Coppock Curve
The Coppock Curve is a long-term momentum indicator, also known as the "Coppock Guide," used to identify potential long-term market turning points, particularly major downturns and upturns, by smoothing the sum of 14-month and 11-month rates of change with a 10-month weighted moving average.
Here's a more detailed breakdown:
What it is:
The Coppock Curve is a technical indicator designed to identify long-term buy and sell signals in major stock market indices and related ETFs.
How it's calculated:
Rate of Change (ROC): The indicator starts by calculating the rate of change (ROC) for 14 and 11 periods (usually months).
Sum of ROCs: The ROC for the 14-period and 11-period are summed.
Weighted Moving Average (WMA): A 10-period weighted moving average (WMA) is then applied to the sum of the ROCs.
Interpreting the Curve:
Buy Signals: A buy signal is often generated when the Coppock Curve crosses above the zero line, suggesting a potential transition from a bearish to a bullish phase.
Sell Signals: While primarily designed to identify market bottoms, some traders may interpret a cross below the zero line as a sell signal or a bearish warning.
Origin and Purpose:
The Coppock Curve was introduced by economist Edwin Coppock in 1962.
It was originally designed to help investors identify opportune moments to enter the market.
Coppock's inspiration came from the Episcopal Church's concept of the average mourning period, which he believed mirrored the stock market's recovery period.
Limitations:
The Coppock Curve is primarily used for long-term analysis and may not be as effective for short-term or intraday trading.
It may lag in rapidly changing markets, and its signals may not always be reliable.
Tìm kiếm tập lệnh với "法国市值最大的10家公司"
Rolling ATR Momentum - EnhancedATR Rolling Momentum Indicator – User Manual
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🔍 Overview
The ATR Rolling Momentum Indicator is a dynamic volatility tool built on the Average True Range (ATR). It not only tracks increasing or decreasing momentum but also provides early warnings and confirmation signals for potential breakout moves. It’s especially powerful for futures and options traders looking to align with expanding price action.
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📊 Core Components
✅ ATR Delta (Rolling ATR)
- Definition: Difference between current ATR and past ATR (user-defined lookback).
- Use: Tells whether volatility is expanding (positive delta) or contracting (negative delta).
- Visual: Green line for rising momentum, red for declining.
🟣 ATR Delta Slope
- Definition: Measures acceleration in momentum.
- Use: Helps identify early signs of breakout buildup.
- Visual: Purple line. Watch for slope turning up from below.
🟡 Volatility Squeeze (Yellow Dot)
- Definition: Current ATR is significantly lower than its 20-period average.
- Use: Indicates the market is coiling—possible breakout ahead.
🔼 Momentum Start (Green Triangle)
- Definition: ATR Delta slope turns from negative to positive.
- Use: Early warning to prepare for volatility expansion.
🔷 Breakout Confirmation (Blue Label Up)
- Definition: ATR Delta exceeds its high of the last 10 candles.
- Use: Confirms volatility breakout—trade opportunity if direction aligns.
🟩/🟥 Background Color
- Green Background: Momentum rising (positive ATR delta)
- Red Background: Momentum falling (negative ATR delta)
- Yellow Tint: Active squeeze zone
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✅ How to Use It (Futures/Options Focus)
Step-by-Step:
1. Squeeze Detected (Yellow Dot) → Stay alert. Market is coiling.
2. Green Triangle Appears → Momentum is starting to rise.
3. Background Turns Green → Confirmed rising momentum.
4. Blue Label Appears → Confirmed breakout (enter trade if trend aligns).
Directional Bias:
- Use your main chart setup (price action, EMAs, trendlines, etc.) to decide direction (Call or Put, Long or Short).
- ATR Momentum only tells you how strong the move is—not which way.
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⚙️ Inputs & Settings
- ATR Period: Default 14 (core volatility measure)
- Rolling Lookback: Used to calculate delta (default 5)
- Slope Length: Used to measure acceleration (default 3)
- Squeeze Factor: Default 0.8 — lower = more sensitive squeeze detection
- Breakout Lookback: Checks ATR delta against last X bars (default 10)
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🧠 Pro Tips
- Works great when paired with EMA stacks, price structure, or breakout patterns.
- Avoid taking trades based only on squeeze or momentum—combine with chart confirmation.
- If background turns red after a breakout, it may be losing momentum—book partials or tighten stops.
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🧭 Ideal For:
- Nifty/BankNifty Futures
- Option directional trades (call/put buying)
- Index scalping and momentum swing setups
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Use this tool as your volatility compass—it won't tell you where to go, but it'll tell you when the wind is strong enough to move fast.
End of Manual
Liquidity Heatmap SwiftEdgeDescription
Liquidity Heatmap with Buy/Sell Side (Blue/Red) is a technical analysis tool designed to help traders identify potential liquidity zones in the market by combining swing high/low detection with volume analysis, visualized as a heatmap overlay on the chart. This script highlights areas where significant buying or selling pressure may exist, often acting as support or resistance levels, and provides a clear visual representation of these zones using color-coded heatmap boxes and labeled bubbles.
What It Does
The script identifies key price levels (swing highs and lows) where liquidity is likely to be concentrated, such as stop-loss clusters or pending orders. These levels are then grouped into a heatmap, with blue zones representing potential buy-side liquidity (below the current price) and red zones indicating sell-side liquidity (above the current price). Each zone is marked with a bubble showing the estimated liquidity amount, derived from volume data, to help traders gauge the strength of the level.
How It Works
The script combines three main components to create a comprehensive liquidity visualization:
Swing Highs and Lows Detection:
The script uses the ta.pivothigh and ta.pivotlow functions to identify swing highs and lows over a user-defined lookback period (Swing Length). These levels often represent areas where price has reversed, indicating potential liquidity zones where stop-losses or pending orders may be placed.
Volume Analysis:
Volume data at each swing high/low is captured and averaged over a specified period (Volume Average Length). This volume is then scaled using a multiplier (Volume Multiplier for Liquidity) to estimate the liquidity amount at each level, displayed in thousands (e.g., "10K") on the chart via labeled bubbles.
Heatmap Visualization:
The identified levels are grouped into price bins to form a heatmap. The price range is divided into a user-defined number of bins (Number of Heatmap Bins), and each bin is drawn as a colored box (blue for buy-side, red for sell-side). The transparency of the heatmap boxes can be adjusted (Heatmap Transparency) to ensure they do not obscure the price action.
Why Combine These Components?
The combination of swing highs/lows, volume analysis, and a heatmap provides a powerful way to visualize liquidity in the market. Swing highs and lows are natural points where liquidity tends to accumulate, as they often coincide with areas where traders place stop-losses or pending orders. By incorporating volume data, the script quantifies the potential strength of these levels, giving traders insight into the magnitude of liquidity present. The heatmap visualization then aggregates these levels into a clear, color-coded overlay, making it easy to see where buy-side and sell-side liquidity is concentrated without cluttering the chart.
This mashup is particularly useful because it bridges price action (swing levels), market activity (volume), and visual clarity (heatmap), offering a holistic view of potential support and resistance zones that might influence price movements.
How to Use It
Add the Indicator to Your Chart:
Apply the script to your chart by adding it from the Pine Script library. It will overlay directly on your price chart.
Interpret the Heatmap:
Blue Zones (Buy-Side Liquidity): These appear below the current price and indicate levels where buying pressure or stop-losses from short positions may be located.
Red Zones (Sell-Side Liquidity): These appear above the current price and indicate levels where selling pressure or stop-losses from long positions may be located.
The intensity of the color is controlled by the Heatmap Transparency setting—lower values make the zones more opaque, while higher values make them more transparent.
Analyze the Bubbles:
Each liquidity zone is marked with a bubble showing the estimated liquidity amount in thousands (e.g., "10K"). The size of the bubble is scaled by the Bubble Size Multiplier, with larger bubbles indicating higher liquidity.
Adjust Settings for Your Needs:
Liquidity Settings:
Swing Length: Controls the lookback period for detecting swing highs and lows. A smaller value (e.g., 10) is better for shorter timeframes like 1-minute charts, while a larger value (e.g., 50) suits higher timeframes.
Liquidity Threshold: Defines how close two levels must be to be considered the same, preventing duplicate zones.
Volume Average Length: Sets the period for averaging volume data at swing points.
