Support Vs Reward RvCSupport Vs Reward RvC
The Support Vs Reward RvC indicator is a simple yet effective tool that analyzes candle strength relative to both price movement and trading volume. Highlights candles where both body size and volume expand or contract, helping traders spot momentum shifts and weakening moves.
📌 How it works:
- “C” expect a Continuation of Trend in the next one or two candles;
- “R” expect a Reverse of Trend in the next one or two candles.
Works well on bigger time candles like 10-15 minutes but also gives important info in day-trading or scalping.
Marks candles where both body size and volume increase or decrease, making momentum shifts easy to spot. This smart candle analyzer reveals momentum surges and fading moves through body size and volume dynamics.
It compares each candle’s body size (open-to-close range) and its volume against the previous candle.
If both the body and volume are greater than the previous candle, a green “C” from Continuation of Trend is displayed under the bar.
If both the body and volume are smaller than the previous candle, a red “R” from Reverse of Trend is displayed under the bar.
Custom filters allow users to ignore insignificant moves by setting a minimum body size (as % of price) and a minimum volume threshold.
📌 Use cases:
Spot momentum shifts when price and volume expand together.
Identify weakening moves when both price action and volume contract.
Can be combined with other strategies for confirmation of entries or exits.
⚙️ Inputs:
Minimum Body Size % (of price): Filters out small candles.
Minimum Volume: Ensures only significant moves are marked.
This indicator is best used as a confirmation tool within a larger trading strategy, rather than as a standalone buy/sell signal.
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Market Outlook Score (MOS)Overview
The "Market Outlook Score (MOS)" is a custom technical indicator designed for TradingView, written in Pine Script version 6. It provides a quantitative assessment of market conditions by aggregating multiple factors, including trend strength across different timeframes, directional movement (via ADX), momentum (via RSI changes), volume dynamics, and volatility stability (via ATR). The MOS is calculated as a weighted score that ranges typically between -1 and +1 (though it can exceed these bounds in extreme conditions), where positive values suggest bullish (long) opportunities, negative values indicate bearish (short) setups, and values near zero imply neutral or indecisive markets.
This indicator is particularly useful for traders seeking a holistic "outlook" score to gauge potential entry points or market bias. It overlays on a separate pane (non-overlay mode) and visualizes the score through horizontal threshold lines and dynamic labels showing the numeric MOS value along with a simple trading decision ("Long", "Short", or "Neutral"). The script avoids using the plot function for compatibility reasons (e.g., potential TradingView bugs) and instead relies on hline for static lines and label.new for per-bar annotations.
Key features:
Multi-Timeframe Analysis: Incorporates slope data from 5-minute, 15-minute, and 30-minute charts to capture short-term trends.
Trend and Strength Integration: Uses ADX to weight trend bias, ensuring stronger signals in trending markets.
Momentum and Volume: Includes RSI momentum impulses and volume deviations for added confirmation.
Volatility Adjustment: Factors in ATR changes to assess market stability.
Customizable Inputs: Allows users to tweak periods for lookback, ADX, and ATR.
Decision Labels: Automatically classifies the MOS into actionable categories with visual labels.
This indicator is best suited for intraday or swing trading on volatile assets like stocks, forex, or cryptocurrencies. It does not generate buy/sell signals directly but can be combined with other tools (e.g., moving averages or oscillators) for comprehensive strategies.
Inputs
The script provides three user-configurable inputs via TradingView's input panel:
Lookback Period (lookback):
Type: Integer
Default: 20
Range: Minimum 10, Maximum 50
Purpose: Defines the number of bars used in slope calculations for trend analysis. A shorter lookback makes the indicator more sensitive to recent price action, while a longer one smooths out noise for longer-term trends.
ADX Period (adxPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Sets the smoothing period for the Average Directional Index (ADX) and its components (DI+ and DI-). Standard value is 14, but shorter periods increase responsiveness, and longer ones reduce false signals.
ATR Period (atrPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Determines the period for the Average True Range (ATR) calculation, which measures volatility. Adjust this to match your trading timeframe—shorter for scalping, longer for positional trading.
These inputs allow customization without editing the code, making the indicator adaptable to different market conditions or user preferences.
Core Calculations
The MOS is computed through a series of steps, blending trend, momentum, volume, and volatility metrics. Here's a breakdown:
Multi-Timeframe Slopes:
The script fetches data from higher timeframes (5m, 15m, 30m) using request.security.
Slope calculation: For each timeframe, it computes the linear regression slope of price over the lookback period using the formula:
textslope = correlation(close, bar_index, lookback) * stdev(close, lookback) / stdev(bar_index, lookback)
This measures the rate of price change, where positive slopes indicate uptrends and negative slopes indicate downtrends.
Variables: slope5m, slope15m, slope30m.
ATR (Average True Range):
Calculated using ta.atr(atrPeriod).
Represents average volatility over the specified period. Used later to derive volatility stability.
ADX (Average Directional Index):
A detailed, manual implementation (not using built-in ta.adx for customization):
Computes upward movement (upMove = high - high ) and downward movement (downMove = low - low).
Derives +DM (Plus Directional Movement) and -DM (Minus Directional Movement) by filtering non-relevant moves.
Smooths true range (trur = ta.rma(ta.tr(true), adxPeriod)).
Calculates +DI and -DI: plusDI = 100 * ta.rma(plusDM, adxPeriod) / trur, similarly for minusDI.
DX: dx = 100 * abs(plusDI - minusDI) / max(plusDI + minusDI, 0.0001).
ADX: adx = ta.rma(dx, adxPeriod).
ADX values above 25 typically indicate strong trends; here, it's normalized (divided by 50) to influence the trend bias.
Volume Delta (5m Timeframe):
Fetches 5m volume: volume_5m = request.security(syminfo.tickerid, "5", volume, lookahead=barmerge.lookahead_on).
Computes a 12-period SMA of volume: avgVolume = ta.sma(volume_5m, 12).
Delta: (volume_5m - avgVolume) / avgVolume (or 0 if avgVolume is zero).
This measures relative volume spikes, where positive deltas suggest increased interest (bullish) and negative suggest waning activity (bearish).
MOS Components and Final Calculation:
Trend Bias: Average of the three slopes, normalized by close price and scaled by 100, then weighted by ADX influence: (slope5m + slope15m + slope30m) / 3 / close * 100 * (adx / 50).
Emphasizes trends in strong ADX conditions.
Momentum Impulse: Change in 5m RSI(14) over 1 bar, divided by 50: ta.change(request.security(syminfo.tickerid, "5", ta.rsi(close, 14), lookahead=barmerge.lookahead_on), 1) / 50.
Captures short-term momentum shifts.
Volatility Clarity: 1 - ta.change(atr, 1) / max(atr, 0.0001).
Measures ATR stability; values near 1 indicate low volatility changes (clearer trends), while lower values suggest erratic markets.
