PLR-Z For Loop🧠 Overview
PLR-Z For Loop is a trend-following indicator built on the Power Law Residual Z-score model of Bitcoin price behavior. By measuring how far price deviates from a long-term power law regression and applying a custom scoring loop, this tool identifies consistent directional pressure in market structure. Designed for BTC, this indicator helps traders align with macro trends.
🧩 Key Features
Power Law Residual Model: Tracks deviations of BTC price from its long-term logarithmic growth curve.
Z-Score Normalization: Applies long-horizon statistical normalization (400/1460 bars) to smooth residual deviations into a usable trend signal.
Loop-Based Trend Filter: Iteratively scores how often the current Z-score exceeds prior values, emphasizing trend persistence over volatility.
Optional Smoothing: Toggleable exponential smoothing helps filter noise in choppier market conditions.
Directional Regime Coloring: Aqua (bullish) and Red (bearish) visuals reinforce trend alignment across plots and candles.
🔍 How It Works
Power Law Curve: Price is compared against a logarithmic regression model fitted to historical BTC price evolution (starting July 2010), defining structural support, resistance, and centerline levels.
Residual Z-Score: The residual is calculated as the log-difference between price and the power law center.
This residual is then normalized using a rolling mean (400 days) and standard deviation (1460 days) to create a long-term Z-score.
Loop Scoring Logic:
A loop compares the current Z-score to a configurable number of past bars.
Each higher comparison adds +1, and each lower one subtracts -1.
The result is a trend persistence score (z_loop) that grows with consistent directional momentum.
Smoothing Option: A user-defined EMA smooths the score, if enabled, to reduce short-term signal noise.
Signal Logic:
Long signal when trend score exceeds long_threshold.
Short signal when score drops below short_threshold.
Directional State (CD): Internally manages the current market regime (1 = long, -1 = short), controlling all visual output.
🔁 Use Cases & Applications
Macro Trend Alignment: Ideal for traders and analysts tracking Bitcoin’s structural momentum over long timeframes.
Trend Persistence Filter: Helps confirm whether the current move is part of a sustained trend or short-lived volatility.
Best Suited for BTC: Built specifically on the BNC BLX price history and Bitcoin’s power law behavior. Not designed for use with other assets.
✅ Conclusion
PLR-Z For Loop reframes Bitcoin’s long-term power law model into a trend-following tool by scoring the persistence of deviations above or below fair value. It shifts the focus from valuation-based mean reversion to directional momentum, making it a valuable signal for traders seeking high-conviction participation in BTC’s broader market cycles.
⚠️ Disclaimer
The content provided by this indicator is for educational and informational purposes only. Nothing herein constitutes financial or investment advice. Trading and investing involve risk, including the potential loss of capital. Always backtest and apply risk management suited to your strategy.
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CHN BUY SELL with EMA 200Overview
This indicator combines RSI 7 momentum signals with EMA 200 trend filtering to generate high-probability BUY and SELL entry points. It uses colored candles to highlight key market conditions and displays clear trading signals with built-in cooldown periods to prevent signal spam.
Key Features
Colored Candles: Visual momentum indicators based on RSI 7 levels
Trend Filtering: EMA 200 confirms overall market direction
Signal Cooldown: Prevents over-trading with adjustable waiting periods
Clean Interface: Simple BUY/SELL labels without clutter
How It Works
Candle Coloring System
Yellow Candles: Appear when RSI 7 ≥ 70 (overbought momentum)
Purple Candles: Appear when RSI 7 ≤ 30 (oversold momentum)
Normal Candles: All other market conditions
Trading Signals
BUY Signal: Triggered when closing price > EMA 200 AND yellow candle appears
SELL Signal: Triggered when closing price < EMA 200 AND purple candle appears
Signal Cooldown
After a BUY or SELL signal appears, the same signal type is suppressed for a specified number of candles (default: 5) to prevent excessive signals in ranging markets.
Settings
RSI 7 Length: Period for RSI calculation (default: 7)
RSI 7 Overbought: Threshold for yellow candles (default: 70)
RSI 7 Oversold: Threshold for purple candles (default: 30)
EMA Length: Period for trend filter (default: 200)
Signal Cooldown: Candles to wait between same signal type (default: 5)
How to Use
Apply the indicator to your chart
Look for yellow or purple colored candles
For LONG entries: Wait for yellow candle above EMA 200, then enter BUY when signal appears
For SHORT entries: Wait for purple candle below EMA 200, then enter SELL when signal appears
Use appropriate risk management and position sizing
Best Practices
Works best on timeframes M15 and higher
Suitable for Forex, Gold, Crypto, and Stock markets
Consider market volatility when setting stop-loss and take-profit levels
Use in conjunction with proper risk management strategies
Technical Details
Overlay: True (plots directly on price chart)
Calculation: Based on RSI momentum and EMA trend analysis
Signal Logic: Combines momentum exhaustion with trend direction
Visual Feedback: Colored candles provide immediate market condition awareness
Regression Channel (Interactive)Weighted Interactive Regression Channel (WIRC)
Overview
The Weighted Interactive Regression Channel improves on traditional regression channels by emphasizing key price points through intelligent weighting. Instead of treating all candles equally, WIRC adapts to market dynamics for better trend detection and channel accuracy.
