergence
• Price makes a Higher High
• RSI makes a Lower High
• Possible bearish reversal
• Momentum weakening
Best Markets
• Forex • Gold (XAUUSD) • Silver (XAGUSD)
• Crypto • Indices • Stocks • Futures
Recommended Timeframes
Scalping • M5 • M15
Intraday • M30 • H1
Swing Trading • H4 • Daily
Indicator Highlights
• Automatic RSI Divergence Detection
• Early Reversal Identification
• Visual Buy & Sell Signals
• High-Probability Momentum Analysis
• Non-Repainting Logic
• Adjustable RSI Parameters
• Beginner Friendly
• Professional Trading Tool
• Works in Trending and Ranging Markets
Suggested Trading Workflow
1. Identify the overall market trend.
2. Wait for a Bullish or Bearish RSI Divergence signal.
3. Confirm the setup using market structure, support/resistance, or candlestick confirmation.
4. Enter the trade with proper risk management and position sizing.
Notes
This indicator is designed to assist traders in identifying potential momentum shifts through RSI divergence analysis. It should be used alongside market structure, price action, and sound risk management principles. Like all technical analysis tools, it does not predict future price movements or guarantee profitable trades. Indicator
Cardwell RSI Trade Navigator [MarkitTick]💡 An advanced, multi-dimensional technical overlay designed to translate hidden momentum shifts into actionable, visually structured chart setups.
By extracting the core principles of Andrew Cardwell's methodology—which applies moving averages directly to the Relative Strength Index (RSI) rather than price—this tool identifies underlying momentum trends before they fully manifest in price action.
✨ Originality and Utility
Standard oscillators force traders to divert their attention away from price action to interpret lower-panel squiggles, which can often lead to a disconnect in charting focus.
This script is highly original because it extracts the mathematical cross of RSI-based moving averages and projects them directly onto the main price chart as a comprehensive, fully visualized trade management ecosystem.
It does not just paint a simple signal arrow; it algorithmically constructs a complete risk-to-reward framework the exact moment a momentum cross is mathematically validated.
By integrating directional filters like the ADX and higher timeframe (HTF) consensus protocols, it effectively filters out low-probability market chop.
The primary utility lies in its ability to automate the visual calculation of entry parameters, construct stop losses based on real-time volatility, and project multiple take-profit milestones based on strict multiples, essentially acting as a dynamic charting assistant built entirely on objective mathematical rules.
🔬 Methodology and Concepts
The core computational engine of this indicator relies on the calculation of a standard 14-period Relative Strength Index (RSI).
Instead of looking for traditional overbought or oversold reversal levels, the script calculates two Relative Moving Averages (RMA) of the RSI itself—a Fast RMA (9-period) and a Slow RMA (45-period).
A bullish bias is generated when the Fast RMA crosses above the Slow RMA, indicating that short-term momentum is accelerating faster than the baseline trend velocity.
Conversely, a bearish bias occurs when the Fast RMA crosses below the Slow RMA, signaling immediate downside momentum acceleration.
To ensure these momentum signals are not triggered in stagnant or mean-reverting markets, the script integrates an Average Directional Index (ADX) filter.
The ADX must register a value above a user-defined threshold (default 20) to mathematically confirm that the market is currently in a trending phase capable of sustaining the RSI momentum push.
Furthermore, a Higher Timeframe (HTF) filter requests the RSI RMA cross status from a macro timeframe. Signals on the current charting timeframe are only validated if they align perfectly with the HTF bias, ensuring that all setups are traded strictly in the direction of the dominant market flow.
Once all conditions of a valid signal are met, the script utilizes the Average True Range (ATR) to calculate a dynamic, volatility-adjusted Stop Loss, and then projects exact Take Profit targets using standardized Risk:Reward multipliers.
🎨 Visual Guide
The script transforms the standard candlestick chart into a highly visual, logically color-coded trade environment.
Candle Coloring: Candlesticks are dynamically colored based on underlying momentum strength. A visual gradient shifts from a neutral gray to a bright green (bullish) or bright red (bearish) depending directly on the separation distance between the Fast and Slow RSI RMAs.
HTF Trend Cloud: An optional visual cloud is plotted both above and below the price action. It is colored teal for HTF bullishness and crimson for HTF bearishness, offering traders macro context at a single glance without switching timeframes.
Trade Setup Lines: Upon a validated signal, dashed white horizontal lines appear on the chart, representing the exact calculated price levels for the Stop Loss, Entry point, Take Profit 1 (TP1), Take Profit 2 (TP2), and Take Profit 3 (TP3).
Risk Zones: The chart background between the entry price and the stop loss is shaded in a semi-transparent dark red. The zones between the entry and the consecutive take-profit levels are shaded in progressive green tones to visually represent risk versus reward areas.
