MVRV | Lyro RS📊 MVRV | Lyro RS is a powerful on-chain valuation tool designed to assess the relative market positioning of Bitcoin (BTC) or Ethereum (ETH) based on the Market Value to Realized Value (MVRV) ratio. It highlights potential undervaluation or overvaluation zones, helping traders and investors anticipate cyclical tops and bottoms.
✨ Key Features :
🔁 Dual Asset Support: Analyze either BTC or ETH with a single toggle.
📐 Dynamic MVRV Thresholds: Automatically calculates median-based bands at 50%, 64%, 125%, and 170%.
📊 Median Calculation: Period-based median MVRV for long-term trend context.
💡 Optional Smoothing: Use SMA to smooth MVRV for cleaner analysis.
🎯 Visual Threshold Alerts: Background and bar colors change based on MVRV position relative to thresholds.
⚠️ Built-in Alerts: Get notified when MVRV enters under- or overvalued territory.
📈 How It Works :
💰 MVRV Calculation: Uses data from IntoTheBlock and CoinMetrics to obtain real-time MVRV values.
🧠 Threshold Bands: Median MVRV is used as a baseline. Ratios like 50%, 64%, 125%, and 170% signal various levels of market extremes.
🎨 Visual Zones: Green zones for undervaluation and red zones for overvaluation, providing intuitive visual cues.
🛠️ Custom Highlights: Toggle individual threshold zones on/off for a cleaner view.
⚙️ Customization Options :
🔄 Switch between BTC or ETH for analysis.
📏 Adjust period length for median MVRV calculation.
🔧 Enable/disable threshold visibility (50%, 64%, 125%, 170%).
📉 Toggle smoothing to reduce noise in volatile markets.
📌 Use Cases :
🟢 Identify undervalued zones for long-term entry opportunities.
🔴 Spot potential overvaluation zones that may precede corrections.
🧭 Use in confluence with price action or macro indicators for better timing.
⚠️ Disclaimer :
This indicator is for educational purposes only. It should not be used in isolation for making trading or investment decisions. Always combine with price action, fundamentals, and proper risk management.
Penunjuk dan strategi
Ehlers Ultimate Bands (UBANDS)UBANDS: ULTIMATE BANDS
🔍 OVERVIEW AND PURPOSE
Ultimate Bands, developed by John F. Ehlers, are a volatility-based channel indicator designed to provide a responsive and smooth representation of price boundaries with significantly reduced lag compared to traditional Bollinger Bands. Bollinger Bands typically use a Simple Moving Average for the centerline and standard deviations from it to establish the bands, both of which can increase lag. Ultimate Bands address this by employing Ehlers' Ultrasmooth Filter for the central moving average. The bands are then plotted based on the volatility of price around this ultrasmooth centerline.
The primary purpose of Ultimate Bands is to offer traders a clearer view of potential support and resistance levels that react quickly to price changes while filtering out excessive noise, aiming for nearly zero lag in the indicator band.
🧩 CORE CONCEPTS
Ultrasmooth Centerline: Employs the Ehlers Ultrasmooth Filter as the basis (centerline) for the bands, aiming for minimal lag and enhanced smoothing.
Volatility-Adaptive Width: The distance between the upper and lower bands is determined by a measure of price deviation from the ultrasmooth centerline. This causes the bands to widen during volatile periods and contract during calm periods.
Dynamic Support/Resistance: The bands serve as dynamic levels of potential support (lower band) and resistance (upper band).
🧮 CALCULATION AND MATHEMATICAL FOUNDATION
Ehlers' Original Concept for Deviation:
John Ehlers describes the deviation calculation as: "The deviation at each data sample is the difference between Smooth and the Close at that data point. The Standard Deviation (SD) is computed as the square root of the average of the squares of the individual deviations."
This describes calculating the Root Mean Square (RMS) of the residuals:
Smooth = UltrasmoothFilter(Source, Length)
Residuals = Source - Smooth
SumOfSquaredResiduals = Sum(Residuals ^2) for i over Length
MeanOfSquaredResiduals = SumOfSquaredResiduals / Length
SD_Ehlers = SquareRoot(MeanOfSquaredResiduals) (This is the RMS of residuals)
Pine Script Implementation's Deviation:
The provided Pine Script implementation calculates the statistical standard deviation of the residuals:
Smooth = UltrasmoothFilter(Source, Length) (referred to as _ehusf in the script)
Residuals = Source - Smooth
Mean_Residuals = Average(Residuals, Length)
Variance_Residuals = Average((Residuals - Mean_Residuals)^2, Length)
SD_Pine = SquareRoot(Variance_Residuals) (This is the statistical standard deviation of residuals)
Band Calculation (Common to both approaches, using their respective SD):
UpperBand = Smooth + (NumSDs × SD)
LowerBand = Smooth - (NumSDs × SD)
🔍 Technical Note: The Pine Script implementation uses a statistical standard deviation of the residuals (differences between price and the smooth average). Ehlers' original text implies an RMS of these residuals. While both measure dispersion, they will yield slightly different values. The Ultrasmooth Filter itself is a key component, designed for responsiveness.