Key Differences from Standard Channels
Weighted vs. Equal: Prioritizes significant events over uniform weighting
Dynamic vs. Static: Adapts in real time to market changes
Accurate vs. Basic: Reduces noise, enhances signal clarity
Customizable vs. Fixed: Full control over weights and visuals
Weighting Methods
Direction Change – Highlights reversal points via local peaks/troughs
Volume-Based – Emphasizes high-volume candles, ideal for breakouts
Price Range – Weights wide-range candles to capture volatility
Time Decay – Prioritizes recent data for current market relevance
Interactive Features
Data Range: Set channel start/end over 1–500 bars
Visuals: Line styles, color coding, fill options, reference lines
Stats: Slope, R², standard deviation, point count, weight method
Technical Implementation
Weighted Regression Formula: Uses weights for slope, intercept, and deviation
Channel Lines: Center = weighted regression; bounds = ± deviation × multiplier
Usage Scenarios
Trend Analysis: Use Direction Change + longer range
Breakouts: Use Volume weighting + fill + boundary watching
Volatility: Apply Price Range weighting + monitor standard deviation
Current Market: Use Time Decay + shorter ranges + stat display
Parameter Tips
Channel Width:
Narrow (1.0–1.5): Responsive
Standard (1.5–2.0): Balanced
Wide (2.0–3.0+): Conservative
Weighting Intensity:
Conservative (1.5–2.0)
Moderate (2.0–3.0)
Aggressive (3.0+)
Advanced Use
Multi-Timeframe: Use different weightings per timeframe
Market Structure: Detect swings, institutional zones
Risk Management: Dynamic S/R levels, volatility-driven sizing
Best Practices
Start with Direction Change
Test different ranges
Monitor stats
Combine with other indicators
Adjust to market context
Recalibrate regularly
Conclusion
WIRC delivers a smarter, more adaptive view of price action than standard regression tools. With real-time customization and multiple weighting options, it’s ideal for traders seeking precision across strategies—trend tracking, breakout confirmation, or volatility insight.
Supply/Demand Zones + Engulfment-based ExecutionSupply/Demand Zones + Engulfment-Based Execution
Strategy Overview
This strategy combines institutional trading concepts—supply/demand zones and engulfing candle patterns—to generate high-probability long and short trade setups. The system uses aggregated price action to identify potential reversal zones and confirms entries with engulfing candle patterns, ensuring trades are only taken when market structure shows commitment in the direction of the trade.
Core Concepts
• Supply & Demand Zones: These are automatically detected by analyzing aggregated bullish and bearish candle structures over user-defined intervals. Supply zones are formed after bearish continuation patterns; demand zones appear after bullish continuation patterns.
• Engulfing Entries: Once price enters a zone, the strategy waits for a bullish engulfing pattern (in a demand zone) or a bearish engulfing pattern (in a supply zone) before executing a trade. This adds confirmation and reduces false signals.
• Risk Management: Stop-loss is placed at the low (for long trades) or high (for short trades) of the engulfed candle. Take-profit can be calculated using a fixed R-multiple (risk-to-reward ratio) or a user-defined target price.
Key Features
Fully customizable aggregation factor for zone detection
Visual zone boxes, entry/SL/TP boxes, and engulfing pattern labels
Optional removal of mitigated zones for cleaner charting
Configurable trade mode (Long only, Short only, or Both)
Support for trading sessions and date filtering
Alerts for price entering supply or demand zones
How to Use
Select Aggregation Factor: Choose how many candles to group together for identifying key zones (e.g., 4x timeframe).
Enable Zones: Turn on supply and/or demand zones as needed.
Set Execution Parameters:
– Choose R-multiple (e.g., 2:1 risk-reward)
– Or use a fixed take-profit price
Define Trade Time Window:
– Set the date and time ranges to restrict execution
– Use Start Hour and End Hour to limit trades to specific sessions (e.g., London/New York)
Run on Desired Timeframe: Typically used on 15m–4H charts, depending on your strategy and the asset’s volatility.
Ideal For
• Traders using Smart Money Concepts (SMC)
• Those who value high-confluence entries
• Intraday to swing traders looking for structure-based automation
⚠️ Important Notes
• The strategy requires engulfing confirmation within the zone to enter a position.
• This script does not repaint and executes trades on a bar close basis.
• Backtest results may vary based on session filters and aggregation factor.
© Attribution
This strategy was developed by The_Forex_Steward and is licensed under the Mozilla Public License 2.0.
You are free to use, modify, and distribute it under the terms of that license.
Candle Count RSI📈 Candle Count RSI — A Dual-Perspective Momentum Engine
The Candle Count RSI is a custom-built momentum oscillator that expands on the classic Relative Strength Index (RSI) by introducing a directional-only variant that tracks the frequency of bullish or bearish closes, rather than price magnitude. It gives traders a second lens through which to evaluate momentum, trend conviction, and subtle divergences—often invisible to traditional price-based RSI.
💡 What Makes It Unique?
While the standard RSI is sensitive to the size of price changes, the Candle Count RSI is magnitude-blind. It counts candle closes above/below open over a lookback period, generating a purer signal of directional consistency. To enhance signal fidelity, it includes a streak amplifier, dynamically weighting extended runs of green or red candles to reflect intensity of market bias—without introducing artificial price sensitivity.
This dual-RSI approach allows for:
- Divergence detection between directional bias and price magnitude.
- Smoother trend confirmation in choppy markets.
- Cleaner visual cues using dynamic glow and background logic.
📐 How Standard RSI Actually Works (Not What You Think)
RSI doesn’t just check if price went up or down over a span—it checks each individual candle and tracks whether it closed higher or lower than the one before. Here's how it works under the hood:
1.) For each bar, it calculates the change from the previous close.
2.) It separates those changes into gains (upward moves) and losses (downward moves).
3.) Then it computes a smoothed average of those gains and losses (usually using an RMA).
4.) It calculates the Relative Strength (RS) as:
RS = AvgGain / AvgLoss
5.) Finally, it plugs that into the RSI formula:
RSI = 100 - (100 / (1 + RS))
⚖️ What Does the 50 Line Mean?
