SR Channel + EMA + RSI MTF + VolHighlightSR + Volume + RSI MTF – edited by Mochi
This indicator combines three tools into a single script:
SR Zones from Pivots
Automatically detects clusters of pivot highs/lows and groups them into support and resistance zones.
Zone width is tightened using a percentage of the pivot cluster range so levels are more precise and cleaner.
Each zone includes:
A colored box (SR area),
A dashed midline,
A POC line (price level with the highest traded volume inside the zone),
A label showing the zone price and distance (%) from current price.
Zone color is dynamic but simple and stable:
If price closes below the mid of the zone → it is treated as resistance (red).
If price closes above the mid of the zone → it is treated as support (green).
Box, lines, and label always share the same color.
Volume Inside the Zone + POC
Calculates buy/sell volume for candles whose close lies inside each zone.
Uses abs(buyVol − sellVol) / (buyVol + sellVol) to measure volume imbalance and control box opacity:
Stronger, more one‑sided volume → darker box (stronger zone).
POC is drawn as a thin line with the same color as the zone to highlight the best liquidity level for entries/TP.
Multi‑Timeframe RSI Dashboard
Shows RSI(14) values for multiple timeframes (1m, 5m, 15m, 30m, 1h, 4h, 8h, 1d), each can be toggled on/off.
Background color of each RSI cell:
RSI > 89 → red (strong overbought),
80–89 → orange (warning area),
RSI < 28 → lime (strong oversold),
Otherwise → white (neutral).
The goal of this script is to give traders a clear view of:
Key support/resistance zones,
Their volume quality and POC,
And multi‑TF overbought/oversold conditions via the RSI dashboard – all in one indicator to support retest/flip‑zone trading.
指标和策略
MSO - Market Stress Oscillator [WavesUnchained]MSO - Market Stress Oscillator
Bidirectional stress oscillator built on WVF + Z-score, with JMA/ADX filters, regime bias, and validated follow-through. Designed to expose downside panic vs upside euphoria and measure whether the market accepts or rejects each stress event.
Quick Setup
- Stress Color Mode : Intuitive (Downside=green, Upside=red) or Technical (classic colors).
CORE CONCEPT
- Downside stress : price flushes below WVF baseline (panic)
- Upside stress : price stretches above WVF baseline (euphoria)
- Stress is normalized via Z-score for cross-asset/timeframe robustness
ENGINE (BI-WVF + Z-SCORE)
- WVF Long and Short computed separately (panic vs euphoria)
- Z-score window normalizes extremes
- Thresholds are TF-aware (15m / 1h / 4h / D / W / M)
QUALITY FILTERS
- JMA trend filter (slope-based, low-lag)
- ADX minimum for trend strength
- Min Extreme Duration to avoid 1-bar noise
- Cooldown to prevent signal clustering
ACCEPT / REJECT LOGIC
- Events are evaluated after reactBars (forward follow-through)
- Accepted : follow-through >= minFollowATR
- Rejected : follow-through < minFollowATR
- Scores (0..1) optionally plotted as acceptance strength
BIAS / REGIME CONTEXT
- Bias line : zL - zS (who dominates)
- Bias band : regime threshold (only meaningful outside band)
- HTF Wind : higher-timeframe bias flip (JMA smoothed)
- Clarity Label : regime entry aligned with HTF + absBias threshold
VISUALIZATION
- Stress Lines : Red = downside stress (panic), Green = upside stress (euphoria)
- Bias Line : zL - zS (who dominates). Neutral inside band, colored outside.
- Bias Band : regime threshold. Fill shows when bias is usable.
- Zones : boxes at peak events (history preserved, FIFO capped)
- Chart Labels : DA/DR/UA/UR (or LA/LR/SA/SR) at peaks
- Lines : reaction window + peak level lines (FIFO capped)
STRESS COLOR MODE
- Intuitive : Downside stress = green, Upside stress = red (opportunity mapping)
- Technical : Downside stress = red, Upside stress = green (classic convention)
- This setting is visual only ; logic, bias, and signals are unchanged
HOW TO USE
1. Read the stress lines : red spikes = panic risk, green spikes = euphoria risk.
2. Check bias : outside the band = usable regime; inside = noise.
3. Use DA/DR/UA/UR :
- DA/UA = stress accepted (follow-through confirmed)
- DR/UR = stress rejected (weak follow-through)
4. Add HTF wind : prefer signals aligned with HTF bias.
5. Tune presets by TF; use manual TF override for testing.
PRESETS & UI
- Full TF preset table (15m / 1h / 4h / D / W / M)
- Manual TF override for testing
- Preset summary panel (optional)
LOGGING (CSV)
- Pivot and stress logs for validation
- Early/First-pivot classification options
- Label IDs included for chart-to-log tracing
BEST USE CASES
- Panic/euphoria detection with follow-through validation
- Regime-aware context (bias + HTF wind)
- Multi-timeframe stress mapping (15m to Weekly)
Version: 1.0.0
Author: WavesUnchained
Pine Script: v6
Educational use only. Test thoroughly before live trading.
BTC Valuation ZonesBTC Valuation – Distance From 200 MA
This indicator provides a simple but powerful Bitcoin valuation framework based on how far price is from the 200-period Moving Average, a level that has historically acted as Bitcoin’s long-term equilibrium.
Instead of predicting tops or bottoms, this tool focuses on mean-reversion behavior:
When price deviates too far above the 200 MA → risk increases
When price deviates deeply below the 200 MA → long-term opportunity increases
SR Channel + EMA + RSI MTF + VolHighlight - Edited by MochiSR + Volume + RSI MTF – edited by Mochi
This indicator combines three tools into a single script:
SR Zones from Pivots
Automatically detects clusters of pivot highs/lows and groups them into support and resistance zones.
Zone width is tightened using a percentage of the pivot cluster range so levels are more precise and cleaner.
Each zone includes:
A colored box (SR area),
A dashed midline,
A POC line (price level with the highest traded volume inside the zone),
A label showing the zone price and distance (%) from current price.