MOS Formula: Weighted average:
textmos = (0.35 * trendBias + 0.25 * momentumImpulse + 0.2 * volumeDelta + 0.2 * volatilityClarity)
Weights prioritize trend (35%) and momentum (25%), with volume and volatility at 20% each. These can be adjusted in code for experimentation.
Trading Decision:
A variable mosDecision starts as "Neutral".
If mos > 0.15, set to "Long".
If mos < -0.15, set to "Short".
Thresholds (0.15 and -0.15) are hardcoded but can be modified.
Visualization and Outputs
Threshold Lines (using hline):
Long Threshold: Horizontal dashed green line at +0.15.
Short Threshold: Horizontal dashed red line at -0.15.
Neutral Line: Horizontal dashed gray line at 0.
These provide visual reference points for MOS interpretation.
Dynamic Labels (using label.new):
Placed at each bar's index and MOS value.
Text: Formatted MOS value (e.g., "0.2345") followed by a newline and the decision (e.g., "Long").
Style: Downward-pointing label with gray background and white text for readability.
This replaces a traditional plot line, showing exact values and decisions per bar without cluttering the chart.
The indicator appears in a separate pane below the main price chart, making it easy to monitor alongside price action.
Usage Instructions
Adding to TradingView:
Copy the script into TradingView's Pine Script editor.
Save and add to your chart via the "Indicators" menu.
Select a symbol and timeframe (e.g., 1-minute for intraday).
Interpretation:
Long Signal: MOS > 0.15 – Consider bullish positions if supported by other indicators.
Short Signal: MOS < -0.15 – Potential bearish setups.
Neutral: Between -0.15 and 0.15 – Avoid trades or wait for confirmation.
Watch for MOS crossings of thresholds for momentum shifts.
Combine with price patterns, support/resistance, or volume for better accuracy.
Limitations and Considerations:
Lookahead Bias: Uses barmerge.lookahead_on for multi-timeframe data, which may introduce minor forward-looking bias in backtesting (use with caution).
No Alerts Built-In: Add custom alerts via TradingView's alert system based on MOS conditions.
Performance: Tested for compatibility; may require adjustments for illiquid assets or extreme volatility.
Backtesting: Use TradingView's strategy tester to evaluate historical performance, but remember past results don't guarantee future outcomes.
Customization: Edit weights in the MOS formula or thresholds to fit your strategy.
This indicator distills complex market data into a single score, aiding decision-making while encouraging users to verify signals with additional analysis. If you need modifications, such as restoring plot functionality or adding features, provide details for further refinement.
MMA, Mid-Price Moving Averages (Open + Close Based MAs)📝 Script Description
This script introduces a custom set of moving averages based on the mid-price, calculated as the average of the open and close prices:
Mid Price = (Open + Close) / 2
Instead of traditional close-based MAs, this approach reflects the average sentiment throughout the trading session, offering a smoother and more realistic view of price action.
🔍 Key Features:
✅ Gap-aware smoothing
Captures opening gaps, offering a better representation of intraday shifts.
✅ Reduced noise
Less vulnerable to sharp closing moves or one-off spikes, making it easier to identify true trend breaks or supports.
✅ Closer to actual flow
Reflects a more natural midline of price movement, ideal for traders who prioritize clean, sustained trends.
✅ Better support/resistance alignment
Especially useful for identifying stable uptrends and minimizing false breakout signals.
📐 Included Moving Averages:
MA 5
MA 10
MA 20
MA 60
MA 120
MA 200
(All based on mid-price, not close)
🎯 Recommended For:
Traders seeking smoother and more reliable trendlines
Those who want a more realistic depiction of support and resistance
Ideal for filtering out noisy movements while focusing on clean, straight-moving charts
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
Trading Rules Panel BJTRADESFXA Simple Panel for Your Trading Rules
Trading can quickly get overwhelming if you’re juggling multiple strategies, indicators, and market conditions. A simple Trading Rules Panel on your chart helps you stay disciplined by keeping your strategy visible at all times. Instead of relying on memory or flipping through notes, the panel displays your personal trading checklist right where you need it — on your screen.
The panel can be customized to show:
✅ Entry conditions (e.g., trend direction, candle patterns, breakout levels)
✅ Exit rules (take profit, stop loss, or trailing stop logic)
✅ Risk management (lot size, max risk %, reward-to-risk ratio)
✅ Trading session reminders (only trade London/New York overlap, etc.)
✅ Personal rules (no revenge trading, stop after 2 losses, follow your plan)
This kind of panel doesn’t place trades for you; rather, it acts as a visual reminder to keep you consistent and accountable. It prevents emotional decisions and reinforces your discipline, especially during high-pressure moments.
A well-placed panel can also:
Reduce mistakes caused by forgetting steps
Keep your focus on the bigger picture
Improve backtesting and journaling since your rules are clearly visible
Help new traders stick to structure instead of chasing trades
Imbalance RSI Divergence Strategy# Imbalance RSI Divergence Strategy - User Guide
## What is This Strategy?
This strategy identifies **imbalance** zones in the market and combines them with **RSI divergence** to generate trading signals. It aims to capitalize on price gaps left by institutional investors and large volume movements.
### Main Settings
- **RSI Period (14)**: Period used for RSI calculation. Lower values = more sensitive, higher values = more stable signals.
- **ATR Period (10)**: Period for volatility measurement using Average True Range.
- **ATR Stop Loss Multiplier (2.0)**: How many ATR units to use for stop loss calculation.
- **Risk:Reward Ratio (4.0)**: Risk-reward ratio. 2.0 = 2 units of reward for 1 unit of risk.
- **Use RSI Divergence Filter (true)**: Enables/disables the RSI divergence filter.
### Imbalance Filters
- **Minimum Imbalance Size (ATR) (0.3)**: Minimum imbalance size in ATR units to filter out small imbalances.
- **Enable Lookback Limit (false)**: Activates historical lookback limitations.
- **Maximum Lookback Bars (300)**: Maximum number of bars to look back.
### Visual Settings
- **Show Imbalance Size**: Displays imbalance size in ATR units.
- **Show RSI Divergence Lines**: Shows/hides divergence lines.
- **Divergence Line Colors**: Colors for bullish/bearish divergence lines.
