CloudScore by ExitAnt📘 CloudScore by ExitAnt
CloudScore by ExitAnt 는 일목균형표(Ichimoku Cloud)의 구름대 돌파 신호를 기반으로,
다양한 추세 보조지표를 결합하여 매수 추세 강도를 점수화(0~5점) 해주는 트렌드 분석 지표입니다.
기존 일목구름 단독 신호는 변동성이 크거나 신뢰도가 낮을 수 있기 때문에,
이 지표는 여러 기술적 요소를 종합적으로 평가하여
“지금이 얼마나 강력한 추세 전환 구간인가?” 를 직관적으로 보여줍니다.
🎯 지표 목적
일목균형표 구름 돌파의 신뢰도 강화
보조지표 신호를 자동으로 점수화하여 한눈에 판단 가능
캔들 위에 이모지를 배치해 시각적으로 즉시 해석 가능
초보자부터 숙련자까지 모두 활용 가능한 추세 진입 필터링 도구
🧠 점수 계산 방식 (0~5점)
구름 상향 돌파가 발생하면 아래 조건들을 체크하여 점수를 부여합니다.
▶ +1점 조건 항목
1. 골든 크로스 발생
* 최근 설정한 n봉 이내에서 Fast MA가 Slow MA를 상향 돌파한 경우
2. RSI 과매도 구간
* RSI가 설정 값 이하일 때 추세 전환 가능성이 증가
3. MACD 강세 전환
* MACD가 0 아래에 있으면서 시그널선 상향 돌파 발생
4. RSI 상승 다이버전스
* 가격은 낮아지지만 RSI는 상승 → 바닥 신호
5. 200MA 위에 위치
* 장기 추세와 일치하는 시점만 점수 강화
▶ 점수별 이모지
1점 🟡 : 약한 진입 신호
2점 🟢 : 관찰이 필요한 강화 신호
3점 📈 : 추세 전환 가능성 증가
4점 🚀 : 강한 추세 신호
5점 👑 : 매우 강력한 진입 시그널
🖥 차트 표시 요소
구름대(Span A / Span B)만 표시하여 더 깔끔한 시각화
이모지는 캔들 위에 자동 배치
필요 시 최근 n개의 캔들만 표시하도록 설정 가능
오른쪽 상단에 조건 요약 안내창 표시
🔧 사용자 설정
Tenkan / Kijun / SenkouB 기간 조정
MA, RSI, MACD, 다이버전스 사용 여부 선택
최근 몇 개의 캔들까지 점수를 표시할지 설정 가능
이모지는 사용자 취향에 따라 변경 가능
⚠️ 유의사항
본 지표는 **가격 움직임의 확률적 해석을 돕는 보조지표**이며, 단독으로 매수·매도 결정을 내려서는 안 됩니다.
시장 상황(변동성, 거래량, 프레임)에 따라 신호의 신뢰도는 달라질 수 있습니다.
실제 매매 전략에 적용하기 전 반드시 백테스트와 검증이 필요합니다.
# **📘 CloudScore by ExitAnt — English Description**
📘 CloudScore by ExitAnt
CloudScore by ExitAnt is a trend analysis indicator that evaluates bullish trend strength by scoring (0–5 points) signals based on Ichimoku Cloud breakouts combined with multiple momentum and trend indicators.
Since the default Ichimoku Cloud breakout alone can be unreliable or highly volatile, this indicator integrates several technical conditions to visually and intuitively show
“How strong is the current trend reversal opportunity?”
🎯 Purpose of the Indicator
Enhance the reliability of Ichimoku Cloud breakout signals
Automatically score multiple signals for quick visual judgment
Place emojis directly above candles for instant interpretation
Works for both beginners and experienced traders as a trend-entry filtering tool
🧠 Scoring Logic (0–5 points)
When a bullish breakout above the cloud occurs, the indicator checks the following conditions and assigns points.
▶ +1 Point Conditions
1. Golden Cross
* Fast MA crosses above Slow MA within the user-defined lookback window
2. RSI Oversold
* RSI below threshold increases the probability of trend reversal
3. MACD Bullish Shift
* MACD is below zero while crossing above the signal line
4. RSI Bullish Divergence
* Price makes a lower low while RSI makes a higher low → potential bottom signal
5. Above the 200MA
* Only scores when price aligns with long-term trend direction
▶ Emoji by Score
1 Point 🟡 : Weak early signal
2 Points 🟢 : Improved setup; watch closely
3 Points 📈 : Decent trend reversal possibility
4 Points 🚀 : Strong trend entry signal
5 Points 👑 : Very strong bullish signal
🖥 Chart Elements
Displays only Span A / Span B to keep the cloud visually clean
Emojis automatically appear above candles
Optionally limit the number of candles displaying signals
Summary box appears in the upper-right corner
🔧 User Settings
Adjustable Tenkan / Kijun / Senkou B periods
Enable/disable MA, RSI, MACD, divergence filters
Set how many recent candles should show the score
Emojis can be customized by the user
⚠️ Disclaimer
This is a technical assistant tool that helps interpret price movement probabilities; it should not be used as a standalone buy/sell signal.
Signal reliability may vary depending on volatility, volume, and timeframe.
Always conduct backtesting and validation before using it in real trading strategies.
1-BTC
BTC 50/200 EMA Trend Meter by FlyingOceanTigerBTC 50/200 EMA Trend Meter
This indicator plots a classic 50/200 EMA trend filter on any chart, with clear visual cues for the major “golden cross” and “death cross” events.
Features
• Plots the 50 EMA (fast) and 200 EMA (slow) on price
• Highlights “trend-on” zones in the background when 50 EMA > 200 EMA
• Prints BUY labels on golden crosses (50 EMA crossing ABOVE 200 EMA)
• Prints SELL labels on death crosses (50 EMA crossing BELOW 200 EMA)
• Alert conditions for both BUY and SELL signals
Designed primarily for BTCUSD on the 1D timeframe as a long-only trend meter, but it works on any symbol or timeframe. Use it to stay aligned with the bigger trend and avoid overtrading chop.