Zone color is dynamic but simple and stable:
If price closes below the mid of the zone → it is treated as resistance (red).
If price closes above the mid of the zone → it is treated as support (green).
Box, lines, and label always share the same color.
Volume Inside the Zone + POC
Calculates buy/sell volume for candles whose close lies inside each zone.
Uses abs(buyVol − sellVol) / (buyVol + sellVol) to measure volume imbalance and control box opacity:
Stronger, more one‑sided volume → darker box (stronger zone).
POC is drawn as a thin line with the same color as the zone to highlight the best liquidity level for entries/TP.
Multi‑Timeframe RSI Dashboard
Shows RSI(14) values for multiple timeframes (1m, 5m, 15m, 30m, 1h, 4h, 8h, 1d), each can be toggled on/off.
Background color of each RSI cell:
RSI > 89 → red (strong overbought),
80–89 → orange (warning area),
RSI < 28 → lime (strong oversold),
Otherwise → white (neutral).
The goal of this script is to give traders a clear view of:
Key support/resistance zones,
Their volume quality and POC,
And multi‑TF overbought/oversold conditions via the RSI dashboard – all in one indicator to support retest/flip‑zone trading.
Market Exhaustion [WavesUnchained]Market Exhaustion
Multi-oscillator exhaustion detector combining MFI + optional CCI, HTF bias, StochRSI timing, and a divergence engine with an Exhaustion Score (0-100).
CORE CONCEPT
- Detects exhaustion via regular divergences anchored on price pivots
- Scores each divergence (0-100) using 5 components
- Line width = quality, color = direction (never thicker than main line)
OSCILLATOR MODES
- MFI : Engine uses MFI only
- CCI : Engine uses CCI mapped to 0-100
- MFI+CCI : Both plotted, engine source selectable (MFI or CCI)
EXHAUSTION SCORE (0-100)
1. Sequence (Div 1/2/3...) - repeated attempts increase score
2. Fatigue - no new oscillator extreme over lookback
3. Formation Time - bars between pivots
4. Reaction - post-divergence bounce/drop vs ATR
5. Impulse - MFI/CCI delta + swing size
DIVERGENCE ENGINE
- Price-pivot anchored (LL/HH) with osc confirmation (HL/LH)
- OS/OB gating with dynamic zones + fallback to 20/80
- Tolerant direction checks (price + osc eps)
- Auto cleanup (max objects)
HTF CONTEXT
- Auto-HTF MFI bias label
- Optional HTF filter for signals
- Bias bonus (optional) for Exhaustion Score
SIGNALS & TIMING
- StochRSI timing + MFI zone confirmation
- Context + timing signals (L/S markers)
- Zone confirm bars
VISUALIZATION
- Color-coded MFI line (OB/OS/neutral)
- Optional CCI (mapped 0-100) line
- Divergence line width = quality, endpoint markers
- Optional mid-label with score
- Dynamic zones + optional fill
BEST USE CASES
- Reversal scouting at extremes
- Filtering weak swings
- 15M-4H swing exhaustion reads
- HTF bias + divergence confluence
Version: 1.0.0
Author: WavesUnchained
Pine Script: v6
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
This Pine Script v6 strategy is designed for cryptocurrency markets operating on 5-minute and faster timeframes. It combines volatility regime detection, multi-path signal confirmation, and adaptive risk management to identify momentum-based trading opportunities in perpetual futures markets.
Core Design Principles
The strategy addresses three challenges specific to cryptocurrency trading:
24/7 market operation without session boundaries requires continuous monitoring and execution logic
Volatility regimes shift rapidly, demanding adaptive stop and target calculations
Tick-level responsiveness is critical for capturing momentum moves before they complete
Strategy Architecture
1. Signal Generation Stack
The strategy uses multiple technical indicators calibrated for cryptocurrency momentum:
MACD with parameters 8/21/5 (fast/slow/signal) optimized for crypto acceleration phases
EMA ribbon using 8/21/34 periods with slope analysis to assess trend structure
Volume impulse detection combining SMA baseline, standard deviation, and z-score filtering
RSI (21 period) and MFI (21 period) for momentum confirmation
Bollinger Bands and Keltner Channels for squeeze detection
2. Volatility Regime Classification
The strategy normalizes ATR as a percentage of price and classifies market conditions into three regimes:
Compression (< 0.8% ATR): Reduced position sizing, tighter stops (1.05x ATR), lower profit targets (1.6x ATR)
Expansion (0.8% - 1.6% ATR): Standard risk parameters, balanced risk-reward (1.55x stop, 2.05x target)
Velocity (> 1.6% ATR): Wider stops (2.1x ATR), amplified targets (2.8x ATR), tighter trailing offsets
ATR is calculated over 21 periods and smoothed with a 13-period EMA to reduce noise from wicks.
3. Multi-Path Entry System
Four independent signal pathways contribute to a composite strength score (0-100):
Trend Break (30 points): Requires EMA ribbon alignment, positive slope, and structure breakout above/below recent highs/lows
Momentum Surge (30 points): MACD histogram exceeds adaptive baseline, MACD line crosses signal, RSI/MFI above/below thresholds, with volume impulse confirmation
Squeeze Release (25 points): Bollinger Bands compress inside Keltner Channels, then release with momentum bias
Micro Pullback (15 points): Shallow retracements within trend structure that reset without breaking support/resistance
Additional scoring modifiers:
Volume impulse: +5 points when present, -5 when absent
Regime bonus: +5 in velocity, -2 in compression
Cycle bias: +5 when aligned, -5 when counter-trend
Trades only execute when the composite score reaches the minimum threshold (default: 55) and all filters agree.