### Volatility-Based Adjustments
- **Low volatility markets**:
- Minimum Imbalance Size: 0.2-0.4 ATR
- ATR Stop Loss Multiplier: 1.5-2.0
- **High volatility markets**:
- Minimum Imbalance Size: 0.5-1.0 ATR
- ATR Stop Loss Multiplier: 2.5-3.5
### Risk Tolerance
- **Conservative approach**:
- Risk:Reward Ratio: 2.0-3.0
- RSI Divergence Filter: Enabled
- Minimum Imbalance Size: Higher (0.5+ ATR)
- **Aggressive approach**:
- Risk:Reward Ratio: 4.0-6.0
- Minimum Imbalance Size: Lower (0.2-0.3 ATR)
###Market Conditions
- **Trending markets**: Higher RSI Period (21-28)
- **Sideways markets**: Lower RSI Period (10-14)
- **Volatile markets**: Higher ATR Multiplier
## Recommended Testing Procedure
1. **Start with default settings** and backtest on 3-6 months of historical data
2. **Adjust RSI Period** to see which value produces better results
3. **Optimize ATR Multiplier** for stop loss levels
4. **Test different Risk:Reward ratios** comparatively
5. **Fine-tune Minimum Imbalance Size** to improve signal quality
## Important Considerations
- **False positive signals**: Imbalances may be less reliable during low volatility periods
- **Market openings**: First hours often produce more imbalances but can be riskier
- **News events**: Consider disabling strategy during major news releases
- **Backtesting**: Test across different market conditions (trending, sideways, volatile)
## Recommended Settings for Beginners
**Safe settings for new users:**
- RSI Period: 14
- ATR Period: 14
- ATR Stop Loss Multiplier: 2.5
- Risk:Reward Ratio: 3.0
- Minimum Imbalance Size: 0.5 ATR
- RSI Divergence Filter: Enabled
## Advanced Tips
### Signal Quality Improvement
- **Combine with market structure**: Look for imbalances near key support/resistance levels
- **Volume confirmation**: Higher volume during imbalance formation increases reliability
- **Multiple timeframe analysis**: Confirm signals on higher timeframes
### Risk Management
- **Position sizing**: Never risk more than 1-2% of account per trade
- **Maximum drawdown**: Set overall stop loss for the strategy
- **Market hours**: Consider avoiding low liquidity periods
### Performance Monitoring
- **Win rate**: Track percentage of profitable trades
- **Average R:R**: Monitor actual risk-reward achieved vs. target
- **Maximum consecutive losses**: Set alerts for strategy review
This strategy works best when combined with proper risk management and market analysis. Always backtest thoroughly before using real money and adjust parameters based on your specific market and trading style.
samc's - Keltner OscillatorThe KELTNER CHANNEL is a widely used technical indicator developed in the 60's by Chester W. Keltner who described it in his 1960 book How To Make Money in Commodities.
so i took the logic, simplified the code and made into an oscillator.
to add a flavor of modern times you can choose among 10 different colorways themes in the settings. (so traders can adjust it for dark or light charts)
Although the initial idea was developed for stocks and commodities, I've carefully back tested this as an oscillator across FX MAJORS , MINORS and high liquidity stocks for the use case of scalping and Medium term trade ideas.
now, this indicator works successfully over all time frames, custom time frames and all assets.
This script builds on the same approach as my earlier session tool — keeping things clean, visual, and easy to read.
I intend to publish more of my work as i develop them from Beta ideas into stable scripts, and i welcome feedback.
samc's FX SESSIONS - on candles So, based on my 8 yrs of experience and over a 2 decade worth of back testing on FX majors pairs one thing i can univocally affirm to the fact that Timing is everything especially in the currency markets.
so i made this indicator to help reduce the noise and focus on signals which is coded by time,
now i made this as GMT+8 in focus but you can adjust based on your requirements.
I classified my indicator colors according to the inter-SESSION High Impact areas only as following :
Primary session colors:
ASIAN - YELLOW
EU - BLUE
US - Magenta (light)
and every first 10 mins of the hour (Great for scalping)
i marked them in a shade of grey.
secondary sessions i marked them as minor sessions.
PRE-EU 1hr of expected trend i marked in color green
and
after hours in a shade of color violet.
so i usually make my candles into light grey by default and remove the body and wicks to minimize the visual stimulus so that this indicator will work great with both dark and light themes and does not obstruct other indicators.
also i made an option to uncheck my naming scheme of session on the top right.
Range Percent Histogram📌 Range Percent Histogram – Indicator Description
The Range Percent Histogram is a custom indicator that behaves like a traditional volume histogram, but instead of showing traded volume it displays the percentage range of each candle.
In other words, the height of each bar represents how much the price moved (in percentage terms) within that candle, from its low to its high.
🔧 What it shows
The indicator has two main components:
Component Description
Histogram Bars Columns plotted in red or green depending on the candle direction (green = bullish candle, red = bearish). The height of each bar = (high - low) / low * 100. That means a candle that moved, for example, 1 % from its lowest point to its highest point will show a bar with 1 % height.
Moving Average (optional) A 20-period Simple Moving Average applied directly to the bar values. It can be turned ON/OFF via a checkbox and helps you detect whether current range activity is above or below the average range of the past candles.
⚙️ How it works
Every time a new candle closes, the indicator calculates its range and converts it into a percentage.
This value is drawn as a column under the chart.
If the closing price is above the opening price → the bar is green (bullish range).
If the closing price is below the opening price → the bar is red (bearish range).
When the Show Moving Average option is enabled, a smooth line is plotted on top of the histogram representing the average percentage range of the last 20 candles.
📈 How to use it
This indicator is very helpful for detecting moments of range expansion or contraction.
One powerful way to use it is similar to a volume exhaustion / low-volume pattern:
Situation Interpretation
Consecutive bars with very low height Price is in a period of low volatility → possible accumulation or "pause" phase.
A sudden large bar after a series of small ones Indicates a strong pickup in volatility → often marks the start of a new impulse in the direction of the breakout.
Trading Macro Windows by BW v2
Trading Macros by BW: Integrating ICT Concepts for Session Analysis
This indicator combines two key Inner Circle Trader (ICT) concepts—Change in State of Delivery (CISD) or Inverted Fair Value Gap (IFVG) signals with Macro Time Windows—to provide a unified tool for analyzing intraday price action, particularly during Pacific Time (PT) sessions. Rather than simply merging existing scripts, this integration creates a cohesive visual framework that highlights how macro consolidation periods interact with potential reversal or continuation signals like CISD or IFVG. By overlaying macro candle styling and borders on the chart alongside selectable signal lines, traders can better contextualize setups within ICT's macro narrative, where price often manipulates liquidity during these windows before displacing toward higher-timeframe objectives.
Core Components and How They Work Together:
Macro Time Windows (Inspired by ICT's Macro Periods):
ICT emphasizes "macro" as 30-minute windows (e.g., 06:45–07:15 PT, 07:45–08:15 PT, up to 11:45–12:15 PT) where price tends to consolidate, sweep liquidity, or form key structures like Fair Value Gaps (FVGs). These periods set the stage for the session's directional bias.
The indicator styles candles within these windows using a user-defined color for wicks, borders, and bodies (translucent for visibility). This visual emphasis helps traders focus on activity inside macros, where reversals or continuations often originate.
Borders are drawn as vertical lines at the start and end of each window (with a +5 minute buffer to capture related activity), using a dotted style by default. This creates a "study zone" that encapsulates macro events, allowing traders to assess if price is respecting or violating these zones in alignment with broader ICT models like the Power of 3 (AMD cycle).
Toggle: "Macro Candles Enabled" (default: true) – Turn off to disable styling and borders if focusing solely on signals.
