🧪 Yuri Garcia Smart Money Strategy FULL (Slope Divergence))📣 Yuri Garcia – Smart Money Strategy FULL
This is my private Smart Money Concept strategy, designed for my family and community to learn, trade, and grow sustainably.
🔑 How it works:
✅ Volume Cluster Zones: Automatically detects areas where strong buyers or sellers concentrate, acting as dynamic S/R levels.
✅ HTF Institutional Zones (4H): Higher timeframe trend filter ensures you’re always trading in the direction of major flows.
✅ Wick Pullback Filter: Confirms price rejects the zone, catching smart money traps and reversals.
✅ Cumulative Delta (CVD): Confirms whether buyers or sellers are truly in control.
✅ Slope-Based Divergence: Optional hidden divergence between price & CVD to spot reversals others miss.
✅ ATR Dynamic SL/TP: Adapts stop loss and take profit to live volatility with adjustable risk/reward.
🧩 Visual Markers Explained:
🟦 Blue X: Price inside HTF zone
🟨 Yellow X: Price inside Volume Cluster zone
🟧 Orange Circle: Wick pullback detected
🟥 Red Square: CVD confirms order flow strength
🔼 Aqua Triangle Up: Bullish slope divergence
🔽 Purple Triangle Down: Bearish slope divergence
🟢 Green Triangle Up: Final Long Entry confirmed
🔴 Red Triangle Down: Final Short Entry confirmed
⚡ Who is this for?
This strategy is best suited for traders who understand smart money concepts, order flow, and want an adaptive framework to trade major assets like BTC, Gold, SP500, NASDAQ, or FX pairs.
🔒 Important
Use responsibly, backtest extensively, and combine with solid risk management. This is for educational purposes only.
✨ Credits
Built with ❤️ by Yuri Garcia – dedicated to my family & community.
✅ How to use it
1️⃣ Add to chart
2️⃣ Adjust inputs for your asset & timeframe
3️⃣ Enable/disable slope divergence filter to match your style
4️⃣ Set your alerts with built-in conditions
在腳本中搜尋"电脑桌面显示BTC"
RSI Overbought/Oversold MTFRSI Overbought / Oversold MTF — Dashboard & Alerts
What it does
This script scans up to 13 symbols at once and shows their RSI readings on three lower‑time‑frames (1 min, 5 min, 15 min).
If all three RSIs for a symbol are simultaneously above the overbought threshold or below the oversold threshold, the script:
Prints the condition (“Overbought” / “Oversold”) in a color‑coded dashboard table.
Fires a one‑per‑bar alert so you never miss the move.
Key features
Feature Details
Multi‑symbol Default list includes BTC, ETH, SOL, BNB, XRP, ADA, AVAX, AVAAI, DOGE, VIRTUAL, SUI, ALCH, LAYER (all Binance pairs). Replace or reorder in the inputs.
Triple‑time‑frame check RSI is calculated on 1 m, 5 m, 15 m for each symbol.
Customizable thresholds Set your own RSI Period, Overbought and Oversold levels. Defaults: 14 / 70 / 30.
Color‑coded dashboard Top‑right table shows:
• Symbol name
• RSI 1 m / 5 m / 15 m (red = overbought, green = oversold, white = neutral)
• Overall Status column (“Overbought”, “Oversold”, “Mixed”).
Alerts built in Triggers once per bar whenever a symbol is overbought or oversold on all three time‑frames simultaneously.
Typical use cases
Scalp alignment — Enter when all short TFs agree on overbought/oversold extremes.
Mean‑reversion spotting — Identify stretched conditions across multiple coins without switching charts.
Quick sentiment scan — Glance at the dashboard to see where momentum is heating up or cooling down.
How to use
Add to chart (overlay = false; it sits in its own pane).
Adjust symbols & thresholds in the Settings panel.
Create alerts → choose “RSI Overbought/Oversold MTF” → “Any Alert() Function Call” to receive push, email, or webhook notifications.
Note: The script queries many symbols each bar; use on lower time‑frames only if your data limits allow.
For educational purposes only — not financial advice. Always test on paper before trading live.
Big Trade % Heatmap### Big Trade % Heatmap
**Quick overview**
This indicator highlights where “whale” activity is clustered by showing what fraction of the recent candles contained *large‑value trades*. A candle is considered “big” when its notional volume (`volume × close`) exceeds your chosen USD threshold. You instantly see:
* **Percent of big candles** in the last *N* bars, refreshed at the cadence you pick.
* **On‑chart labels & markers** every refresh, so the chart stays clean.
* **Optional heat‑map background** that turns orange (>20 %) or green (>50 %) when big‑trade concentration spikes.
* **Ready‑made alert** when big‑trade dominance crosses 50 %.
---
#### How it works
1. **Trade size per candle** – Calculates `close × volume` to estimate dollars traded.
2. **Threshold filter** – Flags candles whose value is above *Big Trade Threshold (\$)*.
3. **Look‑back window** – Counts what percentage of the last *Lookback Window (X Candles)* were “big.”
4. **Refresh interval** – Repeats the measurement only every *Refresh Interval (Every X Candles)* to avoid label spam.
5. **Visuals** –
* A small blue ▼ above the bar + a text label such as `35.00 % > $25 000`.
* Background shading (green/orange) for quick, at‑a‑glance sentiment.
---
#### Inputs
| Input | Purpose | Default |
| -------------------------------------- | ----------------------------------------------------- | ------- |
| **Lookback Window (X Candles)** | How many recent bars to sample for the % calculation. | 20 |
| **Refresh Interval (Every X Candles)** | How often to display a new label/marker. | 5 |
| **Big Trade Threshold (\$)** | Minimum USD value for a candle to count as “big.” | 10 000 |
Tune these to the symbol and timeframe you trade (e.g., raise the threshold for BTC‑USDT 1‑h, lower it for micro‑caps).
---
#### Alerts
Enable **“High Big Trade %”** to get notified the moment more than half of the last *N* candles qualify as big trades—handy for spotting sudden accumulation or distribution.
---
#### Typical use cases
* **Breakout confirmation** – A surge in big‑trade % just before price escapes a range can validate the move.
* **Whale spotting** – Detect hidden accumulation on pullbacks or aggressive selling into rallies.
* **Filter noise** – Combine with your favorite trend indicator; only act when both align.
---
> *Built with Pine Script v6. Always back‑test before trading live; this tool is for educational purposes and not financial advice.*
50/100 EMA Crossover with Candle Confirmation📘 **50/100 EMA Crossover with Candle Confirmation – Strategy Description**
The **50/100 EMA Crossover with Candle Confirmation** is a trend-following strategy designed to filter high-probability entries by combining exponential moving average (EMA) crossovers with strong price action confirmation. This strategy aims to reduce false signals commonly associated with EMA-only systems by requiring a **candle close confirmation in the direction of the trend**, making it more reliable for intraday or swing trading across Forex, crypto, and stock markets.
---
### 🔍 **Core Logic**
* The strategy is based on the interaction of the **50 EMA** (fast-moving average) and the **100 EMA** (slow-moving average).
* **Trend direction** is determined by the crossover:
* **Bullish Trend**: When the 50 EMA crosses **above** the 100 EMA.
* **Bearish Trend**: When the 50 EMA crosses **below** the 100 EMA.