For educational purposes only. This is not financial advice and does not guarantee future performance.
Dumb Money Flow - Retail Panic & FOMO# Dumb Money Flow (DMF) - Retail Panic & FOMO
## 🌊 Overview
**Dumb Money Flow (DMF)** is a powerful **contrarian indicator** designed to track the emotional state of the retail "herd." It identifies moments of extreme **Panic** (irrational selling) and **FOMO** (irrational buying) by analyzing on-chain data, volume anomalies, and price velocity.
In crypto markets, retail traders often buy the top (FOMO) and sell the bottom (Panic). This indicator helps you do the opposite: **Buy when the herd is fearful, and Sell when the herd is greedy.**
---
## 🧠 How It Works
The indicator combines multiple data points into a single **Sentiment Index** (0-100), normalized over a 90-day period to ensure it always uses the full range of the chart.
### 1. Panic Index (Bearish Sentiment)
Tracks signs of capitulation and fear. High values contribute to the **Panic Zone**.
* **Exchange Inflows:** Spikes in funds moving to exchanges (preparing to sell).
* **Volume Spikes:** High volume during price drops (panic selling).
* **Price Crash (ROC):** Rapid, emotional price drops over 3 days.
* **Volatility (ATR):** High market nervousness and instability.
### 2. FOMO Index (Bullish Sentiment)
Tracks signs of euphoria and greed. High values contribute to the **FOMO Zone**.
* **Exchange Outflows:** Funds moving to cold storage (HODLing/Greed).
* **Profitable Addresses:** When >90% of holders are in profit, tops often form.
* **Parabolic Rise:** Rapid, unsustainable price increases.
---
## 🎨 Visual Guide
The indicator uses a distinct color scheme to highlight extremes:
* **🟢 Dark Green Zone (> 80): Extreme FOMO**
* **Meaning:** The crowd is euphoric. Risk of a correction is high.
* **Action:** Consider taking profits or looking for short entries.
* **🔴 Dark Burgundy Zone (< 20): Extreme Panic**
* **Meaning:** The crowd is capitulating. Prices may be oversold.
* **Action:** Look for buying opportunities (catching the knife with confirmation).
* **🔵 Light Blue Line:**
* The smoothed moving average of the sentiment, helpful for seeing the trend direction.
---
## 🛠️ How to Use (Trading Strategies)
### 1. Contrarian Reversals (The Primary Strategy)
* **Buy Signal:** Wait for the line to drop deep into the **Burgundy Panic Zone (< 20)** and then start curling up. This indicates that the worst of the selling pressure is over.
* **Sell Signal:** Wait for the line to spike into the **Green FOMO Zone (> 80)** and then start curling down. This suggests buying exhaustion.
### 2. Divergences
* **Bullish Divergence:** Price makes a **Lower Low**, but the DMF Indicator makes a **Higher Low** (less panic on the second drop). This is a strong reversal signal.
* **Bearish Divergence:** Price makes a **Higher High**, but the DMF Indicator makes a **Lower High** (less FOMO/buying power on the second peak).
### 3. Trend Confirmation (Midline Cross)
* **Crossing 50 Up:** Sentiment is shifting from Fear to Greed (Bullish).
* **Crossing 50 Down:** Sentiment is shifting from Greed to Fear (Bearish).
---
## ⚙️ Settings
* **Data Source:** Defaults to `INTOTHEBLOCK` for on-chain data.
* **Crypto Asset:** Auto-detects BTC/ETH, but can be forced.
* **Normalization Period:** Default 90 days. Determines the "window" for defining what is considered "Extreme" relative to recent history.
* **Weights:** You can customize how much each factor (Volume, Inflows, Price) contributes to the index.
---
**Disclaimer:** This indicator is for educational purposes only. "Dumb Money" analysis is a probability tool, not a crystal ball. Always manage your risk.
**Indicator by:** @iCD_creator
**Version:** 1.0
**Pine Script™ Version:** 6
---
## Updates & Support
For questions, suggestions, or bug reports, please comment below or message the author.
**Like this indicator? Leave a 👍 and share your feedback!**
Smart Money Flow - Exchange & TVL Composite# Smart Money Flow - Exchange & TVL Composite Indicator
## Overview
The **Smart Money Flow (SMF)** indicator combines two powerful on-chain metrics - **Exchange Flows** and **Total Value Locked (TVL)** - to create a composite index that tracks institutional and "smart money" movement in the cryptocurrency market. This indicator helps traders identify accumulation and distribution phases by analyzing where capital is flowing.
## What It Does
This indicator normalizes and combines:
- **Exchange Net Flow** (from IntoTheBlock): Tracks Bitcoin/Ethereum movement to and from exchanges
- **Total Value Locked** (from DefiLlama): Measures capital locked in DeFi protocols
The composite index is displayed on a 0-100 scale with clear zones for overbought/oversold conditions.