📈 INTERPRETATION DETAILS
Reduced Lag: The primary advantage is the significant reduction in lag compared to standard Bollinger Bands, allowing for quicker reaction to price changes.
Volatility Indication: Widening bands indicate increasing market volatility, while narrowing bands suggest decreasing volatility.
Overbought/Oversold Conditions (Use with caution):
• Price touching or exceeding the Upper Band may suggest overbought conditions.
• Price touching or falling below the Lower Band may suggest oversold conditions.
Trend Identification:
• Price consistently "walking the band" (moving along the upper or lower band) can indicate a strong trend.
• The Middle Band (Ultrasmooth Filter) acts as a dynamic support/resistance level and indicates the short-term trend direction.
Comparison to Ultimate Channel: Ehlers notes that the Ultimate Band indicator does not differ from the Ultimate Channel indicator in any major fashion.
🛠️ USE AND APPLICATION
Ultimate Bands can be used similarly to how Keltner Channels or Bollinger Bands are used for interpreting price action, with the main difference being the reduced lag.
Example Trading Strategy (from John F. Ehlers):
Hold a position in the direction of the Ultimate Smoother (the centerline).
Exit that position when the price "pops" outside the channel or band in the opposite direction of the trade.
This is described as a trend-following strategy with an automatic following stop.
⚠️ LIMITATIONS AND CONSIDERATIONS
Lag (Minimized but Present): While significantly reduced, some minimal lag inherent to averaging processes will still exist. Increasing the Length parameter for smoother bands will moderately increase this lag.
Parameter Sensitivity: The Length and StdDev Multiplier settings are key to tuning the indicator for different assets and timeframes.
False Signals: As with any band indicator, false signals can occur, particularly in choppy or non-trending markets.
Not a Standalone System: Best used in conjunction with other forms of analysis for confirmation.
Deviation Calculation Nuance: Be aware of the difference in deviation calculation (statistical standard deviation vs. RMS of residuals) if comparing directly to Ehlers' original concept as described.
📚 REFERENCES
Ehlers, J. F. (2024). Article/Publication where "Code Listing 2" for Ultimate Bands is featured. (Specific source to be identified if known, e.g., "Stocks & Commodities Magazine, Vol. XX, No. YY").
Ehlers, J. F. (General). Various publications on advanced filtering and cycle analysis. (e.g., "Rocket Science for Traders", "Cycle Analytics for Traders").
Supertrade's RVI Long-Only Strategy with SL/TP (RR 1:3)This strategy, titled "Supertrade’s RVI Long-Only Strategy with SL/TP (RR 1:3)", is designed to capitalize on potential bullish reversals using the Relative Vigor Index (RVI) as its core signal generator. It is best optimized for trading XAUUSD on the 15-minute timeframe , where it has demonstrated favorable historical performance.
The RVI is calculated using a 10-period standard deviation of the closing price, with smoothing applied through a 14-period exponential moving average. This approach helps to distinguish between uptrend and downtrend volatility, allowing the strategy to identify momentum shifts with precision. A long position is triggered when the RVI crosses above the 20 level, suggesting a potential transition from a weak to a stronger bullish phase.
Risk management is embedded through a user-defined stop-loss (default set at 1% below the entry price) and a fixed reward-to-risk ratio of 1:3. This means that for every 1% of capital risked, the strategy targets a 3% gain, maintaining favorable risk-reward dynamics throughout its execution. Once a position is entered, it will exit automatically at either the stop-loss or take-profit level, depending on which is reached first.
This strategy is meant for educational and research purposes only. While it has performed well historically on specific assets and timeframes, past performance is not indicative of future results . Market conditions can change, and no strategy guarantees success in all environments. Please exercise proper risk management and test thoroughly before applying in live markets.
Anchored Probability Cone by TenozenFirst of all, credit to @nasu_is_gaji for the open source code of Log-Normal Price Forecast! He teaches me alot on how to use polylines and inverse normal distribution from his indicator, so check it out!
What is this indicator all about?