4. Risk Management Framework
Position sizing is calculated from:
RiskCapital = Equity × (riskPerTradePct / 100)
StopDistance = ATR × StopMultiplier(regime)
Quantity = min(RiskCapital / StopDistance, MaxExposure / Price)
The strategy includes:
Risk per trade: 0.65% of equity (configurable)
Maximum exposure: 12% of equity (configurable)
Regime-adaptive stop and target multipliers
Adaptive trailing stops based on ATR and regime
Kill switch that disables new entries after 6.5% drawdown
Momentum fail-safe exits when MACD polarity flips or ribbon structure breaks
5. Additional Filters
Cycle Oscillator : Measures price deviation from 55-period EMA. Requires cycle bias alignment (default: ±0.15%) before entry
BTC Dominance Filter : Optional filter using CRYPTOCAP:BTC.D to reduce long entries during risk-off periods (rising dominance) and short entries during risk-on periods
Session Filter : Optional time-based restriction (disabled by default for 24/7 operation)
Strategy Parameters
All default values used in backtesting:
Core Controls
Enable Short Structure: true
Restrict to Session Window: false
Execution Session: 0000-2359:1234567 (24/7)
Allow Same-Bar Re-Entry: true
Optimization Constants
MACD Fast Length: 8
MACD Slow Length: 21
MACD Signal Length: 5
EMA Fast: 8
EMA Mid: 21
EMA Slow: 34
EMA Slope Lookback: 8
Structure Break Window: 9
Regime Intelligence
ATR Length: 21
Volatility Soothing: 13
Low Vol Regime Threshold: 0.8% ATR
High Vol Regime Threshold: 1.6% ATR
Cycle Bias Length: 55
Cycle Bias Threshold: 0.15%
BTC Dominance Feed: CRYPTOCAP:BTC.D
BTC Dominance Confirmation: true
Signal Pathways
Volume Baseline Length: 34
Volume Impulse Multiplier: 1.15
Volume Z-Score Threshold: 0.5
MACD Histogram Smoothing: 5
MACD Histogram Sensitivity: 1.15
RSI Length: 21
RSI Momentum Trigger: 55
MFI Length: 21
MFI Momentum Trigger: 55
Squeeze Length: 20
Bollinger Multiplier: 1.5
Keltner Multiplier: 1.8
Squeeze Release Momentum Gate: 1.0
Micro Pullback Depth: 7
Minimum Composite Signal Strength: 55
Risk Architecture
Risk Allocation per Trade: 0.65%
Max Exposure: 12% of Equity
Base Risk/Reward Anchor: 1.8
Stop Multiplier • Low Regime: 1.05
Stop Multiplier • Medium Regime: 1.55
Stop Multiplier • High Regime: 2.1
Take Profit Multiplier • Low Regime: 1.6
Take Profit Multiplier • Medium Regime: 2.05
Take Profit Multiplier • High Regime: 2.8
Adaptive Trailing Engine: true
Trailing Offset Multiplier: 0.9
Quantity Granularity: 0.001
Kill Switch Drawdown: 6.5%
Strategy Settings
Initial Capital: $100,000
Commission: 0.04% (0.04 commission_value)
Slippage: 1 tick
Pyramiding: 1 (no position stacking)
calc_on_every_tick: true
calc_on_order_fills: true
Visualization Features
The strategy includes:
EMA ribbon overlay (8/21/34) with customizable colors
Regime-tinted background (compression: indigo, expansion: purple, velocity: magenta)
Dynamic bar coloring based on signal strength divergence
Signal labels for entry points
On-chart dashboard displaying regime, ATR%, signal strength, position status, stops, targets, and risk metrics
Recommended Usage
Timeframes
The strategy is optimized for 5-minute charts. It can operate on 3-minute and 1-minute timeframes for faster scalping, or 15-minute for swing confirmation. When using higher timeframes, consider:
Increasing structure lookback windows
Raising RSI trigger thresholds above 58 to filter noise
Extending volume baseline length
Markets
Designed for high-liquidity cryptocurrency perpetual futures:
BTC/USDT, BTC/USD perpetuals
ETH perpetuals
Major L1 tokens with sufficient volume
For thinner order books, increase volume impulse multiplier and adjust quantity granularity to match exchange minimums.
Limitations and Compromises
Backtesting Considerations
TradingView strategy backtesting does not replicate broker execution. Actual fills, slippage, and commissions may differ
The strategy uses calc_on_every_tick=true and calc_on_order_fills=true to reduce bar-close distortions, but real execution still depends on broker infrastructure
At least 200 historical bars are required to stabilize regime classification, volume baselines, and cycle context
Market Structure Dependencies
BTC dominance feed ( CRYPTOCAP:BTC.D ) may lag during low-liquidity periods or weekends. Consider disabling the filter if data quality degrades
Volume impulse detection assumes consistent order book depth. During extreme volatility or exchange issues, volume signatures may be unreliable
Regime classification based on ATR percentage assumes normal volatility distributions. During black swan events, regime thresholds may not adapt quickly enough
Parameter Sensitivity
Default parameters are tuned for BTC/ETH perpetuals on 5-minute charts. Different assets or timeframes require recalibration
The composite signal strength threshold (55) balances selectivity vs. opportunity. Higher values reduce false signals but may miss valid setups
Risk per trade (0.65%) and max exposure (12%) are conservative defaults. Aggressive scaling increases drawdown risk
Execution Constraints
Same-bar re-entry requires broker support for rapid order placement
Quantity granularity must match exchange contract minimums
Kill switch drawdown (6.5%) may trigger during normal volatility cycles, requiring manual reset
Performance Expectations
This strategy is a framework for momentum-based cryptocurrency trading. Performance depends on:
Market conditions (trending vs. ranging)
Exchange execution quality
Parameter calibration for specific assets
Risk management discipline
Backtest results shown in publications reflect specific market conditions and parameter sets. Past performance does not indicate future results. Always forward test with paper trading or broker simulation before deploying live capital.
Code Structure
The strategy is organized into functional sections:
Configuration groups for parameter organization
Helper functions for position sizing and normalization
Core indicator calculations (MACD, EMA, ATR, RSI, MFI, volume analytics)
Regime classification logic
Multi-path signal generation and composite scoring
Entry/exit orchestration with risk management
Visualization layer with dashboard and chart elements
The source code is open and can be modified to suit your trading requirements. Everyone is encouraged to understand the logic before deploying and to test thoroughly in their target markets.