## Core Concept
### Exchange Flows
- **Negative Flow (Outflows)** = Bullish Signal
- Coins moving OFF exchanges → Long-term holding/accumulation
- Indicates reduced selling pressure
- **Positive Flow (Inflows)** = Bearish Signal
- Coins moving TO exchanges → Preparation for selling
- Indicates potential distribution phase
### Total Value Locked (TVL)
- **Rising TVL** = Bullish Signal
- Capital flowing into DeFi protocols
- Increased ecosystem confidence
- **Falling TVL** = Bearish Signal
- Capital exiting DeFi protocols
- Decreased ecosystem confidence
### Combined Signals
**🟢 Strong Bullish (70-100):**
- Exchange outflows + Rising TVL
- Smart money accumulating and deploying capital
**🔴 Strong Bearish (0-30):**
- Exchange inflows + Falling TVL
- Smart money preparing to sell and exiting positions
**⚪ Neutral (40-60):**
- Mixed or balanced flows
## Key Features
### ✅ Auto-Detection
- Automatically detects chart symbol (BTC/ETH)
- Uses appropriate exchange flow data for each asset
### ✅ Weighted Composite
- Customizable weights for Exchange Flow and TVL components
- Default: 50/50 balance
### ✅ Normalized Scale
- 0-100 index scale
- Configurable lookback period for normalization (default: 90 days)
### ✅ Signal Zones
- **Overbought**: 70+ (Strong bullish pressure)
- **Oversold**: 30- (Strong bearish pressure)
- **Extreme**: 85+ / 15- (Very strong signals)
### ✅ Clean Interface
- Minimal visual clutter by default
- Only main index line and MA visible
- Optional elements can be enabled:
- Background color zones
- Divergence signals
- Trend change markers
- Info table with detailed metrics
### ✅ Divergence Detection
- Identifies when price diverges from smart money flows
- Potential reversal warning signals
### ✅ Alerts
- Extreme overbought/oversold conditions
- Trend changes (crossing 50 line)
- Bullish/bearish divergences
## How to Use
### 1. Trend Confirmation
- Index above 50 = Bullish trend
- Index below 50 = Bearish trend
- Use with price action for confirmation
### 2. Reversal Signals
- **Extreme readings** (>85 or <15) suggest potential reversal
- Look for divergences between price and indicator
### 3. Accumulation/Distribution
- **70+**: Accumulation phase - smart money buying/holding
- **30-**: Distribution phase - smart money selling
### 4. DeFi Health
- Monitor TVL component for DeFi ecosystem strength
- Combine with exchange flows for complete picture
## Settings
### Data Sources
- **Exchange Flow**: IntoTheBlock real-time data
- **TVL**: DefiLlama aggregated DeFi TVL
- **Manual Mode**: For testing or custom data
### Indicator Settings
- **Smoothing Period (MA)**: Default 14 periods
- **Normalization Lookback**: Default 90 days
- **Exchange Flow Weight**: Adjustable 0-100%
- **Overbought/Oversold Levels**: Customizable thresholds
### Visual Options
- Show/Hide Moving Average
- Show/Hide Zone Lines
- Show/Hide Background Colors
- Show/Hide Divergence Signals
- Show/Hide Trend Markers
- Show/Hide Info Table
## Data Requirements
⚠️ **Important Notes:**
- Uses **daily data** from IntoTheBlock and DefiLlama
- Works on any chart timeframe (data updates daily)
- Auto-switches between BTC and ETH based on chart
- All other crypto charts default to BTC exchange flow data
## Best Practices
1. **Use on Daily+ Timeframes**
- On-chain data is daily, most effective on D/W/M charts
2. **Combine with Price Action**
- Use as confirmation, not standalone signals
3. **Watch for Divergences**
- Price making new highs while indicator falling = warning
4. **Monitor Extreme Zones**
- Sustained readings >85 or <15 indicate strong conviction
5. **Context Matters**
- Consider broader market conditions and fundamentals
## Calculation
1. **Exchange Net Flow** = Inflows - Outflows (inverted for index)
2. **TVL Rate of Change** = % change over smoothing period
3. **Normalize** both metrics to 0-100 scale
4. **Composite Index** = (ExchangeFlow × Weight) + (TVL × Weight)
5. **Smooth** with moving average
## Disclaimer
This indicator uses on-chain data for analysis. While valuable, it should not be used as the sole basis for trading decisions. Always combine with other technical analysis tools, fundamental analysis, and proper risk management.
On-chain data reflects blockchain activity but may lag price action. Use this indicator as part of a comprehensive trading strategy.
---
## Credits
**Data Sources:**
- IntoTheBlock: Exchange flow metrics
- DefiLlama: Total Value Locked data
**Indicator by:** @iCD_creator
**Version:** 1.0
**Pine Script™ Version:** 6
---
## Updates & Support
For questions, suggestions, or bug reports, please comment below or message the author.
**Like this indicator? Leave a 👍 and share your feedback!**
Pi Cycle BTC Top + Pre-Alert BandsPi Cycle BTC Top + Pre-Alert Bands is an advanced implementation of the classic Pi Cycle Top model, designed for Bitcoin cycle analysis on higher timeframes (especially 1D BTCUSD/BTCUSD·INDEX).
The original Pi Cycle Top uses two moving averages:
• 111-day SMA (short MA)
• 350-day SMA ×2 (long MA)
A Pi Top is signaled when the 111 SMA crosses above the 350×2 SMA. Historically, this has occurred near major BTC cycle highs.
This script extends that idea with a 3-step early-warning sequence:
• Pi Green – early compression: short/long MA ratio crosses upward into the green band (convergence from below is required).
• Pi Yellow – mid-cycle warning: only fires if a valid Green has already occurred in the same cycle.
• Pi Cycle Top – final top: the classic Pi Cycle cross, limited to one top signal per cycle. After a top, no new Yellow or Top signals can appear until a new Green event starts the next cycle.
Background shading shows the active phase (Green / Yellow / late-cycle zone), so you can see at a glance where BTC is within its Pi-based macro structure.
All logic is non-repainting: request.security() uses lookahead_off and no future data is accessed.
Typical use
This indicator is intended as a macro-cycle timing and risk-awareness tool, not a stand-alone entry system. Many traders use it to:
• Watch for Pi Green as the start of a potential late-cycle advance.
• Treat Pi Yellow as a rising-risk environment and tighten risk management.
• Use the Pi Cycle Top as a historical high-risk zone where large profit-taking or hedging may be considered.
Always combine this with your own analysis (trend, volume, on-chain, macro) before making decisions.