CISD or IFVG Signals (Selectable Mode):
Mode Selection: Choose between "Change in the State of Delivery" (CISD) or "IFVG" (default: IFVG). Both detect shifts in market delivery during specific 30-minute slices (15–45 or 17–45 minutes past the hour in PT sessions).
CISD Mode: Based on ICT's definition of a sudden directional shift, this identifies aggressive displacements after sweeping recent highs/lows. It uses a rolling reference high/low over 6 bars, checks for sweeps (penetrating by at least 2 ticks in the last 2-3 bars), reclamation (closing beyond the reference with at least 50% body), and displacement (50% of prior range or an immediate FVG of 6+ ticks). Signals plot a horizontal line from the close, extending 24 bars right, labeled "CISD."
IFVG Mode: Focuses on Inverted Fair Value Gaps, where a bullish FVG (low > high by 13+ ticks) forms but is inverted (closed below) in the same slice, signaling bearish intent (or vice versa). This targets violations against opposing liquidity, often leading to raids on external ranges. Signals plot similarly, labeled "IFVG."
Shared Logic: Both modes enforce a 55-bar cooldown to prevent clustering, operate only during PT sessions (06:30–13:00), and use tick-based thresholds for precision across instruments. The integration with macros allows traders to see if signals occur within or at the edges of macro windows, enhancing confirmation—for example, a CISD inside a macro might indicate a manipulated reversal toward the session's true objective.
Toggle: "Signals Enabled" (default: true) – Turn off to hide all signal lines and labels, isolating the macro visualization.
How Components Interact:
Macro windows provide the "narrative context" (consolidation/manipulation), while CISD/IFVG signals detect the "delivery shift" (displacement). Together, they form a mashup that justifies publication: isolated signals can be noisy, but when filtered by macro periods, they align with ICT's session model. For instance, an IFVG inversion during a macro might confirm a liquidity sweep before targeting PD arrays or order blocks.
No external dependencies; all calculations are self-contained using Pine's built-in functions like ta.highest/lowest for references and time-based sessions for windows.
Usage Guidelines:
Apply to intraday charts (e.g., 1-5 min) or stocks during PT hours.
Look for confluence: A bull IFVG signal post-macro low sweep might target the next macro high or daily bias.
Customize colors/styles for signals (solid/dashed/dotted lines) and macros to suit your chart.
Backtest in replay mode to observe how macros frame signals—e.g., price often respects macro borders as S/R.
Limitations: Timezone-fixed to PT (America/Los_Angeles); signals are directional hints, not trade entries. Combine with ICT tools like order blocks or liquidity pools for full setups.
This script draws from community ICT implementations but refines them into a single, purpose-built tool for macro-driven trading, reducing chart clutter while emphasizing interconnected concepts. Feedback welcome!
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Six Meridian Divine Swords [theUltimator5]The Six Meridian Divine Sword is a legendary martial arts technique in the classic wuxia novel “Demi-Gods and Semi-Devils” (天龙八部) by Jin Yong (金庸). The technique uses powerful internal energy (qi) to shoot invisible sword-like energy beams from the six meridians of the hand. Each of the six fingers/meridians corresponds to a “sword,” giving six different sword energies.
The Six Meridian Divine Swords indicator is a compact “signal dashboard” that fuses six classic indicators (fingers)—MACD, KDJ, RSI, LWR (Williams %R), BBI, and MTM—into one pane. Each row is a traffic-light dot (green/bullish, red/bearish, gray/neutral). When all six align, the script draws a confirmation line (“All Bullish” or “All Bearish”). It’s designed for quick consensus reads across trend, momentum, and overbought/oversold conditions.
How to Read the Dashboard
The pane has 6 horizontal rows (explained in depth later):
MACD
KDJ
RSI
LWR (Larry Williams %R)
BBI (Bull & Bear Index)
MTM (Momentum)
Each tick in the row is a dot, with sentiment identified by a color.
Green = bullish condition met
Red = bearish condition met
Gray = inside a neutral band (filtering chop), shown when Use Neutral (Gray) Colors is ON
There are two lines that track the dots on the top or bottom of the pane.
All Bullish Signal Line: appears only if all 6 are strongly bullish (default color = white)
All Bearish Signal Line: appears only if all 6 are strongly bearish (default color = fuchsia)
The Six Meridians (Indicators) — What They Mean:
1) MACD — Trend & Momentum
What it is: A trend-following momentum indicator based on the relationship between two moving averages (typically 12-EMA and 26-EMA)
Logic used: Classic MACD line (EMA12−EMA26) vs its 9-EMA signal.
Bullish: MACD > Signal and |MACD−Signal| > Neutral Threshold
Bearish: MACD < Signal and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Small crosses can whipsaw. The neutral band ignores tiny separations to reduce noise.
Inputs: Fast/Slow/Signal lengths, Neutral Threshold.
2) KDJ — Stochastic with J-line boost
What it is: A variation of the stochastic oscillator popular in Chinese trading systems
Logic used: K = SMA(Stochastic, smooth), D = SMA(K, smooth), J = 3K − 2D.
Bullish: K > D and |K−D| > 2
Bearish: K < D and |K−D| > 2
Neutral: |K−D| ≤ 2
Why: K–D separation filters tiny wiggles; J offers an “extreme” early-warning context in the value label.
Inputs: Length, Smoothing.
3) RSI — Momentum balance (0–100)
What it is: A momentum oscillator measuring speed and magnitude of price changes (0–100)
Logic used: RSI(N).
Bullish: RSI > 50 + Neutral Zone
Bearish: RSI < 50 − Neutral Zone
Neutral: Between those bands
Why: Centerline/adaptive bands (around 50) give a directional bias without relying on fixed 70/30.
Inputs: Length, Neutral Zone (± around 50).
4) LWR (Williams %R) — Overbought/Oversold
What it is: An oscillator similar to stochastic, measuring how close the close is to the high-low range over N periods
Logic used: %R over N bars (0 to −100).
Bullish: %R > −50 + Neutral Zone
Bearish: %R < −50 − Neutral Zone
Neutral: Between those bands
Why: Uses a centered band around −50 instead of only −20/−80, making it act like a directional filter.
Inputs: Length, Neutral Zone (± around −50).
5) BBI (Bull & Bear Index) — Smoothed trend bias
What it is: A composite moving average, essentially the average of several different moving averages (often 3, 6, 12, 24 periods)
Logic used: Average of 4 SMAs (3/6/12/24 by default):
BBI = (MA3 + MA6 + MA12 + MA24) / 4
Bullish: Close > BBI and |Close−BBI| > 0.2% of BBI
Bearish: Close < BBI and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Multiple MAs blended together reduce single-MA whipsaw. A dynamic 0.2% band ignores tiny drift.
Inputs: 4 lengths (default 3/6/12/24). Threshold is auto-scaled at 0.2% of BBI.