Volume Multiplier for Liquidity: Scales the volume to estimate liquidity amounts shown in the bubbles.
Lookback Period (Hours): Limits how far back the script looks for liquidity zones.
Use Price Window Filter: If enabled, only shows zones within a price range defined by Liquidity Window (Points per Side).
Heatmap Settings:
Number of Heatmap Bins: Determines how many price bins the heatmap is divided into. More bins create a finer resolution but may clutter the chart.
Heatmap Bin Height (Points): Sets the vertical height of each heatmap box in price points.
Heatmap Transparency: Adjusts the transparency of the heatmap boxes (0 = fully opaque, 100 = fully transparent).
Display Settings:
Bubble Size Multiplier: Scales the size of the bubbles showing liquidity amounts.
Trading Application:
Use the heatmap to identify potential support (blue zones) and resistance (red zones) levels where price may react.
Pay attention to zones with larger bubbles, as they indicate higher liquidity and may have a stronger impact on price.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
What Makes It Original?
This script stands out by integrating swing high/low detection with volume-based liquidity estimation and a heatmap visualization in a single tool. Unlike traditional support/resistance indicators that only plot static lines, this script dynamically aggregates liquidity zones into a heatmap, making it easier to see clusters of potential buying or selling pressure. The addition of volume-derived liquidity amounts in labeled bubbles provides a unique quantitative measure of each zone's strength, helping traders prioritize key levels. The color-coded buy/sell distinction further enhances its utility by visually separating zones based on their likely market impact.
Example Use Case
On a 1-minute chart of EUR/USD, you might set Swing Length to 10 to capture short-term pivots, Lookback Period (Hours) to 4 to focus on recent data, and Liquidity Window to 200 points (20 pips) to show only nearby zones. The heatmap will then display blue zones below the current price where buy-side liquidity may act as support, and red zones above where sell-side liquidity may act as resistance. A bubble showing "50K" at a blue zone indicates significant buy-side liquidity, suggesting a potential bounce if the price approaches that level.
TTM Squeeze Momentum MTF [Cometreon]TTM Squeeze Momentum MTF combines the core logic of both the Squeeze Momentum by LazyBear and the TTM Squeeze by John Carter into a single, unified indicator. It offers a complete system to analyze the phase, direction, and strength of market movements.
Unlike the original versions, this indicator allows you to choose how to calculate the trend, select from 15 different types of moving averages, customize every parameter, and adapt the visual style to your trading preferences.
If you are looking for a powerful, flexible and highly configurable tool, this is the perfect choice for you.
🔷 New Features and Improvements
🟩 Unified System: Trend Detection + Visual Style
You can decide which logic to use for the trend via the "Show TTM Squeeze Trend" input:
✅ Enabled → Trend calculated using TTM Squeeze
❌ Disabled → Trend based on Squeeze Momentum
You can also customize the visual style of the indicator:
✅ Enable "Show Histogram" for a visual mode using Histogram, Area, or Column
❌ Disable it to display the classic LazyBear-style line
Everything updates automatically and dynamically based on your selection.
🟩 Full Customization
Every base parameter of the original indicator is now fully configurable: lengths, sources, moving average types, and more.
You can finally adapt the squeeze logic to your strategy — not the other way around.
🟩 Multi-MA Engine
Choose from 15 different Moving Averages for each part of the calculation:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
🟩 Dynamic Signal Line
Apply a moving average to the momentum for real-time cross signals, with full control over its length and type.
🟩 Multi-Timeframe & Multi-Ticker Support
You're no longer limited to the chart's current timeframe or ticker. Apply the squeeze to any symbol or timeframe without repainting.
🔷 Technical Details and Customizable Inputs
This indicator offers a fully modular structure with configurable parameters for every component:
1️⃣ Squeeze Momentum Settings – Choose the source, length, and type of moving average used to calculate the base momentum.
2️⃣ Trend Mode Selector – Toggle "Show TTM Squeeze Trend" to select the trend logic displayed on the chart:
✅ Enabled – Shows the trend based on TTM Squeeze (Bollinger Bands inside/outside Keltner Channel)
❌ Disabled – Displays the trend based on Squeeze Momentum logic
🔁 The moving average type for the Keltner Channel is handled automatically, so you don't need to select it manually, even if the custom input is disabled.
3️⃣ Signal Line – Toggle the Signal Line on the Squeeze Momentum. Select its length and MA type to generate visual cross signals.
4️⃣ Bollinger Bands – Configure the length, multiplier, source, and MA type used in the bands.
5️⃣ Keltner Channel – Adjust the length, multiplier, source, and MA type. You can also enable or disable the True Range option.
6️⃣ Advanced MA Parameters – Customize the parameters for advanced MAs (JMA, ALMA, FRAMA, VIDYA), including Phase, Power, Offset, Sigma, and Shift values.
7️⃣ Ticker & Input Source – Select the ticker and manage inputs for alternative chart types like Renko, Kagi, Line Break, and Point & Figure.
8️⃣ Style Settings – Choose how the squeeze is displayed:
Enable "Show Histogram" for Histogram, Area, or Column style
Disable it to show the classic LazyBear-style line
Use Reverse Color to invert line colors
Toggle Show Label to highlight Signal Line cross signals
Customize trend colors to suit your preferences
9️⃣ Multi-Timeframe Options - Timeframe – Use the squeeze on higher timeframes for stronger confirmation
🔟 Wait for Timeframe Closes -
✅ Enabled – Prevents multiple signals within the same candle
❌ Disabled – Displays the indicator smoothly without delay
🔧 Default Settings Reference
To replicate the default settings of the original indicators as they appear when first applied to the chart, use the following configurations:
🟩 TTM Squeeze (John Carter Style)
Squeeze
Length: 20
MA Type: SMA
Show TTM Squeeze Trend: Enabled
Bollinger Bands
Length: 20
Multiplier: 2.0
MA Type: SMA
Keltner Channel
Length: 20
Multiplier: 1.0
Use True Range: ON
MA Type: EMA
Style
Show Histogram: Enabled
Reverse Color: Enabled
🟩 Squeeze Momentum (LazyBear Style)
Squeeze
Length: 10
MA Type: SMA
Show TTM Squeeze Trend: Disabled
Bollinger Bands
Length: 20
Multiplier: 1.5
MA Type: SMA
Keltner Channel
Length: 10
Multiplier: 1.5
Use True Range: ON
MA Type: SMA
Style
Show Histogram: Disabled
Reverse Color: Disabled
⚠️ These values are intended as a starting point. The Cometreon indicator lets you fully customize every input to fit your trading style.
🔷 How to Use Squeeze Momentum Pro
🔍 Identifying Trends
Squeeze Momentum Pro supports two different methods for identifying the trend visually, each based on a distinct logic:
Squeeze Momentum Trend (LazyBear-style):
Displays 3 states based on the position of the Bollinger Bands relative to the Keltner Channel:
🔵 Blue = No Squeeze (BB outside KC and KC outside BB)
⚪️ White = Squeeze Active (BB fully inside KC)
⚫️ Gray = Neutral state (none of the above)
TTM Squeeze Trend (John Carter-style):
Calculates the difference in width between the Bollinger Bands and the Keltner Channel:
🟩 Green = BB width is greater than KC → potential expansion phase
🟥 Red = BB are tighter than KC → possible compression or pre-breakout
📈 Interpreting Signals
Depending on the active configuration, the indicator can provide various signals, including:
Trend color → Reflects the current compression/expansion state (based on selected mode)
Momentum value (above or below 0) → May indicate directional pressure
Signal Line cross → Can highlight momentum shifts
Color change in the momentum → May suggest a potential trend reversal
🛠 Integration with Other Tools
Squeeze Momentum Pro works well alongside other indicators to strengthen market context:
✅ Volume Profile / OBV – Helps confirm accumulation or distribution during squeezes
✅ RSI – Useful to detect divergence between momentum and price
✅ Moving Averages – Ideal for defining primary trend direction and filtering signals
☄️ If you find this indicator useful, leave a Boost to support its development!
Every piece of feedback helps improve the tool and deliver an even better trading experience.
🔥 Share your ideas or feature requests in the comments!
MACD Volume Strategy (BBO + MACD State, Reversal Type)Overview
MACD Volume Strategy (BBO + MACD State, Reversal Type) is a momentum-based reversal system that combines MACD crossover logic with volume filtering to enhance signal accuracy and minimize noise. It aims to identify structural trend shifts and manage risk using predefined parameters.