* To **filter out false breakouts**, a **candle confirmation** is used:
* For a **Buy signal**: After a bullish crossover, wait for a strong bullish candle (e.g., full-body green candle) to **close above both EMAs**.
* For a **Sell signal**: After a bearish crossover, wait for a strong bearish candle to **close below both EMAs**.
---
### ✅ **Entry Conditions**
**Buy Entry:**
* 50 EMA crosses above 100 EMA.
* Latest candle closes **above both EMAs**.
* Candle must be bullish (green/full body preferred).
**Sell Entry:**
* 50 EMA crosses below 100 EMA.
* Latest candle closes **below both EMAs**.
* Candle must be bearish (red/full body preferred).
---
### 🛑 **Exit or Take-Profit Options**
* **Fixed TP/SL**: 1:2 or 1:3 risk-reward.
* **Trailing Stop**: Based on recent swing highs/lows or ATR.
* **EMA Exit**: Exit trade when the candle closes on the opposite side of 50 EMA.
---
### ⚙️ **Best Settings**
* **Timeframes**: 5M, 15M, 1H, 4H (works well on most).
* **Markets**: Forex, Crypto (e.g., BTC/ETH), Indices (e.g., NASDAQ, NIFTY50).
* **Recommended filters**:
* Use with RSI divergence or volume confirmation.
* Avoid using during high-impact news (especially on lower timeframes).
---
### 🧠 **Why This Works**
The 50/100 EMA crossover provides a **medium-term trend signal**, reducing noise seen in fast EMAs (like 9 or 21). The candle confirmation adds a **momentum filter**, ensuring price supports the directional bias. This makes it suitable for traders who want a balance of trend and entry precision without overcomplicating with too many indicators.
---
### 📈 **Advantages**
* Simple yet effective for identifying trends.
* Filters out fakeouts using candle confirmation.
* Easy to automate in Pine Script or other trading bots.
* Can be combined with support/resistance or SMC zones for better confluence.
---
### ⚠️ **Limitations**
* May lag slightly in ranging markets.
* Late entries possible due to confirmation candle.
* Works best with additional volume or volatility filter.
Max Drawdown (Asset-Based Lookback)Max Drawdown (Long-Term Trading)
🟦 Majors BTC, ETH, BNB, LTC 180 – 365
Captures full correction cycles and recovery patterns (6–12 months).
🟩 Altcoins SOL, ADA, DOT, LINK, AVAX 90 – 180
Alts move faster than majors; 3–6 months catches most large swings.
🟥 Meme coins DOGE, SHIB, PEPE, FLOKI 60 – 120
Volatile with quick trend reversals; 2–4 months captures parabolic runs + drawdowns.
📅 Chart Timeframe:
Use Daily (1D) timeframe for all these.
For extra macro insight, try Weekly (1W) with 52 bars (≈ 1 year).
Compare multiple assets using the same period to assess relative risk.
If you're building a long-term portfolio, combine this with:
200-day SMA or EMA for trend context.
Sharpe Ratio or Sortino Ratio if you're looking for risk-adjusted return metrics.
Orthogonal Projections to Latent Structures (O-PLS)Version 0.1
Orthogonal Projections to Latent Structures (O-PLS) Indicator for TradingView
This indicator, named "Orthogonal Projections to Latent Structures (O-PLS)", is designed to help traders understand the relevance or predictive power of various market variables on the future close price of the asset it's applied to. Unlike standard correlation coefficients that show a simple linear relationship, O-PLS aims to separate variables into "predictive" (relevant to Y) and "orthogonal" (irrelevant noise) components. This Pine Script indicator provides a simplified proxy of the relevance score derived from O-PLS principles.
Purpose of the Indicator
The primary purpose of this indicator is to identify which technical factors (such as price, volume, and other indicators) have the strongest relationship with the future price movement of the current trading instrument. By providing a "relevance score" for each input variable, it helps traders focus on the most influential data points, potentially leading to more informed trading decisions.
Inputs
The indicator offers the following user-definable inputs:
* **Lookback Period:** This integer input (default: 100, min: 10, max: 500) determines the number of past bars used to calculate the relevance scores for each variable. A longer lookback period considers more historical data, which can lead to smoother, less reactive scores but might miss recent shifts in variable importance.
* **External Asset Symbol:** This symbol input (default: `BINANCE:BTCUSDT`) allows you to specify an external asset (e.g., `BINANCE:ETHUSDT`, `NASDAQ:TSLA`) whose close price will be included in the analysis as an additional variable. This is useful for cross-market analysis to see how other assets influence the current chart.
* **Plot Visibility Checkboxes (e.g., "Plot: Open Price Relevance", "Plot: Volume Relevance", etc.):** These boolean checkboxes allow you to toggle the visibility of individual relevance score plots on the chart, helping to declutter the display and focus on specific variables.
Outputs
The indicator provides two main types of output:
Relevance Score Plots: These are lines plotted in a separate pane below the main price chart. Each line corresponds to a specific market variable (Open Price, Close Price, High Price, Low Price, Volume, various RSIs, SMAs, MFI, and the External Asset Close). The value of each line represents the calculated "relevance score" for that variable, typically scaled between 0 and 10. A higher score indicates a stronger predictive relationship with the future close price.
Sorted Relevance Table : A table displayed in the top-right corner of the chart provides a clear, sorted list of all analyzed variables and their corresponding relevance scores. The table is sorted in descending order of relevance, making it easy to identify the most influential factors at a glance. Each variable name in the table is colored according to its plot color, and the external asset's name is dynamically displayed without the "BINANCE:" prefix.
How to Use the Indicator
1. **Add to Chart:** Apply the "Orthogonal Projections to Latent Structures (O-PLS)" indicator to your desired trading chart (e.g., ETH/USDT).
2. **Adjust Inputs:**
* **Lookback Period:** Experiment with different lookback periods to see how the relevance scores change. A shorter period might highlight recent correlations, while a longer one might show more fundamental relationships.
* **External Asset Symbol:** If you trade BTC/USDT, you might add ETH/USDT or SPX as an external asset to see its influence.
3. **Analyze Relevance Scores:**
* **Plots:** Observe the individual relevance score plots over time. Are certain variables consistently high? Do scores change before significant price moves?
* **Table:** Refer to the sorted table on the latest confirmed bar to quickly identify the top-ranked variables.
4. **Incorporate into Strategy:** Use the insights from the relevance scores to:
* Prioritize certain indicators or price actions in your trading strategy. For example, if "Volume" has a high relevance score, it suggests volume confirmation is critical for future price moves.
* Understand the influence of inter-market relationships (via the External Asset Close).
How the Indicator Works
The indicator works by performing the following steps on each bar:
1. **Data Fetching:** It gathers historical data for various price components (open, high, low, close), volume, and calculated technical indicators (SMA, RSI, MFI) for the specified `lookback` period. It also fetches the close price of an `External Asset Symbol` .
2. **Standardization (Z-scoring):** All collected raw data series are standardized by converting them into Z-scores. This involves subtracting the mean of each series and dividing by its standard deviation . Standardization is crucial because it brings all variables to a common scale, preventing variables with larger absolute values from disproportionately influencing the correlation calculations.