Modification Guidelines
When adapting this strategy:
Document any parameter changes in your publication
Test modifications across different market regimes
Validate position sizing logic for your exchange's contract specifications
Consider exchange-specific limitations (funding rates, liquidation mechanics, order types)
Conclusion
This strategy provides a structured approach to cryptocurrency momentum trading with regime awareness and adaptive risk controls. It is not a guaranteed profit system, but rather a framework that requires understanding, testing, and ongoing calibration to market conditions.
You should thoroughly understand the logic, test extensively in their target markets, and manage risk appropriately. The strategy's effectiveness depends on proper parameter tuning, reliable execution infrastructure, and disciplined risk management.
Disclaimer
This script and its documentation are for educational and informational purposes only. They do not constitute financial advice, investment recommendations, or trading advice of any kind. Trading cryptocurrencies and derivatives involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by backtesting, does not guarantee future results.
This strategy is provided "as is" without any warranties or guarantees of profitability
You should not rely solely on this strategy for making trading decisions
Always conduct your own research and analysis before making any financial decisions
Consider consulting with a qualified financial advisor before engaging in trading activities
The authors and contributors are not responsible for any losses incurred from using this strategy
Cryptocurrency trading can result in the loss of your entire investment
Only trade with capital you can afford to lose
Use this strategy at your own risk. The responsibility for any trading decisions and their consequences lies entirely with you.
Shock Wave: EMA9 Slope / ATR (Normalized) for SPYShock Wave – EMA9 Slope Normalized by ATR (Fragility Gauge)
This indicator measures trend fragility, not direction.
Instead of relying on visual trendline angles (which change with zoom and chart scaling), this tool normalizes the slope of the 9-EMA by ATR, producing a scale-independent steepness metric that remains consistent across timeframes and zoom levels.
The goal is to identify late-stage acceleration and liquidity vulnerability — conditions where price is advancing faster than inventory can rebalance and the market becomes sensitive to forced liquidation.
What this indicator shows
Normalized EMA9 slope (ATR per bar)
An angle-like degree value derived from the normalized slope (for intuition only)
Background shading to highlight trend maturity / fragility
A compact table showing live readings on the chart
How to interpret
Green / low values (< ~0.30 ATR/bar): Healthy, sustainable trend
Orange / mid values (~0.30–0.40 ATR/bar): Late-stage acceleration
Red / high values (≥ ~0.45 ATR/bar): Fragile / liquidation-prone conditions
These thresholds are empirically derived from historical index behavior (e.g., SPY prior to 2018, 2020, 2022 volatility events).
Important notes
This is not a buy or sell signal
Red does not mean “short”
The indicator highlights risk asymmetry, not timing
Best used on higher timeframes (weekly) in conjunction with liquidity, inducement, and higher-timeframe structure analysis
Why use this
Markets often fail after strong trends, not because they are weak, but because they are crowded. This tool helps quantify when a trend has become structurally vulnerable, providing context for liquidity-based frameworks and macro risk management.
Performance with Okuninushi Line Area Determinations**Performance Indicator with Market Structure Analysis**
Building upon TradingView's official Performance indicator, I've added a custom column to assess current market structure using my Okuninushi Line methodology, which visualizes the AB structure concept.
**What is the AB Structure?**
The AB structure identifies equilibrium levels based on recent price action. The Okuninushi Line calculates the 50% midpoint between the highest high and lowest low over a specified lookback period. In this implementation, I use a 65-day period on the daily timeframe (representing one quarter: 13 weeks × 5 trading days), though this is fully customizable.
**Market Structure Classification:**
- **Above Okuninushi Line** → "upper to okuni" → Price is in the **Premium Area** (bullish structure)
- **Below Okuninushi Line** → "down to okuni" → Price is in the **Discount Area** (bearish structure)
This additional column provides an instant visual reference for whether each asset is currently trading above or below its equilibrium level, complementing the traditional performance metrics with structural context.
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Session Breakout TrackerThis indicator identifies breakout opportunities when price breaks previous session ranges, tracking 4 distinct breakout chains:
Asia → London (Primary Asia breakout during London session)
London → NY (London breakout during NY session)
NY → Asia (NY breakout during next Asia session)
Asia → NY* (Fallback Asia breakout during NY if Chain 1 had no breakout)
For each breakout, it measures the maximum distance price travels before hitting your defined stop-loss, providing exact pip/point calculations.
Features :
Automatic session detection (Asia: 18:00-03:00, London: 03:00-12:00, NY: 12:00-18:00 NYT)
Complete session range tracking - high/low for each session
Session level plotting with adjustable transparency
User Inputs :
Adjustable pip multiplier (0.0001 for Forex, 0.01 for JPY pairs)
Customizable stop-loss distance in pips
Toggle labels/table/session levels independently
Adjustable session duration for optimizing strategies and back testing
BTC - AUI 1: Macro Sentiment & On-Chain CompositeBTC - AUI 1: Macro Sentiment & On-Chain Composite | RM
Overview & Philosophy The AUI 1 ( Another Ultimate Indicator, Volume 1 ) is a 10-pillar quantitative composite designed to solve the "noise problem" in Bitcoin analysis. Most traders fail because they rely on a single metric in isolation. The AUI 1 aggregates ten distinct dimensions of the network — from speculative flow to institutional extension — into a singular 0–100 score.
The 10-Pillar Quant Framework
Each pillar is mathematically normalized to a standardized 0 to 10 scale . The sum of these pillars creates the final 0–100 index:
1. BEAM (Adaptive Logarithmic Multiple)
• Method: Log-deviation from the 4-year cycle mean.
• Logic: Measures price distance from its fundamental growth curve.
(Credit: BitcoinEcon)
2. MVRV Z-Score (Statistical Distance)
• Method: Standard deviations between Market Cap and Realized Cap.
• Logic: Identifies historical "Fair Value" vs. "Bubble" extremes.