6) MTM (Momentum) — Rate of change in price
What it is: A simple measure of rate of change
Logic used: MTM = Close − Close
Bullish: MTM > 0.5% of Close
Bearish: MTM < −0.5% of Close
Neutral: |MTM| ≤ threshold
Why: A percent-based gate adapts across prices (e.g., $5 vs $500) and mutes insignificant moves.
Inputs: Length. Threshold auto-scaled to 0.5% of current Close.
Display & Inputs You Can Tweak
🎨 Use Neutral (Gray) Colors
ON (default): 3-color mode with clear “no-trade”/“weak” states.
OFF: classic binary (green/red) without neutral filtering.
Daily Seasonality Strength + Prediction TableDaily Seasonality Strength + Prediction Table
Return Estimates:
This indicator uses historical price data to calculate average returns for each day (of the week or month) and uses these to predict the next day’s return.
Seasonality Strength:
It measures seasonality strength by comparing predicted returns with actual returns, using the inverse of MSE (higher values mean stronger seasonality).
supports up to 10 assets
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice. I am not a financial advisor. Any decisions you make based on this indicator are your own responsibility. Always do your own research and consult with a qualified financial professional before making any investment decisions.
Past performance is no guarantee of future results. The value of the instruments may fluctuate and is not guaranteed
Multi-Timeframe 200 EMAMulti-Timeframe 200 EMA Indicator
This indicator plots five 200-period Exponential Moving Averages (EMAs) on your chart, each from a different timeframe: 1-hour, 2-hour, 4-hour, 8-hour, and 1-day.
What It Does:
Analyzes Higher Timeframes: It uses the request.security() function to fetch data from higher timeframes. This allows you to see significant long-term support and resistance levels from higher timeframes, all on your current chart.
Customizable: You can easily turn each EMA line on or off individually in the indicator's settings. By default, the 1-hour and 1-day EMAs are off, so you can focus on the intermediate timeframes right away.
Clean and Simple: The indicator is designed to be clean and easy to read, with different colors for each EMA line to help you quickly identify the different timeframes at a glance.
This is a powerful tool for trend analysis and identifying key price levels, helping you make more informed trading decisions.
XMR Divergences vs KrakenSUMMARY
This script finds the percentage difference between Kraken, and multiple other exchanges, for the price of XMRUSD, and then runs a variable length moving average of those differences. Optionally, you can multiply by the reported volume of the exchange in question. Skip to "USAGE" at the bottom for a quick view of the settings. But I recommend reading DETAILED DESCRIPTION as well.
PURPOSE
The purpose of this script is to get a look into the relative funds flows of XMR between Kraken and the other exchanges. So long as an exchange withdraws are open: 1) Negative divergences indicate XMR outflows from the exchange under consideration, 2) Postive divergences indicate XMR inflows from Kraken to the exchange.
This appears to be moderately correlated with price movements in Monero (but not always). There is also the theory that positive accumulation is a leading indication of a growing probability of postive price action in the general crypto market, and negative accumulation is a leading indicator of an upcoming peak. In other words, exchanges like to accumulate Monero quietly during calm downtimes, and they like to manage its price from gaining too much attention (pump) during broad market positivity.
BACKGROUND
It's well known among XMR traders that most exchanges are operating on a heavy fractional reserve basis as regards Monero. The past 2 years have seen regular and repeated withdraw freezes, sometimes for weeks/months at a time. Occasionally, liquidity stress tests have been performed, with predictable results - none of these exchanges are able to continue supporting withdraws.
Kraken is the only exchange of meaningful volume that has never frozen withdraws for more than an hour or so. Thus, we theorize that Kraken is operating with all, or most of the XMR they claim to have.
Furthermore, we have seen in the past, large price negative price divergences of these fractional reserve exchanges relative to Kraken. As the social outcry grew stronger for this malfeasance, these exchanges have gone to greater lengths to hide their price divergences.
On minute-by-minute ; hour-by-hour basis, typically, a look with the naked eye would show oscillation around the zero point. But when you average it out, especially on lower timeframes (like the 1 and 5 min candles), you can very clearly see that when withdraws are shut down, these exchanges simultaneously diverge their prices downwards as well.
DETAILED DESCRIPTION
The ideal view of price divergence would compare second-by-second prices, and then run something like a rolling 4-hr or 1-day SMA to average out the overall divergences. However, due to limitations of TradingView, this is impractical/impossible for actual usage/viewing. As a result, a balance must be struck, when selecting the combination of the candle period, and the SMA lookback length.
I find that 5min candles, with a 48-period lookback (that equates to a rolling 4-hour SMA), offers the best view of recent and historical price divergence activity. This of course means that we're only sampling price divergences once every 5 minutes, but it still provides a decent look at what's happening. If this script gets popular, I wouldn't be surprised if these exchanges start timing their candle closes to mask their misdeeds, but that's of course speculative on my part.
The other important factor here, *IS TO MULTIPLY BY VOLUME*. Some of these no-volume exchanges have large price divergences. But if they're not doing any real volume, then it doesn't really have any real market impact. Thus, I recommend keeping the "Make volume adjustment" option on.
If that ends up happening, we'll have to infer that by comparing the difference in close prices, vs the difference in the highest or lowest intra-candle prices (wicks). Typically a divergence should have all 3 showing similar results.
Notes regarding "Sum_of_All": This only makes sense when multiplying by volume. So only check this if you also made the volume adjustment. Generally I believe that *Binance* sets the tone. However, we have seen numerous occasions where Binance diverges down, and the others diverge up. I believe this is a social influence tactic, since most people look at Binance price. Meanwhile, they're trying to accumulate some small amount on the other exchanges to minimize their overall loss. This of course assumes collusion by these exchanges, which is a high likely hood, seeing as how in May 2021, they all diverged together simultaneously (among other evidence).
USAGE
I recommend using your browser zoom, to see data beyond 1 month in the past.
Lookback - The number of candles over which to conduct a moving average. On 5-min candles for example, here's how the math works out:
12 - Equates to a 1 hr MA
24 - 2 hrs
48 - 4 hrs (default)
288 - 1 day
2880 - 10 days
Make Volume Adjustment - Recommend that you usually keep this on.
Line Widths - Set to preference
Show_Close_Price? - You can compute the difference at candle close. Or you can check the other boxes to compare the highest/lowest prices for intra candle prices (wicks).
Show Sum_of_All? - You can sum all of the differences, which only makes sense if you're making the volume adjustement. Default is off. Below, you can also choose which exchanges to include in the sum.
This works best on lower timeframes, like the 1m, 5, and 15m charts. I personally use 5m, with 48 or 96 length lookback. You get a better view of the real time price divergences that way.
TASC 2025.09 The Continuation Index
█ OVERVIEW
This script implements the "Continuation Index" as described by John F. Ehlers in the September 2025 edition of TASC's Trader's Tips . The Continuation Index uses Laguerre filters (featured in the July 2025 edition) to provide an early indication of trend direction, continuation, and exhaustion.