How to set alerts
Add the indicator to your chart (1D BTCUSD or BTCUSD·INDEX recommended).
Click Alerts → Condition → Pi Cycle BTC Top + Pre-Alert Bands.
Choose one of:
• Pi Cycle – Green Pre-Alert (early convergence)
• Pi Cycle – Yellow Pre-Alert (after Green only)
• Pi Cycle – TOP (Single per Cycle, after Green)
Use “Once per bar close” for higher-timeframe reliability.
Disclaimer
This tool is for educational and analytical purposes only. The Pi Cycle concept is based on historical behavior and does not guarantee future results. This is not financial advice; always do your own research and manage risk appropriately.
McRib Release Dates IndicatorMarks the McRib release dates from 2019-Current. Previous dates from Pre-2019 weren't clear enough to include accurate info. Goated Indicator. 67 😎
Weekend GapsIdentify unfilled gaps between the close of one candle and the opening of the next. Optimised for weekends by highlighting friday gaps with a triangle and bold horizontal ray. Depending on the price action required to fill it, they are marked in red or green.
Bitcoin ETF Cumulative Net InflowIndicator Description:
This indicator calculates and plots the cumulative net inflow (in billions of USD) for selected Bitcoin ETFs on the main price chart. It uses AUM data from TradingView to estimate daily net flows, adjusted for BTC price changes, and accumulates them over time. The line is overlaid on the price chart (e.g., BTCUSD) with a right scale for better visibility, helping to identify correlations between ETF inflows and Bitcoin price movements.
Key Features:
Supports selection of 10 major Bitcoin ETFs (IBIT, FBTC, ARKB, etc.) via inputs.
Cumulative inflow line (purple, linewidth=2) for trend analysis.
Data sourced from request.financial("AUM", "D") for accuracy.
Crypto ETFs AUM📘 Description: BTC ETFs AUM Tracker
This indicator tracks the Assets Under Management (AUM) and daily inflows/outflows of the main U.S.-listed Bitcoin ETFs, allowing you to visualize institutional capital movement into Bitcoin products over time. It helps traders correlate institutional capital movement with Bitcoin price behavior.
🧩 Overview
The script adds up the daily AUM changes from selected Bitcoin ETFs to estimate the total net inflow/outflow of capital into spot BTC funds. It also accumulates those flows over time to display the total aggregated AUM balance, giving you a clearer sense of market direction and institutional sentiment. Two display modes are available: Balance view: plots the cumulative sum of net inflows (total ETF AUM). Inflows view: shows daily inflows (green) and outflows (red) as histogram columns, together with a smoothed moving average line.
⚙️ Inputs
Explained Base Settings Base Multiplier (base_multi) – Scaling factor applied to all AUM values. Leave at 1 for USD units, or adjust to display values in millions (1e6) or billions (1e9). Smoothing (c_smoothing) – Period length for the simple moving average used to calculate the smoothed mean inflow/outflow line. Show Balance (showBalance) – When enabled, displays the total cumulative AUM balance (sum of all net inflows over time). Show Inflows (showInflows) – When enabled, displays the daily inflows/outflows as colored columns. ETF Selection You can toggle which ETFs are included in the calculation:
BIT (BlackRock)
GBTC (Grayscale)
FBTC (Fidelity)
ARKB (ARK/21Shares)
BITB (Bitwise)
EZBC (Franklin Templeton)
BTCW (WisdomTree)
BTCO (Invesco Galaxy)
BRRR (Valkyrie)
HODL (VanEck)
Each switch determines whether the ETF’s AUM and daily flow data are included in the total calculation.
📊 Displayed Values Green Columns → Positive daily net inflows (AUM increased). Red Columns → Negative daily net outflows (AUM decreased). Orange Line → Smoothed moving average of net flows, used to identify persistent inflow/outflow trends. Blue Line (if enabled) → Total cumulative AUM balance (sum of all historical flows).
💡 Usage Notes Works best on daily timeframe, since ETF data is typically updated once per trading day. Not all ETFs have identical data history; missing data points are automatically skipped. The indicator doesn’t represent official fund NAV or guarantee data accuracy — it visualizes TradingView’s public financial feed. You can combine this tool with price action or on-chain metrics to analyze institutional Bitcoin flows.
Note: Some ETF data may not be available to all users depending on their TradingView data subscription or market access. Missing values are automatically skipped.
🧠 Disclaimer This script is for educational and analytical purposes only. It is not financial advice, and no investment decisions should be based solely on this indicator. Data accuracy depends on TradingView’s financial data sources and exchange reporting frequency.
EMA Oscillator [Alpha Extract]A precision mean reversion analysis tool that combines advanced Z-score methodology with dual threshold systems to identify extreme price deviations from trend equilibrium. Utilizing sophisticated statistical normalization and adaptive percentage-based thresholds, this indicator provides high-probability reversal signals based on standard deviation analysis and dynamic range calculations with institutional-grade accuracy for systematic counter-trend trading opportunities.
🔶 Advanced Statistical Normalization
Calculates normalized distance between price and exponential moving average using rolling standard deviation methodology for consistent interpretation across timeframes. The system applies Z-score transformation to quantify price displacement significance, ensuring statistical validity regardless of market volatility conditions.
// Core EMA and Oscillator Calculation
ema_values = ta.ema(close, ema_period)
oscillator_values = close - ema_values
rolling_std = ta.stdev(oscillator_values, ema_period)
z_score = oscillator_values / rolling_std
🔶 Dual Threshold System
Implements both statistical significance thresholds (±1σ, ±2σ, ±3σ) and percentage-based dynamic thresholds calculated from recent oscillator range extremes. This hybrid approach ensures consistent probability-based signals while adapting to varying market volatility regimes and maintaining signal relevance during structural market changes.