(Credit: M. Mahmudov & D. Puell)
3. Metcalfe’s Law (Network Utility)
• Method: Logarithmic scaling of Active Addresses.
• Logic: Ensures price growth is supported by actual user adoption.
(Credit: T. Peterson)
4. RHODL Proxy (Speculative Flow)
• Method: Supply rotation intensity between HODLers and New Money.
• Logic: Cycle peaks are defined by "Old Money" distributing to "New Money."
(Credit: Philip Swift)
5. AXIS Momentum (Structural Trend Intensity)
• Method: Dual-speed Rate of Change (RoC) fusion engine.
• Logic: Identifies the acceleration and "torque" of the macro trend.
(Credit: Rob_Maths)
6. Mayer Multiple (Institutional Extension)
• Method: Raw distance from the 200-day SMA.
• Logic: Tracks the primary anchor used by institutional mean-reversion desks.
(Credit: Trace Mayer)
7. Unrealized Profit (Financial Pressure)
• Method: Absolute MVRV Ratio mapping.
• Logic: Measures the financial "stress" or "greed" held by the average holder.
8. Retail Participation (Psychology Proxy)
• Method: Inverted Log-Average Transaction Size (USD).
• Logic: Declining transaction sizes historically signal retail FOMO (Euphoria).
9. Volatility Overextension (Structural Risk)
• Method: 30-day Standard Deviation relative to the mean.
• Logic: High-intensity volatility clusters often precede cycle trend-shifts.
10. Macro RSI (Cycle Maturity)
• Method: High-timeframe momentum saturation levels.
• Logic: Identifies the statistical "Buying Exhaustion" of a macro move.
(Credit: J. Welles Wilder Jr.)
How to Read the AXIS Quadrants
The AUI 1 uses a Seamless Heatmap to categorize the market into four specific macro regimes:
❄️ 0–25: FROZEN (Deep Blue) Maximum Opportunity. Structural capitulation where only long-term conviction remains. Historically the "Generational Wealth" window.
🔵 25–50: DISCOUNT (Light Blue to Gray) Value Accumulation. The market is cooling down; risk is mathematically low, and the network is building a structural floor.
🟠 50–75: EXPANSION (Gray to Orange) Trend Acceleration. Healthy bullish growth supported by network utility and positive momentum.
🔥 75–100: SCORCHED (Orange to Deep Red) Terminal Euphoria. Maximum Risk zone. Speculative FOMO is at its peak; the market is fundamentally overextended.
The Orange Signal Line
To filter short-term noise, the AUI 1 includes a Signal Smoothing Line (Parametrizable).
• Cycle Confirmation: Index Bars crossing above the Signal Line indicates trend acceleration.
• Peak Confirmation: If the Index Score rolls over and breaks below the Signal Line while in the SCORCHED zone, the cycle peak is likely confirmed.
Credits & Data Built by Rob_Maths (2025) using on-chain frameworks from Glassnode and IntoTheBlock. Special recognition to the pioneers: Murad Mahmudov, David Puell, Philip Swift, Trace Mayer, and Timothy Peterson.
Strategic Recommendation: For the most accurate macro cycle signals and to filter daily market noise, it is strongly recommended to use this indicator on the Weekly (1W) timeframe.
⚠️ Data Requirement Note: This quantitative composite utilizes professional on-chain data feeds, specifically GLASSNODE:BTC_ACTIVEADDRESSES , GLASSNODE:BTC_ACTIVE1Y , and INTOTHEBLOCK:BTC_MVRV . A TradingView paid plan (Essential or higher) may be required to access these institutional data streams.
Disclaimer This script is for macro-economic research purposes. It is a probabilistic model, not a crystal ball. Past performance is not a guarantee of future results.
Tags:
bitcoin, btc, on-chain, macro, composite, mvrv, rhodl, momentum, index, valuation, active-addresses, cycles, sentiment, risk, AUI, Rob Maths
Participation-Weighted Orderflow Bubbles (HTF / LTF Context ToolThis indicator visualizes participation-weighted market pressure by aggregating lower-timeframe price and volume data into higher-timeframe context bubbles. It is designed to help identify directional dominance, balance, and absorption across timeframes. This is a context and bias tool, not a trade signal generator.
What the indicator shows
Each bubble represents a single chart bar, built from lower-timeframe candles.
Total Notional
Aggregated volume multiplied by price from lower-timeframe candles.
Buy / Sell Proxies
Lower-timeframe candles are classified based on where they close within their range:
– Close near the high → buy-side proxy
– Close near the low → sell-side proxy
– Middle of the range → neutral
Delta (USD and %)
Buy proxy notional minus sell proxy notional, expressed as both absolute USD delta and percentage of total notional.
Bubble colors
Green
Buy-side participation dominance.
Sell color (user configurable)
Sell-side participation dominance. The default is chosen for visibility on bearish candles and can be changed in settings.
Grey
Balanced participation. Indicates two-way trade, consolidation, or auction.
Yellow (Absorption)
High notional with limited price movement, suggesting potential absorption or distribution.
Coloring uses both relative dominance (delta percentage) and absolute dominance (minimum delta in USD), which improves behavior on higher timeframes.
Bubble size and visuals
Bubble size scales with total notional.
HD glow layers adapt automatically by timeframe.
Bubbles are drawn in front of candles for clarity.
Optional text displays delta and total notional.
Hovering over a bubble shows detailed information including total notional, buy/sell/neutral proxies, delta values, absorption status, and the number of lower-timeframe candles used.
Timeframe behavior
The indicator is designed to work across multiple timeframes. On higher timeframes, more grey bubbles are expected due to natural auction and balance behavior. Colored bubbles on higher timeframes represent sustained participation rather than short-term momentum. Visual density and performance are automatically adjusted on higher timeframes.
How to use it
Recommended workflow:
1. Higher timeframe (1H, 4H, Daily)
Use the bubbles to identify dominant buy or sell participation, balance zones, and absorption near highs or lows.