- The RSI scale runs from 0 to 100, but 50 is the true neutral zone:
- RSI > 50 means average gains outweigh average losses over the period.
- RSI < 50 means losses dominate.
- RSI ≈ 50? The market is balanced—momentum is indecisive, no clear trend bias.
- This makes 50 a powerful midline for trend filters, directional bias tools, and divergence detection—especially when paired with alternative RSI logic like Candle Count RSI.
🔧 Inputs and Customization
- Everything is fully modular and customizable:
🧠 Core Settings
- RSI Length: Used for both the standard RSI and Candle Count RSI.
📉 Standard RSI
- Classic RSI calculation based on price changes.
- Optional WMA smoothing to reduce noise.
- Glow effect toggle with custom intensity.
🕯 Candle Count RSI
- Computes RSI using only the count of up/down candles.
- Optional smoothing for stability.
- Amplifies streaks (e.g., multiple consecutive bullish candles increase strength).
- Glow effect toggle with adjustable strength.
🎇 Glow Visuals
- Background glow (subpane and/or main chart).
- Fades based on RSI distance from the 50 midpoint.
- Independent color settings for bull and bear bias.
🧬 Divergence Zones
- Detects when Candle RSI and Standard RSI diverge.
- Highlights:
- Bullish Divergence: Candle RSI > 50, Standard RSI < threshold.
- Bearish Divergence: Candle RSI < 50, Standard RSI > threshold.
- Background fill optionally shown in subpane and/or main chart.
📊 Directional Histogram
- MACD-style histogram showing the difference between the two RSI lines.
- Color-coded based on directional agreement:
- Both rising → green.
- Both falling → red.
- Conflict → yellow.
🧠 Under the Hood — How It Works
🔹 Standard RSI
- Classic ta.rsi() applied to close prices, optionally WMA-smoothed.
🔹 Candle Count RSI (CCR)
- Counts how many candles closed up/down over the period.
- Computes a magnitude-free RSI from these counts.
- Applies a streak-based multiplier to exaggerate trend strength during consecutive green/red runs.
- Optionally smoothed with WMA to create a clean signal line.
- This makes CCR ideal for detecting true directional bias without being faked out by volatile price spikes.
🔹 Divergence Logic
- When Candle RSI and Standard RSI disagree strongly across defined thresholds, background fills highlight early signs of momentum decay or hidden accumulation/distribution.
🔹 Glow Logic
- Glow zones are controlled by a master toggle and drawn with dynamic transparency:
- Further from 50 = stronger conviction = darker glow.
- Shows up in subpane and/or main chart depending on user preference.
📷 Suggested Use Case / Visual Setup
- Use in conjunction with your primary price action system.
- Watch for divergences between the Candle Count RSI and Standard RSI for early trend reversals.
- Use glow bias zones on the main chart to get subconscious directional cues during fast scalping.
- Histogram helps you confirm when both RSI variants agree—useful during strong trending conditions.
🛠️ Tip for Traders
- This tool isn’t trying to “predict” price. It’s designed to visualize hidden market psychology—when buyers are showing up with consistent pressure, or when momentum has a disconnect between conviction and magnitude. Use this to filter entries, spot weak rallies, or sense when a trend is about to break down.
⚠️ WARNING
- Not for use with Heikin Ashi, Renko, etc.).
🧠 Summary
Candle Count RSI is not just another mashup—it's a precision-built, dual-perspective oscillator that captures directional conviction using real candle behavior. Whether you're scalping intraday or swing trading momentum, this script helps clarify trend integrity and exposes hidden weaknesses with elegance and clarity.
—
🛠️ Built by: Sherlock_MacGyver
Feel free to share feedback or reach out if you'd like to collaborate on custom features.
Auto Fractal [theUltimator5]This indicator is what I call the Auto Fractal. It is a unique algorithm that looks back in time, finds a segment on the chart that closest matches the recent price action, then projects the price forwards. It effectively finds chart patterns and shows you what the price did the last time the same/similar chart pattern was observed.
Creating an algorithm to match abstract curves to other abstract curves and provide a confidence score was the fundamental problem that needed to be solved in order to create this indicator, which curve matches with surprising accuracy.
The most effective method to "curve match" that I found is the Pearson Coefficient, set by a segment length and a lookback period. After the highest coefficient curve is located, the curve then gets scaled and offset to match the current price.
The past segment is drawn over the current price (orange line), giving a visualization of the two curves and how closely they match each other. The indicator then projects the price forwards in time based on the price action of the chart from the historical segment (dashed fuchsia line).
A bounding box also gets drawn around the historical segment to give you a clear visual of where the price is getting pulled from for proper analysis and ease of use.
The Pearson Coefficient % is shown in a table in the top right-hand corner of the chart and can be toggled off if desired. The values range from -100% (perfectly inverse correlation) to +100% (perfectly correlated) with 0 meaning no correlation whatsoever. The closer to +100% the value is, the better the segment match.
As with most/all of my indicators, user interface and simplicity was at the top of my priority list. I designed this to be easily readable and intuitive to both novice and veteran traders, without cluttering the chart.
Note:
This indicator is extremely heavy in terms of memory usage due to nested for loops, and takes several seconds to initially load the chart overlay. If the lookback period is increased too high (>600) then the indicator may time out and fail to load anything. If nothing loads on the chart, try reducing the lookback length and wait up to 10 seconds for lines to appear.