█ CONCEPTS
The idea for the Continuation Index was formed from an observation about Laguerre filters. In his article, Ehlers notes that when price is in trend, it tends to stay to one side of the filter. When considering smoothing, the UltimateSmoother was an obvious choice to reduce lag. With that in mind, The Continuation Index normalizes the difference between UltimateSmoother and the Laguerre filter to produce a two-state oscillator.
To minimize lag, the UltimateSmoother length in this indicator is fixed to half the length of the Laguerre filter.
█ USAGE
The Continuation Index consists of two primary states.
+1 suggests that the trader should position on the long side.
-1 suggests that the user should position on the short side.
Other readings can imply other opportunities, such as:
High Value Fluctuation could be used as a "buy the dip" opportunity.
Low Value Fluctuation could be used as a "sell the pop" opportunity.
█ INPUTS
By understanding the inputs and adjusting them as needed, each trader can benefit more from this indicator:
Gamma : Controls the Laguerre filter's response. This can be set anywhere between 0 and 1. If set to 0, the filter’s value will be the same as the UltimateSmoother.
Order : Controls the lag of the Laguerre filter, which is important when considering the timing of the system for spotting reversals. This can be set from 1 to 10, with lower values typically producing faster timing.
Length : Affects the smoothing of the display. Ehlers recommends starting with this value set to the intended amount of time you plan to hold a position. Consider your chart timeframe when setting this input. For example, on a daily chart, if you intend to hold a position for one month, set a value of 20.
Doji Detector - ZTFNon-Lagging Doji Detector
This indicator automatically identifies and plots four types of doji candlestick patterns in real-time.
Common Doji - Small body with balanced upper and lower shadows (blue diamond)
Long-Legged Doji - Small body with very long shadows on both sides (purple square)
Dragonfly Doji - Small body with long lower shadow, minimal upper shadow (green triangle)
Four-Price Doji - All prices (OHLC) nearly equal, forming a flat line (orange cross)
Key Features:
Detects patterns as they form (non-lagging) or waits for candle close confirmation
Adjustable body size threshold (default 10% of candle range)
Tiny, unobtrusive labels positioned below bars
Works on all timeframes and instruments
Simple pattern recognition without directional bias
How it works: The indicator analyzes each candle's body size relative to its total range and shadow proportions. It uses a hierarchy system to classify each doji into its most specific type, ensuring only one label per candle.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
VSA - The Volume HUDVSA Volume HUD: Your At-a-Glance Volume Dashboard
Tired of cluttered charts with multiple indicators taking up screen space?
The VSA Volume HUD is a clean, powerful, and fully customisable Heads-Up Display that puts all the critical volume and price action data you need into one compact box, right on your chart.
Designed for traders who rely on Volume Spread Analysis (VSA), this tool helps you instantly gauge the strength, conviction, and context behind every price move as it happens.
Key Features
This indicator isn't just about showing the current volume; it provides a comprehensive, real-time analysis of the market's activity.
Real-time VSA Dashboard: A persistent on-screen table that updates with every tick, giving you instant feedback without needing to look away from the price. The HUD is fully draggable (hold Ctrl/Cmd + click and drag) to place it anywhere you like.
Essential Volume Metrics:
Current Volume: Displayed in a clean, abbreviated format (e.g., 1.25M for millions, 54.3K for thousands).
% Change (vs. Previous Bar): Instantly see if volume is expanding or contracting.
Vs Short-Term Average: Compare the current bar's volume to a moving average to spot unusual spikes.
Volume Velocity: Measures the rate of change in volume over a short period, helping you spot acceleration or deceleration in market interest.
Relative Volume (RVOL): See how the current volume compares to the average for that specific time of day, perfect for identifying abnormally high or low activity.
Price Action & Volatility Context:
Range vs. ATR: Quickly determine if the current bar's volatility is expanding or contracting compared to the recent average.
Price vs. VWAP: See how far the current price has deviated from the session's Volume-Weighted Average Price, a key level for institutional traders.
Deep Customization is Key
Tailor the HUD to perfectly match your trading style and chart aesthetic.
Display & Layout:
Compact Mode: Remove the metric labels for a sleek, minimalist view that saves screen space.
Bar Meters: Enable optional visual bars next to key metrics for a quick, graphical representation of strength.
Total Control: Toggle every single metric on or off to build the exact dashboard you need. Adjust text size, position, and background opacity with ease.
Smart Coloring & Visual Alerts:
Advanced VSA Coloring: This isn't just about up/down candles. The script intelligently colors volume based on confluence. It highlights increasing volume on a strong up-bar (bullish confirmation) or increasing volume on a down-bar (potential climax or distribution), giving you a deeper VSA context.
High Volume Highlight: Make standout bars impossible to miss! The entire HUD background can change color automatically when volume surges past a custom threshold (e.g., over 150% of the average), instantly drawing your attention to critical moments.
Full Color Customization: Change every color to match your chart's theme, including separate colors for bullish/bearish moves, the background, and the border.
How to Use It
The VSA Volume HUD is a powerful confirmation tool. Use it to:
Confirm Breakouts: Look for a spike in Volume vs. Average and RVOL as price breaks a key level.
Spot Exhaustion: Notice high volume on a narrow-range candle after a long trend, visible through the Range/ATR metric.
Gauge Conviction: Use the Advanced Coloring to see if volume is supporting the price move (e.g., green volume on a green candle) or diverging from it.