Price Labels: Distinctive text labels featuring geometric icons are plotted dynamically at the end of the trade lines, displaying the exact numeric price coordinates for the Stop Loss, Entry, and all TPs.
Signal Strength Score Label: is a calculated metric designed to quantify the momentum and quality of the trade setup at the exact moment the signal is triggered. This value provides a "snapshot" of the signal's conviction level the moment it appears, whereas dashboard metrics track ongoing market conditions.
Dashboard Table: Located permanently in the top right corner, this dark-themed data table displays real-time metrics including the ticker symbol, current trend direction, current ATR value, a visual ADX strength bar, an overall signal strength percentage, the overarching HTF bias, and a counter tracking the number of bars since the last valid signal.
📖 How to Use
Traders can utilize this framework to efficiently identify and manage momentum-based trend continuation setups across any asset.
First, wait for a clear momentum shift, visually indicated by a change in the candlestick gradient color and the sudden appearance of the geometric trade setup zones.
Before considering the setup valid, reference the top-right dashboard table. Confirm that the ADX bar is registering sufficient trend strength and that the HTF Bias aligns with the direction of the signal.
Once the dashed white lines and colored risk zones appear, use the Entry line as the suggested area of execution.
The Stop Loss line provides a definitive, volatility-based invalidation point that should be respected.
As price moves in favor of the active setup, closely monitor the progression through the green reward zones.
If the "Breakeven on TP1" feature is enabled in the settings, observe the Stop Loss label automatically transitioning to a Breakeven line once the first target is struck, theoretically securing the position.
Finally, use the dynamic Risk:Reward live label attached to the current price action to actively monitor the floating R-multiple of the current signal.
⚙️ Inputs and Settings
RSI Length & RMA Lengths: Controls the core sensitivity of the underlying momentum engine. Lower values create more frequent signals, while higher values smooth the data for longer-term trend captures.
ATR Length & SL Multiplier: Defines the strictness of the stop loss protocol. A higher multiplier increases the breathing room for the trade but mathematically requires a larger price move to achieve a 1R target.
TP Risk:Reward Multipliers: Customizes the exact distance of the three take-profit targets relative to the initial ATR-based risk unit.
HTF Timeframe: Sets the macro timeframe used for the overarching trend consensus filter.
Choppiness / ADX Filter: Toggles the strict requirement for a minimum ADX threshold to validate signals, preventing entries in tight trading ranges.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Momentum Derivatives and Relative Strength
The foundational architecture of this script rests upon J. Welles Wilder Jr.'s Relative Strength Index (RSI), a momentum oscillator that measures the speed and change of price movements.
The mathematical formula bounds the output between absolute values of 0 and 100.
By taking a derivative of this oscillator—specifically applying Relative Moving Averages (RMAs, which are mathematically equivalent to Wilder's Smoothing method or an Exponential Moving Average with alpha = 1/length)—the script effectively isolates the velocity of the momentum itself.
The intersection of a fast-period RMA and a slow-period RMA of the RSI mathematically represents a point of momentum inflection, where short-term acceleration deviates significantly from the longer-term mean.
● Volatility-Normalized Risk Management
The utilization of the Average True Range (ATR) establishes a statistically sound, non-static risk framework.
ATR quantifies the historical volatility of an asset by calculating the greatest of the current high minus the current low, the absolute value of the current high minus the previous close, and the absolute value of the current low minus the previous close.
By multiplying the ATR by a specific scalar value, the script dynamically calculates a stop-loss distance that is statistically placed outside the normal noise distribution of the current market environment.
This approach is scientifically superior to static percentage-based stop losses, as it continuously adapts to the heteroskedasticity (changing variance) inherent in complex financial time series.
● Trend Directionality and Vector Strength
The Average Directional Index (ADX) component provides a purely quantitative measure of trend strength that is entirely independent of direction.
ADX is derived from the smoothed moving averages of the +DI and -DI, which measure the positive and negative directional movement vectors.
By requiring the ADX to breach a specific numerical threshold, the script mathematically filters out random walk (stochastic) market phases.
This ensures that the structural momentum setups only trigger when they occur within a statistically significant directional drift, massively increasing the probability of trend continuation.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
Multi-Factor Divergence MatrixMulti-Factor Divergence Matrix
OVERVIEW
Most divergence tools read one oscillator against price. The Multi-Factor Divergence Matrix reads fifteen independent lenses at once, standardizes them onto a single shared standard-deviation (sigma) scale, and then organizes them into a structure: lenses roll up into 14 aspects (distinct questions), aspects roll up into 6 families (factor classes), and families roll up into one composite. Divergence is detected five different ways on that construction, and a built-in calibration harness scores whether each method has actually carried any edge on your instrument.
