Trend Volatility Index (TVI)Trend Volatility Index (TVI)
A robust nonparametric oscillator for structural trend volatility detection
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What is this?
TVI is a volatility oscillator designed to measure the strength and emergence of price trends using nonparametric statistics.
It calculates a U-statistic based on the Gini mean difference across multiple simple moving averages.
This allows for objective, robust, and unbiased quantification of trend volatility in tick-scale values.
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What can it do?
• Quantify trend strength as a continuous value aligned with tick price scale
• Detect trend breakouts and volatility expansions
• Identify range-bound market states
• Detect early signs of new trends with minimal lag
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What can’t it do?
• Predict future price levels
• Predict trend direction before confirmation
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How it works
TVI computes a nonparametric dispersion metric (Gini mean difference) from multiple SMAs of different lengths.
As this metric shares the same dimension as price ticks, it can be directly interpreted on the chart as a volatility gauge.
The output is plotted using candlestick-style charts to enhance visibility of change rate and trend behavior.
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Disclaimer
TVI does not predict price. It is a structural indicator designed to support discretionary judgment.
Trading carries inherent risk, and this tool does not guarantee profitability. Use at your own discretion.
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Innovation
This indicator introduces a novel approach to trend volatility by applying U-statistics over time series
to produce a nonparametric, unbiased, and robust estimate of structural volatility.
日本語要約
Trend Volatility Index (TVI) は、ノンパラメトリックなU統計量（Gini平均差）を使ってトレンドの強度を客観的に測定することを目的に開発されたボラティリティ・オシレーターです。
ティック単位で連続的に変化し、トレンドのブレイク・レンジ・初動の予兆を定量的に検出します。
未来の価格や方向は予測せず、現在の構造的ばらつきだけをロバストに評価します。
M-oscillator
Kinetic Price Momentum Oscillator📈 Kinetic Price Momentum Oscillator (Sri-PMO)
Author's Note:
This script is an educational and custom-adapted visualization based on the concept of the Price Momentum Oscillator (PMO). It is not a direct clone of any proprietary implementation, and it introduces enhancements such as timeframe sensitivity, customizable smoothings, multi-timeframe analysis, and visual trend meters.
🔍 Overview:
The Kinetic Price Momentum Oscillator (Kinetic-PMO) is a dynamic momentum indicator that analyzes price rate of change smoothed with dual exponential moving averages. It offers a clear view of momentum trends across multiple timeframes—the chart's current timeframe, the 1-hour timeframe, and the 1-day timeframe. It includes optional visual cues for zero-line crossovers, trend ribbon fills, and a daily trend meter.
🧮 Calculation Logic:
At its core, Kinetic-PMO calculates momentum by:
Measuring Rate of Change (ROC) over 1 bar.
Applying double EMA smoothing:
The first smoothing (len1) smooths the ROC.
The second smoothing (len2) smooths the result further.
This produces the main KPMO Line.
A third EMA (sigLen) is applied to the KPMO line to produce the Signal Line.
The formula includes a multiplier of 10 to scale values.
pinescript
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roc = ta.roc(source, 1)
kmo = ta.ema(10 * ta.ema(roc, len1), len2)
signal = ta.ema(kmo, sigLen)
To allow responsiveness across timeframes, the script provides sensitivity inputs (sensA, sensB, sensC) which dynamically scale the smoothing lengths for different contexts:
Intraday (current chart timeframe)
Hourly (1H)
Daily (1D)
🧭 Features:
✅ Multi-Timeframe Calculation:
Intraday: Based on current chart resolution
1H: PMO for the hourly trend
1D: Daily trend meter using KPMO structure
✅ Trend Identification:
Green if PMO is above Signal Line (bullish)
Red if PMO is below Signal Line (bearish)
Daily Trend Meter includes nuanced color mapping:
Lime = Bullish above zero
Orange = Bullish below zero
Red = Bearish below zero
Yellow = Bearish above zero
✅ Custom Visual Enhancements:
Optional filled ribbons between KPMO and Signal
Optional zero-line crossover background highlight
Compact daily trend meter displayed as a color-coded shape
🛠 Customization Parameters:
Input Description
Primary Smoothing Controls ROC smoothing depth (1st EMA)
Secondary Smoothing Controls final smoothing (2nd EMA)
Signal Smoothing Controls EMA of the PMO line
Input Source Default is close, but any price type can be selected
Sensitivity Factors Separate multipliers for intraday, 1H, and 1D
Visual Settings Toggle zero-line highlight and ribbon fill
🧠 Intended Use:
The Kinetic-PMO is suitable for trend confirmation, momentum divergence detection, and entry/exit refinement. The multi-timeframe aspect helps align short-term and long-term momentum trends, supporting better trade decision-making.