BecakFloatingPanelsLibrary "BecakFloatingPanels"
Library for creating floating indicator panels with MACD, RSI, and Stochastic indicators
calculateMacd(source, fastLength, slowLength, signalLength)
Calculate MACD components
Parameters:
source (float) : Price source for calculation
fastLength (simple int) : Fast EMA period
slowLength (simple int) : Slow EMA period
signalLength (simple int) : Signal line period
Returns: MacdData MACD calculation results
calculateRsi(source, length)
Calculate RSI
Parameters:
source (float) : Price source for calculation
length (simple int) : RSI period
Returns: float RSI value
calculateStochastic(source, high, low, kLength, kSmoothing, dSmoothing)
Calculate Stochastic components
Parameters:
source (float) : Price source for calculation
high (float) : High prices
low (float) : Low prices
kLength (int) : %K period
kSmoothing (int) : %K smoothing period
dSmoothing (int) : %D smoothing period
Returns: StochData Stochastic calculation results
calculateStochSignals(stochK, stochD, overboughtLevel, oversoldLevel)
Calculate Stochastic signals
Parameters:
stochK (float) : Stochastic %K series
stochD (float) : Stochastic %D series
overboughtLevel (float) : Overbought threshold
oversoldLevel (float) : Oversold threshold
Returns: StochSignals Signal flags
calculateChartMetrics(high, low, lookbackLength)
Calculate chart range and positioning metrics
Parameters:
high (float) : High prices
low (float) : Low prices
lookbackLength (int) : Lookback period
Returns: ChartMetrics Chart positioning data
calculateMacdRange(macdLine, signalLine, histogram, safeLookback)
Calculate MACD range for normalization
Parameters:
macdLine (float) : MACD line series
signalLine (float) : Signal line series
histogram (float) : Histogram series
safeLookback (int) : Lookback period
Returns: MacdRange MACD range metrics
initVisualArrays()
Initialize visual arrays
Returns: VisualArrays Container with initialized arrays
clearVisuals(visuals)
Clear all visual elements
Parameters:
visuals (VisualArrays) : VisualArrays container
Returns: void
calculatePanelPositions(chartMetrics, oscPlacement, panelHeight, panelSpacing, centerOffset)
Calculate panel positions based on placement option
Parameters:
chartMetrics (ChartMetrics) : Chart metrics object
oscPlacement (string) : Panel placement option
panelHeight (float) : Panel height percentage
panelSpacing (float) : Panel spacing percentage
centerOffset (float) : Center offset percentage
Returns: PanelPositions Panel boundary coordinates
createPanelBackgrounds(visuals, positions, panelLeft, panelRight, showBackground, transparency)
Create panel backgrounds
Parameters:
visuals (VisualArrays) : VisualArrays container
positions (PanelPositions) : PanelPositions object
panelLeft (int) : Left boundary
panelRight (int) : Right boundary
showBackground (bool) : Show background flag
transparency (int) : Background transparency
Returns: void
drawReferenceLines(visuals, positions, chartMetrics, macdRange, dataLeft, dataRight, panelHeight, rsiOverbought, rsiOversold, stochOverbought, stochOversold)
Draw reference lines for all panels
Parameters:
visuals (VisualArrays) : VisualArrays container
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
macdRange (MacdRange) : MacdRange object
dataLeft (int) : Left data boundary
dataRight (int) : Right data boundary
panelHeight (float) : Panel height percentage
rsiOverbought (int) : RSI overbought level
rsiOversold (int) : RSI oversold level
stochOverbought (int) : Stochastic overbought level
stochOversold (int) : Stochastic oversold level
Returns: void
drawMacdIndicator(visuals, macdLine, signalLine, histogram, macdRange, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight)
Draw MACD indicator
Parameters:
visuals (VisualArrays) : VisualArrays container
macdLine (float) : MACD line series
signalLine (float) : Signal line series
histogram (float) : Histogram series
macdRange (MacdRange) : MacdRange object
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
barIndex (int) : Current bar index
nextBarIndex (int) : Next bar index
barIndexOffset (int) : Horizontal offset
panelHeight (float) : Panel height percentage
Returns: void
drawRsiIndicator(visuals, rsiValue, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight)
Draw RSI indicator
Parameters:
visuals (VisualArrays) : VisualArrays container
rsiValue (float) : RSI value
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
barIndex (int) : Current bar index
nextBarIndex (int) : Next bar index
barIndexOffset (int) : Horizontal offset
panelHeight (float) : Panel height percentage
Returns: void
drawStochasticIndicator(visuals, stochK, stochD, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight, stochOverbought, stochOversold)
Draw Stochastic indicator
Parameters:
visuals (VisualArrays) : VisualArrays container
stochK (float) : Stochastic %K series
stochD (float) : Stochastic %D series
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
barIndex (int) : Current bar index
nextBarIndex (int) : Next bar index
barIndexOffset (int) : Horizontal offset
panelHeight (float) : Panel height percentage
stochOverbought (int) : Overbought level
stochOversold (int) : Oversold level
Returns: void
addStochasticSignals(visuals, buySignal, sellSignal, positions, chartMetrics, currentBarIndex, barIndexOffset, panelHeight, signalIndex)
Add Stochastic buy/sell signals
Parameters:
visuals (VisualArrays) : VisualArrays container
buySignal (bool) : Buy signal series
sellSignal (bool) : Sell signal series
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
currentBarIndex (int) : Current bar index
barIndexOffset (int) : Horizontal offset
panelHeight (float) : Panel height percentage
signalIndex (int) : Signal index for lookback
Returns: void
setPanelLabels(macdLabel, rsiLabel, stochLabel, positions, chartMetrics, labelOffset, panelHeight, barIndexOffset)
Set panel title labels
Parameters:
macdLabel (label) : MACD label reference
rsiLabel (label) : RSI label reference
stochLabel (label) : Stochastic label reference
positions (PanelPositions) : PanelPositions object
chartMetrics (ChartMetrics) : ChartMetrics object
labelOffset (int) : Label horizontal offset
panelHeight (float) : Panel height percentage
barIndexOffset (int) : Horizontal offset
Returns: void
showDebugInfo(chartMetrics, debugMode)
Display debug information
Parameters:
chartMetrics (ChartMetrics) : ChartMetrics object
debugMode (bool) : Debug mode flag
Returns: void
ChartMetrics
Chart metrics container
Fields:
visibleHigh (series float) : Highest visible price
visibleLow (series float) : Lowest visible price
chartRange (series float) : Price range of chart
chartCenter (series float) : Center point of chart
MacdData
MACD calculation results
Fields:
macdLine (series float) : Main MACD line
signalLine (series float) : Signal line
histogram (series float) : MACD histogram
MacdRange
MACD range metrics for normalization
Fields:
highest (series float) : Highest MACD value
lowest (series float) : Lowest MACD value
BRange (series float) : Total range
StochData
Stochastic calculation results
Fields:
k_smooth (series float) : Smoothed %K line
d (series float) : %D line
StochSignals
Stochastic signals
Fields:
buySignal (series bool) : Buy signal flag
sellSignal (series bool) : Sell signal flag
PanelPositions
Panel positioning data
Fields:
macdTop (series float) : MACD panel top
macdBottom (series float) : MACD panel bottom
rsiTop (series float) : RSI panel top
rsiBottom (series float) : RSI panel bottom
stochTop (series float) : Stochastic panel top
stochBottom (series float) : Stochastic panel bottom
VisualArrays
Visual elements arrays container
Fields:
macdLines (array) : Array of MACD lines
macdHist (array) : Array of MACD histogram boxes
rsiLines (array) : Array of RSI lines
stochLines (array) : Array of Stochastic lines
stochAreas (array) : Array of Stochastic areas
stochSignals (array) : Array of Stochastic signals
panelBackgrounds (array) : Array of panel backgrounds
Fractal Circles#### FRACTAL CIRCLES ####
I combined 2 of my best indicators Fractal Waves (Simplified) and Circles.
Combining the Fractal and Gann levels makes for a very simple trading strategy.
Core Functionality
Gann Circle Levels: This indicator plots mathematical support and resistance levels based on Gann theory, including 360/2, 360/3, and doubly strong levels. The system automatically adjusts to any price range using an intelligent multiplier system, making it suitable for forex, stocks, crypto, or any market.
Fractal Wave Analysis: Integrates real-time trend analysis from both current and higher timeframes. Shows the current price range boundaries (high/low) and trend direction through dynamic lines and background fills, helping traders understand market structure.