// Statistical Thresholds
mild_threshold = 1.0 // ±1σ (68% confidence)
moderate_threshold = 2.0 // ±2σ (95% confidence)
extreme_threshold = 3.0 // ±3σ (99.7% confidence)
// Percentage-Based Dynamic Thresholds
osc_high = ta.highest(math.abs(z_score), lookback_period)
mild_pct_thresh = osc_high * (mild_pct / 100.0)
moderate_pct_thresh = osc_high * (moderate_pct / 100.0)
extreme_pct_thresh = osc_high * (extreme_pct / 100.0)
🔶 Signal Generation Framework
Triggers buy/sell alerts when Z-score crosses extreme threshold boundaries, indicating statistically significant price deviations with high mean reversion probability. The system generates continuation signals at moderate levels and reversal signals at extreme boundaries with comprehensive alert integration.
// Extreme Signal Detection
sell_signal = ta.crossover(z_score, selected_extreme)
buy_signal = ta.crossunder(z_score, -selected_extreme)
// Dynamic Color Coding
signal_color = z_score >= selected_extreme ? #ff0303 : // Extremely Overbought
z_score >= selected_moderate ? #ff6a6a : // Overbought
z_score >= selected_mild ? #b86456 : // Mildly Overbought
z_score > -selected_mild ? #a1a1a1 : // Neutral
z_score > -selected_moderate ? #01b844 : // Mildly Oversold
z_score > -selected_extreme ? #00ff66 : // Oversold
#00ff66 // Extremely Oversold
🔶 Visual Structure Analysis
Provides a six-tier color gradient system with dynamic background zones indicating mild, moderate, and extreme conditions. The histogram visualization displays Z-score intensity with threshold reference lines and zero-line equilibrium context for precise mean reversion timing.
snapshot
4H
1D
🔶 Adaptive Threshold Selection
Features intelligent threshold switching between statistical significance levels and percentage-based dynamic ranges. The percentage system automatically adjusts to current volatility conditions using configurable lookback periods, while statistical thresholds maintain consistent probability-based signal generation across market cycles.
🔶 Performance Optimization
Utilizes efficient rolling calculations with configurable EMA periods and threshold parameters for optimal performance across all timeframes. The system includes comprehensive alert functionality with customizable notification preferences and visual signal overlay options.
🔶 Market Oscillator Interpretation
Z-score > +3σ indicates statistically significant overbought conditions with high reversal probability, while Z-score < -3σ signals extreme oversold levels suitable for counter-trend entries. Moderate thresholds (±2σ) capture 95% of normal price distributions, making breaches statistically significant for systematic trading approaches.
snapshot
🔶 Intelligent Signal Management
Automatic signal filtering prevents false alerts through extreme threshold crossover requirements, while maintaining sensitivity to genuine statistical deviations. The dual threshold system provides both conservative statistical approaches and adaptive market condition responses for varying trading styles.
Why Choose EMA Oscillator ?
This indicator provides traders with statistically-grounded mean reversion analysis through sophisticated Z-score normalization methodology. By combining traditional statistical significance thresholds with adaptive percentage-based extremes, it maintains effectiveness across varying market conditions while delivering high-probability reversal signals based on quantifiable price displacement from trend equilibrium, enabling systematic counter-trend trading approaches with defined statistical confidence levels and comprehensive risk management parameters.
Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.
BTC Power Law Valuation BandsBTC Power Law Rainbow
A long-term valuation framework for Bitcoin based on Power Law growth — designed to help identify macro accumulation and distribution zones, aligned with long-term investor behavior.
🔍 What Is a Power Law?
A Power Law is a mathematical relationship where one quantity varies as a power of another. In this model:
Price ≈ a × (Time)^b
It captures the non-linear, exponentially slowing growth of Bitcoin over time. Rather than using linear or cyclical models, this approach aligns with how complex systems, such as networks or monetary adoption curves, often grow — rapidly at first, and then more slowly, but persistently.
🧠 Why Power Law for BTC?
Bitcoin:
Has finite supply and increasing adoption.
Operates as a monetary network , where Metcalfe’s Law and power laws naturally emerge.
Exhibits exponential growth over logarithmic time when viewed on a log-log chart .
This makes it uniquely well-suited for power law modeling.
🌈 How to Use the Valuation Bands
The central white line represents the modeled fair value according to the power law.
Colored bands represent deviations from the model in logarithmic space, acting as macro zones:
🔵 Lower Bands: Deep value / Accumulation zones.
🟡 Mid Bands: Fair value.
🔴 Upper Bands: Euphoria / Risk of macro tops.
📐 Smart Money Concepts (SMC) Alignment
Accumulation: Occurs when price consolidates near lower bands — often aligning with institutional positioning.
Markup: As price re-enters or ascends the bands, we often see breakout behavior and trend expansion.
Distribution: When price extends above upper bands, potential for exit liquidity creation and distribution events.
Reversion: Historically, price mean-reverts toward the model — rarely staying outside the bands for long.
This makes the model useful for:
Cycle timing
Long-term DCA strategy zones
Identifying value dislocations
Filtering short-term noise
⚠️ Disclaimer
This tool is for educational and informational purposes only . It is not financial advice. The power law model is a non-predictive, mathematical framework and does not guarantee future price movements .
Always use additional tools, risk management, and your own judgment before making trading or investment decisions.
Volume Profile Grid [Alpha Extract]A sophisticated volume distribution analysis system that transforms market activity into institutional-grade visual profiles, revealing hidden support/resistance zones and market participant behavior. Utilizing advanced price level segmentation, bullish/bearish volume separation, and dynamic range analysis, the Volume Profile Grid delivers comprehensive market structure insights with Point of Control (POC) identification, Value Area boundaries, and volume delta analysis. The system features intelligent visualization modes, real-time sentiment analysis, and flexible range selection to provide traders with clear, actionable volume-based market context.