3. **Correlation Calculation (Proxy for O-PLS Relevance):** The indicator then calculates a simplified form of correlation between each standardized input variable and the standardized future close price (Y variable) . This correlation is a proxy for the relevance that O-PLS would identify. A high absolute correlation indicates a strong linear relationship.
4. **Relevance Scaling:** The calculated correlation values are then scaled to a range of 0 to 10 to provide an easily interpretable "relevance score" .
5. **Output Display:** The relevance scores are presented both as time-series plots (allowing observation of changes over time) and in a real-time sorted table (for quick identification of top factors on the current bar) .
How it Differs from Full O-PLS
This indicator provides a *simplified proxy* of O-PLS principles rather than a full, mathematically rigorous O-PLS model. Here's why and how it differs:
* **Dimensionality Reduction:** A full O-PLS model would involve complex matrix factorization techniques to decompose the independent variables (X) into components that are predictive of Y and components that are orthogonal (unrelated) to Y but still describe X's variance. Pine Script's array capabilities and computational limits make direct implementation of these matrix operations challenging.
* **Orthogonal Components:** A true O-PLS model explicitly identifies and removes orthogonal components (noise) from the X data that are unrelated to Y. This indicator, in its simplified form, primarily focuses on the direct correlation (relevance) between each X variable and Y after standardization, without explicitly modeling and separating these orthogonal variations.
* **Predictive Model:** A full O-PLS model is ultimately a predictive model that can be used for regression (predicting Y). This indicator, however, focuses solely on **identifying the relevance/correlation of inputs to Y**, rather than building a predictive model for Y itself. It's more of an analytical tool for feature importance than a direct prediction engine.
* **Computational Intensity:** Full O-PLS involves Singular Value Decomposition (SVD) or Partial Least Squares (PLS) algorithms, which are computationally intensive. The indicator uses simpler statistical measures (mean, standard deviation, and direct correlation calculation over a lookback window) that are feasible within Pine Script's execution limits.
In essence, this Pine Script indicator serves as a practical tool for gaining insights into variable relevance, inspired by the spirit of O-PLS, but adapted for the constraints and common use cases of a TradingView environment.
RSI Mansfield +RSI Mansfield+ – Adaptive Relative Strength Indicator with Divergences
Overview
RSI Mansfield+ is an advanced relative strength indicator that compares your instrument’s performance against a configurable benchmark index or asset (e.g., Bitcoin Dominance, S&P 500). It combines Mansfield normalization, adaptive smoothing techniques, and automatic detection of bullish and bearish divergences (regular and hidden), delivering a comprehensive tool for assessing relative strength across any market and timeframe.
Originality and Motivation
Unlike traditional relative strength scripts, this indicator introduces several distinctive improvements:
Mansfield Normalization: Scales the ratio between the asset and the benchmark relative to its moving average, transforming it into a normalized oscillator that fluctuates around zero, making it easier to spot outperformance or underperformance.
Adaptive Smoothing: Automatically selects whether to use EMA or SMA based on the market type (crypto or stocks) and timeframe (intraday, daily, weekly, monthly), avoiding manual configuration and providing more robust results under varying volatility conditions.
Divergence Detection: Identifies four types of divergences in the Mansfield oscillator to help anticipate potential reversal points or trend confirmations.
Multi-Market Support: Offers benchmark selection among major crypto and global stock indices from a single input.
These enhancements make RSI Mansfield+ more practical and powerful than conventional relative strength scripts with static benchmarks or without divergence capabilities.
Core Concepts
Relative Strength (RS): Compares price evolution between your asset and the selected benchmark.
Mansfield Normalization: Measures how much the RS deviates from its historical moving average, expressed as a scaled oscillator.
Divergences: Detects regular and hidden bullish or bearish divergences within the Mansfield oscillator.
Timeframe Adaptation: Dynamically adjusts moving average lengths based on timeframe and market type.
How It Works
Benchmark Selection
Choose among over 10 indices or market domains (BTC Dominance, ETH Dominance, S&P 500, European indices, etc.).
Ratio Calculation
Computes the price-to-benchmark ratio and smooths it with the adaptive moving average.
Normalization and Scaling
Transforms deviations into a Mansfield oscillator centered around zero.
Dynamic Coloring
Green indicates relative outperformance, red signals underperformance.
Divergence Detection
Automatically identifies bullish and bearish (regular and hidden) divergences by comparing oscillator pivots against price pivots.
Baseline Reference
A clear zero line helps interpret relative strength trends.
Usage Guidelines
Benchmark Comparison
Ideal for traders analyzing whether an asset is outperforming or lagging its sector or market.
Divergence Analysis
Helps detect potential reversal or continuation signals in relative strength.
Multi-Timeframe Compatibility
Can be applied to intraday, daily, weekly, or monthly charts.
Interpretation
Oscillator >0 and green: outperforming the benchmark.
Oscillator <0 and red: underperforming.
Bullish divergences: potential relative strength reversal to the upside.
Bearish divergences: possible loss of momentum or reversal to the downside.
Credits
The concept of Mansfield Relative Strength is based on Stan Weinstein’s original work on relative performance analysis. This script was built entirely from scratch in TradingView Pine Script v6, incorporating original logic for adaptive smoothing, normalized scaling, and divergence detection, without reusing any external open-source code.
Exponential-Decay Cumulative Spread (Cycle-Tuned)## Indicator Overview
**Exponential-Decay Cumulative Spread (Cycle-Tuned)** – short title **LambdaCumDelta** – tracks the percentage spread between CEXs BTC spot prices.
By clipping outliers, applying an exponential-decay running sum, and comparing that sum to rolling percentile bands, the script flags potential **cycle bottoms** and **cycle tops** whenever the cumulative spread stays beyond extreme thresholds for three consecutive bars.
---
### Core Logic
1. **Price Spread**
`spread_pct = (cexA – cexB) / cexB × 100`.
2. **Outlier Suppression**
* Calculates the **90-day standard deviation σ** of `spread_pct`.
* Uses a **clip coefficient `k_clip`** (0.5–5.0) to cap the spread at `±k_clip × σ`, damping single-day anomalies.
3. **Exponential-Decay Sum**
* Applies a decay factor **λ** (0.50–0.999):
```
CumΔₜ = spread_clipₜ + λ × CumΔₜ₋₁
```
* Larger λ → longer memory half-life.
4. **Rolling Percentile Bands**
* Uses a **365-bar window** to derive dynamic percentile thresholds.
* Upper / Lower bands are set by **perc\_hi** and **perc\_lo** (e.g., 85 % and 15 %).
5. **Signal Definition**
* **Bullish** (cycle bottom): `CumΔ` above the upper band for **3 straight bars**.
* **Bearish** (cycle top): `CumΔ` below the lower band for **3 straight bars**.
---
### Chart Elements
| Plot | Style | Meaning |
| --------------- | ----------------- | ----------------------------------- |
| **CumΔ** | Teal thick line | Exponential-decay cumulative spread |
| Upper Threshold | Green thin line | Rolling upper percentile |
| Lower Threshold | Red thin line | Rolling lower percentile |
| Background | Faded green / red | Bullish / bearish signal zone |
---
### Key Inputs
| Input | Default | Purpose |
| -------------------- | ------- | ------------------------------- |
| **Decay factor λ** | 0.95 | Memory length of CumΔ |
| **Clip coefficient** | 2.0 | Multiple of σ for outlier cap |
| **Upper percentile** | 85 | Cycle-bottom trigger percentile |
| **Lower percentile** | 15 | Cycle-top trigger percentile |
---
### Practical Tips
1. **Timing bias**
* Green background often precedes mean-reversion of the spread – consider scaling into longs or covering shorts.