2. Lower timeframe (5m, 15m)
Take trades in alignment with the most recent higher-timeframe dominance. Be cautious or range-focused inside higher-timeframe balance zones. Use structure and price action for entries.
What this indicator is not
This indicator does not show true bid/ask data.
It does not display actual market versus limit orders.
It does not replace a DOM or exchange orderflow feed.
It should not be used as a standalone entry signal.
The indicator works within TradingView’s available data and provides a probabilistic, participation-weighted view of market pressure rather than true tape or orderflow data.
Best practices
Use a 1-minute lower timeframe for best results.
Avoid setting the lower timeframe too high relative to the chart timeframe.
Combine this tool with structure, levels, and session context.
Treat grey bubbles as information about balance, not as noise.
This tool is intended for traders who want better context and bias, not more signals.
Dynamic EMA Trend Table [Customizable]Overview
The Dynamic EMA Trend Table is a comprehensive dashboard designed to give traders an instant overview of the market trend across five distinct Exponential Moving Averages (EMAs). Instead of cluttering your chart with multiple lines, this script organizes the data into a clean, customizable table, allowing you to assess trend alignment at a glance.
How It Works
This indicator calculates five user-defined EMAs (defaulting to the popular 5, 20, 50, 100, and 200 periods). It then compares the Current Price against each EMA value to determine the immediate trend status:
Bullish State: When the current price is above the specific EMA, the table cell turns Green (customizable).
Bearish State: When the current price is below the specific EMA, the table cell turns Red (customizable).
This logic allows swing traders and scalpers to instantly see if the asset is in a strong uptrend (all cells Green), a strong downtrend (all cells Red), or a consolidation phase (mixed colors).
Key Features
Fully Customizable Periods: Change the length of all 5 EMAs to fit your specific strategy (e.g., Fibonacci numbers or standard Swing Trading settings).
Dynamic UI: Position the table anywhere on the screen (Top/Bottom/Left/Right) and adjust the size to fit your screen resolution.
Visual Cleanliness: You can choose to show the table only, or toggle the "Show EMAs on Chart" option to plot the actual lines on your chart.
Smart Coloring: The lines on the chart (if enabled) inherit the same color logic as the table—turning Green when price is above them and Red when price is below.
Settings & Configuration
Price Source: Select Close, High, Low, etc. (Default is Close).
Table Position & Size: Customize where the dashboard appears.
EMA Lengths: Set your 5 preferred lookback periods.
Color Theme: Fully adjustable colors for Bullish, Bearish, Neutral, and Background elements to match your chart theme (Dark/Light mode friendly).
Use Case Example
Trend Confirmation: A trader looking for a "Buy" entry might wait for the short-term EMAs (5 and 20) and the medium-term EMA (50) to all turn Green in the table before entering.
Support/Resistance Watch: By quickly glancing at the values in the table, you can see exactly where the 200 EMA sits without needing to scroll back on your chart to find the line.
Simple ATR Volatility Context v1.0This indicator provides a simple visual view of market volatility using ATR expressed as a percentage of price. It is designed to help identify when a market transitions from low-activity (compression) to higher-activity (expansion).
What it does
Calculates ATR as a percentage of price
Highlights the chart when volatility exceeds a user-defined threshold
Helps distinguish between quiet markets and trade-worthy conditions
How to use it
Green background indicates elevated volatility
Neutral / muted background indicates low volatility
Use alongside your own trend, structure, or entry tools
What this is not
Not a buy or sell signal
Not predictive
No performance claims
This tool is intended for market context and awareness, not standalone trading decisions.
BTC - Institutional Cost Corridor (Overlay)BTC - Institutional Cost Corridor | RM
Strategic Context
The approval of Spot Bitcoin ETFs on January 11, 2024, signaled the beginning of the "Institutional Era." Since then, price discovery has shifted from being purely retail-driven to being heavily influenced by massive, off-chain equity flows.
The Institutional Cost Corridor is an approach for a quantitative tool designed to solve the problem of "Institutional Blindness" by mapping the aggregate cost basis of Wall Street's entry. It allows for the identification of structural "gravity zones" where institutional capital is most likely to move from a state of profit into a state of defense.
The Methodology: Data Selection & Weighting
To ensure the output is statistically significant, the data engine focuses exclusively on the "Big 3" liquidity providers: BlackRock (IBIT), Fidelity (FBTC), and Bitwise (BITB). These three funds represent over 80% of total Spot ETF liquidity. A weighted ratio is applied (prioritizing BlackRock) to reflect the reality that a dollar flowing into IBIT has a significantly higher impact on market structure than a dollar in smaller, fragmented funds. This ensures the indicator follows the actual mass of institutional capital.
Recalculating the Shadow: Nominal Price & AUM
A common point of confusion is that Bitcoin ETFs have a completely different nominal price than Bitcoin itself (e.g., an IBIT share may trade at $50 while BTC is at $100,000). To solve this, the script does not look at the dollar price of the shares. Instead, it uses Assets Under Management (AUM) and Relative Performance Mapping . By calculating the percentage growth of the funds' underlying value since inception and projecting that growth onto the Bitcoin price axis, the script "re-scales" the institutional entry levels. This allows us to see exactly where Wall Street is "underwater" on a standard Bitcoin chart.
The Mathematical Foundations: Genesis vs. Anchored
The indicator utilizes two distinct mathematical approaches to triangulate the "Truth" of institutional positioning. These are not arbitrary assumptions, but forward-mapped models verified against professional financial benchmarks.
1. Conservative Floor (Genesis Mode)
• The Logic: This model uses a Cumulative Inflow VWAP . It treats every dollar that has entered the ETFs since Day 1 as part of a single, massive ledger.
• Scientific Justification: This approach maps to the "Fortress Zone" of early, high-conviction capital. Historical AUM performance data suggests that the largest influx of structural capital occurred during the launch phase of 2024. This logic identifies the Ultimate Floor —the level where the entire ETF cohort would flip to a net loss. In late 2025 research (e.g., Glassnode "True Market Mean"), this model consistently aligns with the deepest structural support of the bull cycle.