※This strategy is for educational and research purposes only. All results are based on historical simulations and do not guarantee future performance.
Strategy Objectives
Identify early trend transitions with high probability
Filter entries using volume dynamics to validate momentum
Maintain continuous exposure using a reversal-style model
Apply a consistent 1:1.5 risk-to-reward ratio per trade
Key Features
Integrated MACD and volume oscillator filtering
Zero repainting (all signals confirmed on closed candles)
Automatic position flipping for seamless direction shifts
Stop-loss and take-profit based on recent structural highs/lows
Trading Rules
Long Entry Conditions
MACD crosses above the zero line (BBO Buy arrow)
Volume oscillator is positive (short EMA > long EMA)
MACD is above the signal line
Close any existing short and enter a new long
Short Entry Conditions
MACD crosses below the zero line (BBO Sell arrow)
Volume oscillator is positive
MACD is below the signal line
Close any existing long and enter a new short
Exit Rules
Take Profit (TP) = Entry ± (risk distance × 1.5)
Stop Loss (SL) = Recent swing low (for long) or high (for short)
Early Exit = Triggered when a reversal signal appears (flip logic)
Risk Management Parameters
Pair: ETH/USD
Timeframe: 10-minute
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted for sustainable practice)
Total Trades: 312 (backtest on selected dataset)
※Risk parameters are fully configurable and should be adjusted to suit each trader's personal setup and broker conditions.
Parameters & Configurations
Volume Short Length: 6
Volume Long Length: 12
MACD Fast Length: 11
MACD Slow Length: 21
Signal Smoothing: 10
Oscillator MA Type: SMA
Signal Line MA Type: SMA
Visual Support
Green arrow = Long entry
Red arrow = Short entry
MACD lines, signal line, and histogram
SL/TP markers plotted directly on the chart
Strategic Advantages & Uniqueness
Volume filtering eliminates low-participation, weak signals
Structurally aligned SL/TP based on recent market pivots
No repainting — decisions are made only on closed candles
Always in the market due to the reversal-style framework
Inspirations & Attribution
This strategy is inspired by the excellent work of:
Bitcoinblockchainonline – “BBO_Roxana_Signals MACD + vol”
Leveraging MACD zero-line cross and volume oscillator for intuitive signal generation.
HasanRifat – “MACD Fake Filter ”
Introduced a signal filter using MACD wave height averaging to reduce false positives.
This strategy builds upon those ideas to create a more automated, risk-aware, and technically adaptive system.
Summary
MACD Volume Strategy is a clean, logic-first automated trading system built for precision-seeking traders. It avoids discretionary bias and provides consistent signal logic under backtested historical conditions.
100% mechanical — no discretionary input required
Designed for high-confidence entries
Can be extended with filters, alerts, or trailing stops
※Strategy performance depends on market context. Past performance is not indicative of future results. Use with proper risk management and careful configuration.
PumpC Opening Range Breakout (ORB) Stretch RangePumpC ORB Stretch
The PumpC ORB Stretch is a volatility-based indicator that helps traders identify potential breakout zones by analyzing how price typically behaves around the open. This tool is inspired by concepts introduced by Toby Crabel in his well-known book “Day Trading with Short-Term Price Patterns and Opening Range Breakout.”
Rather than predicting market direction, this indicator highlights areas where price is likely to expand based on recent volatility. It is designed for traders who prefer dynamic, data-driven breakout levels over static support and resistance zones.
What Is the "Stretch"?
In Toby Crabel’s framework, the Stretch is the average of the smaller of two price moves:
The distance from the open to the high of the bar
The distance from the open to the low of the bar
This smaller value captures the “quiet side” of the candle and reflects recent price compression. Averaged over multiple periods (commonly 10 daily bars), it creates a baseline to assess how far price may move away from the open under typical market conditions.
How the Indicator Works
The PumpC ORB Stretch follows this process:
Uses a higher timeframe (such as daily) to calculate the open, high, and low.
For each bar, measures the smaller of the two distances: open to high or open to low.
Applies a moving average to the result over a user-defined number of bars (default is 10).
Multiplies the average stretch by customizable levels (e.g., 0.382, 1.0, 2.0).
Plots breakout levels above and below the open of the selected timeframe.
The result is a set of adaptive levels that expand or contract with market volatility.
Customization Options
Stretch Timeframe: Choose the timeframe used for stretch calculation (default: Daily).
Stretch Length: Set the number of bars to include in the moving average.
Breakout Levels: Enable or disable individual levels and define multipliers.
Color Settings: Customize colors for each range level for easy visual distinction.
Plot Style: Circular markers are used to reduce chart clutter and improve readability.
How to Use It
Use plotted levels to anticipate possible breakouts from the open.
Adjust stretch length to reflect short-term or longer-term volatility trends.
Combine this tool with momentum indicators, volume, or price action for confirmation.
Use levels to help guide stop placement or profit targets in breakout strategies.
Important Notes
This script is based on an interpretation of Crabel’s concepts and is not affiliated with Crabel Capital or the original author.
The indicator does not predict direction; it is a tool for context and structure.
It is recommended that users test and validate this tool in a simulated environment before applying it to live trading.
This indicator is intended for educational purposes only.
Licensing and Attribution
This script is built entirely in Pine Script v5 and follows TradingView’s open-source standards. It does not include any third-party or proprietary code. If you modify or share it, please credit the original idea and follow all TradingView script publishing rules.
Multi-MA Strategy Analyzer with BacktestMulti-MA Strategy Analyzer with Backtest
This TradingView Pine Script indicator is designed to analyze multiple moving averages (SMA or EMA) dynamically and identify the most profitable one based on historical performance.
Features
Dynamic MA Range:
Specify a minLength, maxLength, and step size.
Automatically calculates up to 20 MAs.
Custom MA Calculation:
Uses custom SMA and EMA implementations to support dynamic length values.
Buy/Sell Logic:
Buy when price crosses above a MA.
Sell when price crosses below.
Supports both long and short trades.
Performance Tracking:
Tracks PnL, number of trades, win rate, average profit, and drawdown.
Maintains individual stats for each MA.
Best MA Detection:
Automatically highlights the best-performing MA.
Optional showBestOnly toggle to focus only on the best line and its stats.
Visualization:
Up to 20 plot() calls (static) for MAs.
Green highlight for the best MA.
Color-coded result table and chart.
Table View
When showBestOnly = false, the table displays all MAs with stats.
When showBestOnly = true, the table displays only the best MA with a summary row.
Includes:
Best MA length
Total PnL
Number of trades
Win rate
Avg PnL per trade
Max Drawdown
Configuration
minLength (default: 10)
maxLength (default: 200)
step (default: 10)
useEMA: Toggle between EMA and SMA
showBestOnly: Focus on best-performing MA only
Notes
MA plotting is static, limited to 20 total.
Table supports highlighting and is optimized for performance.
Script is structured to run efficiently using arrays and simple int where required.
Potential Extensions
Add visual buy/sell arrows
Export stats to CSV
Strategy tester conversion
Custom date range filtering for backtesting
Author: Muhammad Wasim
Version: 1.0
MOEX Sectors: % Above MA 50/100/200 (EMA/SMA)🧠 Name:
MOEX Sectors: % Above MA 50/100/200 (EMA/SMA)
📋 Description (for TradingView “Description” tab):
This indicator shows the percentage of Moscow Exchange sectoral indices trading above the selected moving average (SMA or EMA) with periods of 50, 100, or 200.
It uses 10 official MOEX sector indices:
MOEXOG (Oil & Gas)
MOEXCH (Chemicals)
MOEXMM (Metals & Mining)
MOEXTN (Transport)
MOEXCN (Consumer)
MOEXFN (Financials)
MOEXTL (Telecom)
MOEXEU (Utilities)
MOEXIT (IT)
MOEXRE (Real Estate)
The indicator plots up to 3 lines representing the % of sectors trading above MA 50, 100, and/or 200. The MA type is user-selectable: EMA (default) or SMA.