⚖️ Legal & Attribution Statement:
This script was independently created and modified for educational and analytical purposes. While the concept of the PMO is inspired by technical analysis literature, this implementation does not copy or reverse-engineer any proprietary code. It introduces custom parameters, visualization enhancements, and multi-timeframe logic. Posting this script complies with TradingView’s policy on derivative work and educational indicators.
Technical Signal Master概要
このインジケーターは、30種類以上のテクニカル指標を自動で分析し、「買い」「売り」「中立」に分類して視覚的なテーブル形式で表示します。
トレンド・モメンタム・ボリューム・オシレーターなどを横断的に統合し、裁量トレーダーの意思決定を補助することを目的としています。
🔍 独自性（オリジナリティ）と設計思想
単なるマッシュアップではなく、カテゴリ別に機能分類された構造
Pine Scriptが読めないユーザーでも視覚的に判断できる設計
全指標の同時出力を整理・要約し、チャート上の混乱を回避
EMA群（20/50/75/100/200）・TDI・CCI・Force Indexなど高度な構成
🧭 使用方法
チャートに追加すると、左下にテーブル形式のシグナル判定表が表示されます
テーブルの各行には「買い」「売り」「中立」のいずれかが表示され、判断の補助となります
同じ方向のシグナルが多い場合、その方向への優位性が高いと判断できます
スキャル・デイトレ・スイングのすべてで活用可能です
✅ 推奨される活用場面
複数インジケーターの同時判断（コンフルエンス）
トレード前の環境認識や、逆張り時の過熱感の確認
ファンダメンタルズ判断と併用したテクニカル裏付け
📌 注意事項
このスクリプトは単体で使用可能です。他のスクリプトと併用する必要はありません
Overview
Technical Signal Master automatically analyzes 30+ technical indicators and summarizes their states in a visual signal table with "Buy", "Sell", or "Neutral" results. It combines trend, momentum, oscillator, and volume-based tools into a single panel to support discretionary traders.
🔍 Originality
Not a simple mashup: indicators are categorized and structured logically
Designed for users who cannot read Pine Script
Summarizes all signals clearly without overlapping chart clutter
Includes advanced tools like EMA sets, CCI, TDI, Force Index, etc.
🧭 How to Use
Add the script to any chart
Signal table will appear in the corner of the screen
When multiple signals align in the same direction, it suggests a high-probability setup
Useful for scalping, day trading, and swing trading alike
✅ Best Use Cases
Signal confluence analysis
Overbought/oversold confirmation
Visual risk management and bias confirmation
📌 Note
This script is standalone; no other scripts are needed
Volume Flow OscillatorVolume Flow Oscillator
Overview
The Volume Flow Oscillator is an advanced technical analysis tool that measures buying and selling pressure by combining price direction with volume. Unlike traditional volume indicators, this oscillator reveals the force behind price movements, helping traders identify strong trends, potential reversals, and divergences between price and volume.
Reading the Indicator
The oscillator displays seven colored bands that fluctuate around a zero line:
Three bands above zero (yellow) indicate increasing levels of buying pressure
Three bands below zero (red) indicate increasing levels of selling pressure
The central band represents the baseline volume flow
Color intensity changes based on whether values are positive or negative
Trading Signals
The Volume Flow Oscillator provides several valuable trading signals:
Zero-line crossovers: When multiple bands cross from negative to positive, potential bullish shift; opposite for bearish
Divergences: When price makes new highs/lows but oscillator bands fail to confirm, signals potential reversal
Volume climax: Extreme readings where outer bands stretch far from zero often precede reversals
Trend confirmation: Strong expansion of bands in direction of price movement confirms genuine momentum
Support/resistance: During trends, bands may remain largely on one side of zero, showing continued directional pressure
Customization
Adjust these key parameters to optimize the oscillator for your trading style:
Lookback Length: Controls overall sensitivity (shorter = more responsive, longer = smoother)
Multipliers: Adjust sensitivity spread between bands for different market conditions
ALMA Settings: Fine-tune how the indicator weights recent versus historical data
VWMA Toggle: Enable for additional smoothing in volatile markets
Best Practices
For optimal results, use this oscillator in conjunction with price action and other confirmation indicators. The multi-band approach helps distinguish between minor fluctuations and significant volume events that might signal important market turns.
Stoch RSI Approaching Zones (Dots)🧠 Stoch RSI Strategy with Trend Filter, Risk Management & Early Signal Visualization
This strategy combines Stochastic RSI signals with a 200 EMA trend filter and risk-based position sizing to create a well-rounded approach for both long and short trades. It includes built-in take profit / stop loss logic and supports early exits based on momentum shifts.
🔧 Key Features:
Stoch RSI-Based Entries
Long: %K crosses above 20
Short: %K crosses below 80
Optional Trend Filter
Longs only when price is above the 200 EMA
Shorts only when price is below the 200 EMA
Risk Management
Position sizing based on risk percentage of initial capital
Customizable stop loss and take profit (%)
Early Exit Logic
Closes positions if %K crosses back through key levels (80 for longs, 20 for shorts)
Visual Tools
Optional plot of Stoch RSI %K and %D
Horizontal markers for overbought (80) and oversold (20) zones
Approaching Signal Indicator (Add-On)
Aqua and fuchsia dots plotted on the chart when %K is approaching overbought (70–80) or oversold (20–30) zones, helping spot momentum before a crossover occurs.