2. Wall Street Entry (Anchored Mode)
• The Logic: This model utilize a Relative Performance Anchor . It synchronizes the Bitcoin price on Launch Day with the growth performance of the ETF fund shares.
• Scientific Justification: This approach identifies the "Active Participant Basis." It reflects the entry price for the capital that fueled the most recent expansion cycles. It maps directly to the "Active Investors' Realized Price" cited by institutional research firms, identifying the immediate psychological "pain threshold" for the current market majority.
3. Institutional Mean (Hybrid Mode)
• The Logic: A 50/50 mathematical blend of the Conservative Floor and the Wall Street Entry .
• Justification: This is the "Equilibrium Zone." It serves as a neutral baseline by balancing early-stage "Genesis" conviction with late-cycle volatility. It represents the median cost basis of all current institutional holders.
4. The Shadow Corridor (Full Range)
• The Logic: Visualizes the entire spread between the Conservative Floor and the Wall Street Entry.
• Justification: The "Structural Support Cloud." Instead of a single price, it defines a regime . As long as Bitcoin remains above this cloud, the institutional trend remains in an "Expansion Phase." A re-entry into this corridor suggests a transition from a trending market into a value-accumulation phase.
Tactical Playbook: Scenario Logic
The Shadow Corridor (Full Range) visualizes the area between these two models, creating an "Institutional War Zone."
• Active Support Test: When price tests the Wall Street Entry (upper boundary), it indicates the active institutional majority is at breakeven. Expect significant defensive buying (bids) as funds protect their yearly performance reports.
• Deep Value Regime: Trading inside the Corridor is defined as a "Value Regime." This is where institutional accumulation historically absorbs retail capitulation.
• The Premium Trap: When the distance between price and the Corridor exceeds 35-40%, the market is "speculatively overextended," signaling a high probability of mean-reversion.
• Macro Breakdown: A Weekly (1W) candle closing below the Conservative Floor (lower boundary) signals a structural trend shift, indicating the majority of ETF-era capital is officially in a drawdown.
Operational Recommendation Best viewed on the Daily (1D) timeframe for macro structural analysis, providing the most reliable signal for institutional defense zones.
Tags: bitcoin, btc, etf, blackrock, ibit, institutional, cost-basis, vwap, macro, cycle, realized-price, Rob Maths
MA150 Respect Ratio (ATR-adjusted)This indicator measures how reliably price respects the 150-day moving average as support.
It computes an empirical probability (Respect Ratio) based on historical interactions with MA150:
– Dynamic touch tolerance based on ATR
– Optional shallow breaks allowed (user-defined)
– Trend filter (MA150 rising + price above)
– Minimum event count for statistical reliability
The output is a probability score (0–1) indicating how often MA150 held as support when tested.
This tool is intended for research and decision support, not as a standalone trading signal.
Cantillon Clean Moving Averages [Free]Overview Standard Moving Averages are static. The Cantillon Clean MA is dynamic. It automatically changes color based on price interaction, giving you an instant visual read on the trend health of the Short (20), Medium (50), and Long (200) term flows.
Features
Dynamic Coloring: Green when Bullish, Red when Bearish.
Smart Weighting: Uses Exponential Moving Averages (EMA) to react faster than standard SMAs.
Crossover Signals: Subtle "X" markers when the short-term trend flips.
Want the Real Institutional Trend? Moving averages lag. To track the True Institutional Cost Basis (Anchored VWAP) and statistical reversal points, you need the Cantillon Terminal .
Optimized Options Day Trading Script -Anurag Dec20-2025This indicator is a specialized Multi-Timeframe Trend & Regime System designed specifically for intraday trading on SPY, QQQ, and SPX. It is optimized for high-volatility execution (like 0DTE) by filtering out "choppy" low-probability conditions before they happen.
Unlike standard indicators that only look at the current chart, this script runs a background check on the 15-Minute Timeframe
Butterworth LPF Flip + AutoTune (PF)Butterworth LPF Flip + AutoTune (PF)
This strategy trades price trend flips using two Butterworth low-pass filters (a FAST filter and a SLOW filter). A trade is taken when the FAST filter crosses the SLOW filter. Optionally, the script can auto-tune the filter lengths by simulating many Fast/Slow combinations and selecting the pair with the best Profit Factor (PF).
What the Script Does
- Computes two 2‑pole Butterworth low‑pass filters on price.
- Enters LONG when FAST crosses above SLOW.
- Enters SHORT when FAST crosses below SLOW.
- Optionally simulates many Fast/Slow length combinations internally.
- Chooses the Fast/Slow pair with the highest Profit Factor.
- Trades only the selected best pair.
Manual Mode (Default)
1. Leave Auto‑Tune OFF.
2. Set:
- FAST cutoff period (bars)
- SLOW cutoff period (bars)
3. The strategy will trade using only these values.
Use this mode for normal trading or live deployment.
Auto‑Tune Mode
1. Enable Auto‑Tune.
2. Define Fast and Slow ranges:
- FAST min / max / step
- SLOW min / max / step
3. The script simulates ALL Fast × Slow combinations bar‑by‑bar.
4. Each combination tracks:
- Gross Profit
- Gross Loss
- Closed trades
- Profit Factor (PF = GP / GL)
5. At the end of the chart, the best PF pair is selected and used for trading.
Interpreting the End Box
The status label at the end of the chart reports:
- Whether Auto‑Tune is enabled
- Number of candidate pairs tested
- Best FAST period
- Best SLOW period
- Profit Factor of the best pair
- Win Rate (wins ÷ closed trades)
If PF is near 1.0 or trades are very low, expand the range or length of the test.
Best Practices
- Use Auto‑Tune ONLY for research and optimization.
- After finding good parameters, disable Auto‑Tune and trade manually.
- Keep Fast < Slow (logical separation).
- Longer charts produce more reliable PF results.
- Avoid very small step sizes (performance + noise).