The core idea: a price move is more trustworthy when many independent reads confirm it, and a divergence is more meaningful when it shows up across different kinds of information — not just three flavours of momentum that all say the same thing.
WHY THE COMPONENTS BELONG IN ONE SCRIPT (mashup rationale)
This is a deliberate multi-factor engine, not indicators stacked side by side. Every part answers the same question — is this price move confirmed, and by how broad a set of independent reads? — and each fixes a blind spot of the others:
A single oscillator can only diverge one way. Fifteen lenses across six families let price be unconfirmed by momentum, by trend efficiency, by location, by volatility, by order flow, or by cross-asset carry — independently.
Raw factor-stacking double-counts. Standardizing every lens to one sigma scale makes them directly comparable, and grouping correlated lenses into aspects (then families) means consensus is counted where it carries independent information, not where it merely repeats.
One detection method misses what another catches. Pivot divergence is precise but lags; slope fires earlier; correlation is continuous; sequential catches structured exhaustion; the intra-family split is often the very first crack. Run together, they cover the ways divergence actually appears.
Assertions are cheap. The calibration harness ties the whole construction back to realized forward outcomes, per method, so the tool reports whether its own signals carry edge rather than claiming they do.
Remove any one layer and the central question is answered less completely — which is what makes them one tool.
HOW IT WORKS
The 15 lenses → 14 aspects → 6 families
Momentum — oscillatory (RSI + Know Sure Thing), velocity (low-lag two-pole strength), stationary (fractional-difference of log price)
Trend / Efficiency — path quality (Kaufman efficiency ratio), extension (SAR distance in ATR units), rollover (dual-horizon efficiency gap)
Location / Mean — volume-anchored (VWAP deviation), geometric (linear-regression deviation)
Volatility — realized expansion (directional range), implied-vs-realized (variance-risk-premium spread)
Flow / Volume — net pressure (cumulative signed-volume delta, lower-timeframe estimated), volume-weighted (Money Flow Index)
Cross-Asset — carry (futures-vs-spot basis), fear (volatility-index vs price)
Each lens is z-scored over a rolling window (up = bullish). Correlated lenses that answer the same question (e.g. RSI and KST) are averaged into one aspect — the anti-redundancy step. A family agrees only when a majority of its filled aspects align; when its aspects disagree it is flagged SPLIT.
Two consensus axes, both at family resolution, auto-scaled by timeframe
Extreme-count — how many families are stretched to their extreme.
Divergence-count — how many families are diverging from price right now.
Five detection methods
Pivot — regular, hidden, exaggerated (equal-extreme) and triple divergence on the composite.
Slope — price-vs-composite regression-slope sign disagreement (fires earlier than pivots).
Correlation — rolling price-composite correlation flipping negative (continuous, always-on).
Sequential — a structured RSI exhaustion pattern (three deeper pushes, then a turn).
Leading — the intra-family SPLIT, often the first warning before a family flips.
Calibration. Each event is a directional hypothesis, queued and resolved a fixed horizon later versus an ATR threshold, then compared with the unconditional same-horizon base rate. The dashboard reports, per method: number of events, Hit %, and Edge = Hit − Base. Events are logged and resolved on confirmed bars only.
HOW TO USE
The dashboard has two modes. Compact (default) shows the decision essentials: the composite zone, the two consensus counts (Stretched X/6 · Diverging Y/6), a one-line family summary (bull / bear / split), and the single best-calibrated method with its Edge. Pro expands this to every family row (vote arrow, aspect agreement, SPLIT flag) and every per-method calibration class. In both, a high divergence-count backed by clean family agreement is strong context; the Edge figure tells you whether that read has actually preceded a move on this symbol and timeframe. Treat consensus as context, never a standalone trigger.
UNIVERSAL ACROSS MARKETS
Price, high, low, the VWAP source, the spot reference symbol and the volatility symbol are all inputs, so the engine runs on any instrument and timeframe. Volume-based lenses (VWAP, flow, MFI) need real traded volume — use the futures contract, not a cash index. Defaults target NSE NIFTY index futures intraday with an NSE:NIFTY spot reference and NSE:INDIAVIX; lenses without data quietly drop out and the consensus scales to whatever stays active.
ORIGINALITY
The individual techniques are public and credited below. The original work is the integration: standardizing fifteen heterogeneous reads onto one sigma axis, the aspect → family → composite roll-up that counts agreement only where it is independent, the dual extreme-and-divergence consensus, the surfacing of intra-family disagreement as a leading signal, and the forward base-rate calibration over every detection method. No third-party Pine code is reused.