System 0530 - Stoch RSI Strategy with ATR filterStrategy Description: System 0530 - Multi-Timeframe Stochastic RSI with ATR Filter
Overview:
This strategy, "System 0530," is designed to identify trading opportunities by leveraging the Stochastic RSI indicator across two different timeframes: a shorter timeframe for initial signal triggers (assumed to be the chart's current timeframe, e.g., 5-minute) and a longer timeframe (15-minute) for signal confirmation. It incorporates an ATR (Average True Range) filter to help ensure trades are taken during periods of adequate market volatility and includes a cooldown mechanism to prevent rapid, successive signals in the same direction. Trade exits are primarily handled by reversing signals.
How It Works:
1. Signal Initiation (e.g., 5-Minute Timeframe):
Long Signal Wait: A potential long entry is considered when the 5-minute Stochastic RSI %K line crosses above its %D line, AND the %K value at the time of the cross is at or below a user-defined oversold level (default: 30).
Short Signal Wait: A potential short entry is considered when the 5-minute Stochastic RSI %K line crosses below its %D line, AND the %K value at the time of the cross is at or above a user-defined overbought level (default: 70). When these conditions are met, the strategy enters a "waiting state" for confirmation from the 15-minute timeframe.
2. Signal Confirmation (15-Minute Timeframe):
Once in a waiting state, the strategy looks for confirmation on the 15-minute Stochastic RSI within a user-defined number of 5-minute bars (wait_window_5min_bars, default: 5 bars).
Long Confirmation:
The 15-minute Stochastic RSI %K must be greater than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be below a user-defined threshold (stoch_15min_long_entry_level, default: 40).
Short Confirmation:
The 15-minute Stochastic RSI %K must be less than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be above a user-defined threshold (stoch_15min_short_entry_level, default: 60).
3. Filters:
ATR Volatility Filter: If enabled, trades are only confirmed if the current ATR value (converted to ticks) is above a user-defined minimum threshold (min_atr_value_ticks). This helps to avoid taking signals during periods of very low market volatility. If the ATR condition is not met, the strategy continues to wait for the condition to be met within the confirmation window, provided other conditions still hold.
Signal Cooldown Filter: If enabled, after a signal is generated, the strategy will wait for a minimum number of bars (min_bars_between_signals) before allowing another signal in the same direction. This aims to reduce overtrading.
4. Entry and Exit Logic:
Entry: A strategy.entry() order is placed when all trigger, confirmation, and filter conditions are met.
Exit: This strategy primarily uses reversing signals for exits. For example, if a long position is open, a confirmed short signal will close the long position and open a new short position. There are no explicit take profit or stop loss orders programmed into this version of the script.
Key User-Adjustable Parameters:
Stochastic RSI Parameters: RSI Length, Stochastic RSI Length, %K Smoothing, %D Smoothing.
Signal Trigger & Confirmation:
5-minute %K trigger levels for long and short.
15-minute %K confirmation thresholds for long and short.
Wait window (in 5-minute bars) for 15-minute confirmation.
Filters:
Enable/disable and configure the Signal Cooldown filter (minimum bars between signals).
Enable/disable and configure the ATR Volatility filter (ATR period, minimum ATR value in ticks).
Strategy Parameters:
Leverage Multiplier (Note: This primarily affects theoretical position sizing for backtesting calculations in TradingView and does not simulate actual leveraged trading risks).
Recommendations for Users:
Thorough Backtesting: Test this strategy extensively on historical data for the instruments and timeframes you intend to trade.
Parameter Optimization: Experiment with different parameter settings to find what works best for your trading style and chosen markets. The default values are starting points and may not be optimal for all conditions.
Understand the Logic: Ensure you understand how each component (Stochastic RSI on different timeframes, ATR filter, cooldown) interacts to generate signals.
Risk Management: Since this version does not include explicit stop-loss orders, ensure you have a clear risk management plan in place if trading this strategy live. You might consider manually adding stop-loss orders through your broker or using TradingView's separate strategy order settings for stop-loss if applicable.
Disclaimer:
This strategy description is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Trading involves significant risk of loss. Always do your own research and understand the risks before trading.
NDOG & NWOG Indicatorndicator automatically identifies and displays New Day Opening Gaps (NDOG) and New Week Opening Gaps (NWOG) directly on your chart. It focuses on gaps based on specific session times in the New York (NY) timezone.
Key Features:
NDOG: Identifies the gap between the NY 4:59 PM (daily close) and the NY 6:00 PM (daily open).
NWOG: Identifies the gap between the Friday NY 4:59 PM (weekly close) and the Sunday NY 6:00 PM (weekly open).
Draws customizable lines for the high and low levels of each gap.
Option to show an additional mid-level line for each gap.
Includes options for line colors, styles, and width.
Allows filtering gaps by a minimum size.
Control the maximum number of recent NDOGs and NWOGs displayed.
Optionally shows text labels on the lines and a summary table on the chart.
This tool can help traders visualize potential areas of interest related to these specific opening gaps.
Note: Calculations are based on the "America/New_York" timezone.
Disclaimer: Trading involves risk and may not be suitable for all investors. This indicator is provided for informational and educational purposes only and does not constitute financial advice or a recommendation to trade. Use at your own risk.
Last Week's APM & Daily % Move(Corrected)Last Week's Average Price Movement + Daily Percentage Move (based on NY time)
This indicator accurately displays last week's Average Pip Movement (APM) consistently across all timeframes and tracks the true daily percentage move relative to that APM in a clear table in the top-right corner.
Key Features:
-Consistent Last Week's APM: Calculates the average pip movement from Monday to Friday of the previous trading week (based on daily wick-to-wick ranges, divided by 5). This APM value is now stable and the same across all chart timeframes.
-Accurate Live Daily % Move: Tracks the maximum percentage the price has moved (either up or down) since the 5 PM New York time daily open, compared to last week's APM. The percentage holds the maximum value reached during the day and resets at the next 5 PM NY open.