Alerts Ready
Entry, exit, and early-exit alerts built in
📈 Best used across multiple timeframes—some assets (like AAPL) may respond especially well depending on the timeframe. The 200 EMA filter alone significantly improves signal quality, and the "approaching zone" dots can help traders prepare for moves in advance.
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator -
Version: PineScript™ v5
📌 Description
The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators.
Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments.
🚀 Points of Innovation
Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights.
Offers real-time visual cues for trending, mean-reverting, or random price action zones.
User-controllable EMA smoothing reduces noise for clearer interpretation.
Dynamic coloring and fill for immediate visual categorization of market regime.
Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6).
Fully customizable appearance settings to fit different charting preferences.
🔧 Core Components
Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis.
Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate.
Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity.
Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths.
Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone.
🔥 Key Features
Visually differentiates between trending, mean-reverting, and random market modes.
User-adjustable lookback and smoothing periods for tailored sensitivity.
Distinct fill and line styles for each regime to avoid ambiguity.
On-chart reference lines for strong trending and mean-reverting thresholds.
Works with any price series (close, open, HL2, etc.) for versatile application.
🎨 Visualization
Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent.
Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime.
Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime.
All visual elements can be customized for thickness, color intensity, and opacity for user preference.
📖 Usage Guidelines
Data Settings
Hurst Calculation Length
Default: 100
Range: 10-300
Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction.
Data Source
Default: close
Description: Select which data series to analyze (e.g., Close, Open, HL2).
Smoothing Length (EMA)
Default: 5
Range: 1-50
Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results.
Style Settings
Trending Color (Hurst > 0.5)
Default: Blue tone
Description: Color used when trending regime is detected.
Mean-Reverting Color (Hurst < 0.5)
Default: Orange tone
Description: Color used when mean-reverting regime is detected.
Neutral/Random Color
Default: Soft blue
Description: Color when market behavior is indeterminate or shifting.
Fill Opacity
Default: 70-80
Range: 0-100
Description: Transparency of area fills—higher opacity for stronger visual effect.
Line Width
Default: 2
Range: 1-5
Description: Thickness of the main indicator curve.
✅ Best Use Cases
Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa).
Filtering signals in automated or systematic trading strategies.
Spotting periods of randomness where trading signals should be deprioritized.
Enhancing mean-reversion or trend-following models with regime-awareness.
⚠️ Limitations
Not predictive: Reflects current and recent market state, not future direction.
Sensitive to input parameters—overfitting may occur if settings are changed too frequently.
Smoothing can introduce lag in regime recognition.
May not work optimally in markets with structural breaks or extreme volatility.
💡 What Makes This Unique
Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits.
Offers immediate regime visualization through smart dynamic coloring and zone fills.
🔬 How It Works
Rolling Log Return Calculation:
Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally.
Rescaled Range Analysis:
A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”.
Exponent Calculation & Smoothing:
The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals.
Regime Detection Logic:
The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display.
💡 Note:
Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
MA Dist Z-ScoreThe Moving Average Distance Z-Score shows how far the current price is from its moving average, measured in standard deviations.
When the Z-score is above 0, price is above the average.
When the Z-score is below 0, price is below the average.
A Z-score of +2 or -2 means price is very far from the average and might return to it (mean reversion).
This tool helps identify statistically unusual price levels and can be used for reversion setups and trend exhaustion.
Stochastic XThe "Stochastic X" script is a customizable momentum oscillator designed to help traders identify potential overbought and oversold conditions, as well as trend reversals, by analyzing the relationship between a security's closing price and its price range over a specified period. This indicator is particularly useful for traders looking to fine-tune their entry and exit points based on momentum shifts.
🔧 Indicator Settings and Customization
The script offers several user-configurable settings to tailor the indicator to specific trading strategies:
In addition to the source type, %K Period, %D Period, and Signal line periods you can now change moving average calculation for the stochastic and signal lines.
This script allows selection among various moving average methods (e.g., SMA, EMA, WMA, T3) for smoothing the %K and signal lines. Different methods can affect the responsiveness of the indicator.
🎨 Interpreting Background Colors
The script enhances visual analysis by changing the background color of the indicator panel based on the %K line's value:
Green Background: Indicates that the %K line is above 50, suggesting bullish momentum.
Red Background: Signifies that the %K line is below 50, pointing to bearish momentum.
Light Green Overlay: Appears when the %K line exceeds 80, highlighting overbought conditions.
Light Red Overlay: Shows up when the %K line falls below 20, indicating oversold conditions.