Horizontal reference levels (90, 50, 10) help interpret market conditions:
🔼 >90% — Overbought zone, potential market exhaustion
⚖️ ~50% — Neutral state
🔽 <10% — Oversold zone, possible rebound
📈 How to Use in Strategy:
✅ 1. Trend Filter
If >50% of sectors are above MA 200 → market in long-term uptrend
If <50% → avoid long bias, bearish regime likely
✅ 2. Bottom Detection
When <10% of sectors are above MA 200, the market is heavily oversold — often a bottoming signal
✅ 3. Trend Confirmation
If the main index is rising and % of sectors above MA is growing, the trend is supported by breadth
If the index rises while breadth declines → bearish divergence
✅ 4. Contrarian Setups
>90% of sectors above MA 50 → market may be overheated, watch for pullback
<20% above MA 50 → potential local bottom
⚙️ Tips:
Overlay this indicator on the IMOEX index chart to detect narrow leadership
Combine with other breadth metrics or RSI on the index
Use the EMA/SMA toggle to fine-tune sensitivity
TICK Bias Timer with EMA Position📌 Description
This indicator tracks the time in minutes that the Exponential Moving Average (EMA) of the NYSE USI:TICK remains above or below the zero line. It serves as a powerful market breadth confirmation tool to support your intraday directional bias.
Rather than focusing on momentary TICK spikes, this tool emphasizes duration and persistence of buying/selling pressure across the entire NYSE – helping traders stay on the right side of the flow.
🔧 Features
✅ Measures how long the EMA of TICK stays above or below 0
✅ Visual plots of upward and downward pressure duration (in minutes)
✅ Background color changes based on EMA position relative to 0
✅ Automatic daily reset at a customizable time (e.g. 15:30 for RTH open)
✅ Gap filter to avoid spikes during overnight or weekend sessions
✅ Clean, minimalist design – built for real-time decision making
🎯 How to Use
EMA > 0 for 10+ minutes → sustained bullish breadth → intraday bullish bias
EMA < 0 for 10+ minutes → sustained bearish breadth → intraday bearish bias
Frequent flip between sides → uncertain or choppy market → trade with caution
Can be used in confluence with Volume Profile, VWAP, price action, and Bookmap to reinforce trade setups.
💡 Ideal For:
Scalpers looking for flow confirmation
Day traders who want to filter fake strength/weakness
Professionals using TICK, USI:ADD , USI:VOLD , and other internals for decision-making
ZRK 30m This TradingView indicator draws alternating 30-minute boxes aligned precisely to real clock times (e.g., 10:00, 10:30, 11:00), helping traders visually segment intraday price action. It highlights every other 30-minute block with customizable colors, line styles, and opacity, allowing users to clearly differentiate between trading intervals. The boxes automatically adjust based on the chart’s timeframe, maintaining accuracy on 1-minute to 60-minute charts. Optional time labels can also be displayed for additional context. This tool is useful for identifying patterns, measuring volatility, or applying breakout strategies based on defined, consistent time windows across global trading sessions.
Enhanced Fuzzy SMA Analyzer (Multi-Output Proxy) [FibonacciFlux]EFzSMA: Decode Trend Quality, Conviction & Risk Beyond Simple Averages
Stop Relying on Lagging Averages Alone. Gain a Multi-Dimensional Edge.
The Challenge: Simple Moving Averages (SMAs) tell you where the price was , but they fail to capture the true quality, conviction, and sustainability of a trend. Relying solely on price crossing an average often leads to chasing weak moves, getting caught in choppy markets, or missing critical signs of trend exhaustion. Advanced traders need a more sophisticated lens to navigate complex market dynamics.
The Solution: Enhanced Fuzzy SMA Analyzer (EFzSMA)
EFzSMA is engineered to address these limitations head-on. It moves beyond simple price-average comparisons by employing a sophisticated Fuzzy Inference System (FIS) that intelligently integrates multiple critical market factors:
Price deviation from the SMA ( adaptively normalized for market volatility)
Momentum (Rate of Change - ROC)
Market Sentiment/Overheat (Relative Strength Index - RSI)
Market Volatility Context (Average True Range - ATR, optional)
Volume Dynamics (Volume relative to its MA, optional)
Instead of just a line on a chart, EFzSMA delivers a multi-dimensional assessment designed to give you deeper insights and a quantifiable edge.
Why EFzSMA? Gain Deeper Market Insights
EFzSMA empowers you to make more informed decisions by providing insights that simple averages cannot:
Assess True Trend Quality, Not Just Location: Is the price above the SMA simply because of a temporary spike, or is it supported by strong momentum, confirming volume, and stable volatility? EFzSMA's core fuzzyTrendScore (-1 to +1) evaluates the health of the trend, helping you distinguish robust moves from noise.
Quantify Signal Conviction: How reliable is the current trend signal? The Conviction Proxy (0 to 1) measures the internal consistency among the different market factors analyzed by the FIS. High conviction suggests factors are aligned, boosting confidence in the trend signal. Low conviction warns of conflicting signals, uncertainty, or potential consolidation – acting as a powerful filter against chasing weak moves.
// Simplified Concept: Conviction reflects agreement vs. conflict among fuzzy inputs
bullStrength = strength_SB + strength_WB
bearStrength = strength_SBe + strength_WBe
dominantStrength = max(bullStrength, bearStrength)
conflictingStrength = min(bullStrength, bearStrength) + strength_N
convictionProxy := (dominantStrength - conflictingStrength) / (dominantStrength + conflictingStrength + 1e-10)
// Modifiers (Volatility/Volume) applied...
Anticipate Potential Reversals: Trends don't last forever. The Reversal Risk Proxy (0 to 1) synthesizes multiple warning signs – like extreme RSI readings, surging volatility, or diverging volume – into a single, actionable metric. High reversal risk flags conditions often associated with trend exhaustion, providing early warnings to protect profits or consider counter-trend opportunities.
Adapt to Changing Market Regimes: Markets shift between high and low volatility. EFzSMA's unique Adaptive Deviation Normalization adjusts how it perceives price deviations based on recent market behavior (percentile rank). This ensures more consistent analysis whether the market is quiet or chaotic.
// Core Idea: Normalize deviation by recent volatility (percentile)
diff_abs_percentile = ta.percentile_linear_interpolation(abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff := raw_diff / diff_abs_percentile
// Fuzzy sets for 'normalized_diff' are thus adaptive to volatility
Integrate Complexity, Output Clarity: EFzSMA distills complex, multi-factor analysis into clear, interpretable outputs, helping you cut through market noise and focus on what truly matters for your decision-making process.
Interpreting the Multi-Dimensional Output
The true power of EFzSMA lies in analyzing its outputs together:
A high Trend Score (+0.8) is significant, but its reliability is amplified by high Conviction (0.9) and low Reversal Risk (0.2) . This indicates a strong, well-supported trend.
Conversely, the same high Trend Score (+0.8) coupled with low Conviction (0.3) and high Reversal Risk (0.7) signals caution – the trend might look strong superficially, but internal factors suggest weakness or impending exhaustion.
Use these combined insights to:
Filter Entry Signals: Require minimum Trend Score and Conviction levels.
Manage Risk: Consider reducing exposure or tightening stops when Reversal Risk climbs significantly, especially if Conviction drops.
Time Exits: Use rising Reversal Risk and falling Conviction as potential signals to take profits.
Identify Regime Shifts: Monitor how the relationship between the outputs changes over time.
Core Technology (Briefly)
EFzSMA leverages a Mamdani-style Fuzzy Inference System. Crisp inputs (normalized deviation, ROC, RSI, ATR%, Vol Ratio) are mapped to linguistic fuzzy sets ("Low", "High", "Positive", etc.). A rules engine evaluates combinations (e.g., "IF Deviation is LargePositive AND Momentum is StrongPositive THEN Trend is StrongBullish"). Modifiers based on Volatility and Volume context adjust rule strengths. Finally, the system aggregates these and defuzzifies them into the Trend Score, Conviction Proxy, and Reversal Risk Proxy. The key is the system's ability to handle ambiguity and combine multiple, potentially conflicting factors in a nuanced way, much like human expert reasoning.
Customization
While designed with robust defaults, EFzSMA offers granular control:
Adjust SMA, ROC, RSI, ATR, Volume MA lengths.
Fine-tune Normalization parameters (lookback, percentile). Note: Fuzzy set definitions for deviation are tuned for the normalized range.
Configure Volatility and Volume thresholds for fuzzy sets. Tuning these is crucial for specific assets/timeframes.