* Red background suggests stretched positive spread – consider trimming longs or lightening exposure.
2. **Combine with volume, trend filters (MA, MACD, etc.)** to weed out false extremes.
3. Designed for **daily charts**; ensure both exchange feeds are synchronized.
---
### Alerts
Two built-in `alertcondition`s fire when bullish or bearish criteria are met, enabling push / email / webhook notifications.
---
### Disclaimer
This script is for educational and research purposes only and is **not** financial advice. Test thoroughly and trade at your own risk.
Dynamic SL/TP Levels (ATR or Fixed %)This indicator, "Dynamic SL/TP Levels (ATR or Fixed %)", is designed to help traders visualize potential stop loss (SL) and take profit (TP) levels for both long and short positions, refreshing dynamically on each new bar. It assumes entry at the current bar's close price and uses a fixed 1:2 risk-reward ratio (TP is twice the distance of SL in the profit direction). Levels are displayed in a compact table in the chart pane for easy reference, without cluttering the main chart with lines.
Key Features:
Calculation Modes:
ATR-Based (Dynamic): SL distance is derived from the Average True Range (ATR) multiplied by a user-defined factor (default 1.5x). This adapts to the asset's volatility, providing breathing room based on recent price movements.
Fixed Percentage: SL is set as a direct percentage of the current close price (default 0.5%), offering consistent gaps regardless of volatility.
Long and Short Support: Calculates and shows SL/TP for longs (SL below close, TP above) and shorts (SL above close, TP below), with toggles to hide/show each.
Real-Time Updates: Levels recalculate every bar, making them readily available for entry decisions in your trading system.
Display: Outputs to a table in the top-right pane, showing precise values formatted to the asset's tick size (e.g., full decimal places for crypto).
How to Use:
Add the indicator to your chart via TradingView's Pine Editor or library.
Adjust settings:
Toggle "Use ATR?" on/off to switch modes.
Set "ATR Length" (default 14) and "ATR Multiplier for SL" for dynamic mode.
Set "Fixed SL %" for percentage mode.
Enable/disable "Show Long Levels" or "Show Short Levels" as needed.
Interpret the table: Use the displayed SL/TP values when your strategy signals an entry. For risk management, combine with position sizing (e.g., risk 1% of account per trade based on SL distance).
Example: On a volatile asset like BTC, ATR mode might set a wider SL for realism; on stable pairs, fixed % ensures predictability.
This tool promotes disciplined trading by tying levels to price action or fixed rules, but it's not financial advice—always backtest and use with your full strategy. Feedback welcome!
Asset Premium/Discount Monitor📊 Overview
The Asset Premium/Discount Monitor is a tool for analyzing the relative value between two correlated assets. It measures when one asset is trading at a premium or discount compared to its historical relationship with another asset, helping traders identify potential mean reversion opportunities, or pairs trading opportunities.
🎯 Use Cases
Perfect for analyzing:
NASDAQ:MSTR vs CRYPTO:BTCUSD - MicroStrategy's premium/discount to Bitcoin
NASDAQ:COIN vs BITSTAMP:BTCUSD - Coinbase's relative value to Bitcoin
NASDAQ:TSLA vs NASDAQ:QQQ - Tesla's premium to tech sector
Regional banks AMEX:KRE vs AMEX:XLF - Individual bank stocks vs financial sector
Any two correlated assets where relative value matters
Example of a trade: MSTR vs BTC - When indicator shows MSTR at 95% percentile (extreme premium): Short MSTR, Buy BTC. Then exit when the spread reverts to the mean, say 40-60% percentile.
🔧 How It Works
Core Calculation
Ratio Analysis: Calculates the price ratio between your asset and the correlated asset
Historical Baseline: Establishes the "normal" relationship using a 252-day moving average. You can change this.
Premium Measurement: Measures current deviation from historical average as a percentage
Statistical Context: Provides percentile rankings and standard deviation bands
The Math
Premium % = (Current Ratio / Historical Average Ratio - 1) × 100
🎨 Customization Options
Correlated Asset: Choose any symbol for comparison
Lookback Period: Adjust historical baseline (50-1000 days)
Smoothing: Reduce noise with moving average (1-50 days)
Visual Toggles: Show/hide bands and percentile lines
Color Themes: Customize premium/discount colors
📊 Interpretation Guide
Premium/Discount Reading
Positive %: Asset trading above historical relationship (premium)
Negative %: Asset trading below historical relationship (discount)
Near 0%: Asset at fair value relative to correlation
Percentile Ranking
90%+: Near recent highs - potential selling opportunity
10% and below: Near recent lows - potential buying opportunity
25-75%: Normal trading range
Signal Classifications
🔴 SELL PREMIUM: Asset expensive relative to recent range
🟡 Premium Rich: Moderately expensive, monitor for reversal
⚪ NEUTRAL: Fair value territory
🟡 Discount Opportunity: Moderately cheap, potential accumulation zone
🟢 BUY DISCOUNT: Asset cheap relative to recent range
🚨 Built-in Alerts
Extreme Premium Alert: Triggers when percentile > 95%
Extreme Discount Alert: Triggers when percentile < 5%
⚠️ Important Notes
Works best with highly correlated assets
Historical relationships can change - monitor correlation strength
Not investment advice - use as one factor in your analysis
Backtest thoroughly before implementing any strategy
🔄 Updates & Future Features
This indicator will be continuously improved based on user feedback. So... please give me your feedback!
Dynamic VWAP: Fair Value & Divergence SuiteDynamic VWAP: Fair Value & Divergence Suite
Dynamic VWAP: Fair Value & Divergence Suite is a comprehensive tool for tracking contextual valuation, overextension, and potential reversal signals in trending markets. Unlike traditional VWAP that anchors to the start of a session or a fixed period, this indicator dynamically resets the VWAP anchor to the most recent swing low. This design allows you to monitor how far price has extended from the most recent significant low, helping identify zones of potential profit-taking or reversion.
Deviation bands (standard deviations above the anchored VWAP) provide a clear visual framework to assess whether price is in a fair value zone (±1σ), moderately extended (+2σ), or in zones of extreme extension (+3σ to +5σ). The indicator also highlights contextual divergence signals, including slope deceleration, weak-volume retests, and deviation failures—giving you actionable confluence around potential reversal points.
Because the anchor updates dynamically, this tool is particularly well suited for trend-following assets like BTC or stocks in sustained moves, where price rarely returns to deep negative deviation zones. For this reason, the indicator focuses on upside extension rather than symmetrical reversion to a long-term mean.
🎯 Key Features
✅ Dynamic Swing Low Anchoring
Continuously re-anchors VWAP to the most recent swing low based on your chosen lookback period.
Provides context for trend progression and overextension relative to structural lows.
✅ Standard Deviation Bands
Plots up to +5σ deviation bands to visualize levels of overextension.