-NY Time Alignment: All time-based calculations are aligned with the New York time zone
Pip Adjustment: Automatically adjusts for JPY pairs.
⚠️ Important: For the intended display and relevance of the daily percentage move, this indicator is best used on timeframes 4-hour and under. On Daily and Weekly timeframes, the APM display will show a message indicating this.
We hope this indicator enhances your trading analysis.
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
Prev Candle Before Biggest Body (3-7am EST)This indicator automatically identifies and marks, for each trading day, the candle immediately preceding the largest open-to-close movement (in pips) during the key London session window from 3:00am to 7:00am EST (New York time). The largest candle is determined by the absolute difference between its open and close prices, measured in pips. The candle just before this “biggest” move is highlighted with a distinctive pink flag above the bar. This tool is especially useful for traders seeking to analyze pre-breakout price action or to identify key levels and setups that occur right before significant volatility during the early London session.
3 Bar Reversal3 Bar Reversal
This pattern is described in John Carter's "Mastering the Trade"
The 3 Bar Reversal indicator is a simple but effective price action tool designed to highlight potential short-term reversals in market direction. It monitors consecutive bar behavior and identifies turning points based on a three-bar pattern. This tool can assist traders in spotting trend exhaustion or early signs of a reversal, particularly in scalping or short-term trading strategies.
How It Works
This indicator analyzes the relationship between consecutive bar closes:
It counts how many bars have passed since the price closed higher than the previous close (barssince(close >= close )) — referred to as an "up streak".
It also counts how many bars have passed since the price closed lower than the previous close (barssince(close <= close )) — known as a "down streak".
A reversal condition is met when:
There have been exactly 3 bars in a row moving in one direction (up or down), and
The 4th bar closes in the opposite direction.
When this condition is detected, the script performs two actions:
Plots a triangle on the chart to signal the potential reversal:
A green triangle below the bar for a possible long (buy) opportunity.
A red triangle above the bar for a possible short (sell) opportunity.
Triggers an alert condition so users can set notifications for when a reversal is detected.
Interpretation
Long Signal: The market has printed 3 consecutive lower closes, followed by a higher close — suggesting bullish momentum may be emerging.
Short Signal: The market has printed 3 consecutive higher closes, followed by a lower close — indicating possible bearish momentum.
These patterns are common in market retracements and can act as confirmation signals when used with other indicators such as RSI, MACD, support/resistance, or volume analysis.
Usage Examples
Scalping: Use the reversal signal to quickly enter short-term trades after a short-term exhaustion move.
Swing Trading: Combine this with trend indicators (e.g., moving averages) to time pullbacks within larger trends.
Confirmation Tool: Use this indicator alongside candlestick patterns or support/resistance zones to validate entry or exit points.
Alert Setup: Enable alerts based on the built-in alertcondition to receive instant notifications for potential trade setups.
Limitations
The 3-bar reversal logic does not guarantee a trend change; it signals potential reversals, which may need confirmation.
Best used in conjunction with broader context such as trend direction, market structure, or other technical indicators.
COT-Index-NocTradingCOT Index Indicator
The COT Index Indicator is a powerful tool designed to visualize the Commitment of Traders (COT) data and offer insights into market sentiment. The COT Index is a measurement of the relative positioning of commercial traders versus non-commercial and retail traders in the futures market. It is widely used to identify potential market reversals by observing the extremes in trader positioning.
Customizable Timeframe: The indicator allows you to choose a custom time interval (in months) to visualize the COT data, making it flexible to fit different trading styles and strategies.
How to Use:
Visualize Market Sentiment: A COT Index near extremes (close to 0 or 100) can indicate potential turning points in the market, as it reflects extreme positioning of different market participant groups.
Adjust the Time Interval: The ability to adjust the time interval (in months) gives traders the flexibility to analyze the market over different periods, which can be useful in detecting longer-term trends or short-term shifts in sentiment.
Combine with Other Indicators: To enhance your analysis, combine the COT Index with your technical analysis.
This tool can serve as an invaluable addition to your trading strategy, providing a deeper understanding of the market dynamics and the positioning of major market participants.
VIDYA (Chande)This script brings you VIDYA – the Variable Index Dynamic Average, developed by Tushar Chande. It’s not your typical moving average. Unlike the standard SMA or EMA, VIDYA adapts its speed and smoothness based on real-time market momentum using the Chande Momentum Oscillator (CMO).
Think of it like a moving average that gets faster during strong trends and slows down during sideways or choppy markets — just like how a smart trader would!
🧠 What Makes VIDYA Different?
Traditional moving averages use fixed smoothing, so they lag more during big moves or chop during weak trends.
VIDYA fixes that by adapting its behavior dynamically:
When momentum is strong → VIDYA reacts faster 🚀
When momentum is weak → VIDYA smooths out the noise 🧘
⚙️ How It Works (Explained Simply):
1️⃣ CMO Calculation (Chande Momentum Oscillator):
We look at the past cmoLength candles (default 9) and:
i) Add up all the positive price changes (gains)
ii) Add up all the negative price changes (losses)
iii) Use those to compute a normalized momentum score between -100 and +100
📌 CMO = (Gains - Losses) / (Gains + Losses)
• This gives us a momentum reading that powers the next step.
2️⃣ Dynamic Alpha Smoothing:
• We convert the absolute value of the CMO into an alpha — this is the "speed" of the VIDYA.
📌 Higher momentum = higher alpha → faster response
📌 Lower momentum = lower alpha → smoother behavior
3️⃣ VIDYA Formula:
• Finally, we apply the smoothing:
📌 VIDYA = α × Price + (1 - α) × Previous VIDYA
• This equation continuously adapts to market behavior — trending or ranging.
📊 What’s Plotted?