This indicator draws a probability cone that visualizes possible future price ranges with varying levels of statistical confidence using Inverse Normal Distribution , anchored to the start of a selected timeframe (4h, W, M, etc.)
Feutures:
Anchored Cone: Forecasts begin at the first bar of each chosen higher timeframe, offering a consistent point for analysis.
Drift & Volatility-Based Forecast: Uses log returns to estimate market volatility (smoothed using VWMA) and incorporates a trend angle that users can set manually.
Probabilistic Price Bands: Displays price ranges with 5 customizable confidence levels (e.g., 30%, 68%, 87%, 99%, 99,9%).
Dynamic Updating: Recalculates and redraws the cone at the start of each new anchor period.
How to use:
Choose the Anchored Timeframe (PineScript only be able to forecast 500 bars in the future, so if it doesn't plot, try adjusting to a lower anchored period).
You can set the Model Length, 100 sample is the default. The higher the sample size, the higher the bias towards the overall volatility. So better set the sample size in a balanced manner.
If the market is inside the 30% conifidence zone (gray color), most likely the market is sideways. If it's outside the 30% confidence zone, that means it would tend to trend and reach the other probability levels.
Always follow the trend, don't ever try to trade mean reversions if you don't know what you're doing, as mean reversion trades are riskier.
That's all guys! I hope this indicator helps! If there's any suggestions, I'm open for it! Thanks and goodluck on your trading journey!
Bitcoin Power Law OscillatorThis is the oscillator version of the script. The main body of the script can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B(Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Bitcoin Power LawThis is the main body version of the script. The Oscillator version can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
IU Three Line Strike Candlestick PatternIU Three Line Strike Candlestick Pattern
This indicator identifies the Three Line Strike candlestick pattern — a rare yet powerful 4-bar reversal setup that captures exhaustion and momentum shifts at the end of strong trends.
Pattern Logic:
The Three Line Strike is a 4-candle pattern that typically signals a sharp reversal after a sustained directional move. This script detects both bullish and bearish variations using strict criteria to ensure accuracy.
Bullish Three Line Strike:
* Previous three candles must be bearish (red)
* Each of these candles must close progressively lower (indicating a strong downtrend)
* The current candle must:
* Be bullish (green)
* Open below the prior close
* Completely engulf the previous three candles by closing above the first candle's open
* And make a higher high than the last 3 bars — confirming a strong reversal
* Once confirmed, a green shaded box is drawn around the 4-bar zone to highlight the pattern
Bearish Three Line Strike:
* Previous three candles must be bullish (green)
* Each must close progressively higher (indicating a strong uptrend)
* The current candle must:
* Be bearish (red)
* Open above the prior close
* Completely engulf the prior three candles by closing below the first candle's open
* And make a lower low than the last 3 bars — confirming downside strength
* A red shaded box is plotted around the 4-bar formation to emphasize the reversal zone
Why this is unique:
Most candlestick tools focus on 1–2 bar patterns. The Three Line Strike goes a step further by combining trend exhaustion (3 same-colored candles) with a full reversal engulfing candle. This pattern is both rare and highly expressive of sentiment shift, making it a standout signal for discretionary and algorithmic traders alike.
How users can benefit:
* High-probability setups: Filters out weak signals using multi-bar confirmation logic
* Clear visual cues: Dynamic shaded boxes and labels make spotting reversals effortless
* Cross-timeframe compatible: Works on intraday and higher timeframes across all markets
* Real-time alerts: Get notified instantly when a bullish or bearish setup forms
This indicator is a valuable addition for traders who want to capture key reversals backed by strong multi-bar price action logic. Whether you are a price action purist or a pattern-based strategist, the IU Three Line Strike gives you a reliable edge.
Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results. Always do your own research and consult with a licensed financial advisor before making trading decisions.
VWAP + Engulfing CandlesHere’s a clear breakdown of what your merged Pine Script does:
---
### 📌 **Indicator Name: VWAP + Engulfing Candles**
* This custom TradingView indicator **plots VWAP (Volume Weighted Average Price)** along with **up to 3 dynamic bands** around it.
* It also **detects Bullish and Bearish Engulfing Candlestick Patterns**, displaying visual markers and triggering alerts.
---
## 🔹 **1. VWAP Section**
### ➤ **Main Features:**
* Calculates VWAP anchored to a **customizable time period**:
* Options: Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits.
* Optional **hiding of VWAP on Daily/Weekly/Monthly charts** to reduce clutter.
### ➤ **Bands Around VWAP:**
* Up to **3 bands** can be plotted above and below the VWAP.