Extended bands (+3σ to +5σ) can be toggled for simplicity.
✅ Conditional Zone Fills
Colored background fills show when price is inside each valuation zone.
Helps you immediately see if price is in fair value, moderately extended, or highly stretched territory.
✅ Divergence Detection
VWAP Slope Divergence: Flags when price makes a higher high but VWAP slope decelerates.
Low Volume Retest: Highlights weak re-tests of VWAP on low volume.
Deviation Failure: Identifies when price reverts back inside +1σ after closing beyond +3σ.
✅ Volume Fallback
If volume is unavailable, uses high-low range as a proxy.
✅ Highly Customizable
Adjust lookbacks, show/hide extended bands, toggle fills, and enable or disable divergences.
🛠️ How to Use
Identify Buy and Sell Zones
Price in the fair value band (±1σ) suggests equilibrium.
Reaching +2σ to +3σ signals increasing overextension and potential areas to take profits.
+4σ to +5σ zones can be used to watch for exhaustion or mean-reversion setups.
Monitor Divergence Signals
Use slope divergence and deviation failures to look for confluence with overextension.
Low volume retests can flag rallies lacking conviction.
Adapt Swing Lookback
30–50 bars: Faster re-anchoring for swing trading.
75–100 bars: More stable anchors for longer-term trends.
🧭 Best Practices
Combine the anchored VWAP with higher timeframe structure.
Confirm signals with other tools (momentum, volume profiles, or trend filters).
Use extended deviation zones as context, not as standalone signals.
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security or asset. Always do your own research and consult a qualified financial professional before making any trading decisions. Past performance does not guarantee future results.
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
Simple Market Kill-Zones + Open (UTC)What it does
This Pine v6 indicator highlights the “kill-zones” around the big session opens—Asian (23:00–03:00 UTC), London (07:00–09:00 UTC) and New York (13:30–15:30 UTC)—by reading each bar’s actual UTC timestamp. It also draws dashed vertical lines at exactly 23:00, 07:00 and 13:30 UTC, so you never miss the liquidity ramps. Because it uses raw UTC hours/minutes, it stays accurate even when exchanges pause (e.g. Nano-BTC’s daily halt) or your chart’s display timezone changes.
Key Inputs
Show Asia/London/NY Kill Zone – toggle each shaded band on/off
Zone Colors – pick your own semi-transparent hues
Show Session-Open Lines – enable dashed verticals at the exact open times
Line Colors – customize the line opacity and style
How to use
Apply on your favorite timeframe (15 min–1 h is a sweet spot).
Toggle the zones you care about and pick readable colors.
Use the dashed lines as entry triggers or as visual bookmarks.
In your own Pine strategies, wrap order logic with the zone booleans to only trade when liquidity’s alive.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Expanded Cloud [LuxAlgo]The Expanded Cloud tool allows traders to identify and follow trends accurately. It is based on the well-known Donchian Channels, but with enhanced features.
It features a trailing cloud that expands with the price and a trading stats dashboard.
🔶 USAGE
The tool is super easy to use. Traders can identify bigger or smaller trends just by adjusting the length from the settings panel.
Trend identification is based on Donchian Channels. An uptrend is indicated when the cloud is located below the price, while a downtrend is indicated when the cloud is above it.
Dots signal the start of a new trend, and the width of the clouds identifies the strength of the price expansion. The wider the cloud, the bigger the move.
The expanded cloud, due to its visual, can also act as a trailing stop.
🔹 Trend Identification
As we can see in the chart above, different length values identify different trends on the same BTC daily chart. Larger values identify larger trends.
🔹 Cloud Expansion
From the settings panel, traders can adjust how the clouds expand based on the Expansion % parameter. It accepts values from 0 to 100, which controls how much of the expansion is taken into account. Higher values will make the cloud expand and get closer to the price faster.
When the cloud moves opposite to the direction of the indicated trend (e.g: the cloud decreases while being below the price), it is often indicative of the end of a retracement, and we can expect the price to move with the indicated trend.
The chart above shows the effect of different Expansion % values.
🔹 Dashboard
The trading statistics dashboard informs traders of key metrics derived from the tool. The following are notable:
PNL: Theoretical profit or loss from all trends identified by the tool in the right scale units.
EXPECT.: Expected value of each trade. It is derived from win rate and risk-to-reward metrics.
AVG: 1st TOUCH: The average number of bars from the beginning of a new trend until the price touches the cloud for the first time.
🔶 SETTINGS
Length: Length for trend detection
Expansion %: Percentage of price expansion for cloud formation
Source: Source of the data
🔹 Dashboard
Show Dashboard: Enable/disable the statistics dashboard
Location: Dashboard location
Size: Dashboard size
Simple Pips GridOverview
This is a clean, simple, and highly practical indicator that draws horizontal grid lines at user-defined pip intervals.
Unlike other complex grid indicators, this script is designed to be lightweight and error-free. It eliminates automatic symbol detection and instead gives you full manual control, ensuring it works perfectly with any symbol you trade—FX, CFDs, Crypto, Stocks, Indices, and more.
Key Features
Universal Compatibility: Works with any trading pair by letting you manually define the pip value.
Fully Customizable: Easily set the pip interval for your grid (e.g., 10 pips, 50 pips, 100 pips).
Lightweight & Fast: Simple code ensures smooth performance without lagging your chart.
Visual Customization: Change the color, width, and style (solid, dashed, dotted) of the grid lines.
How to Use
It's incredibly simple to set up. You only need to configure two main settings:
Step 1: Set the "Pip Value"
This is the most important setting. You need to tell the indicator what "1 pip" means for the symbol you are currently viewing.
Go to the indicator settings and find the "Pip Value" input. Here are some common examples:
Symbol Pip Value (Input this number)
USD/JPY 0.01
EUR/USD 0.0001
GBP/USD 0.0001
XAU/USD (Gold) 0.1
JP225 (Nikkei 225) 10
US500 (S&P 500) 1
BTC/USD 0.1 or 1.0 (depending on your preference)
Step 2: Set the "Pip Interval"
Next, in the "Pip Interval" input, simply type how many pips you want between each line.
For a 10-pip grid, enter 10.
For a 50-pip grid, enter 50.
That's it! The grid will now be perfectly aligned to your specifications.
Additional Settings
Line Color, Width, Style: Customize the appearance of the lines to match your chart theme.
Number of Lines: Adjust how many lines are drawn above and below the current price to optimize performance and visibility.
This script was created with the assistance of Gemini (Google's AI) to be a simple and reliable tool for all traders. Feel free to use and modify it. Happy trading!
Bitcoin Power Law [LuxAlgo]The Bitcoin Power Law tool is a representation of Bitcoin prices first proposed by Giovanni Santostasi, Ph.D. It plots BTCUSD daily closes on a log10-log10 scale, and fits a linear regression channel to the data.
This channel helps traders visualise when the price is historically in a zone prone to tops or located within a discounted zone subject to future growth.
🔶 USAGE
Giovanni Santostasi, Ph.D. originated the Bitcoin Power-Law Theory; this implementation places it directly on a TradingView chart. The white line shows the daily closing price, while the cyan line is the best-fit regression.
A channel is constructed from the linear fit root mean squared error (RMSE), we can observe how price has repeatedly oscillated between each channel areas through every bull-bear cycle.