🟠 The VIDYA Line:
A smooth, responsive line plotted on your price chart that adjusts in real-time with price momentum.
🔎 How to Use It:
✅ Use it like a moving average, but smarter:
• Price > VIDYA and rising → Trend is likely up
• Price < VIDYA and falling → Trend is likely down
• Flat VIDYA = Possible consolidation or sideways market
✅ Combine with:
• Breakout strategies (VIDYA confirms momentum)
• Reversal entries (look for price crossing VIDYA)
• Volatility filters (ignore signals when VIDYA flattens)
🧪 Bonus Tip:
Pair this with a volume indicator (like my Volume Confirmation Bars or Volume Strength Highlight) to confirm whether momentum is backed by real participation or just a fakeout.
📩 Want alerts, dual-timeframe overlays, or VIDYA with other base inputs (like typical price or HLC3)? Let me know — happy to expand this for your setup!
Stay adaptive, not reactive — trade smarter with VIDYA! 🧠📉📈
Volume Strength HighlightThis simple script helps you quickly see when volume is strong or weak on the chart — it highlights the candles based on how the current volume compares to the recent average 📊
🔍 Here's what it does:
Calculates a 20-bar average volume
Marks candles green or red if volume is much higher than average (more than 1.5x)
Marks candles gray if volume is very low (less than 0.5x the average)
Normal candles stay unchanged
You can also turn on a basic volume plot in a separate panel if you want to compare visually (just toggle it in settings).
⚠️ It’s not a buy/sell signal — just a helper to see when the market is waking up or going quiet.
Not perfect but works well with other indicators! Let me know if you like it or have ideas to add more 💡
Market Sleep ZonesHey traders 👋
This script shows when the market is in a "sleeping" or low volatility phase. I call it Market Sleep Zones 😴
It looks at the average price movement over a window (default 20 bars), and if the price changes are small (under a % threshold you set), it highlights that area on the chart with a soft green background.
💡 This can help spot moments when the market is quiet — maybe before a breakout or just moving sideways.
It also places labels to mark where these zones start and end, so it's easy to track.
You can change:
The window size (how many bars to look back)
The breath depth (how much price is allowed to move before it’s "not sleeping" anymore)
Not perfect, but helpful if you want to avoid getting chopped in low-volatility zones or want to prepare for when the market "wakes up" 😄
Let me know if you find it useful or have ideas to improve it!
Volume Spike Alert & Overlay"Volume Spike Alert & Overlay" highlights unusually high trading volume on a chart. It calculates whether the current volume exceeds a user-defined percentage above the historical average and triggers an alert if it does. The information is also displayed in a customizable on-screen table.
What It Does
Monitors volume for each bar and compares it to an average over a user-defined lookback period.
Supports multiple smoothing methods (SMA, EMA, WMA, RMA) for calculating the average volume.
Triggers an alert when current volume exceeds the threshold percentage above the average.
Displays a table on the chart with:
Current Volume
Average Volume
Threshold Percentage
Optional empty row for spacing/formatting
How It Works
User Inputs:
lookbackPeriods: Number of bars used to calculate the average volume.
thresholdPercent: % above the average that triggers a volume spike alert.
smoothingType: Type of moving average used for volume calculation.
textColor, bgColor: Formatting for the display table.
tablePositionInput: Where the table appears on the chart (e.g., Bottom Right).
Toggles for showing/hiding parts of the table.
Volume Calculations:
Calculates current bar's volume.
Calculates average volume using the selected smoothing method.
Computes the threshold: avgVol * (1 + thresholdPercent / 100).
Compares current volume to threshold.
Table Display:
Dynamically creates a table with volume stats.
Adds rows based on user preferences.
Alerts:
alertcondition fires when currentVol crosses above the calculated threshold.
Message: "Volume Threshold Exceeded"
Usage Examples
Example 1: Spotting High Activity
Apply the script to a stock like AAPL on a 5-minute chart.
Set lookbackPeriods to 20 and thresholdPercent to 30.
Use EMA for more reactive volume tracking.
When volume spikes more than 30% above the 20-period EMA, an alert triggers.
Example 2: Day Trading Filter
For scalpers, apply it to a 1-minute crypto chart (e.g., BTC/USDT).
Set thresholdPercent to 50 to catch only strong surges.
Position the table at the top left and reduce visible info for a clean layout.
Example 3: Long-Term Context
On a daily chart, use SMA and set lookbackPeriods to 50.
Helps identify breakout moves supported by strong volume.
How this is different from Trading View's Volume indicator:
The standard volume plot from trading view allows users to set a alert when the average line is crossed, but it does not allow you to set a custom percentage at which to trigger an alert. This indicator will allow you to set any percentage you wish to monitor and above that percentage threshold will trigger your alert.
===== ORIGINAL DESCRIPTION =====
Volume Spike Alert & Overlay
This indicator will display the following as an overlay on your chart:
Current volume
Average Volume
Threshold for Alert
Description:
This indicator will display the current bar volume based on the chart time frame,
display the average volume based on selected conditions,
allow user selectable threshold over the average volume to trigger an alert.
Options:
Average lookback period
Smoothing type
Alert Threshold %
Enable / Disable Each Value
Change Text Color
Change Background Color
Change Table location
Add/Remove extra row for placement in top corner
Usage Example:
I use this indicator to alert when the current volume exceeds the average volume by a specified percentage to alert to volume spikes.
Set the threshold to 25% in the settings
Create an alert by clicking on the 3 dots on the right of the indicator title on the chart
When the threshold is exceeded the alert will trigger
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description
The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators.
---
\ 1. Calculation Basis\
1. Volume Normalization
$$
\text{normVol}_t
= \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t}
\quad(\text{e.g., }n_{\text{Vol}} = 13)
$$
This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”).