* Bands can be based on either:
* **Standard Deviation** of the price from VWAP (volatility-based), or
* **Percentage** deviation from VWAP (fixed range).
* You can control:
* Whether each band is shown
* Band width via multiplier (e.g., 1x, 2x, 3x)
### ➤ **Plot Colors:**
* VWAP: Blue
* Bands: Green (1x), Olive (2x), Teal (3x)
* Band fill areas are semi-transparent.
---
## 🔹 **2. Engulfing Candlestick Pattern Detector**
### ➤ **Bullish Engulfing Criteria:**
* Current candle opens **below** or **equal to** the close of the previous candle.
* Current candle opens **below** the previous candle's open.
* Current candle closes **above** the previous candle’s open.
### ➤ **Bearish Engulfing Criteria:**
* Current candle opens **above** or **equal to** the close of the previous candle.
* Current candle opens **above** the previous candle’s open.
* Current candle closes **below** the previous candle’s open.
### ➤ **Visual Signals:**
* 🔼 Green triangle **below bar** for **Bullish Engulfing**
* 🔽 Red triangle **above bar** for **Bearish Engulfing**
### ➤ **Alerts:**
* The script includes two alert conditions:
* One for Bullish Engulfing
* One for Bearish Engulfing
These alerts can be used to automate notifications for potential reversal points.
---
## 🛠️ **Use Cases**
* **Trend following or reversal spotting**: VWAP helps identify the average trading price; engulfing patterns often signal reversals.
* **Intraday and swing trading**: Works best on timeframes like 5m, 15m, 1h for intraday, or 4h, 1D for swing.
* **Mean reversion strategies**: Bands help spot overbought/oversold areas relative to VWAP.
JDXBT Monthly VWAPIt calculates the average price for each month, weighted by trading volume, and automatically resets the calculation at the start of each new month. The VWAP line changes colour based on direction: black if rising, fuchsia if falling — helping traders quickly identify monthly price trends with volume context. It’s a useful tool for spotting key levels and momentum shifts on a monthly basis.
WaveTrend [LazyBear] with Long/Short LabelsWaveTrend Oscillator with Entry Signals (LONG/SHORT) – Advanced Edition
This indicator is based on the renowned WaveTrend Oscillator by LazyBear, a favorite among professional traders for spotting trend reversals with precision.
🚀 Features:
Original WaveTrend formula with dual-line structure (WT1 & WT2).
Customizable overbought and oversold zones for visual clarity.
Automatic LONG and SHORT signals plotted directly on the chart:
✅ LONG: When WT1 crosses above WT2 below the oversold zone.
❌ SHORT: When WT1 crosses below WT2 above the overbought zone.
Momentum histogram shows strength of market moves.
Fully optimized for Pine Script v5 and lightweight across all timeframes.
🔍 How to use:
Combine with support/resistance levels or candlestick reversal patterns.
Works best on 15min, 1H, or 4H charts.
Suitable for all markets: crypto, stocks, forex, indices.
📊 Ideal for:
Traders seeking clean, reliable entry signals.
Reversal strategies with technical confluence.
Visual confirmation of WaveTrend crossovers without manual interpretation.
💡 Pro Tip: Combine with EMA or RSI filters to further enhance accuracy.
Enhanced Volume w/ Pocket Pivots, Milestones & LiquiditySure! Here’s a professional and clear **description** you can use when saving or publishing the script on TradingView:
---
## 📄 Script Description: *Enhanced Volume w/ Pocket Pivots, Milestones & Liquidity*
This custom volume indicator enhances the default volume view by combining key institutional-level insights into a single tool. It highlights meaningful volume activity, liquidity conditions, and milestone events to help traders better understand accumulation/distribution and smart money participation.
### 🔍 Features:
* **Color-coded volume bars**:
* 🔵 **Pocket Pivot Volume (PPV)**: Up-day with volume > highest down-day volume of last 10 bars.
* 🟢 **Up Volume**: Up-day with volume > 50-day average.
* 🔴 **Down Volume**: Down-day with volume > 50-day average.
* 🟠 **Dry Volume**: Low-volume bars < 20% of 50-day average.
* ⚫ **Neutral/Other bars**: No significant signal.
* **Volume Milestones**:
* **HVE**: Highest volume ever (20 years lookback).
* **HVY**: Highest volume in the past 1 year (252 bars).
* **HVQ**: Highest volume in the past quarter (63 bars).
* **Projected Volume**:
* Real-time estimate of end-of-day volume based on elapsed session time.
* **Liquidity Metrics**:
* Displays current and 50-day average dollar volume.