Excursions into the upper channel area can be followed by price surges and finishing on a top, whereas price touching the lower channel area coincides with a cycle low.
Users can change the channel areas multipliers, helping capture moves more precisely depending on the intended usage.
This tool only works on the daily BTCUSD chart. Ticker and timeframe must match exactly for the calculations to remain valid.
🔹 Linear Scale
Users can toggle on a linear scale for the time axis, in order to obtain a higher resolution of the price, (this will affect the linear regression channel fit, making it look poorer).
🔶 DETAILS
One of the advantages of the Power Law Theory proposed by Giovanni Santostasi is its ability to explain multiple behaviors of Bitcoin. We describe some key points below.
🔹 Power-Law Overview
A power law has the form y = A·xⁿ , and Bitcoin’s key variables follow this pattern across many orders of magnitude. Empirically, price rises roughly with t⁶, hash-rate with t¹² and the number of active addresses with t³.
When we plot these on log-log axes they appear as straight lines, revealing a scale-invariant system whose behaviour repeats proportionally as it grows.
🔹 Feedback-Loop Dynamics
Growth begins with new users, whose presence pushes the price higher via a Metcalfe-style square-law. A richer price pool funds more mining hardware; the Difficulty Adjustment immediately raises the hash-rate requirement, keeping profit margins razor-thin.
A higher hash rate secures the network, which in turn attracts the next wave of users. Because risk and Difficulty act as braking forces, user adoption advances as a power of three in time rather than an unchecked S-curve. This circular causality repeats without end, producing the familiar boom-and-bust cadence around the long-term power-law channel.
🔹 Scale Invariance & Predictions
Scale invariance means that enlarging the timeline in log-log space leaves the trajectory unchanged.
The same geometric proportions that described the first dollar of value can therefore extend to a projected million-dollar bitcoin, provided no catastrophic break occurs. Institutional ETF inflows supply fresh capital but do not bend the underlying slope; only a persistent deviation from the line would falsify the current model.
🔹 Implications
The theory assigns scarcity no direct role; iterative feedback and the Difficulty Adjustment are sufficient to govern Bitcoin’s expansion. Long-term valuation should focus on position within the power-law channel, while bubbles—sharp departures above trend that later revert—are expected punctuations of an otherwise steady climb.
Beyond about 2040, disruptive technological shifts could alter the parameters, but for the next order of magnitude the present slope remains the simplest, most robust guide.
Bitcoin behaves less like a traditional asset and more like a self-organising digital organism whose value, security, and adoption co-evolve according to immutable power-law rules.
🔶 SETTINGS
🔹 General
Start Calculation: Determine the start date used by the calculation, with any prior prices being ignored. (default - 15 Jul 2010)
Use Linear Scale for X-Axis: Convert the horizontal axis from log(time) to linear calendar time
🔹 Linear Regression
Show Regression Line: Enable/disable the central power-law trend line
Regression Line Color: Choose the colour of the regression line
Mult 1: Toggle line & fill, set multiplier (default +1), pick line colour and area fill colour
Mult 2: Toggle line & fill, set multiplier (default +0.5), pick line colour and area fill colour
Mult 3: Toggle line & fill, set multiplier (default -0.5), pick line colour and area fill colour
Mult 4: Toggle line & fill, set multiplier (default -1), pick line colour and area fill colour
🔹 Style
Price Line Color: Select the colour of the BTC price plot
Auto Color: Automatically choose the best contrast colour for the price line
Price Line Width: Set the thickness of the price line (1 – 5 px)
Show Halvings: Enable/disable dotted vertical lines at each Bitcoin halving
Halvings Color: Choose the colour of the halving lines
Flux Capacitor (FC)# Flux Capacitor
**A volume-weighted, outlier-resistant momentum oscillator designed to expose hidden directional pressure from institutional participants.**
---
### Why "Flux Capacitor"?
The name pays homage to the fictional energy core in *Back to the Future* — an invisible engine that powers movement. Similarly, this indicator detects whether price movement is being powered by real market participation (volume) or if it's coasting without conviction.
---
### Methodology
The Flux Capacitor fuses three statistical layers:
- **Normalized Momentum**: `(Close – Open) / ATR`
Controls for raw price size and volatility.
- **Volume Scaling**:
Amplifies the effect of price moves that occur with elevated volume.
- **Robust Normalization**:
- *Winsorization* caps outlier spikes.
- *MAD-Z scoring* normalizes the signal across assets (crypto, futures, stocks).
- This produces consistent scaling across timeframes and symbols.
The result is a smooth oscillator that reliably indicates **liquidity-backed momentum** — not just price movement.
---
### Signal Events
- **Divergence (D)**: Price makes higher highs or lower lows, but Flux does not.
- **Absorption (A)**: Candle shows high volume and small body, while Flux opposes the candle direction — indicates smart money stepping in.
- **Compression (◆)**: High volume with low momentum — potential breakout zone.
- **Zero-Cross**: Indicates directional regime flip.
- **Flux Acceleration**: Histogram shows pressure rate of change.
- **Regime Background**: Color fades with weakening trend conviction.
All signals are color-coded and visually compact for easy pattern recognition.
---
### Interpreting Divergence & Absorption Correctly
Signal strength improves significantly when it appears **in the correct zone**:
#### Divergence:
| Signal | Zone | Meaning | Strength |
|--------|------------|------------------------------------------|--------------|
| Green D | Below 0 | Bullish reversal forming in weakness | **Strong** |
| Green D | Above 0 | Bullish, but less convincing | Moderate |
| Red D | Above 0 | Bearish reversal forming in strength | **Strong** |
| Red D | Below 0 | Bearish continuation — low warning value | Weak |
#### Absorption:
| Signal | Zone | Meaning | Strength |
|--------|------------|-----------------------------------------|--------------|
| Green A | Below 0 | Buyers absorbing panic-selling | **Strong** |
| Green A | Above 0 | Support continuation | Moderate |
| Red A | Above 0 | Sellers absorbing FOMO buying | **Strong** |
| Red A | Below 0 | Trend continuation — not actionable | Weak |
Look for **absorption or divergence signals in “enemy territory”** for the most actionable entries.
---
### Reducing Visual Footprint
If your chart shows a long line of numbers across the top of the Flux Capacitor pane (e.g. "FC 14 20 9 ... Bottom Right"), it’s due to TradingView’s *status line input display*.
**To fix this**:
Right-click the indicator pane → **Settings** → **Status Line** tab → uncheck “Show Indicator Arguments”.
This frees up vertical space so top-edge signals (like red `D` or yellow `◆`) remain visible and unobstructed.
---
### Features
- Original MAD-Z based momentum design
- True volume-based divergence and absorption logic
- Built-in alerts for all signal types
- Works across timeframes (1-min to weekly)
- Minimalist, responsive layout
- 25+ customizable parameters
- No future leaks, no repainting
---
### Usage Scenarios
- **Trend confirmation**: Flux > 0 confirms bullish trend strength
- **Reversal detection**: Divergence or absorption in opposite territory = high-probability reversal
- **Breakout anticipation**: Compression signal inside range often precedes directional move
- **Momentum shifts**: Watch for zero-crosses + flux acceleration spikes
---
### ⚠ Visual Note for BTC, ETH, Crude Oil & Futures
These high-priced or rapidly accelerating instruments can visually compress any linear oscillator. You may notice the Flux Capacitor’s line appears "flat" or muted on these assets — especially over long lookbacks.