2. Price Factor
$$
\text{priceFactor}_t
= \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}.
$$
Positive values for bullish bars, negative for bearish bars.
3. Component per Bar
$$
\text{component}_t
= \text{normVol}_t \times \text{priceFactor}_t.
$$
If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls.
4. Raw DI (Rolling Sum)
Over a window of \$w\$ bars (e.g., 20):
$$
\text{RawDI}_t
= \sum_{i=0}^{w-1} \text{component}_{\,t-i}.
$$
Alternatively, recursively for \$t \ge w\$:
$$
\text{RawDI}_t
= \text{RawDI}_{t-1}
+ \text{component}_t
- \text{component}_{\,t-w}.
$$
5. Optional EMA Smoothing
An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends:
$$
\text{EMA\_DI}_t
= \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t.
$$
6.Zero Line
Handy guideline:
RawDI > 0: Accumulated buying power dominates.
RawDI < 0: Accumulated selling power dominates.
2. Interpretation & Application
Crossing Zero
RawDI above zero → Indication of increasing buying pressure (potential long signal).
RawDI below zero → Indication of increasing selling pressure (potential short signal).
Not to be used alone for entry—always confirm with price action.
RawDI vs. EMA_DI
RawDI > EMA\_DI → Acceleration of demand.
RawDI < EMA\_DI → Weakening of demand.
Divergences
Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend.
Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend.
3. Typical Signals (for Beginners)
\ 1. Long Setup\
RawDI crosses zero from below,
RawDI > EMA\_DI (acceleration),
Price closes above a short-term swing high or resistance.
Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R.
2. Short Setup
RawDI crosses zero from above,
RawDI < EMA\_DI (increased selling pressure),
Price closes below a short-term swing low or support.
Stop-Loss: just above the last swing high.
---
4. Notes and Parameters
Recommended Values (Beginners):
Volume EMA (n₍Vol₎) = 13
RawDI window (w) = 20
EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing)
Attention:\
NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns).
Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals.
---
Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
atr stop loss for double SMA v6Strategy Name
atr stop loss for double SMA v6
Credit: This v6 update is based on Daveatt’s “BEST ATR Stop Multiple Strategy.”
Core Logic
Entry: Go long when the 15-period SMA crosses above the 45-period SMA; go short on the inverse cross.
Stop-Loss: On entry, compute ATR(14)×2.0 and set a fixed stop at entry ± that amount. Stop remains static until hit.
Trend Tracking: Uses barssince() to ensure only one active long or short position; stop is only active while that trend persists.
Visualization
Plots fast/slow SMA lines in teal/orange.
On each entry bar, displays a label showing “ATR value” and “ATR×multiple” positioned at the 30-bar low (long) or high (short).
Draws an “×” at the stop-price level in green (long) or red (short) while the position is open.
Execution Settings
Initial Capital: $100 000, Size = 100 shares per trade.
Commission: 0.075% per trade.
Pyramiding: 1.
Calculations: Only on bar close (no intra-bar ticks).
Usage Notes
Static ATR stop adapts to volatility but does not trail.
Ideal for trending, liquid markets (stocks, futures, FX).
Adjust SMA lengths or ATR multiple for faster/slower signals.
Directional Strength IndexThis indicator is designed to detect the dominant market direction and quantify its strength by aggregating signals across six key timeframes: 1H, 4H, 1D, 3D, 1W, and 1M.
At its core, it uses a SMEMA 'the Simple Moving Average of an EMA' as the main trend reference. This hybrid smoothing method was chosen for its balance: the EMA ensures responsiveness to recent price moves, while the SMA dampens short-term volatility. This makes the SMEMA more stable than a raw EMA and more reactive than a simple SMA, especially in noisy or volatile environments.
For each timeframe, a score between -10 and +10 is calculated. This score reflects:
- the distance of the price from the SMEMA, using ATR as a dynamic threshold
- the number of price deviations above or below the SMEMA
- the slope of the SMEMA, which adjusts the score based on momentum
These six timeframe scores are then combined into a single Global Score, using weighted averages. Three weighting profiles are available depending on your trading horizon:
- Long Term: emphasizes weekly and monthly data
- Swing Trading: gives balanced importance to all timeframes
- Short Term: prioritizes 1H and 4H action
This multi-timeframe aggregation makes the indicator adaptable to different styles while maintaining a consistent logic.
The result is displayed in a table on the chart, showing:
- the trend direction per timeframe (up, down or neutral)
- the strength score per timeframe
- the overall trend direction and strength based on the selected profile
Optional deviation bands based on ATR multiples are also plotted to provide visual context for overextensions relative to the SMEMA.
This indicator is non-repainting and built for objective, trend-based decision making.
DECODE Global Liquidity IndexDECODE Global Liquidity Index 🌊
The DECODE Global Liquidity Index is a powerful tool designed to track and aggregate global liquidity by combining data from the world's 13 largest economies. It offers a comprehensive view of financial liquidity, providing crucial insights into the underlying currents that can influence asset prices and market trends.
The economies covered are: United States, China, European Union, Japan, India, United Kingdom, Brazil, Canada, Russia, South Korea, Australia, Mexico, and Indonesia. The European Union accounts for major individual economies within the EU like Germany, France, Italy, Spain, Netherlands, Poland, etc.
Key Features:
1. Customizable Liquidity Sources
Include Global M2: You can opt to include the M2 money supply from the 13 listed economies. M2 is a broad measure of money supply that includes cash, checking deposits, savings deposits, money market securities, mutual funds, and other time deposits. (Note: Australia uses M3 as its primary measure, which is included when M2 is selected for Australia).