* Estimates 1-minute liquidity for large-position feasibility.
* **Relative Volume Label**:
* Displays how today’s volume compares to the 50-day average.
* **Alerts Included**:
* Set alerts for HVE, HVY, and HVQ to catch key breakout or climactic volume events.
---
### 🧠 Ideal For:
* Growth stock traders
* Volume/price analysts
* Intraday & swing traders
* Institutions or prop traders needing liquidity benchmarks
---
Let me know if you'd like a short or promotional version (for sharing with others).
NIFTY Option Chain Table with Custom CE/PE Price FiltersThis Pine Script creates a powerful and visually organized option chain dashboard for NIFTY Index Options, showing 10 Call Options (CE) and 10 Put Options (PE), with real-time prices updated on a 5-minute chart.
You can filter and view only the most relevant option contracts based on your preferred price ranges, helping you make quick decisions for scalping, intraday, or positional trades.
🔍 How It Works:
You manually select up to 10 Call Option symbols and 10 Put Option symbols from NSE (e.g., NIFTY240530C18000, NIFTY240530P18000, etc.).
Keep that time options this are old options in defalt so there will be a error
The script fetches the real-time close price of each option using the request.security() function.
You define the minimum and maximum price range separately for Calls and Puts.
The script filters out any options that fall outside of your desired price range.
Only a limited number of matching options (as set by you) are displayed in the table for both Calls and Puts.
The table is shown at your preferred location on the chart (Bottom Right, Top Left, etc.).
✅ Features:
🔟 Supports exactly 10 CE and 10 PE options for tracking.
📈 Live price updates pulled directly from the chart timeframe (5-min).
🎯 Custom price filters for CE and PE (separate inputs).
📊 Show only the top X number of contracts that meet your filter criteria.
🧱 Vertical layout with clear headers and color-coded sections (green for Calls, red for Puts).
🎛️ Position the table wherever it's most convenient on your chart.
⚡ Helps you quickly spot low premium or range-bound options during the day.
📌 Use Case:
Ideal for:
Option scalpers and day traders who want to focus only on options within a specific price zone.
Traders who want to monitor multiple strikes simultaneously without clutter.
Users building custom NIFTY strategies based on option premiums.
Strike Price selection by GoldenJetThis script is designed to assist options traders in selecting appropriate strike prices based on the latest prices of two financial instruments. It retrieves the latest prices, rounds them to the nearest significant value, and calculates potential strike prices for both call and put options. The results are displayed in a customizable table, allowing traders to quickly see the relevant strike prices for their trading decisions.
The strike prices shown are In-The-Money (ITM), which helps options traders in several ways:
Saving from Theta Decay: On expiry day, ITM options experience less time decay (Theta), which can help preserve the option's value.
Capturing Good Points: ITM options have a higher Delta, meaning they move more in line with the underlying asset's price. This can help traders capture a good amount of points as the underlying asset's price changes.
In essence, this tool simplifies the process of determining strike prices, making it easier for traders to make informed decisions and potentially improve their trading outcomes.
DXY Z-ScoreThe "DXY Z-Score" indicator measures the US Dollar Index’s (DXY) current price relative to its recent average, normalized by its standard deviation.
It calculates a standardized Z-Score that oscillates around zero, highlighting when the DXY is significantly overbought or oversold.
Key features include:
- The Z-Score line oscillating between fixed upper (+2) and lower (-2) horizontal levels
- A shaded background to emphasize the Z-Score range between these bands
- A dynamic table showing the current Z-Score value linked linearly to the Z-Score plot
This indicator is useful for assessing the strength or weakness of the US Dollar relative to its recent history, providing insights into potential market reversals or trend continuations.
ADX Z-Score OscillatorTitle: ADX Z-Score Oscillator
Description:
The ADX Z-Score Oscillator is a normalized version of the traditional Average Directional Index (ADX), designed to oscillate between fixed bounds for easier interpretation of trend strength. Instead of plotting the raw ADX line, this indicator calculates the Z-Score of the ADX relative to its recent average and standard deviation, allowing for consistent comparison over time and across different assets.
The Z-Score oscillates between fixed horizontal levels of +2 and -2, highlighting extreme values.
The orange line represents the current Z-Score of the ADX.
Horizontal reference lines at +2 (red), 0 (gray), and -2 (green) help define overbought/oversold or strong/weak trend zones.