These visual cues assist traders in quickly assessing market momentum and potential reversal.
📈 Trading Strategies Using Stochastic X
Traders can utilize the Stochastic X indicator in various ways:
Overbought/Oversold Conditions:
A %K value above 80 may suggest that the asset is overbought, potentially signaling a price correction.
A %K value below 20 could indicate that the asset is oversold, possibly leading to a price rebound.
Signal Line Crossovers:
When the %K line crosses above the signal line, it may be interpreted as a bullish signal.
Conversely, a %K line crossing below the signal line might be seen as a bearish signal.
Divergence Analysis:
If the price makes a new high while the %K line does not, this bearish divergence could precede a price decline.
If the price hits a new low but the %K line forms a higher low, this bullish divergence might signal an upcoming price increase.
Trend Confirmation:
Sustained %K values above 50 can confirm an uptrend.
Persistent %K values below 50 may validate a downtrend.
In this chart, observe how the background colors change in response to the %K line's value, providing immediate visual feedback on market conditions. The crossovers between the %K and signal lines offer potential entry and exit points, while the overbought and oversold overlays help identify possible reversal zones.
⚙️ Adjusting Settings for Optimal Use
The Stochastic X indicator's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 14 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Macd, Wt Cross & HVPMacd Wt Cross & HVP – Advanced Multi-Signal Indicator
This script is a custom-designed multi-signal indicator that brings together three proven concepts to provide a complete view of market momentum, reversals, and volatility build-ups. It is built for traders who want to anticipate key market moves, not just react to them.
Why This Combination ?
While each tool has its strengths, their combined use creates powerful signal confluence.
Instead of juggling multiple indicators separately, this script synchronizes three key perspectives into a single, intuitive display—helping you trade with greater clarity and confidence.
1. MACD Histogram – Momentum and Trend Clarity
At the core of the indicator is the MACD histogram, calculated as the difference between two exponential moving averages (EMAs).
Color-coded bars represent momentum direction and intensity:
Green / blue bars: bullish momentum
Red / pink bars: bearish momentum
Color intensity shows acceleration or weakening of trend.
This visual makes it easy to detect trend shifts and momentum divergence at a glance.
2. WT Cross Signals – Early Reversal Detection
Overlaid on the histogram are green and red dots, based on the logic of the WaveTrend oscillator cross:
Green dots = potential bullish cross (buy signal)
Red dots = potential bearish cross (sell signal)
These signals are helpful for identifying reversal points during both trending and ranging phases.
3. Historical Volatility Percentile (HVP) – Volatility Compression Zones
Behind the histogram, purple vertical zones highlight periods of low historical volatility, based on the HVP:
When volatility compresses below a specific threshold, these zones appear.
Such periods are often followed by explosive price moves, making them prime areas for pre-breakout positioning.
By integrating HVP, the script doesn’t just tell you where the trend is—it tells you when the trend is likely to erupt.
How to Use This Script
Use the MACD histogram to confirm the dominant trend and its strength.
Watch for WT Cross dots as potential entry/exit signals in alignment or divergence with the MACD.
Monitor HVP purple zones as warnings of incoming volatility expansions—ideal moments to prepare for breakout trades.
Best results occur when all three elements align, offering a high-probability trade setup.
What Makes This Script Original?
Unlike many mashups, this script was not created by simply merging indicators. Each component was carefully integrated to serve a specific, complementary purpose:
MACD detects directional bias
WT Cross adds precision timing
HVP anticipates volatility-based breakout timing
This results in a strategic tool for traders, useful on multiple timeframes and adaptable to different trading styles (trend-following, breakout, swing).
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.
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).
Stochastic RainbowThe Stochastic Rainbow indicator is a multi-layered momentum oscillator designed to provide a comprehensive view of market dynamics by combining multiple stochastic oscillators of varying periods. This approach allows traders to analyze both short-term and long-term momentum within a single visual framework, enhancing decision-making for entries and exits.
🔧 Indicator Settings and Customization
Select from various moving average methods (e.g., SMA, EMA, DEMA, TEMA, WMA, VWMA, RMA, T3) to smooth the stochastic lines. Different methods can affect the responsiveness of the indicator.
The indicator computes five sets of stochastic oscillators with Fibonacci values.
Each %K line is smoothed using the selected moving average type, and a corresponding %D line is plotted for each %K.
🎨 Visual Interpretation
The Stochastic Rainbow indicator plots multiple %K and %D lines, each with distinct colors for easy differentiation.
Additionally, horizontal dotted lines are drawn at levels 80 (Upper Band), 50 (Midline), and 20 (Lower Band) to indicate overbought, neutral, and oversold conditions, respectively.
📈 Trading Strategies Using Stochastic Rainbow
The multi-layered structure of the Stochastic Rainbow allows for nuanced analysis.
Trend Confirmation:
When all %K lines are above 50 and aligned in ascending order (short-term above long-term), it suggests a strong uptrend.