🔶 Dynamic Range Analysis Engine
Implements dual-mode range selection with visible chart analysis and fixed period lookback, automatically adjusting to current market view or analyzing specified historical periods. The system intelligently calculates optimal bar counts while maintaining performance through configurable maximum limits, ensuring responsive profile generation across all timeframes with institutional-grade precision.
// Dynamic period calculation with intelligent caching
get_analysis_period() =>
if i_use_visible_range
chart_start_time = chart.left_visible_bar_time
current_time = last_bar_time
time_span = current_time - chart_start_time
tf_seconds = timeframe.in_seconds()
estimated_bars = time_span / (tf_seconds * 1000)
range_bars = math.floor(estimated_bars)
final_bars = math.min(range_bars, i_max_visible_bars)
math.max(final_bars, 50) // Minimum threshold
else
math.max(i_periods, 50)
🔶 Advanced Bull/Bear Volume Separation
Employs sophisticated candle classification algorithms to separate bullish and bearish volume at each price level, with weighted distribution based on bar intersection ratios. The system analyzes open/close relationships to determine volume direction, applying proportional allocation for doji patterns and ensuring accurate representation of buying versus selling pressure across the entire price spectrum.
🔶 Multi-Mode Volume Visualization
Features three distinct display modes for bull/bear volume representation: Split mode creates mirrored profiles from a central axis, Side by Side mode displays sequential bull/bear segments, and Stacked mode separates volumes vertically. Each mode offers unique insights into market participant behavior with customizable width, thickness, and color parameters for optimal visual clarity.
// Bull/Bear volume calculation with weighted distribution
for bar_offset = 0 to actual_periods - 1
bar_high = high
bar_low = low
bar_volume = volume
// Calculate intersection weight
weight = math.min(bar_high, next_level) - math.max(bar_low, current_level)
weight := weight / (bar_high - bar_low)
weighted_volume = bar_volume * weight
// Classify volume direction
if bar_close > bar_open
level_bull_volume += weighted_volume
else if bar_close < bar_open
level_bear_volume += weighted_volume
else // Doji handling
level_bull_volume += weighted_volume * 0.5
level_bear_volume += weighted_volume * 0.5
🔶 Point of Control & Value Area Detection
Implements institutional-standard POC identification by locating the price level with maximum volume accumulation, providing critical support/resistance zones. The Value Area calculation uses sophisticated sorting algorithms to identify the price range containing 70% of trading volume, revealing the market's accepted value zone where institutional participants concentrate their activity.
🔶 Volume Delta Analysis System
Incorporates real-time volume delta calculation with configurable dominance thresholds to identify significant bull/bear imbalances. The system visually highlights price levels where buying or selling pressure exceeds threshold percentages, providing immediate insight into directional volume flow and potential reversal zones through color-coded delta indicators.
// Value Area calculation using 70% volume accumulation
total_volume_sum = array.sum(total_volumes)
target_volume = total_volume_sum * 0.70
// Sort volumes to find highest activity zones
for i = 0 to array.size(sorted_volumes) - 2
for j = i + 1 to array.size(sorted_volumes) - 1
if array.get(sorted_volumes, j) > array.get(sorted_volumes, i)
// Swap and track indices for value area boundaries
// Accumulate until 70% threshold reached
for i = 0 to array.size(sorted_indices) - 1
accumulated_volume += vol
array.push(va_levels, array.get(volume_levels, idx))
if accumulated_volume >= target_volume
break
❓How It Works
🔶 Weighted Volume Distribution
Implements proportional volume allocation based on the percentage of each bar that intersects with price levels. When a bar spans multiple levels, volume is distributed proportionally based on the intersection ratio, ensuring precise representation of trading activity across the entire price spectrum without double-counting or volume loss.
🔶 Real-Time Profile Generation
Profiles regenerate on each bar close when in visible range mode, automatically adapting to chart zoom and scroll actions. The system maintains optimal performance through intelligent caching mechanisms and selective line updates, ensuring smooth operation even with maximum resolution settings and extended analysis periods.
🔶 Market Sentiment Analysis
Features comprehensive volume analysis table displaying total volume metrics, bullish/bearish percentages, and overall market sentiment classification. The system calculates volume dominance ratios in real-time, providing immediate insight into whether buyers or sellers control the current price structure with percentage-based sentiment thresholds.
🔶 Visual Profile Mapping
Provides multi-layered visual feedback through colored volume bars, POC line highlighting, Value Area boundaries, and optional delta indicators. The system supports profile mirroring for alternative perspectives, line extension for future reference, and customizable label positioning with detailed price information at critical levels.
Why Choose Volume Profile Grid
The Volume Profile Grid represents the evolution of volume analysis tools, combining traditional volume profile concepts with modern visualization techniques and intelligent analysis algorithms. By integrating dynamic range selection, sophisticated bull/bear separation, and multi-mode visualization with POC/Value Area detection, it provides traders with institutional-quality market structure analysis that adapts to any trading style. The comprehensive delta analysis and sentiment monitoring system eliminates guesswork while the flexible visualization options ensure optimal clarity across all market conditions, making it an essential tool for traders seeking to understand true market dynamics through volume-based price discovery.
[c3s] CWS - M2 Global Liquidity Index & BTC Correlation CWS - M2 Global Liquidity Index with Offset BTC Correlation
This custom indicator visualizes and analyzes the relationship between the global M2 money supply and Bitcoin (BTC) price movements. It calculates the correlation between these two variables to provide insights into how changes in global liquidity may impact Bitcoin’s price over time.
Key Features:
Global M2 Liquidity Index Calculation:
Fetches M2 money supply data from multiple economies (China, US, EU, Japan, UK) and normalizes using currency exchange rates (e.g., CNY/USD, EUR/USD).
Combines all M2 data points and normalizes by dividing by 1 trillion (1e12) for easier visualization.
Offset for M2 Data:
The offset parameter allows users to shift the M2 data by a specified number of days, helping track the influence of past global liquidity on Bitcoin.