CONCEPT CREDIT
RSI, Parabolic SAR, ATR, DMI — J. Welles Wilder. Know Sure Thing — Martin J. Pring. Efficiency Ratio — Perry J. Kaufman. Money Flow Index — Quong & Soudack. VWAP and cumulative volume delta — standard public market-microstructure concepts. Fractional differentiation — the long-memory / stationarity literature (Hosking 1981; adapted for finance by M. López de Prado). Two-pole low-pass smoothing — John F. Ehlers. The basis is explained by the cost-of-carry framework (N. Kaldor 1939; H. Working 1948–49). Variance risk premium — the implied-minus-realized literature. Linear regression and price/oscillator divergence are long-established public techniques. Not affiliated with, nor endorsed by, any third party.
HONESTY / LIMITATIONS
Consensus is context, not a trigger. Independence is managed, not perfect — lenses inside a family still share inputs, which is exactly why consensus counts families and aspects rather than raw lenses, and why a high count is never proof. The Edge figures are in-sample, close-to-close, with overlapping forward windows and no costs — descriptive context, not a verified backtest. An Edge near zero, negative, or unstable across timeframes is the harness honestly telling you the method has no reliable edge on that instrument; do not tune parameters until it turns green — that is curve-fitting. Divergence and reversals confirm a few bars after their pivot (inherent to honest pivot detection). Nothing here predicts price.
DISCLAIMER
Research and educational tool only. NOT financial advice and NO guarantee of profitability or accuracy. Indicators describe past behaviour; they do not predict the future. Trading carries risk of loss. Test out-of-sample and make your own decisions. The author accepts no liability for any use of this script. Indicator
Fractional-Diff Momentum OscillatorFractional-Diff Momentum Oscillator
What it does
The Fractional-Diff Momentum Oscillator is a momentum line, scaled in standard-deviation (σ) units around a zero balance, built on the fractional differencing of price — the smallest amount of differencing that makes price statistically stationary while still keeping its memory.
Why this is different (and original)
Almost every momentum oscillator works on returns — that is, price differenced once (integer order d = 1). Returns are stationary, but differencing once erases the series' memory, throwing away the slow, persistent structure that carries trend information. Raw price (order d = 0) keeps all the memory but is non-stationary and unusable by most statistical tools.
Fractional differencing uses a non-integer order (typically 0.3–0.6) that sits between the two: it removes just enough drift to reach stationarity while retaining long memory. The result is a momentum series that is both well-behaved and information-rich. This transform is standard in quantitative research but rare on retail charts, where oscillators almost universally difference once and discard the signal. That is what makes this original: it is a momentum oscillator built on a memory-preserving transform rather than plain returns.
How it works
The fixed-width fractional-difference weights are generated recursively — w(0) = 1, w(k) = −w(k−1)·(d − k + 1)/k — and truncated once they fall below a tolerance, giving a finite window. Those weights are convolved with log-price to produce the fractionally-differenced series. That series is then z-scored over the normalization window and lightly smoothed into the σ oscillator you see, centred on zero.
How to use it
Zero is the balance line. Above zero = net up-momentum; below = net down-momentum.
Dashed σ bands mark stretched momentum; dotted bands mark extremes prone to exhaustion (red on top, green on the bottom in the standard reading).
Zero-crosses (triangles) are momentum-flip events.
Divergences (circles) warn when price makes a new extreme that momentum does not confirm.
Read the EDGE row. The dashboard runs a live forward-return harness: for every momentum flip it checks whether a favourable move (≥ k×ATR within the horizon) actually occurred, and compares that Hit % against the unconditional Base %. EDGE = Hit − Base is the honest measure of whether the signal adds information on your instrument and timeframe. If EDGE is near zero, the signal is not helping there — and the tool says so.
Settings guide
01 · Data & Differencing — source, log-price toggle, differencing order d, weight tolerance, max window, and a universal price source for the harness.
02 · Normalization — z-score window and output smoothing.
03 · Calibration — horizon, favourable-move threshold (×ATR), base-rate window.
04 · Bands — momentum and extreme σ bands; divergence pivot.
05 · Display & Theme — visual style (gradient area + glow / histogram / line), regime tint, dashboard, colors.
Non-repaint
The weights are fixed and the convolution reads only closed bars — no recalculation of past values, no future leak.
Concept credit
Fixed-width window fractional differentiation — Marcos López de Prado, Advances in Financial Machine Learning (2018).
Fractional integration in time series — Hosking (1981); Granger & Joyeux (1980).
Disclaimer
For research and education only. Not financial advice, not a recommendation, and not a guarantee of future results. All statistics shown are in-sample, close-to-close, and exclude costs — a study aid, not a backtest. Do your own research and manage your own risk. Indicator