Conversely, when all %K lines are below 50 and aligned in descending order, it indicates a strong downtrend.
Overbought/Oversold Conditions:
If the shorter-term %K lines (e.g., %K 5,3 and %K 8,3) enter the overbought zone (>80) while longer-term lines remain below, it may signal a potential reversal.
Similarly, if shorter-term lines enter the oversold zone (<20) while longer-term lines remain above, it could indicate an upcoming bullish reversal.
Crossovers:
A bullish signal occurs when a %K line crosses above its corresponding %D line.
A bearish signal occurs when a %K line crosses below its corresponding %D line.
Divergence Analysis:
If price makes a new high while the %K lines do not, it may indicate bearish divergence and a potential reversal.
If price makes a new low while the %K lines do not, it may indicate bullish divergence and a potential reversal.
⚙️ Adjusting Settings for Optimal Use
The Stochastic Rainbow's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 55 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Global M2 YoY % Change (USD)+108 Days Daily ChartGlobal M2 YoY % Change pushed 108 days forward. Showing Global Liquidity as a proxy. It is the correlation between Global Liquidity and the bitcoin price after 108 Days. Be careful this proxy only works well on the Daily timeframe.
Volume Spike Filter### Volume Spike Detector with Alerts
**Overview:**
This indicator helps traders quickly identify unusual spikes in trading volume by comparing the current volume against a simple moving average (SMA) threshold. It's particularly useful for beginners seeking clear signals of increased market activity.
**Settings:**
* **SMA Length:** Defines the period for calculating the average volume (default = 20).
* **Multiplier:** Determines how much the volume must exceed the SMA to be considered a spike (default = 1.5).
* **Highlight Spikes:** Toggle to visually highlight spikes on the chart (default = enabled).
**Signals:**
* 🟩 **Highlighted Background:** Indicates a volume spike that surpasses the defined threshold.
* 🏷️ **"Vol Spike" Label:** Clearly marks the exact bar of the spike for quick reference.
**Usage:**
Use these clear volume spike alerts to identify potential trading opportunities, confirmations, or shifts in market momentum. Combine this with other technical indicators for enhanced analysis.
Golden chart v1## Golden Chart v1 – Trend Tracking & Signal Visualization Tool
**Version**: v1
**Pine Script**: version=5
**Visibility**: Invite-only
### Overview
Golden Chart v1 combines EMA-based trend bands (Golden Chart 2) with ATR-derived dynamic levels (Golden Chart 3) to help traders identify potential trend phases, visualize BUY/SELL signals, and color candles by trend direction.
### Key Features
- **Golden Chart 2 (EMA bands)**
- Calculates `emaHigh` & `emaLow` using `gc2_ema_period` (default 10)
- Determines SSL-style trend lines `sslUp` & `sslDown`
- **Golden Chart 3 (ATR levels)**
- Computes weighted ATR (`avgTR`) over `gc3_length` (default 13)
- Sets dynamic levels `hiLimit` & `loLimit` with `gc3_multiplier` (default 2.0)
- Plots `ret` line as the active trend level
- **Trade Signals**
- `BUY` label on bullish cross (`sslUp` → `sslDown` + close>open)
- `SELL` label on bearish cross (`sslDown` → `sslUp` + close **Request:** Invite-only v1 review for House Rules approval. Thank you!
Golden chart v1## Golden Chart v1 – Trend Tracking & Signal Visualization Tool
**Version**: v1
**Pine Script**: version=5
**Visibility**: Invite-only
### Overview
Golden Chart v1 combines EMA-based trend bands (Golden Chart 2) with ATR-derived dynamic levels (Golden Chart 3) to help traders identify potential trend phases, visualize BUY/SELL signals, and color candles by trend direction.
### Key Features
- **Golden Chart 2 (EMA bands)**
- Calculates `emaHigh` & `emaLow` using `gc2_ema_period` (default 10)
- Determines SSL-style trend lines `sslUp` & `sslDown`
- **Golden Chart 3 (ATR levels)**
- Computes weighted ATR (`avgTR`) over `gc3_length` (default 13)
- Sets dynamic levels `hiLimit` & `loLimit` with `gc3_multiplier` (default 2.0)
- Plots `ret` line as the active trend level
- **Trade Signals**
- `BUY` label on bullish cross (`sslUp` → `sslDown` + close>open)
- `SELL` label on bearish cross (`sslDown` → `sslUp` + close **Request:** Invite-only v1 review for House Rules approval. Thank you!
DS_StochA custom stochastic-based indicator with EMA smoothing. Useful for identifying overbought and oversold conditions.
TASC 2025.06 Cybernetic Oscillator█ OVERVIEW
This script implements the Cybernetic Oscillator introduced by John F. Ehlers in his article "The Cybernetic Oscillator For More Flexibility, Making A Better Oscillator" from the June 2025 edition of the TASC Traders' Tips . It cascades two-pole highpass and lowpass filters, then scales the result by its root mean square (RMS) to create a flexible normalized oscillator that responds to a customizable frequency range for different trading styles.