Toggle visual elements (Proxies, BG Color, Risk Shapes, Volatility-based Transparency).
Recommended Use & Caveats
EFzSMA is a sophisticated analytical tool, not a standalone "buy/sell" signal generator.
Use it to complement your existing strategy and analysis.
Always validate signals with price action, market structure, and other confirming factors.
Thorough backtesting and forward testing are essential to understand its behavior and tune parameters for your specific instruments and timeframes.
Fuzzy logic parameters (membership functions, rules) are based on general heuristics and may require optimization for specific market niches.
Disclaimer
Trading involves substantial risk. EFzSMA is provided for informational and analytical purposes only and does not constitute financial advice. No guarantee of profit is made or implied. Past performance is not indicative of future results. Use rigorous risk management practices.
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
Adaptive Regression Channel [MissouriTim]The Adaptive Regression Channel (ARC) is a technical indicator designed to empower traders with a clear, adaptable, and precise view of market trends and price boundaries. By blending advanced statistical techniques with real-time market data, ARC delivers a comprehensive tool that dynamically adjusts to price action, volatility, volume, and momentum. Whether you’re navigating the fast-paced world of cryptocurrencies, the steady trends of stocks, or the intricate movements of FOREX pairs, ARC provides a robust framework for identifying opportunities and managing risk.
Core Components
1. Color-Coded Regression Line
ARC’s centerpiece is a linear regression line derived from a Weighted Moving Average (WMA) of closing prices. This line adapts its calculation period based on market volatility (via ATR) and is capped between a minimum of 20 bars and a maximum of 1.5 times the user-defined base length (default 100). Visually, it shifts colors to reflect trend direction: green for an upward slope (bullish) and red for a downward slope (bearish), offering an instant snapshot of market sentiment.
2. Dynamic Residual Channels
Surrounding the regression line are upper (red) and lower (green) channels, calculated using the standard deviation of residuals—the difference between actual closing prices and the regression line. This approach ensures the channels precisely track how closely prices follow the trend, rather than relying solely on overall price volatility. The channel width is dynamically adjusted by a multiplier that factors in:
Volatility: Measured through the Average True Range (ATR), widening channels during turbulent markets.
Trend Strength: Based on the regression slope, expanding channels in strong trends and contracting them in consolidation phases.
3. Volume-Weighted Moving Average (VWMA)
Plotted in orange, the VWMA overlays a volume-weighted price trend, emphasizing movements backed by significant trading activity. This complements the regression line, providing additional confirmation of trend validity and potential breakout strength.
4. Scaled RSI Overlay
ARC features a Relative Strength Index (RSI) overlay, plotted in purple and scaled to hover closely around the regression line. This compact display reflects momentum shifts within the trend’s context, keeping RSI visible on the price chart without excessive swings. User-defined overbought (default 70) and oversold (default 30) levels offer reference points for momentum analysis."
Technical Highlights
ARC leverages a volatility-adjusted lookback period, residual-based channel construction, and multi-indicator integration to achieve high accuracy. Its parameters—such as base length, channel width, ATR period, and RSI length—are fully customizable, allowing traders to tailor it to their specific needs.
Why Choose ARC?
ARC stands out for its adaptability and precision. The residual-based channels offer tighter, more relevant support and resistance levels compared to standard volatility measures, while the dynamic adjustments ensure it performs well in both trending and ranging markets. The inclusion of VWMA and scaled RSI adds depth, merging trend, volume, and momentum into a single, cohesive overlay. For traders seeking a versatile, all-in-one indicator, ARC delivers actionable insights with minimal noise.
Best Ways to Use the Adaptive Regression Channel (ARC)
The Adaptive Regression Channel (ARC) is a flexible tool that supports a variety of trading strategies, from trend-following to breakout detection. Below are the most effective ways to use ARC, along with practical tips for maximizing its potential. Adjustments to its settings may be necessary depending on the timeframe (e.g., intraday vs. daily) and the asset being traded (e.g., stocks, FOREX, cryptocurrencies), as each market exhibits unique volatility and behavior.
1. Trend Following
• How to Use: Rely on the regression line’s color to guide your trades. A green line (upward slope) signals a bullish trend—consider entering or holding long positions. A red line (downward slope) indicates a bearish trend—look to short or exit longs.
• Best Practice: Confirm the trend with the VWMA (orange line). Price above the VWMA in a green uptrend strengthens the bullish case; price below in a red downtrend reinforces bearish momentum.
• Adjustment: For short timeframes like 15-minute crypto charts, lower the Base Regression Length (e.g., to 50) for quicker trend detection. For weekly stock charts, increase it (e.g., to 200) to capture broader movements.
2. Channel-Based Trades
• How to Use: Use the upper channel (red) as resistance and the lower channel (green) as support. Buy when the price bounces off the lower channel in an uptrend, and sell or short when it rejects the upper channel in a downtrend.
• Best Practice: Check the scaled RSI (purple line) for momentum cues. A low RSI (e.g., near 30) at the lower channel suggests a stronger buy signal; a high RSI (e.g., near 70) at the upper channel supports a sell.
• Adjustment: In volatile crypto markets, widen the Base Channel Width Coefficient (e.g., to 2.5) to reduce false signals. For stable FOREX pairs (e.g., EUR/USD), a narrower width (e.g., 1.5) may work better.
3. Breakout Detection
• How to Use: Watch for price breaking above the upper channel (bullish breakout) or below the lower channel (bearish breakout). These moves often signal strong momentum shifts.
• Best Practice: Validate breakouts with VWMA position—price above VWMA for bullish breaks, below for bearish—and ensure the regression line’s slope aligns (green for up, red for down).
• Adjustment: For fast-moving assets like crypto on 1-hour charts, shorten ATR Length (e.g., to 7) to make channels more reactive. For stocks on daily charts, keep it at 14 or higher for reliability.
4. Momentum Analysis
• How to Use: The scaled RSI overlay shows momentum relative to the regression line. Rising RSI in a green uptrend confirms bullish strength; falling RSI in a red downtrend supports bearish pressure.
• Best Practice: Look for RSI divergences—e.g., price hitting new highs at the upper channel while RSI flattens or drops could signal an impending reversal.
• Adjustment: Reduce RSI Length (e.g., to 7) for intraday trading in FOREX or crypto to catch short-term momentum shifts. Increase it (e.g., to 21) for longer-term stock trades.
5. Range Trading
• How to Use: When the regression line’s slope is near zero (flat) and channels are tight, ARC indicates a ranging market. Buy near the lower channel and sell near the upper channel, targeting the regression line as the mean price.
• Best Practice: Ensure VWMA hovers close to the regression line to confirm the range-bound state.
• Adjustment: For low-volatility stocks on daily charts, use a moderate Base Regression Length (e.g., 100) and tight Base Channel Width (e.g., 1.5). For choppy crypto markets, test shorter settings.
Optimization Strategies
• Timeframe Customization: Adjust ARC’s parameters to match your trading horizon. Short timeframes (e.g., 1-minute to 1-hour) benefit from lower Base Regression Length (20–50) and ATR Length (7–10) for agility, while longer timeframes (e.g., daily, weekly) favor higher values (100–200 and 14–21) for stability.
• Asset-Specific Tuning:
○ Stocks: Use longer lengths (e.g., 100–200) and moderate widths (e.g., 1.8) for stable equities; tweak ATR Length based on sector volatility (shorter for tech, longer for utilities).
○ FOREX: Set Base Regression Length to 50–100 and Base Channel Width to 1.5–2.0 for smoother trends; adjust RSI Length (e.g., 10–14) based on pair volatility.
○ Crypto: Opt for shorter lengths (e.g., 20–50) and wider widths (e.g., 2.0–3.0) to handle rapid price swings; use a shorter ATR Length (e.g., 7) for quick adaptation.
• Backtesting: Test ARC on historical data for your asset and timeframe to optimize settings. Evaluate how often price respects channels and whether breakouts yield profitable trades.
• Enhancements: Pair ARC with volume surges, key support/resistance levels, or candlestick patterns (e.g., doji at channel edges) for higher-probability setups.