> **This does not affect signal validity.** Divergence, absorption, and compression triggers still fire based on underlying logic — only the line’s amplitude appears reduced due to scaling constraints.
---
### Disclaimer
This indicator is for educational purposes only. It is not trading advice. Past results do not guarantee future performance. Use in combination with your own risk management and analysis.
RSI Divergence StrategyOverview
The RSI Divergence Strategy Indicator is a trading tool that uses the RSI and divergences created to generate high-probability buy and sell signals.
I have provided the best formula of numbers to use for BTC on a 30 minute timeframe.
You can change where on RSI you enter and exit both long or short trades. This way you can experiment on different tokens using different entry/exit points. Can use on multiple timeframes.
This strategy is designed to open and close long or short trades based on the levels you provide it. You can then check on the RSI where the best levels are for each token you want to trade and amend it as required to generate a profitable strategy.
How It Works
The RSI Divergence Strategy Indicator uses bear and bull divergences in conjuction with a level you have input on the RSI.
RSI for Overbought/Oversold:
• Input variables for entry and exit levels and when the entry levels combine with a bear or bull divergence signal, a trade is alerted.
RSI Divergence:
• Buy and sell signals are confirmed when the RSI creates bearish or bullish divergences and these divergences are in the same area as your levels you input for entry to short or long.
After 7 years of experience and testing I have calculated the exact numbers required and produced a formula to calculate the exact input variables for a 30 minute Bitcoin chart.
Key Features
1️⃣ Divergence Identification – Ensures trades are taken only when a bull or bear divergence has formed.
2️⃣ Overbought/Oversold Input Filtering – Set up your own variables on the RSI for different markets after identifying patterns on the RSI in relation to a bearish or bullish divergence.
3️⃣ Works on any chart – Suitable for all markets and timeframes once you input the correct variables for entry and exit levels.
How to Use
🟢 Basic Trading:
• Use on any timeframe.
• Enter trade only when alert has fired off. Close when it says to exit.
• Change entry and exit levels in the properties of the strategy indicator.
• Make entry and exit levels coincide with bearish or bullish divergences on the RSI.
Check the strategy tester to see backtesting so you know if the indicator is profitable or not for that market and timeframe as each crypto token is different and so is the timeframe you choose.
📢 Webhook Automation:
• Set up TradingView Alerts to auto-execute trades via Webhook-compatible platforms.
Key additions for divergence visualization:
Divergence Arrows:
Bullish divergence: Green label with white 'bull ' text
Bearish divergence: Red label with white 'bear' text
Positioned at the pivot point
Divergence Lines:
Connects consecutive RSI pivot points
Automatically drawn between consecutive pivot points
Enhanced RSI Coloring:
Overbought zone: Red
Oversold zone: Green
Neutral zone: Gray
The visualization helps you instantly spot:
Where divergences are forming on the RSI
The pattern of higher lows (bullish) or lower highs (bearish)
Contextual coloring of RSI relative to standard levels
All divergence markers appear at the correct historical pivot points, making it easy to visually confirm divergence patterns as they develop.
Strategy levels and background zones also shown to help visual look.
Why This Combination?
This indicator is just a simple RSI tool.
It is designed to filter out weak trades and only execute trades that have:
✅ RSI Divergence
✅ Overbought or Oversold Conditions
It does not calculate downtrends or bear markets so care is recommended taking long trades during these times.
Why It’s Worth Using?
📈 Open Source – Free to use and learn from.
📉 Long or Short Term Trading Style – Entry/Exit parameters options are designed for both short or long term trades allowing you to experiment until you find a profitable strategy for that market you want to trade.
📢 Seamless Webhook Automation – Execute trades automatically with TradingView alerts.
💲 Ready to trade smarter?
✅ Add the RSI Divergence Strategy Indicator to your TradingView chart.
Multi Asset Comparative📊 Multi Asset Comparative – Compare Baskets of Cryptos Visually
This indicator allows you to compare the performance of two groups of cryptocurrencies (or any assets) over time, using a clean and intuitive chart.
Instead of looking at each asset separately, this tool gives you a global view by showing how one group performs relative to another — all displayed in the form of candlesticks.
🧠 What This Tool Is For
Markets constantly shift, and capital rotates between sectors or tokens. This script helps you visually track those shifts by answering a key question:
"Is this group of assets getting stronger or weaker compared to another group?"
For example:
Compare altcoins vs Bitcoin
Track the DeFi sector vs Ethereum
Analyze your custom portfolio vs the market
Spot moments when money flows from majors to smaller caps, or vice versa
🧩 How It Works (Simplified)
You select two groups of assets:
Group 1 (up to 20 assets) — the one you want to analyze
Group 2 (up to 5 assets) — your comparison baseline
The indicator then creates a single line of candles that represents the performance of Group 1 compared to Group 2. If the candles go up, it means Group 1 is gaining strength over Group 2. If the candles go down, it's losing ground.
This lets you see market dynamics in one glance, instead of switching charts or running calculations manually.
🚀 Why It's Unique
Unlike many indicators that just show data from one asset, this one provides a bird's-eye view of multiple assets at once — condensed into a simple visual ratio.
It’s:
Customizable (you choose the assets)
Visual and intuitive (no need to interpret tables or formulas)
Actionable (helps with trend confirmation, macro views, and market rotation)
Whether you're a swing trader, a macro analyst, or building your own strategy, this tool can help you spot opportunities hidden in plain sight.
✅ How to Use It
Choose your two groups of assets (e.g., altcoins vs BTC/ETH)
Watch the direction of the candles:
Uptrend = Group 1 gaining strength over Group 2
Downtrend = Group 1 weakening
Use it to confirm market shifts, anticipate rotations, or analyze sector strength
Open Interest-RSI + Funding + Fractal DivergencesIndicator — “Open Interest-RSI + Funding + Fractal Divergences”
A multi-factor oscillator that fuses Open-Interest RSI, real-time Funding-Rate data and price/OI fractal divergences.
It paints BUY/SELL arrows in its own pane and directly on the price chart, helping you spot spots where crowd positioning, leverage costs and price action contradict each other.
1 Purpose
OI-RSI – measures conviction behind position changes instead of price momentum.
Funding Rate – shows who pays to hold positions (longs → bull bias, shorts → bear bias).
Fractal Divergences – detects HH/LL in price that are not confirmed by OI-RSI.
Optional Funding filter – hides signals when funding is already extreme.
Together these elements highlight exhaustion points and potential mean-reversion trades.
2 Inputs
RSI / Divergence
RSI length – default 14.
High-OI level / Low-OI level – default 70 / 30.
Fractal period n – default 2 (swing width).
Fractals to compare – how many past swings to scan, default 3.
Max visible arrows – keeps last 50 BUY/SELL arrows for speed.
Funding Rate
mode – choose FR, Avg Premium, Premium Index, Avg Prem + PI or FR-candle.