A dynamic table on the chart shows the current Z-Score with color coding to indicate trend strength:
🔴 Z > 1.5 → Very strong trend
🟠 Z > 0.5 → Moderate trend
🔵 Z < -0.5 → Weakening or reversing trend
🟢 Z < -1.5 → Very weak trend or potential reversal zone
This transformation of the ADX into a bounded oscillator helps traders easily assess trend strength and changes in momentum without the ambiguity of varying ADX scale levels.
Bollinger Bands Z-ScoreBollinger Bands Z-Score Indicator
This indicator transforms the classic Bollinger Bands into a Z-Score oscillator displayed in a separate pane. It standardizes the Bollinger Bands’ basis line by calculating the Z-Score over a user-defined period, allowing you to see how many standard deviations the price deviates from the mean.
Upper and Lower Fixed Lines: These are set at +2 and -2 Z-Score levels, representing common thresholds for overbought and oversold conditions.
Z-Score Oscillator: The normalized Bollinger Bands oscillate smoothly between these fixed boundaries, providing a clearer perspective on volatility extremes.
Z-Score Table: Displayed on the right side, this table shows the current Z-Score value, along with fixed maximum (+2) and minimum (-2) limits, making it easy to track current momentum and volatility in real-time.
Use Cases:
Identify overextended price moves with standardized volatility measures.
Spot potential reversals or continuation setups by observing the Z-Score crossing key levels.
Complement traditional Bollinger Bands analysis with a statistically normalized perspective.
Input Parameters:
Length: The period used for Bollinger Bands and Z-Score calculation.
MA Type: Choose the moving average type for the basis line (SMA, EMA, SMMA, WMA, VWMA).
StdDev: Multiplier for the standard deviation bands.
Z-Score Length: The lookback period used to compute the mean and standard deviation for Z-Score normalization.
This indicator is perfect for traders seeking a statistically sound and visually clear representation of Bollinger Bands volatility and extremes.
Dynamic Volume Clusters with Retest Signals (Zeiierman)█ Overview
The Dynamic Volume Clusters with Retest Signals indicator is designed to detect key Volume Clusters and provide Retest Signals. This tool is specifically engineered for traders looking to capitalize on volume-based trends, reversals, and key price retest points.
The indicator seamlessly combines volume analysis, dynamic cluster calculations, and retest signal logic to present a comprehensive trading framework. It adapts to market conditions, identifying clusters of volume activity and signaling when the price retests critical zones.
█ How It Works
⚪ Volume Cluster Detection
The indicator dynamically calculates volume clusters by analyzing the highest and lowest price points within a specified lookback period.
Cluster Logic:
Bright Lines (Strong Red/Green):
These indicate that the price has frequently revisited these levels, creating a dense cluster.
Such areas serve as support or resistance, where significant historical trading has occurred, often acting as barriers to price movement.
Traders should consider these levels as potential reversal zones or consolidation points.
Faded or Darker Lines:
These lines indicate areas where the price has less historical activity, suggesting weaker clustering.
These zones have less market memory and are more likely to break, supporting trend continuation and rapid price movement.
⚪ Candle Color Logic (Market Memory)
Blue Candles (High Cluster Density):
Candles turn blue when the price has revisited a particular area many times.
This signals a highly clustered zone, likely to act as a barrier, creating consolidation or range phases.
These areas indicate strong market memory, potentially rejecting price attempts to break through.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these dense clusters, the candles turn green (bullish) or red (bearish).
This suggests the price has moved into a less clustered territory, where the path forward is clearer and trends are likely to extend without immediate resistance.
⚪ Retest Signal Logic
The indicator identifies critical retest points where the price crosses a cluster boundary and then reverses. These points are essential for traders looking to catch continuation or reversal setups.
⚪ Dynamic Price Clustering
The indicator dynamically adapts the clustering logic based on price movement and volume shifts.
Uses a dynamic moving average (VPMA) to maintain adaptive cluster levels.
Integrates a Kalman Filter for smoothing, reducing noise, and improving trend clarity.
Automatically updates as new data is received, keeping the clusters relevant in real-time.
█ How to Use
⚪ Trend Following & Reversal Detection
Use Retest signals to identify potential trend continuation or reversal points.
⚪ Trading Volume Clusters and Market Memory
Identify Key Zones:
Focus on bright, saturated cluster lines (strong red or green) as they indicate high market memory, where price has spent significant time in the past.
These zones are likely to exhibit a more choppy market. Apply range or mean reversion strategies.
Spot Potential Breakouts:
Faded or darker cluster lines indicate areas of low market memory, where the price has moved quickly and spent less time.
Use these areas to identify possible trend setups, as they represent lower resistance to price movement.
⚪ Interpreting Candle Colors for Market Phases
Blue Candles (High Cluster Density):
When candles turn blue, it signals that the price has revisited this area multiple times, creating a dense cluster.