Practical Considerations
ARC’s adaptability makes it suitable for diverse markets, but its performance hinges on proper calibration. Cryptocurrencies, with their high volatility, may require shorter, wider settings to capture rapid moves, while stocks on longer timeframes benefit from broader, smoother configurations. FOREX pairs often fall in between, depending on their inherent volatility. Experiment with the adjustable parameters to align ARC with your trading style and market conditions, ensuring it delivers the precision and reliability you need.
Deviation ChannelsIndicator Name: Deviation Channels (Dev Chan)
Why Use This Indicator?
Visualize Volatility Ranges:
The indicator plots Keltner Channels at four levels above and below an average line, letting you easily see how far price has deviated from a typical range. Each “dev” line highlights potential support or resistance during pullbacks or surges.
Color-Coded Clarity:
Each band shifts color intensity depending on whether the current price is trading above or below it, letting you spot breakouts and rejections at a glance. Meanwhile, the Fast SMA (default 10) also changes color – green if price is above, red if below – adding a quick momentum read.
Adjustable Source & Length:
Choose your input source (open, close, ohlc4, or hlc3) and set your Keltner length to suit different asset classes or timeframes. Whether you want a tighter, more reactive channel or a smoother, longer-term reading, the script adapts with minimal effort.
A Simple Trading Approach
Identify Trend with Fast SMA:
If the Fast SMA (default length 10) is green (price above it), treat that as a bullish environment. If it’s red (price below), favor bearish or neutral stances.
Wait for Price to Reach Lower/Upper Deviations:
In a bullish setup (Fast SMA green), watch for price to dip into one of the lower channels (e.g., -1 Dev or -2 Dev). Such pullbacks can become potential “buy the dip” zones if price stabilizes and resumes upward momentum.
Conversely, if the Fast SMA is red, watch for price to test the upper channels (1 Dev or 2 Dev). That might be a short opportunity or a place to close out any remaining longs before a deeper correction.
Manage Risk with Channel Levels:
Place stop-losses just beyond the next “dev” band to protect against volatility. For example, if you enter on a bounce at -1 Dev, consider placing a stop near -2 Dev or -3 Dev, depending on your risk tolerance.
Take Profits Gradually:
In an uptrend, you might scale out of positions as price moves toward higher lines (e.g., 1 Dev or 2 Dev). Conversely, if price fails to hold above the Fast SMA or repeatedly closes below a key band, it might be time to exit.
Disclaimer: No single indicator is foolproof. Always combine with sound risk management, observe multiple timeframes, and consider fundamental factors before making trading decisions. Experiment with the Keltner length and Fast SMA fastLength to find the sweet spot for your market and time horizon.
EM Yield Curve IndexThis script calculates the Emerging Markets (EM) Yield Curve Index by aggregating the 2-year and 10-year bond yields of major emerging economies. The bond yields are weighted based on each country's bond market size, with data sourced from TradingView. The yield curve is derived by subtracting the 2-year yield from the 10-year yield, providing insights into economic conditions, risk sentiment, and potential recessions in emerging markets. The resulting EM Yield Curve Index is plotted for visualization.
Note: In some cases, TradingView's TVC data did not provide a 2-year bond yield. When this occurred, the best available alternative yield (such as 3-month, 1-year or 4-year yields) was used to approximate the short-term interest rate for that country.
Momentum Volume Divergence (MVD) EnhancedMomentum Volume Divergence (MVD) Enhanced is a powerful indicator that detects price-momentum divergences and momentum suppression for reversal trading. Optimized for XRP on 1D charts, it features dynamic lookbacks, ATR-adjusted thresholds, and SMA confirmation. Signals include strong divergences (triangles) and suppression warnings (crosses). Includes a detailed user guide—try it out and share your feedback!
Setup: Add to XRP 1D chart with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA crossovers. See full guide for details!
Disclaimer: This indicator is for educational purposes only, not financial advice. Trading involves risk—use at your discretion.
Momentum Volume Divergence (MVD) Enhanced Indicator User Guide
Version: Pine Script v6
Designed for: TradingView
Recommended Use: XRP on 1-day (1D) chart
Date: March 18, 2025
Author: Herschel with assistance from Grok 3 (xAI)
Overview
The Momentum Volume Divergence (MVD) Enhanced indicator is a powerful tool for identifying price-momentum divergences and momentum suppression patterns on XRP’s 1-day (1D) chart. Plotted below the price chart, it provides clear visual signals to help traders spot potential reversals and trend shifts.
Purpose
Detect divergences between price and momentum for buy/sell opportunities.
Highlight momentum suppression as warnings of fading trends.
Offer actionable trading signals with intuitive markers.
Indicator Components
Main Plot
Volume-Weighted Momentum (vw_mom): Blue line showing momentum adjusted by volume.
Above 0 = bullish momentum.
Below 0 = bearish momentum.
Zero Line: Gray dashed line at 0, separating bullish/bearish zones.
Key Signals
Strong Bearish Divergence:
Marker: Red triangle at the top.
Meaning: Price makes a higher high, but momentum weakens, confirmed by a drop below the 5-day SMA.
Action: Potential sell/short signal.
Strong Bullish Divergence:
Marker: Green triangle at the bottom.
Meaning: Price makes a lower low, but momentum strengthens, confirmed by a rise above the 5-day SMA.
Action: Potential buy/long signal.
Bearish Suppression:
Marker: Orange cross at the top + red background.
Meaning: Strong bullish momentum with low volume in a volume downtrend, suggesting fading strength.
Action: Warning to avoid longs or exit early.
Bullish Suppression:
Marker: Yellow cross at the bottom + green background.
Meaning: Strong bearish momentum with low volume in a volume uptrend, suggesting fading weakness.
Action: Warning to avoid shorts or exit early.
Debug Plots (Optional)
Volume Ratio: Gray line (volume vs. its MA) vs. yellow line (threshold).
Momentum Threshold: Purple lines (positive/negative momentum cutoffs).
Smoothed Momentum: Orange line (raw momentum).
Confirmation SMA: Purple line (price trend confirmation).
Labels
Text labels (e.g., "Bear Div," "Bull Supp") mark detected patterns.
How to Use the Indicator
Step-by-Step Trading Process
1. Monitor the Chart
Load your XRP 1D chart with the indicator applied.
Observe the blue vw_mom line and signal markers.
2. Spot a Signal
Primary Signals: Look for red triangles (strong_bear) or green triangles (strong_bull).
Warnings: Note orange crosses (suppression_bear) or yellow crosses (suppression_bull).
3. Confirm the Signal
For Strong Bullish Divergence (Buy):
Green triangle appears.
Price closes above the 5-day SMA (purple line) and a recent swing high.
Optional: Volume ratio (gray line) exceeds the threshold (yellow line).
For Strong Bearish Divergence (Sell):
Red triangle appears.
Price closes below the 5-day SMA and a recent swing low.
Optional: Volume ratio (gray line) falls below the threshold (yellow line).
4. Enter the Trade
Long:
Buy at the close of the signal bar.
Stop loss: Below the recent swing low or 2 × ATR(14) below entry.
Short:
Sell/short at the close of the signal bar.
Stop loss: Above the recent swing high or 2 × ATR(14) above entry.
5. Manage the Trade
Take Profit:
Aim for a 2:1 or 3:1 risk-reward ratio (e.g., risk $0.05, target $0.10-$0.15).
Or exit when an opposite suppression signal appears (e.g., orange cross for longs).
Trailing Stop:
Move stop to breakeven after a 1:1 RR move.
Trail using the 5-day SMA or 2 × ATR(14).
Early Exit:
Exit if a suppression signal appears against your position (e.g., suppression_bull while short).
6. Filter Out Noise
Avoid trades if a suppression signal precedes a divergence within 2-3 days.
Optional: Add a 50-day SMA on the price chart:
Longs only if price > 50-SMA.
Shorts only if price < 50-SMA.
Example Trades (XRP 1D)
Bullish Trade
Signal: Green triangle (strong_bull) at $0.55.
Confirmation: Price closes above 5-SMA and $0.57 high.
Entry: Buy at $0.58.
Stop Loss: $0.53 (recent low).
Take Profit: $0.63 (2:1 RR) or exit on suppression_bear.
Outcome: Price hits $0.64, exit at $0.63 for profit.
Bearish Trade
Signal: Red triangle (strong_bear) at $0.70.
Confirmation: Price closes below 5-SMA and $0.68 low.
Entry: Short at $0.67.
Stop Loss: $0.71 (recent high).