Include Central Bank Balance Sheets (CBBS): Alternatively, or in addition, you can include the total assets held by the central banks of these economies. Central bank balance sheets expand or contract based on monetary policy operations like quantitative easing (QE) or tightening (QT).
Combined View: If you select both M2 and CBBS, and data is available for both, the indicator will display an average of the two aggregated values. If only one source type is selected, or if data for one type is unavailable despite both being selected, the indicator will display the single available and selected component. This provides flexibility in how you define and analyze global liquidity.
2. Lead/Lag Analysis (Forward Projection):
Lead Offset (Days): This feature allows you to project the liquidity index forward by a specified number of days.
Why it's useful: Global liquidity changes can often be a leading indicator for various asset classes, particularly those sensitive to risk appetite, like Bitcoin or growth stocks. These assets might lag shifts in liquidity. By applying a lead (e.g., 90 days), you can shift the liquidity data forward on your chart to more easily visualize potential correlations and identify if current asset price movements might be responding to past changes in liquidity.
3. Rate of Change (RoC) Oscillator:
Year-over-Year % View: Instead of viewing aggregate liquidity, you can switch to a Year-over-Year (YoY%) Rate of Change (ROC) oscillator.
Why it's useful:
Momentum Identification: The ROC highlights the speed and direction of liquidity changes. Positive values indicate liquidity is increasing compared to a year ago, while negative values show it's decreasing.
Turning Points: Oscillators make it easier to spot potential accelerations, decelerations, or reversals in liquidity trends. A cross above the zero line can signal strengthening liquidity momentum, while a cross below can signal weakening momentum.
Cycle Analysis: It helps in assessing the cyclical nature of liquidity provision and its potential impact on market cycles.
This indicator aims to provide a clear, customizable, and insightful measure of global liquidity to aid traders and investors in their market analysis.
Momentum Fusion v1Momentum Fusion v1
Overview
Momentum Fusion v1 (MFusion) is a multi-oscillator indicator that combines several components to analyze market momentum and trend strength. It incorporates modified versions of classic indicators such as PVI (Positive Volume Index), NVI (Negative Volume Index), MFI (Money Flow Index), RSI, Stochastic, and Bollinger Bands Oscillator. The indicator displays a histogram that changes color based on momentum strength and includes "FUSION🔥" signal labels when extreme values are reached.
Indicator Settings
Parameters:
EMA Length – Smoothing period for the moving average (default: 255).
Smoothing Period – Internal calculation smoothing parameter (default: 15).
BB Multiplier – Standard deviation multiplier for Bollinger Bands (default: 2.0).
Show verde / marron / media lines – Toggles the display of auxiliary lines.
Show FUSION🔥 label – Enables/disables signal labels.
Indicator Components
1. PVI (Positive Volume Index)
Formula:
pvi := volume > volume ? nz(pvi ) + (close - close ) / close * sval : nz(pvi )
Description:
PVI increases when volume rises compared to the previous bar and accounts for price percentage change. The stronger the price movement with increasing volume, the higher the PVI value.
2. NVI (Negative Volume Index)
Formula:
nvi := volume < volume ? nz(nvi ) + (close - close ) / close * sval : nz(nvi )
Description:
NVI tracks price movements during declining volume. If the price rises on low volume, it may indicate a "stealth" trend.
3. Money Flow Index (MFI)
Formula:
100 - 100 / (1 + up / dn)
Description:
An oscillator measuring money flow strength. Values above 80 suggest overbought conditions, while values below 20 indicate oversold conditions.
4. Stochastic Oscillator
Formula:
k = 100 * (close - lowest(low, length)) / (highest(high, length) - lowest(low, length))
Description:
A classic stochastic oscillator showing price position relative to the selected period's range.
5. Bollinger Bands Oscillator
Formula:
(tprice - BB midline) / (upper BB - lower BB) * 100
Description:
Indicates the price position relative to Bollinger Bands in percentage terms.
Key Lines & Histogram
1. Verde (Green Line)
Calculation:
verde = marron + oscp (normalized PVI)
Interpretation:
Higher values indicate stronger bullish momentum. A FUSION🔥 signal appears when the value reaches 750+.
2. Marron (Brown Line)
Calculation:
marron = (RSI + MFI + Bollinger Osc + Stochastic / 3) / 2
Interpretation:
A composite oscillator combining multiple indicators. Higher values suggest overbought conditions.
3. Media (Red Line)
Calculation:
media = EMA of marron with smoothing period
Interpretation:
Acts as a signal line for trend confirmation.
4. Histogram
Calculation:
histo = verde - marron
Colors:
Bright green (>100) – Strong bullish momentum.
Light green (>0) – Moderate bullish momentum.
Orange (<0) – Bearish momentum.
Red (<-100) – Strong bearish momentum.
Signals & Alerts
1. FUSION🔥 (Strong Momentum)
Condition:
verde >= 750
Visualization:
A "FUSION🔥" label appears below the chart.
Alert:
Can be set to trigger notifications when the condition is met.
2. Background Aura
Condition:
verde > 850
Visualization:
The chart background turns teal, indicating extreme momentum.
Usage Recommendations
FUSION🔥 Signal – Can be used as a long entry point when confirmed by other indicators.
Histogram:
1. Green bars – Potential long entry.
2. Red/orange bars – Potential short entry.
3. Media & Marron Crossover – Can serve as an additional trend filter.
4. Suitable for a 5-15 minute time frame
Conclusion
Momentum Fusion v1 is a powerful tool for momentum analysis, combining multiple indicators into a unified system. It is suitable for:
Trend traders (catching strong movements).
Scalpers (identifying short-term impulses).
Swing traders (filtering entry points).
The indicator features customizable settings and visual signals, making it adaptable to various trading styles.