These zones often trap price movement, leading to consolidations or range phases.
Use these areas as caution zones, where price can slow down or reverse.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these clustered zones, the candles turn green (bullish) or red (bearish), indicating lower market memory.
This signals a trend initiation with less immediate resistance, ideal for momentum and breakout trades.
Use these signals to identify emerging trends and ride the momentum.
█ Settings
Range Lookback Period: Sets the number of bars for calculating the range.
Zone Width (% of Range): Determines how wide the volume clusters are relative to the calculated range.
Volume Line Colors: Customize the appearance of bullish and bearish lines.
Retest Signals: Toggle the appearance of Triangle Up/Down retest markers.
Minimum Bars for Retest: Define the minimum number of bars required before a retest is valid.
Maximum Bars for Retest: Set the maximum number of bars within which a retest can occur.
Price Cluster Period: Adjusts the sensitivity of the dynamic clustering logic.
Cluster Confirmation: Controls how tightly the clusters respond to price action.
Price Cluster Start/Peak: Sets the minimum and maximum touches required to fully form a cluster.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
OBV Z-Score + Table📘 OBV Z-Score — Indicator Description
Overview
This indicator converts the On-Balance Volume (OBV) into a Z-Score oscillator, providing a normalized statistical view of volume flow strength relative to its recent history.
How It Works
OBV Calculation
The On-Balance Volume accumulates volume based on price direction, showing whether volume is flowing into or out of an asset.
Z-Score Transformation
The OBV values are normalized via Z-Score:
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Z = (OBV - Mean) / Standard Deviation
This reveals how unusually strong or weak volume momentum is compared to recent norms.
Smoothing
An optional moving average smoothing (SMA, EMA, VWMA, etc.) can be applied for cleaner signals.
Z-Score Table
A live Z-Score value is displayed in a table on the top-right of the indicator pane, clamped between +2 and -2:
+2 indicates unusually high positive volume momentum
-2 indicates unusually high negative volume momentum
How to Use It
Bullish Signal: Z-Score crossing above +1.5 or +2 signals strong buying volume pressure
Bearish Signal: Z-Score crossing below -1.5 or -2 signals strong selling volume pressure
Combine with Price Action: Use alongside price trends or other Z-Score indicators to improve decision making in SDCA or volume-based trading systems
RSI Z-Score + TableHow It Works
RSI Calculation
The standard RSI is computed over a user-defined period (default: 14), measuring the strength of recent price movements.
Z-Score Transformation
The RSI is then normalized using the Z-Score formula:
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Z = (RSI - Mean) / Standard Deviation
This highlights whether RSI is unusually high or low compared to its historical behavior.
Smoothing
An optional EMA is applied to the Z-Score for smoother and more reliable signals (default: 10-period smoothing).
Z-Score Table
A real-time value of the RSI Z-Score is displayed in a table in the top-right of the indicator pane.
The value is clamped between +2 and -2
+2 aligns with strong overbought RSI conditions
-2 aligns with strong oversold RSI conditions
How to Use It
Buy Signal Potential: When the Z-Score drops below -1.5 or -2 → statistically oversold RSI
Sell Signal Potential: When the Z-Score rises above +1.5 or +2 → statistically overbought RSI
Use in Confluence: Combine with price action, trend filters, or other Z-Score indicators (e.g. OBV, VWAP, VIX) for SDCA or mean-reversion strategies
VIX Z-Score (Inverted)📘 Indicator: VIX Z-Score (Inverted) + Table
🔍 Overview
This indicator calculates the Z-Score of the VIX (Volatility Index) and inverts it to identify potential buying opportunities during periods of fear and caution during periods of extreme optimism. The Z-Score is smoothed and visually displayed alongside a dynamic info table.
⚙️ How It Works
VIX Data: The VIX (ticker: CBOE:VIX) is pulled in real time.
Z-Score Calculation:
𝑍
=
(
𝑉
𝐼
𝑋
−
mean
)
standard deviation
Z=
standard deviation
(VIX−mean)
Over a customizable lookback period (default: 50).
Inversion:
Since high VIX usually means fear (often a contrarian buying signal), we invert the Z-Score:
𝑍
inv
=
−
𝑍
Z
inv
=−Z
Smoothing:
An EMA is applied to reduce noise and false signals.
Clamping:
The Z-Score is linearly scaled and capped between +2 and -2 for easy visualization in the info table.