Visual scale (×) – multiplies raw funding to fit 0-100 oscillator scale (default 10).
specify symbol – enable only if funding symbol differs from chart.
use lower tf – averages 1-min premiums for smoother intraday view.
show table – tiny two-row widget at chart edge.
Signal Filter
Use Funding filter – ON hides long signals when funding > Buy-threshold and short signals when funding < Sell-threshold.
BUY threshold (%) – default 0.00 (raw %).
SELL threshold (%) – default 0.00 (raw %).
(Enter funding thresholds as raw percentages, e.g. 0.01 = +0.01 %).
3 Visual Outputs
Sub-pane
Aqua OI-RSI curve with 70 / 50 / 30 reference lines.
Funding visualised according to selected mode (green above 0, red below 0, or other).
BUY / SELL arrows at oscillator extremes.
Price chart
Identical BUY / SELL arrows plotted with force_overlay = true above/below candles that formed qualifying fractals.
Optional table
Shows current asset ticker and latest funding value of the chosen mode.
4 Signal Logic (Summary)
Load _OI series and compute RSI.
Retrieve Funding-Rate + Premium Index (optionally from lower TF).
Find fractal swings (n bars left & right).
Check divergence:
Bearish – price HH + OI-RSI LH.
Bullish – price LL + OI-RSI HL.
If Funding-filter enabled, require funding < Buy-thr (long) or > Sell-thr (short).
Plot arrows and trigger two built-in alerts (Bearish OI-RSI divergence, Bullish OI-RSI divergence).
Signals are fixed once the fractal bar closes; they do not repaint afterwards.
5 How to Use
Attach to a liquid perpetual-futures chart (BTC, ETH, major Binance contracts).
If _OI or funding series is missing you’ll see an error.
Choose timeframe:
15 m – 4 h for intraday;
1 D+ for swing trades.
Lower TFs → more signals; raise Fractals to compare or use Funding filter to trim noise.
Trade checklist
Funding positive and rising → longs overcrowded.
Price makes higher high; OI-RSI makes lower high; Funding above Sell-threshold → consider short.
Reverse logic for longs.
Combine with trend filter (EMA ribbon, SuperTrend, etc.) so you fade only when price is stretched.
Automation – set TradingView alerts on the two alertconditions and send to webhooks/bots.
Performance tips
Keep Max visible arrows ≤ 50.
Disable lower-TF premium aggregation if script feels heavy.
6 Limitations
Some symbols lack _OI or funding history → script stops with a console message.
Binance Premium Index begins mid-2020; older dates show na.
Divergences confirm only after n bars (no forward repaint).
7 Changelog
v1.0 – 10 Jun 2025
Initial public release.
Added price-chart arrows via force_overlay.
MA Cross MTF Alert (Miu)This script extends the classic moving average crossover strategy with support for up to 8 user-defined symbols across 4 custom timeframes, combined with a visual and alert system designed for traders who monitor multiple assets simultaneously.
Unlike traditional MA crossover tools, this script enables traders to receive real-time alerts for crossovers across multiple assets and timeframes, even when the script is not actively displayed on the chart — ideal for passive monitoring in multi-asset strategies.
What it does:
This script calculates two customizable moving averages (SMA or EMA) for each selected symbol and timeframe.
It then tracks crossover events:
- Bullish crossover when the fast MA crosses above the slow MA
- Bearish crossunder when the fast MA crosses below the slow MA
On the chart, it also displays the crossover signals for the current symbol and timeframe using color-coded cross icons.
Key features:
- Select SMA or EMA type for both moving averages
- Customize MA lengths and colors
- Works with any asset and timeframe
- Alerts include symbol and timeframe info for easy identification
How to use:
1) Add the indicator to your chart.
2) Choose the moving average type and lengths.
3) Enable/disable any of the 8 symbols and 4 timeframes.
4) Set up TradingView alerts by clicking “Create Alert” and selecting one of the alert() calls.
5) You will receive a message like:
BTC (1h) | MA Crossover ▲ or ETH (15m) | MA Crossunder ▼
Technical note:
This script uses request.security() to retrieve moving average values from up to 8 different symbols and 4 different timeframes in real time.
Feel free to leave your feedback or suggestions in the comments section below.
Enjoy!
Volume Spike Alert & Overlay"Volume Spike Alert & Overlay" highlights unusually high trading volume on a chart. It calculates whether the current volume exceeds a user-defined percentage above the historical average and triggers an alert if it does. The information is also displayed in a customizable on-screen table.
What It Does
Monitors volume for each bar and compares it to an average over a user-defined lookback period.
Supports multiple smoothing methods (SMA, EMA, WMA, RMA) for calculating the average volume.
Triggers an alert when current volume exceeds the threshold percentage above the average.
Displays a table on the chart with:
Current Volume
Average Volume
Threshold Percentage
Optional empty row for spacing/formatting
How It Works
User Inputs:
lookbackPeriods: Number of bars used to calculate the average volume.
thresholdPercent: % above the average that triggers a volume spike alert.
smoothingType: Type of moving average used for volume calculation.
textColor, bgColor: Formatting for the display table.
tablePositionInput: Where the table appears on the chart (e.g., Bottom Right).
Toggles for showing/hiding parts of the table.
Volume Calculations:
Calculates current bar's volume.
Calculates average volume using the selected smoothing method.
Computes the threshold: avgVol * (1 + thresholdPercent / 100).
Compares current volume to threshold.
Table Display:
Dynamically creates a table with volume stats.
Adds rows based on user preferences.
Alerts:
alertcondition fires when currentVol crosses above the calculated threshold.
Message: "Volume Threshold Exceeded"
Usage Examples
Example 1: Spotting High Activity
Apply the script to a stock like AAPL on a 5-minute chart.
Set lookbackPeriods to 20 and thresholdPercent to 30.
Use EMA for more reactive volume tracking.
When volume spikes more than 30% above the 20-period EMA, an alert triggers.
Example 2: Day Trading Filter
For scalpers, apply it to a 1-minute crypto chart (e.g., BTC/USDT).
Set thresholdPercent to 50 to catch only strong surges.
Position the table at the top left and reduce visible info for a clean layout.
Example 3: Long-Term Context
On a daily chart, use SMA and set lookbackPeriods to 50.
Helps identify breakout moves supported by strong volume.
How this is different from Trading View's Volume indicator:
The standard volume plot from trading view allows users to set a alert when the average line is crossed, but it does not allow you to set a custom percentage at which to trigger an alert. This indicator will allow you to set any percentage you wish to monitor and above that percentage threshold will trigger your alert.
===== ORIGINAL DESCRIPTION =====
Volume Spike Alert & Overlay
This indicator will display the following as an overlay on your chart:
Current volume
Average Volume
Threshold for Alert
Description:
This indicator will display the current bar volume based on the chart time frame,
display the average volume based on selected conditions,
allow user selectable threshold over the average volume to trigger an alert.
Options:
Average lookback period
Smoothing type
Alert Threshold %
Enable / Disable Each Value
Change Text Color
Change Background Color
Change Table location
Add/Remove extra row for placement in top corner
Usage Example:
I use this indicator to alert when the current volume exceeds the average volume by a specified percentage to alert to volume spikes.
Set the threshold to 25% in the settings
Create an alert by clicking on the 3 dots on the right of the indicator title on the chart
When the threshold is exceeded the alert will trigger