BTC Price Correlation:
Computes the correlation between shifted global M2 liquidity and Bitcoin (BTC) price, using a 52-day lookback period by default.
Correlation Quality Display:
Categorizes correlation quality as:
Excellent : Correlation >= 0.8
Good : Correlation >= 0.6 and < 0.8
Weak : Correlation >= 0.4 and < 0.6
Very Weak : Correlation < 0.4
Displays correlation quality as a label on the chart for easy assessment.
Visual Enhancements:
Labels : Displays dynamic labels on the chart with metrics like M2 value and correlation.
Plot Shapes : Uses shapes to indicate data availability for global M2 and correlation.
Data Table : Optionally shows a data table in the top-right corner summarizing:
Global M2 value (in trillions)
The correlation between global M2 and BTC
The correlation quality
Optional Debugging:
Debug plots help identify when data is missing for M2 or correlation, ensuring transparency and accurate functionality.
Inputs:
Offset: Shift the M2 data (in days) to see past liquidity effects on Bitcoin.
Lookback Period: Number of periods (default 52) used to calculate the correlation.
Show Labels: Toggle to show or hide labels for M2 and correlation values.
Show Table: Toggle to show or hide the data table in the top-right corner.
Usage:
Ideal for traders and analysts seeking to understand the relationship between global liquidity and Bitcoin price. The offset and lookback period can be adjusted to explore different timeframes and correlation strengths, aiding more informed trading decisions.
BTC CME Futures Gaps (BTCGapHunt_CME)BTC CME Futures Gaps Indicator
Overview
This indicator visualises price gaps between the daily close and open of Bitcoin CME futures (CME:BTC1!). These gaps are often revisited ("filled") by market price action and may serve as technical targets.
Thanks
... to Maven and the Blockchain Masons (x.com/Masons_DAO) to push me on this topic.
What Is a CME Gap?
CME Bitcoin Futures do not trade 24/7. Gaps form when the market reopens at a different price than where it last closed.
Gaps are often used as support/resistance or liquidity targets.
This indicator tracks, visualises, and alerts on these gaps.
Key Features
Automatic gap detection using daily open/close on CME:BTC1!
Dynamic gap size threshold based on ATR (Average True Range)
Highlight unfilled gaps and track partial fills visually
Alerts for gap formation and fill events
Parameter overlay showing real-time settings
Supported and Overrideable Parameters
ATR Length: Defines the lookback period for ATR calculation (default: 14)
Gap Size Multiplier: Multiplies the ATR to set the dynamic gap threshold (default: 1.0)
Proximity Threshold: Price distance from gap edge to consider it filled (default: 100 USD)
Max Gaps Tracked: Maximum number of concurrent gaps shown (default: 50)
Alerts Enabled: Toggle alerts for gap formation and gap fill events
How the Gap Size Is Calculated
Minimum Gap Size = ATR(14) * Gap Size Multiplier
ATR Length and Gap Size Multiplier are configurable.
Gap threshold adjusts dynamically with market volatility.
Visual Guide
Red Box: Fully unfilled gap
Lemon Yellow Box: Partially filled gap
Right Margin Boxes: Snapshot of unfilled gaps for quick access
Top-Right Panel: Current ATR, Gap Size, Thresholds, etc.
Alerts
Gap Formed: A new gap is detected.
Gap Filled: The gap is either partially or fully filled.
Recommended Timeframes
1H, 4H, 1D (best resolution)
Designed for BTC spot/perpetual charts (e.g., BTCUSD, BTCUSDT)
How To Use
Add the script to your BTC chart.
Monitor red/yellow boxes for unfilled gaps.
Check config panel for current threshold and settings.
Enable alerts via TradingView for real-time updates.
Notes
Up to 50 gaps are tracked (adjustable).
Data source: CME futures via request.security.
All visuals and alerts are time-synced with your chart.
Disclaimer
This script is for educational purposes only. Trade at your own risk.
BTC Dominance Excluding StablecoinsBTC Dominance Excluding Stablecoins
Description:
The "BTC Dominance Excluding Stablecoins" indicator calculates Bitcoin's dominance as a percentage of the total cryptocurrency market capitalization, excluding the market caps of major stablecoins (USDT and USDC). Unlike the standard BTC.D ticker, which includes stablecoins in the total market cap, this indicator provides a clearer view of Bitcoin’s dominance relative to the "non-stable" crypto market. This can be useful for traders and analysts who want to assess Bitcoin’s strength without the influence of stablecoin market caps, which often skew dominance metrics during periods of high stablecoin usage.
How It Works:
Bitcoin Market Cap: Fetches Bitcoin’s market capitalization using CRYPTOCAP:BTC.
Total Market Cap: Retrieves the total cryptocurrency market cap via CRYPTOCAP:TOTAL.
Stablecoin Adjustment: Subtracts the market caps of USDT (CRYPTOCAP:USDT) and USDC (CRYPTOCAP:USDC) from the total market cap.
Dominance Calculation: Computes Bitcoin’s dominance as (BTC Market Cap / Adjusted Total Market Cap) * 100, where the adjusted total excludes stablecoins.
Output: Plots the resulting dominance percentage as a line chart.
Features:
Displays Bitcoin dominance excluding stablecoins on any timeframe.
Customizable line color and thickness for better visualization.
Provides a more accurate representation of Bitcoin’s market share in the volatile, non-stablecoin crypto ecosystem.
Usage:
Add this indicator to your TradingView chart to compare Bitcoin’s dominance against the broader altcoin market, free from stablecoin distortions. Use it alongside other indicators like BTC.D or price charts to analyze market trends, especially during periods of high stablecoin inflows or outflows.
Notes:
The indicator currently excludes USDT and USDC, the two largest stablecoins by market cap. Additional stablecoins (e.g., DAI, BUSD) can be added by modifying the script if desired.