📊 Z-Score Table (Top-Right)
Range Interpretation Table Color
+1.5 to +2 Extreme fear → Buy zone 🟩 Green
+0.5 to +1.5 Moderate fear 🟨 Lime
–0.5 to +0.5 Neutral ⬜ Gray
–0.5 to –1.5 Growing complacency 🟧 Orange
–1.5 to –2 Extreme optimism → Caution 🟥 Red
The current Z-Score (clamped version) is shown in real time on the right-hand info panel.
🧠 How to Use It
+2 Zone (Table: Green):
Market fear is at an extreme. Historically, such conditions are contrarian bullish—possible entry zones.
–2 Zone (Table: Red):
Indicates extreme optimism and low fear. Often a signal to be cautious or take profits.
Middle range (±0.5):
Market is neutral. Avoid major decisions based solely on sentiment here.
🧪 Best Practices
Combine with price action, volume, or trend filters.
Works well on daily or 4H timeframes.
Not a standalone signal—best used to confirm or fade sentiment extremes.
SSRO Z-ScoreSSRO Z-Score Indicator — Description
What it does:
This indicator measures the Stablecoin Supply Ratio (SSR) relative to Bitcoin’s market cap and calculates a normalized Z-Score of this ratio to help identify potential market tops and bottoms in the crypto market.
How it works:
The Stablecoin Supply Ratio (SSR) is calculated by dividing Bitcoin’s market capitalization by the combined market capitalization of major stablecoins (USDT, USDC, TUSD, DAI, FRAX).
The SSR is then smoothed over a user-defined lookback period to reduce noise.
A Z-Score is computed by normalizing the SSR over a specified moving window, which shows how far the current SSR deviates from its historical average in terms of standard deviations.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter short-term volatility.
How to read the Z-Score:
Z-Score = 0: SSR is at its historical average.
Z-Score > 0: SSR is above average, indicating Bitcoin’s market cap is relatively high compared to stablecoin supply, potentially signaling bullish market conditions.
Z-Score < 0: SSR is below average, indicating stablecoin supply is high relative to Bitcoin’s market cap, possibly signaling bearish pressure or increased liquidity waiting to enter the market.
Upper and Lower Bands: These user-defined levels (e.g., +2 and -2) represent thresholds for extreme conditions. Values above the upper band may indicate overbought or overheated market conditions, while values below the lower band may indicate oversold or undervalued conditions.
Additional Features:
A dynamic table displays a linear scaled Z-Score alongside the main plot, clamped between -2 and +2 relative to the upper and lower bands for intuitive interpretation.
Usage Tips:
Combine the SSRO Z-Score with other technical indicators or volume analysis for more reliable signals.
Look for divergence between price and Z-Score extremes as potential reversal signals.
Smoothed ROC Z-Score with TableSmoothed ROC Z-Score with Table
This indicator calculates the Rate of Change (ROC) of a chosen price source and transforms it into a smoothed Z-Score oscillator, allowing you to identify market cycle tops and bottoms with reduced noise.
How it works:
The ROC is calculated over a user-defined length.
A moving average and standard deviation over a separate window are used to standardize the ROC into a Z-Score.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter noise and highlight clearer cycle signals.
The smoothed Z-Score oscillates around zero, with upper and lower bands defined by user inputs (default ±2 standard deviations).
When the Z-Score reaches or exceeds ±3 (customizable), the value shown in the table is clamped at ±2 for clearer interpretation.
The indicator plots the smoothed Z-Score line with zero and band lines, and displays a colored Z-Score table on the right for quick reference.
How to read it:
Values near zero indicate neutral momentum.
Rising Z-Scores towards the upper band suggest increasing positive momentum, possible market tops or strength.
Falling Z-Scores towards the lower band indicate negative momentum, potential bottoms or weakness.
The color-coded table gives an easy visual cue: red/orange for strong positive signals, green/teal for strong negative signals, and gray for neutral zones.
Use cases:
Identify turning points in trending markets.
Filter noisy ROC data for cleaner signals.
Combine with other indicators to time entries and exits more effectively.
S&P 500 Estimated PE (Sampled Every 4)📊 **S&P 500 Estimated PE Ratio (from CSV)**
This indicator visualizes the forward-looking estimated PE ratio of the S&P 500 index, imported from external CSV data.
🔹 **Features:**
- Real historical daily data from 2008 onward
- Automatically aligns PE values to closest available trading date
- Useful for macro valuation trends and long-term entry signals
📌 **Best for:**
- Investors interested in forward-looking valuation
- Analysts tracking over/undervaluation trends
- Long-term timing overlay on price action
Category: `Breadth indicators`, `Cycles`