█ CONCEPTS
Oscillators are indicators widely used by technical traders. These indicators swing above and below a center value, emphasizing cyclic movements within a frequency range. In his article, Ehlers explains that all oscillators share a common characteristic: their calculations involve computing differences . The reliance on differences is what causes these indicators to oscillate about a central point.
The difference between two data points in a series acts as a highpass filter — it allows high frequencies (short wavelengths) to pass through while significantly attenuating low frequencies (long wavelengths). Ehlers demonstrates that a simple difference calculation attenuates lower-frequency cycles at a rate of 6 dB per octave. However, the difference also significantly amplifies cycles near the shortest observable wavelength, making the result appear noisier than the original series. To mitigate the effects of noise in a differenced series, oscillators typically smooth the series with a lowpass filter, such as a moving average.
Ehlers highlights an underlying issue with smoothing differenced data to create oscillators. He postulates that market data statistically follows a pink spectrum , where the amplitudes of cyclic components in the data are approximately directly proportional to the underlying periods. Specifically, he suggests that cyclic amplitude increases by 6 dB per octave of wavelength.
Because some conventional oscillators, such as RSI, use differencing calculations that attenuate cycles by only 6 dB per octave, and market cycles increase in amplitude by 6 dB per octave, such calculations do not have a tangible net effect on larger wavelengths in the analyzed data. The influence of larger wavelengths can be especially problematic when using these oscillators for mean reversion or swing signals. For instance, an expected reversion to the mean might be erroneous because oscillator's mean might significantly deviate from its center over time.
To address the issues with conventional oscillator responses, Ehlers created a new indicator dubbed the Cybernetic Oscillator. It uses a simple combination of highpass and lowpass filters to emphasize a specific range of frequencies in the market data, then normalizes the result based on RMS. The process is as follows:
Apply a two-pole highpass filter to the data. This filter's critical period defines the longest wavelength in the oscillator's passband.
Apply a two-pole SuperSmoother (lowpass filter) to the highpass-filtered data. This filter's critical period defines the shortest wavelength in the passband.
Scale the resulting waveform by its RMS. If the filtered waveform follows a normal distribution, the scaled result represents amplitude in standard deviations.
The oscillator's two-pole filters attenuate cycles outside the desired frequency range by 12 dB per octave. This rate outweighs the apparent rate of amplitude increase for successively longer market cycles (6 dB per octave). Therefore, the Cybernetic Oscillator provides a more robust isolation of cyclic content than conventional oscillators. Best of all, traders can set the periods of the highpass and lowpass filters separately, enabling fine-tuning of the frequency range for different trading styles.
█ USAGE
The "Highpass period" input in the "Settings/Inputs" tab specifies the longest wavelength in the oscillator's passband, and the "Lowpass period" input defines the shortest wavelength. The oscillator becomes more responsive to rapid movements with a smaller lowpass period. Conversely, it becomes more sensitive to trends with a larger highpass period. Ehlers recommends setting the smallest period to a value above 8 to avoid aliasing. The highpass period must not be smaller than the lowpass period. Otherwise, it causes a runtime error.
The "RMS length" input determines the number of bars in the RMS calculation that the indicator uses to normalize the filtered result.
This indicator also features two distinct display styles, which users can toggle with the "Display style" input. With the "Trend" style enabled, the indicator plots the oscillator with one of two colors based on whether its value is above or below zero. With the "Threshold" style enabled, it plots the oscillator as a gray line and highlights overbought and oversold areas based on the user-specified threshold.
Below, we show two instances of the script with different settings on an equities chart. The first uses the "Threshold" style with default settings to pass cycles between 20 and 30 bars for mean reversion signals. The second uses a larger highpass period of 250 bars and the "Trend" style to visualize trends based on cycles spanning less than one year:
OrangeCandle Multi-Wave Trend Analyzer🍊 OrangeCandle Multi-Wave Trend Analyzer - OrangeCandle TripleWave
Your all-in-one visual helper for spotting market momentum, reversals, and volume-driven trends.
This indicator blends three trusted tools into one cozy setup:
Elliott Wave Oscillator (EWO) shows whether momentum is leaning bullish or bearish — with color-coded bars for easy viewing.
WaveTrend Oscillator helps you catch those classic overbought/oversold moments, along with crossover signals that hint at potential reversals.
Volume-Supported Linear Regression Trend gives you a sense of buying vs. selling pressure, using volume-weighted trend slopes for both short- and long-term outlooks.
It’s like having a weather forecast for the markets: clean, colorful, and surprisingly intuitive once you get the hang of it. Whether you're day trading or swing trading, this script aims to keep your chart informative without the clutter. Just plug it in, take a look, and let the waves guide you.