Data is sourced from TradingView’s CRYPTOCAP symbols, which may have slight delays or variations depending on exchange data feeds.
Best used on daily or higher timeframes for smoother, more reliable results.
Author:
Created by K Du₿
Version:
Pine Script v5
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Excess Liquidity IndicatorExcess Liquidity Indicator
This script visualizes excess liquidity trends in relation to risk assets. It estimates excess liquidity by combining various macroeconomic factors such as WW M2 money supply, central bank balance sheets, and interest rates, oil, and the dollar index, and it substracts WW GDP. The tool helps traders analyze liquidity-driven market trends in a structured manner.
Note: This script is for research purposes only and does not provide financial advice.
I cannot point names cause I get banned but work is inspired by others...
Ultimate Volatility Scanner by NHBprod - Requested by Client!Hey Everyone!
I created another script to add to my growing library of strategies and indicators that I use for automated crypto and stock trading! This strategy is for BITCOIN but can be used on any stock or crypto. This was requested by a client so I thought I should create it and hopefully build off of it and build variants!
This script gets and compares the 14-day volatility using the ATR percentage for a list of cryptocurrencies and stocks. Cryptocurrencies are preloaded into the script, and the script will show you the TOP 5 coins in terms of volatility, and then compares it to the Bitcoin volatility as a reference. It updates these values once per day using daily timeframe data from TradingView. The coins are then sorted in descending order by their volatility.
If you don't want to use the preloaded set of coins, you have the option of inputting your own coins AND/OR stocks!
Let me know your thoughts.
TOTAL3/BTC This Pine Script™ code, named "TOTAL3/BTC with Arrow," is designed for cryptocurrency analysis on TradingView.
This script essentially provides a visual tool for traders to gauge when altcoins might be gaining or losing ground relative to Bitcoin through moving average analysis and color-coded trend indication.
Intention was to help the community with a script based on classic TA only.
Use it with SASDv2r indicator.
Feel free to make it better. If you did so, please let me know.
Main elements:
Data Fetching: It retrieves market cap data for all cryptocurrencies excluding Bitcoin and Ethereum (TOTAL3) and for Bitcoin (BTC).
Ratio Calculation: The script calculates the ratio of TOTAL3 to BTC market caps, which indicates how altcoins (excluding ETH) are performing relative to Bitcoin.
Plotting the Ratio: This ratio is plotted on the chart with a blue line, allowing traders to see the relative performance visually.
Moving Averages: Two Simple Moving Averages (SMA) are calculated for this ratio, one for 20 periods (ma20) and another for 50 periods (ma50), though these are not plotted in the current version of the code.
Reference Lines: Horizontal lines are added at ratios of 0.3 and 0.8 to serve as visual equilibrium points or thresholds for analysis.
Complex Moving Average: The script uses constants (len, len2, cc, smoothe) from another script, suggesting it's adapting or simplifying another's logic for multi-timeframe analysis.
Average Calculation: Two SMAs (avg and avg2) are computed using the constants defined, focusing on different lengths for trend analysis.
Direction Determination: It checks if the moving average is trending up or down by comparing the current value with its value smoothe bars earlier.
Color Coding: The color of the plotted moving average changes based on its direction (lime for up, red for down, aqua if no clear direction), aiding in quick visual interpretation of trends.
Plotting: Finally, the script plots this multi-timeframe moving average with a dynamic color to reflect the current market trend of the TOTAL3/BTC ratio, with a thicker line for visibility.
2-Year MA Multiplier [UAlgo]The 2-Year MA Multiplier is a technical analysis tool designed to assist traders and investors in identifying potential overbought and oversold conditions in the market. By plotting the 2-year moving average (MA) of an asset's closing price alongside an upper band set at five times this moving average, the indicator provides visual cues to assess long-term price trends and significant market movements.
🔶 Key Features
2-Year Moving Average (MA): Calculates the simple moving average of the asset's closing price over a 730-day period, representing approximately two years.
Visual Indicators: Plots the 2-year MA in forest green and the upper band in firebrick red for clear differentiation.
Fills the area between the 2-year MA and the upper band to highlight the normal trading range.
Uses color-coded fills to indicate overbought (tomato red) and oversold (cornflower blue) conditions based on the asset's closing price relative to the bands.
🔶 Idea
The concept behind the 2-Year MA Multiplier is rooted in the cyclical nature of markets, particularly in assets like Bitcoin. By analyzing long-term price movements, the indicator aims to identify periods of significant deviation from the norm, which may signal potential buying or selling opportunities.
2-year MA smooths out short-term volatility, providing a clearer view of the asset's long-term trend. This timeframe is substantial enough to capture major market cycles, making it a reliable baseline for analysis.
Multiplying the 2-year MA by five establishes an upper boundary that has historically correlated with market tops. When the asset's price exceeds this upper band, it may indicate overbought conditions, suggesting a potential for price correction. Conversely, when the price falls below the 2-year MA, it may signal oversold conditions, presenting potential buying opportunities.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Bitcoin Events HistoryWith this tool, you can travel back to Bitcoin’s very first price quote and retrace its entire history directly on your chart. Major events are plotted as labels or markers, providing context for how significant moments shaped Bitcoin’s journey.
Key Features
Comprehensive Event Coverage: From Bitcoin’s inception to the most recent updates.
Custom View: Change label colors, styles, sizes, and fonts using the script’s settings.
Regular Updates: New events are added regularly to keep the history current.
Replay History
Use Bar Replay Mode to step through Bitcoin’s price history and see events unfold in sequence.
Follow the on-screen instructions for a more immersive experience.
Community Contributions
If you notice a significant event missing or misplaced on a particular date, feel free to leave a comment! Your suggestions will be considered for the next update.
To all Bitcoin enthusiasts, traders, and anyone eager to explore the history of cryptocurrency from its inception, I hope you enjoy this indicator :)