Key Trading Benefits
Active Level Detection: The closest Gann level to current price is automatically highlighted in green with increased line thickness. This eliminates guesswork about which level is most likely to act as immediate support or resistance.
Real-Time Price Tracking: A customizable line follows current price with an offset to the right, projecting where price sits relative to upcoming levels. A gradient-filled box visualizes the exact distance between current price and the active Gann level.
Multi-Timeframe Context: View fractal waves from higher timeframes while maintaining current timeframe precision. This helps identify whether short-term moves align with or contradict longer-term structure.
Smart Alert System: Comprehensive alerts trigger when price crosses any Gann level, with options to monitor all levels or focus only on the active level. Reduces the need for constant chart monitoring while ensuring you never miss significant level breaks.
Practical Trading Applications
Entry Timing: Use active level highlighting to identify the most probable support/resistance for entries. The real-time distance box helps gauge risk/reward before entering positions.
Risk Management: Set stops based on Gann level breaks, particularly doubly strong levels which tend to be more significant. The gradient visualization makes it easy to see how much room price has before hitting key levels.
Trend Confirmation: Fractal waves provide immediate context about whether current price action aligns with broader market structure. Bullish/bearish background fills offer quick visual confirmation of trend direction.
Multi-Asset Analysis: The auto-scaling multiplier system works across all markets and timeframes, making it valuable for traders who monitor multiple instruments with vastly different price ranges.
Confluence Trading: Combine Gann levels with fractal wave boundaries to identify high-probability setups where multiple technical factors align.
This tool is particularly valuable for traders who appreciate mathematical precision in their technical analysis while maintaining the flexibility to adapt to real-time market conditions.
Multi-Band Trend LineThis Pine Script creates a versatile technical indicator called "Multi-Band Trend Line" that builds upon the concept of the popular "Follow Line Indicator" by Dreadblitz. While the original Follow Line Indicator uses simple trend detection to place a line at High or Low levels, this enhanced version combines multiple band-based trading strategies with dynamic trend line generation. The indicator supports five different band types and provides more sophisticated buy/sell signals based on price breakouts from various technical analysis bands.
Key Features
Multi-Band Support
The indicator supports five different band types:
- Bollinger Bands: Uses standard deviation to create bands around a moving average
- Keltner Channels: Uses ATR (Average True Range) to create bands around a moving average
- Donchian Channels: Uses the highest high and lowest low over a specified period
- Moving Average Envelopes: Creates bands as a percentage above and below a moving average
- ATR Bands: Uses ATR multiplier to create bands around a moving average
Dynamic Trend Line Generation (Enhanced Follow Line Concept)
- Similar to the Follow Line Indicator, the trend line is placed at High or Low levels based on trend direction
- Key Enhancement: Instead of simple trend detection, this version uses band breakouts to trigger trend changes
- When price breaks above the upper band (bullish signal), the trend line is set to the low (optionally adjusted with ATR) - similar to Follow Line's low placement
- When price breaks below the lower band (bearish signal), the trend line is set to the high (optionally adjusted with ATR) - similar to Follow Line's high placement
- The trend line acts as dynamic support/resistance, following the price action more precisely than the original Follow Line
ATR Filter (Follow Line Enhancement)
- Like the original Follow Line Indicator, an ATR filter can be selected to place the line at a more distance level than the normal mode settled at candles Highs/Lows
- When enabled, it adds/subtracts ATR value to provide more conservative trend line placement
- Helps reduce false signals in volatile markets
- This feature maintains the core philosophy of the Follow Line while adding more precision through band-based triggers
Signal Generation
- Buy Signal: Generated when trend changes from bearish to bullish (trend line starts rising)
- Sell Signal: Generated when trend changes from bullish to bearish (trend line starts falling)
- Signals are displayed as labels on the chart
Visual Elements
- Upper and lower bands are plotted in gray
- Trend line changes color based on direction (green for bullish, red for bearish)
- Background color changes based on trend direction
- Buy/sell signals are marked with labeled shapes
How It Works
Band Calculation: Based on the selected band type, upper and lower boundaries are calculated
Signal Detection: When price closes above the upper band or below the lower band, a breakout signal is generated
Trend Line Update: The trend line is updated based on the breakout direction and previous trend line value
Trend Direction: Determined by comparing current trend line with the previous value
Alert Generation: Buy/sell conditions trigger alerts and visual signals
Use Cases
Enhanced trend following strategies: More precise than basic Follow Line due to band-based triggers
Breakout trading: Multiple band types provide various breakout opportunities
Dynamic support/resistance identification: Combines Follow Line concept with band analysis
Multi-timeframe analysis with different band types: Choose the most suitable band for your timeframe
Reduced false signals: Band confirmation provides better entry/exit points compared to simple trend following
MTF Oscillator Stack [BigBeluga]🔵 OVERVIEW
The MTF Oscillator Stack brings powerful multi-timeframe momentum analysis directly into your price chart. You can select one oscillator— RSI , MFI , or Stochastic RSI —and display it across up to 4 different timeframes. Each panel is neatly stacked horizontally above price , offering quick insight into cross-timeframe conditions like trend direction, exhaustion zones, and momentum shifts.
🔵 CONCEPTS
Single Oscillator Mode: Select one oscillator type (RSI, MFI, or Stoch RSI) to analyze across all selected timeframes.
Top-Chart Horizontal Panels: Oscillator plots are aligned horizontally at the top of the chart for seamless top-down reading.
Signal Comparison Arrows: Arrows (🢁 / 🢃) indicate oscillator position relative to its signal line.
Overbought/Oversold Zones: Transparent 30–70 fill zones highlight key reversal areas.
Dynamic Display Logic: Only enabled panels are shown; spacing adjusts based on active timeframes.
Timeframe Tagging: Each oscillator panel is labeled with its corresponding timeframe (e.g., 1H, 2H, 4H).
🔵 FEATURES
Choose one oscillator (RSI, MFI, or Stoch RSI) and apply it across up to 4 timeframes.
Each oscillator panel includes: price-synced plot, signal line, and zone shading.
Scale alignment allows users to place charts at the bottom or top.
Clear arrow signals show whether oscillator is bullish or bearish.
Individual length and signal settings per timeframe.
Toggle for alignment mode: evenly spaced or floating layout.
All panels use a consistent layout for faster decision-making.
🔵 HOW TO USE
Select your preferred oscillator and activate 2–4 key timeframes (e.g., 1H, 4H, D1, W1).
Use signal crossovers as a bullish (🢁) or bearish (🢃) trend cue.
Look for aligned extremes (e.g., all timeframes overbought) to spot momentum exhaustion.
Ideal for momentum confluence strategies and top-down confirmation.
Use horizontal layout to stay focused on price while assessing broader structure.
🔵 CONCLUSION
MTF Oscillator Stack simplifies complex multi-timeframe momentum analysis into one clean, actionable visual. Whether you're tracking RSI, MFI, or Stoch RSI, this tool helps you stay aligned with the broader trend—without ever leaving your main chart.