Synapse Trade PanelReplace multiple technical indicators with 1 panel that shows you vital technicals at a glance. Includes RSI and Stochastic indicators and a risk management section with suggested stops in either direction, and EMA trend
Range Expansion Index (REI)Introduction and History
I'm sharing an indicator today that I have developed: the Range Expansion Index (REI). This powerful oscillator was developed by the renowned technical analyst Thomas DeM., known for his unique approach to market timing and price exhaustion. The REI was introduced as part of his comprehensive suite of technical tools, detailed in his influential work, such as "The New Science of Technical Analysis."
DeM. designed the REI to be a more refined momentum oscillator. His goal was to create an indicator that could accurately reflect the underlying strength or weakness of price movements while minimizing the false signals often generated by traditional oscillators during sideways or choppy markets. The REI achieves this by focusing on significant price expansions and contractions, comparing recent price behavior to the overall price changes over a specified lookback period.
You can find more information and the basis for this indicator here:
QuantifiedStrategies: www.quantifiedstrategies.com
Infront Help Center: infront-portfolio-manager.helpcenter.infront.co
How the REI Works
The core of the REI's calculation lies in identifying and quantifying "strong" price changes within a given period (typically 8 bars). It does this by evaluating specific price relationships and conditions between current and past bars. The indicator then computes a ratio comparing the sum of these "strong" price changes to the sum of the absolute total price changes over the lookback period, scaling the result to oscillate between -100 and +100.
The key levels for interpreting the REI are generally:
+60: Overbought Zone
-60: Oversold Zone
Unlike oscillators that might simply signal overbought/oversold upon entering these zones, the REI's interpretation, according to DeM., often focuses on the exit from these extreme areas.
Traditional Trading Signals
Based on DeM.'s methodology and the descriptions in the provided links, the primary trading signals generated by the REI occur when the indicator crosses back from an extreme zone:
Sell Signal: The REI moves above the +60 level and then crosses back down below +60. This suggests potential price weakness after a period of strong upward momentum.
Buy Signal: The REI moves below the -60 level and then crosses back up above -60. This indicates potential price strength after a period of strong downward momentum.
Duration Analysis: An Optional Signal Filter
The QuantifiedStrategies link highlights the concept of "Duration Analysis," suggesting that the amount of time (number of bars) the REI spends in the overbought or oversold region can add crucial context. A brief stay might precede a reversal, while a prolonged stay could indicate a strong, persistent trend.
The indicator incorporates this concept as an optional filter. You can enable this feature and specify a number of bars. When enabled, a buy or sell signal will only be triggered if the REI crosses the respective overbought/oversold level AND the duration of the REI being in that extreme zone precisely matches the number of bars you specify in the input settings.
Indicator Features in This Pine Script
The Pine Script code I have developed provides a comprehensive implementation of the REI with additional trading utilities:
REI Calculation: Implements the core REI formula based on conditional price changes and summations over a defined period.
Configurable REI Period: Easily adjust the main lookback period for the REI calculation.
Customizable Lookback Parameters: Fine-tune the specific lookback periods used in the internal conditions (n1L, n2L, n3L) as described in the calculation method.
Plotting: Displays the REI line in a separate pane, along with horizontal lines at +60 (Overbought), -60 (Oversold), and 0 (Zero Line) for clear visual analysis.
Configurable Alerts: Set up Buy and Sell alerts that trigger when the REI crosses the +60/-60 levels. Control global alert enabling, and specifically enable/disable Buy and Sell alerts.
Plot Shapes for Signals: Optionally display visual triangle shapes directly on the price chart (red triangle down for Sell above the bar, green triangle up for Buy below the bar) to easily spot signal occurrences. Control global shape enabling and specifically enable/disable Buy/Sell shapes.
Optional Duration Analysis Filter: Activate a filter that requires the REI to have spent an exact number of consecutive bars in the overbought/oversold zone at the moment of the cross for a signal to be considered valid. Configure the required number of bars.
How to Use This Code in TradingView
Open TradingView and navigate to the Pine Editor (usually the icon on the left sidebar or via the bottom panel).
Delete any existing code in the editor and paste the REI code.
Save the script (you can name it "Range Expansion Index with Duration Filter" or similar).
Add the indicator to your chart by clicking the "Add to Chart" button in the Pine Editor.
Access the indicator's settings on your chart to adjust the REI Period, Lookbacks, and enable/disable Alerts, Plot Shapes, and the optional Duration Filter (including setting the number of bars).
To receive actual notifications: You must set up alerts manually through the TradingView platform's alert system (right-click on the indicator -> Add alert on Range Expansion Index (REI)...). Select the specific conditions "REI Sell Signal" or "REI Buy Signal" from the dropdown menu and configure your desired notification methods (popup, email, etc.).
Disclaimer:
Trading financial markets involves risk, and past performance is not indicative of future results. This indicator is a tool for analysis and should be used as part of a comprehensive trading strategy, always combined with other techniques and proper risk management. Always conduct your own research and backtest the indicator to understand its behavior on the markets and timeframes you trade.