Known Limitations
- Pine Script runs bar‑by‑bar; tuning is approximate, not vectorized.
- Large grids increase execution time.
- Results are historical and NOT predictive.
- Not suitable for live auto‑optimization.
Summary
This script is best viewed as a *research tool first, strategy second*. Use it to discover stable Fast/Slow regimes, then lock them in for simple, repeatable trading.
PDH PDL PWH PWL + IMB 15m / 1H / 4H + Weekly LogicPDH PDL PWH PWL indycators
weekly indycators automaticly generated.
for a every week
EMA and Dow Theory Strategies V2📘 Overview
This strategy is an advanced evolution of the original EMA × Dow Theory hybrid model. V2 introduces true swing‑based trend detection, gradient trend‑zones, higher‑timeframe swing overlays, and dynamic exit logic designed for intraday to short‑term trading across crypto, forex, stocks, and indices.
The system provides precise entries, adaptive exits, and highly visual guidance that helps traders understand trend structure at a glance.
🧠 Key Features
🔹 1. Dual‑EMA Trend Logic (Symbol + External Index)
Both the chart symbol and an external index (OTHERS.D) are evaluated using fast/slow EMAs to determine correlation‑based trend bias.
🔹 2. Dow Theory Swing Detection (Real‑time)
The script identifies swing highs/lows and updates trend direction when price breaks them. This creates a structural trend model that reacts faster than EMAs alone.
🔹 3. Gradient Trend Zones (Visual Trend Strength)
When trend is up or down, the area between price and the latest swing level is filled with a multi‑step gradient. This makes trend strength and distance-to-structure visually intuitive.
🔹 4. Higher‑Timeframe Swing Trend (htfTrend)
Swing highs/lows from a higher timeframe (e.g., 4H) are plotted to show macro structure. Used only for visual context, not for filtering entries.
🔹 5. RSI‑Based Entry Protection
RSI prevents entries during extreme overbought/oversold conditions.
🔹 6. Dynamic Exit System
Includes:
Custom stop‑loss (%)
Partial take‑profit (TP1/TP2/TP3)
Automatic scale‑out when trend color weakens
“Color‑change lockout” to prevent immediate re‑entry
Real‑time PnL tracking and labels
🔹 7. Alerts for All Key Events
Entry, stop‑loss, partial exits, and trend‑change exits all generate structured JSON alerts.
🔹 8. Visual PnL Labels & Equity Tracking
PnL for the latest trade is displayed directly on the chart, including scale‑out adjustments.
⚙️ Input Parameters
Parameter Description
Fast EMA / Slow EMA EMAs used for symbol trend detection
Index Fast / Slow EMA EMAs applied to external index
StopLoss (%) Custom stop‑loss threshold
Scale‑Out % Portion to exit when trend color weakens
RSI Period / Levels Overbought/oversold filters
Swing Detection Length Bars used to detect swing highs/lows
Stats Display Position of statistics table
🧭 About htfTrend (Higher Timeframe Trend)
The higher‑timeframe swing trend is displayed visually but not used for entry logic.
Why? Strict HTF filtering reduces trade frequency and often removes profitable setups. By keeping it visual‑only, traders retain flexibility while still benefiting from macro structure awareness.
Use it as a contextual guide, not a constraint.
📘 概要
本ストラテジーは、V1 を大幅に拡張した EMA × ダウ理論 × スイング構造 × 上位足トレンド可視化 の複合型モデルです。 短期〜デイトレード向けに最適化されており、仮想通貨・FX・株式・指数など幅広いアセットで利用できます。
V2 では、スイング構造の自動検出、グラデーションによるトレンド強度の可視化、上位足スイングライン、動的な利確/損切りロジック が追加され、視覚的にもロジック的にも大幅に強化されています。
🧠 主な機能
🔹 1. 銘柄＋外部インデックスの EMA クロス判定
対象銘柄と OTHERS.D の EMA を比較し、相関を考慮したトレンド方向を判定します。
🔹 2. ダウ理論に基づくスイング高値・安値の自動検出
スイング更新によりトレンド方向を切り替える、構造ベースのトレンド判定を採用。
🔹 3. グラデーション背景によるトレンド強度の可視化
スイングラインから現在価格までを段階的に塗り分け、 「どれだけトレンドが伸びているか」を直感的に把握できます。
🔹 4. 上位足スイングトレンド（htfTrend）の表示
4H などの上位足でのスイング高値・安値を表示し、 大局的なトレンド構造を視覚的に把握できます（ロジックには未使用）。
🔹 5. RSI による過熱・売られすぎフィルター
極端な RSI 状態でのエントリーを防止。
🔹 6. 動的イグジットシステム
カスタム損切り（％）
TP1/TP2/TP3 の段階的利確
トレンド色の弱まりによる自動スケールアウト
色変化後の再エントリー制限（waitForColorChange）
リアルタイム PnL の追跡とラベル表示
🔹 7. アラート完備（JSON 形式）
エントリー、損切り、部分利確、トレンド反転などすべてに対応。
🔹 8. 損益ラベル・統計表示
直近トレードの損益をチャート上に表示し、視覚的に把握できます。
⚙️ 設定項目
設定項目名 説明
Fast / Slow EMA 銘柄の EMA 設定
Index Fast / Slow EMA 外部インデックスの EMA 設定
損切り（％） カスタム損切りライン
部分利確割合 トレンド弱化時のスケールアウト割合
RSI 期間・水準 過熱/売られすぎフィルター
スイング検出期間 スイング高値・安値の検出に使用
統計表示位置 テーブルの表示位置
🧭 上位足トレンド（htfTrend）について
上位足スイングの更新に基づくトレンド判定を表示しますが、 エントリー条件には使用していません。
理由： 上位足を厳密にロジックへ組み込むと、トレード機会が大幅に減るためです。
本ストラテジーでは、 「大局の把握は視覚で、エントリーは柔軟に」 という設計思想を採用しています。
→ 裁量で利確判断や逆張り回避に活用できます。