Take Profit: $0.62 (2:1 RR) or exit on suppression_bull.
Outcome: Price drops to $0.61, exit at $0.62 for profit.
Tips for Success
Combine with Price Levels:
Use support/resistance zones (e.g., weekly pivots) to confirm entries.
Monitor Volume:
Rising volume (gray line above yellow) strengthens signals.
Adjust Sensitivity:
Too many signals? Increase div_strength_threshold to 0.7.
Too few signals? Decrease to 0.3.
Backtest:
Review 20-30 past signals on XRP 1D to assess performance.
Avoid Choppy Markets:
Skip signals during low volatility (tight price ranges).
Troubleshooting
No Signals:
Lower div_strength_threshold to 0.3 or mom_threshold_base to 0.2.
Check if XRP’s volatility is unusually low.
False Signals:
Increase sma_confirm_length to 7 or add a 50-SMA filter.
Indicator Not Loading:
Ensure the script compiles without errors.
Customization (Optional)
Change Colors: Edit color.* values (e.g., color.red to color.purple).
Add Alerts: Use TradingView’s alert menu for "Strong Bearish Divergence Confirmed," etc.
Test Other Assets: Experiment with BTC or ETH, adjusting inputs as needed.
Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion.
Setup: Use on XRP 1D with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA cross. Stop: 2x ATR(14). Profit: 2:1 RR or suppression exit. Full guide available separately!
Volume Predictor [PhenLabs]📊 Volume Predictor
Version: PineScript™ v6
📌 Description
The Volume Predictor is an advanced technical indicator that leverages machine learning and statistical modeling techniques to forecast future trading volume. This innovative tool analyzes historical volume patterns to predict volume levels for upcoming bars, providing traders with valuable insights into potential market activity. By combining multiple prediction algorithms with pattern recognition techniques, the indicator delivers forward-looking volume projections that can enhance trading strategies and market analysis.
🚀 Points of Innovation:
Machine learning pattern recognition using Lorentzian distance metrics
Multi-algorithm prediction framework with algorithm selection
Ensemble learning approach combining multiple prediction methods
Real-time accuracy metrics with visual performance dashboard
Dynamic volume normalization for consistent scale representation
Forward-looking visualization with configurable prediction horizon
🔧 Core Components
Pattern Recognition Engine : Identifies similar historical volume patterns using Lorentzian distance metrics
Multi-Algorithm Framework : Offers five distinct prediction methods with configurable parameters
Volume Normalization : Converts raw volume to percentage scale for consistent analysis
Accuracy Tracking : Continuously evaluates prediction performance against actual outcomes
Advanced Visualization : Displays actual vs. predicted volume with configurable future bar projections
Interactive Dashboard : Shows real-time performance metrics and prediction accuracy
🔥 Key Features
The indicator provides comprehensive volume analysis through:
Multiple Prediction Methods : Choose from Lorentzian, KNN Pattern, Ensemble, EMA, or Linear Regression algorithms
Pattern Matching : Identifies similar historical volume patterns to project future volume
Adaptive Predictions : Generates volume forecasts for multiple bars into the future
Performance Tracking : Calculates and displays real-time prediction accuracy metrics
Normalized Scale : Presents volume as a percentage of historical maximums for consistent analysis
Customizable Visualization : Configure how predictions and actual volumes are displayed
Interactive Dashboard : View algorithm performance metrics in a customizable information panel
🎨 Visualization
Actual Volume Columns : Color-coded green/red bars showing current normalized volume
Prediction Columns : Semi-transparent blue columns representing predicted volume levels
Future Bar Projections : Forward-looking volume predictions with configurable transparency
Prediction Dots : Optional white dots highlighting future prediction points
Reference Lines : Visual guides showing the normalized volume scale
Performance Dashboard : Customizable panel displaying prediction method and accuracy metrics
📖 Usage Guidelines
History Lookback Period
Default: 20
Range: 5-100
This setting determines how many historical bars are analyzed for pattern matching. A longer period provides more historical data for pattern recognition but may reduce responsiveness to recent changes. A shorter period emphasizes recent market behavior but might miss longer-term patterns.
🧠 Prediction Method
Algorithm
Default: Lorentzian
Options: Lorentzian, KNN Pattern, Ensemble, EMA, Linear Regression
Selects the algorithm used for volume prediction:
Lorentzian: Uses Lorentzian distance metrics for pattern recognition, offering excellent noise resistance
KNN Pattern: Traditional K-Nearest Neighbors approach for historical pattern matching
Ensemble: Combines multiple methods with weighted averaging for robust predictions
EMA: Simple exponential moving average projection for trend-following predictions
Linear Regression: Projects future values based on linear trend analysis
Pattern Length
Default: 5
Range: 3-10
Defines the number of bars in each pattern for machine learning methods. Shorter patterns increase sensitivity to recent changes, while longer patterns may identify more complex structures but require more historical data.
Neighbors Count
Default: 3
Range: 1-5
Sets the K value (number of nearest neighbors) used in KNN and Lorentzian methods. Higher values produce smoother predictions by averaging more historical patterns, while lower values may capture more specific patterns but could be more susceptible to noise.
Prediction Horizon
Default: 5
Range: 1-10
Determines how many future bars to predict. Longer horizons provide more forward-looking information but typically decrease accuracy as the prediction window extends.
📊 Display Settings
Display Mode
Default: Overlay
Options: Overlay, Prediction Only
Controls how volume information is displayed:
Overlay: Shows both actual volume and predictions on the same chart
Prediction Only: Displays only the predictions without actual volume
Show Prediction Dots
Default: false
When enabled, adds white dots to future predictions for improved visibility and clarity.
Future Bar Transparency (%)
Default: 70
Range: 0-90
Controls the transparency of future prediction bars. Higher values make future bars more transparent, while lower values make them more visible.
📱 Dashboard Settings
Show Dashboard
Default: true
Toggles display of the prediction accuracy dashboard. When enabled, shows real-time accuracy metrics.
Dashboard Location
Default: Bottom Right
Options: Top Left, Top Right, Bottom Left, Bottom Right
Determines where the dashboard appears on the chart.
Dashboard Text Size
Default: Normal
Options: Small, Normal, Large
Controls the size of text in the dashboard for various display sizes.
Dashboard Style
Default: Solid
Options: Solid, Transparent
Sets the visual style of the dashboard background.
Understanding Accuracy Metrics
The dashboard provides key performance metrics to evaluate prediction quality:
Average Error
Shows the average difference between predicted and actual values
Positive values indicate the prediction tends to be higher than actual volume
Negative values indicate the prediction tends to be lower than actual volume
Values closer to zero indicate better prediction accuracy
Accuracy Percentage
A measure of how close predictions are to actual outcomes
Higher percentages (>70%) indicate excellent prediction quality
Moderate percentages (50-70%) indicate acceptable predictions
Lower percentages (<50%) suggest weaker prediction reliability
The accuracy metrics are color-coded for quick assessment:
Green: Strong prediction performance
Orange: Moderate prediction performance
Red: Weaker prediction performance
✅ Best Use Cases
Anticipate upcoming volume spikes or drops
Identify potential volume divergences from price action
Plan entries and exits around expected volume changes
Filter trading signals based on predicted volume support
Optimize position sizing by forecasting market participation
Prepare for potential volatility changes signaled by volume predictions
Enhance technical pattern analysis with volume projection context
⚠️ Limitations
Volume predictions become less accurate over longer time horizons
Performance varies based on market conditions and asset characteristics
Works best on liquid assets with consistent volume patterns
Requires sufficient historical data for pattern recognition
Sudden market events can disrupt prediction accuracy
Volume spikes may be muted in predictions due to normalization
💡 What Makes This Unique
Machine Learning Approach : Applies Lorentzian distance metrics for robust pattern matching
Algorithm Selection : Offers multiple prediction methods to suit different market conditions
Real-time Accuracy Tracking : Provides continuous feedback on prediction performance
Forward Projection : Visualizes multiple future bars with configurable display options
Normalized Scale : Presents volume as a percentage of maximum volume for consistent analysis
Interactive Dashboard : Displays key metrics with customizable appearance and placement
🔬 How It Works
The Volume Predictor processes market data through five main steps:
1. Volume Normalization:
Converts raw volume to percentage of maximum volume in lookback period
Creates consistent scale representation across different timeframes and assets
Stores historical normalized volumes for pattern analysis
2. Pattern Detection:
Identifies similar volume patterns in historical data
Uses Lorentzian distance metrics for robust similarity measurement
Determines strength of pattern match for prediction weighting
3. Algorithm Processing:
Applies selected prediction algorithm to historical patterns
For KNN/Lorentzian: Finds K nearest neighbors and calculates weighted prediction
For Ensemble: Combines multiple methods with optimized weighting
For EMA/Linear Regression: Projects trends based on statistical models
4. Accuracy Calculation:
Compares previous predictions to actual outcomes
Calculates average error and prediction accuracy
Updates performance metrics in real-time
5. Visualization:
Displays normalized actual volume with color-coding
Shows current and future volume predictions
Presents performance metrics through interactive dashboard
💡 Note:
The Volume Predictor performs optimally on liquid assets with established volume patterns. It’s most effective when used in conjunction with price action analysis and other technical indicators. The multi-algorithm approach allows adaptation to different market conditions by switching prediction methods. Pay special attention to the accuracy metrics when evaluating prediction reliability, as sudden market changes can temporarily reduce prediction quality. The normalized percentage scale makes the indicator consistent across different assets and timeframes, providing a standardized approach to volume analysis.