Disparity Index with Volatility ZonesDisparity Index with Volatility Zones
is a momentum oscillator that measures the percentage difference between the current price and its simple moving average (SMA). This allows traders to identify overbought/oversold conditions, assess momentum strength, and detect potential trend reversals or continuations.
🔍 Core Concept:
The Disparity Index (DI) is calculated as:
DI = 100 × (Price − SMA) / SMA
A positive DI indicates the price is trading above its moving average (potential bullish sentiment), while a negative DI suggests the price is below the average (potential bearish sentiment).
This version of the Disparity Index introduces a dual-zone volatility framework, offering deeper insight into the market's current state.
🧠 What Makes This Version Unique?
1. High Volatility Zones
When DI crosses above +1.0% or below –1.0%, it often indicates the start or continuation of a strong trend.
Sustained readings beyond these thresholds typically align with trending phases, offering opportunities for momentum-based entries.
A reversal back within ±1.0% after exceeding these levels can suggest a shift in momentum — similar to how RSI exits the overbought/oversold zones before reversals.
These thresholds act as dynamic markers for breakout confirmation and potential trend exhaustion.
2. Low Volatility Zones
DI values between –0.5% and +0.5% define the low-volatility zone, shaded for visual clarity.
This area typically indicates market indecision, sideways price action, or consolidation.
Trading within this range may favor range-bound or mean-reversion strategies, as trend momentum is likely limited.
The logic is similar to interpreting a flat ADX, tight Bollinger Bands, or contracting Keltner Channels — all suggesting consolidation.
⚙️ Features:
Customizable moving average length and input source
Adjustable thresholds for overbought/oversold and low-volatility zones
Optional visual fill between low-volatility bounds
Clean and minimal chart footprint (non-essential plots hidden by default)
📈 How to Use:
1. Trend Confirmation:
A break above +1.0% can be used as a bullish continuation signal.
A break below –1.0% may confirm bearish strength.
Long periods above/below these thresholds support trend-following entries.
2. Reversal Detection:
If DI returns below +1.0% after exceeding it, bullish momentum may be fading.
If DI rises above –1.0% after falling below, bearish pressure may be weakening.
These shifts resemble overbought/oversold transitions in oscillators like RSI or Stochastic, and can be paired with divergence, volume, or price structure analysis for higher reliability.
3. Sideways Market Detection:
DI values within ±0.5% indicate low volatility or a non-trending environment.
Traders may avoid breakout entries during these periods or apply range-trading tactics instead.
Observing transitions out of the low-volatility zone can help anticipate breakouts.
4. Combine with Other Indicators:
DI signals can be enhanced using tools like MACD, Volume Oscillators, or Moving Averages.
For example, a DI breakout beyond ±1.0% supported by a MACD crossover or volume spike can help validate trend initiation.
This indicator is especially powerful when paired with Bollinger Bands:
A simultaneous price breakout from the Bollinger Band and DI moving beyond ±1.0% can help identify early trend inflection points.
This combination supports entering positions early in a developing trend, improving the efficiency of trend-following strategies and enhancing decision-making precision.
It also helps filter false breakouts when DI fails to confirm the move outside the band.
This indicator is designed for educational and analytical purposes and works across all timeframes and asset classes.
It is particularly useful for traders seeking a clear framework to identify momentum strength, filter sideways markets, and improve entry timing within a larger trading system.
4H Golden Cross - The Sign of GloryCalculates the golden cross on the 4-hour timeframe
Displays the result on any timeframe
Draws a green vertical beam (a vertical line or background stripe) on the bar where the golden cross happened, so it’s clearly visible regardless of your chart timeframe
This is used to see the effectiveness of the 4h golden cross without having to change timeframes continually
Pulse DPO with Z-Score📌 Pulse DPO with Z-Score — Indicator Description (English)
The Pulse DPO (Detrended Price Oscillator) helps identify major market cycle tops and bottoms by removing long-term trends and focusing on shorter-term price cycles.
This enhanced version includes:
A normalized oscillator (0–100) based on recent price deviations.
A smoothed signal to reduce noise.
A Z-Score transformation, scaling the output to a range from –3 to +3, where:
–3 represents extreme oversold conditions (former normalized value = 100),
+3 represents extreme overbought conditions (former normalized value = 1).
🔍 How it works:
The indicator subtracts a delayed moving average from price to isolate short-term cycles (DPO logic).
It then normalizes the oscillator within a lookback window.
Finally, it converts this to a Z-Score scale for easier interpretation of extremes.
🟢 Suggested Usage:
Consider Long entries or Short exits when Z-Score reaches –2 to –3 (deep oversold).
Consider Short entries or Long exits when Z-Score reaches +2 to +3 (deep overbought).
Use in combination with other signals for higher-confidence setups.