Gold Price LevelsThis indicator identifies and displays key price levels for gold trading. It highlights important psychological and technical price points that often act as support and resistance levels.
Features
Automatically identifies and displays key price levels ending in 92, 84, 78, 55, 42, 27, and 00
Special emphasis on critical levels ending in 68, 32, and 10 with increased line width
Color-coded visualization: green for levels above current price, red for levels below
Customizable line style, width, and label visibility
Automatically adjusts to different price ranges (works with any gold price)
How to Use
This indicator helps gold traders identify potential support and resistance zones. Watch for price reactions at these levels for potential trade entries, exits, or stop placement. The thicker lines (68, 32, 10) often represent more significant price levels where stronger reactions may occur.
Perfect for both day traders and swing traders looking to optimize their gold trading strategy with key price levels.
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
Pivot P/N VolumesTitle: Pivot P/N Volumes
Short Title: PPNV
Description:
The "Pivot P/N Volumes" indicator is a minimalistic volume analysis tool designed to cut through market noise and highlight key volume events in a separate pane. It strips away conventional volume clutter, focusing on four distinct volume types with clear visual cues, making it ideal for traders seeking actionable insights without distractions.
Key Features:
Blue Bars: Pocket Pivot Volumes (PPV) - Up-day volumes exceeding the highest down-day volume of the last 10 down-days, signaling potential bullish strength.
Orange Bars: Pivot Negative Volumes - Down-day volumes greater than the highest up-day volume of the last 10 up-days, indicating significant bearish pressure.
Red Bars: Down-day volumes above the 50-period EMA of volume, highlighting above-average selling activity.
Green Bars: Up-day volumes above the 50-period EMA of volume, showing above-average buying interest.
Noise: All other volumes are muted as dark grey (down-days) or light grey (up-days) for easy filtering.
Volume Buy/Sell ChartVolume Buy/Sell Chart
This script visualizes the distribution of buying and selling volume within each candlestick, helping traders identify dominant market pressure at a glance. It separates volume into Buy Volume (Green) and Sell Volume (Red) using a unique calculation based on price movement within a candle.
Features:
✅ Customizable Bar Display: Choose to display 5, 10, or 100 bars using a simple dropdown selection.
✅ Buy & Sell Volume Calculation: The script determines buying and selling volume dynamically based on price action within the candle.
✅ Custom Volume Threshold for Alerts: Set a percentage threshold (0–100) to trigger alerts when buy or sell volume exceeds a predefined level.
✅ Color-Coded Histogram:
Green Bars: Represent the estimated buy volume.
Red Bars: Represent the estimated sell volume.
✅ Alerts Integration: Automatically detect strong buy or sell signals when the respective volume percentage exceeds your set threshold.
How It Works:
The script calculates total price movement within a candle.
It then estimates buying and selling volume ratios based on whether the price closes higher or lower than it opened.
Finally, it normalizes the buy/sell volume against the total volume and plots it as a column chart.
Usage Guide:
Add the script to your chart.
Select how many bars to display (5, 10, or 100).
Adjust the Custom Volume Percentage Threshold (default: 75%).
Watch for significant buy/sell volume imbalances that might indicate market turning points!
This tool is great for traders looking to analyze volume flow and market sentiment with a simple yet effective visualization. 🚀
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
JP225 Influence AnalyzerThis tool provides a way to assess how USDJPY and DJIA influence JP225, using standardization and linear regression for quantitative evaluation. It also detects deviations from the linear model and displays the results in a colored table.
Table Structure
Row 1: Current value of USDJPY and its change from the previous bar
Row 2: Current value of DJIA and its change from the previous bar
Row 3: Theoretical value of Nikkei 225 calculated using the least squares method from USDJPY
and DJIA, and its change from the previous bar
Row 4: Current value of the chart symbol (Nikkei 225) and its change from the previous bar
Background Color Meanings
A. Current Value Column (Column 2)
If USDJPY or DJIA significantly contributes to the change in the theoretical value of Nikkei 225, the cell turns blue (increase) or red (decrease). The threshold is 1.5.
If the current value of Nikkei 225 increases, it turns blue; if it decreases, it turns red.
B. Change Value Column (Column 3)
If there is a discrepancy between the change in the theoretical value and the actual change of Nikkei 225, the cell turns yellow (moderate discrepancy: threshold 20) or red (significant discrepancy: threshold 50).
Judgment Based on Current Value Column (Column 2)
If the color of USDJPY or DJIA matches the color of Nikkei 225, that symbol is the main cause.
If there is no match, the main cause is "other factors."
Judgment Based on Change Column (Column 3)
Yellow: Suggests that other factors may be influencing the price.
Red: Strongly indicates that other factors are the main cause.
Parameter Descriptions Parameter Descriptions
symbol_x: Symbol for USDJPY (default: "SAXO:USDJPY")
symbol_y: Symbol for DJIA (default: "OSE:DJIA1!")
threshold_value1: Threshold for determining the influence of USDJPY and DJIA (blue/red color) (default: 1.5)
threshold_value2: Threshold for detecting specific price movements in Nikkei 225 (yellow color) (default: 20)
threshold_value3: Threshold for detecting significant price movements in Nikkei 225 (red color) (default: 50)
data_count: Number of past data points used for calculations (default: 10)
インジケーターの概要
このインジケーターは、日経225先物やCFDの値動きの主な原因が
以下のどれに起因するのかをリアルタイムで表示します
1. ドル円 (USDJPY)
2. ダウ (DJIA)
3. その他の要因（突発的なニュース、225の節目価格への攻防など）
テーブルの構成
1行目 ドル円の現在値と前足からの増減
2行目 ダウの現在値と前足からの増減
3行目 ドル円とダウから最小二乗法で算出した225の理論値とその増減
4行目 チャート銘柄（225）の現在値と前足からの増減
背景色の意味
1. 現在値列 (2列目):ドル円またはダウが225の理論値増減に大きく寄与した場合、
それぞれ青（増加）または赤（減少）に変化。閾値は1.5
225の現在値が増加すれば青、減少すれば赤。
2. 増減値列 (3列目):225の理論値増減と実際の増減が乖離した場合、
黄（中程度：閾値は20）または赤（大幅：閾値は50）に変化。
現在値列(2列目)での判断:
1. 銘柄（ドル円またはダウ）の色が225の色と一致する場合、その銘柄が主な原因。
2. 一致しない場合、主な原因は「その他」。
増減列(3列目)での判断:
黄色 その他の要因が影響している可能性。
赤色 その他の要因が主な原因と強く示唆。
パラメータの説明
symbol_x ドル円のシンボル（デフォルト: "SAXO:USDJPY"）
symbol_y ダウのシンボル（デフォルト: "OSE:DJIA1!"）
threshold_value1 ドル円とダウの影響を判定する(青/赤色)閾値（デフォルト: 1.5）
threshold_value2 225固有の値動きを判定する(黄色)閾値（デフォルト: 20）
threshold_value3 225固有の大きな値動きを判定する(赤色)閾値（デフォルト: 50）
data_count 計算に使用する過去データの本数（デフォルト: 10）
