Liquidation Cascade Detector [QuantAlgo]🟢 Overview
The Liquidation Cascade Detector employs multi-dimensional microstructure analysis to identify forced liquidation events by synthesizing volume anomalies, price acceleration dynamics, and volatility regime shifts. Unlike conventional momentum indicators that merely track directional bias, this indicator isolates the specific market conditions where leveraged positions experience forced unwinding, creating asymmetric opportunities for mean reversion traders and market makers to take advantage of temporary liquidity imbalances.
These liquidation cascades manifest through various catalysts: overwhelming spot selling coupled with leveraged long liquidation forced unwinding creates downward spirals where organic sell pressure triggers margin calls, which generate additional selling that triggers more margin calls. Conversely, sudden large buy orders or coordinated buying can squeeze overleveraged shorts, forcing buy-to-cover orders that push price higher, triggering additional short stops in a self-reinforcing feedback loop. The indicator captures both scenarios, regardless of whether the initial catalyst is organic flow or forced liquidation.
For sophisticated traders/market makers deploying amplification strategies, this indicator serves as an early warning system for distressed order flow. By detecting the moments when cascading stop-losses and margin calls create self-reinforcing price movements, the system enables traders to: (1) identify forced participants experiencing capital pressure, (2) strategically add liquidity in the direction of panic flow to amplify displacement, (3) accumulate contra-positions during the overshoot phase, and (4) capture mean reversion profits as equilibrium pricing reasserts itself. This approach transforms destructive liquidation events into potential profit opportunities by systematically front-running and then fading coordinated forced selling/buying.
🟢 How It Works
The detection engine operates through a three-tier confirmation framework that validates liquidation events only when multiple independent market stress indicators align simultaneously:
► Tier 1: Volume Anomaly Detection
The system calculates bar-to-bar volume ratios to identify abnormal participation spikes characteristic of forced liquidations. The Volume Spike threshold filters for transactions where current volume significantly exceeds previous bar volume. When leveraged positions hit stop-losses or margin requirements, their simultaneous unwinding creates distinctive volume signatures absent during organic price discovery. This metric isolates moments when market makers face one-sided order flow from distressed participants unable to control execution timing, whether triggered by whale orders absorbing liquidity or cascading margin calls creating relentless directional pressure.
► Tier 2: Price Acceleration Measurement
By comparing current bar's absolute body size against the previous bar's movement, the algorithm quantifies momentum acceleration. The Price Acceleration threshold identifies scenarios where price velocity increases dramatically, a hallmark of cascading liquidations where each stop-loss triggers additional stops in a feedback loop. This calculation distinguishes between gradual trend development (irrelevant for amplification attacks) and explosive moves driven by forced order flow requiring immediate liquidity provision. The metric captures both panic selling scenarios where spot sellers overwhelm bid liquidity triggering long liquidations, and short squeeze dynamics where aggressive buying exhausts offer-side depth forcing short covering.
► Tier 3: Volatility Expansion Analysis
The indicator measures bar range expansion by computing the current high-low range relative to the previous bar. The Volatility Spike threshold captures regime shifts where intrabar price action becomes erratic, evidence that market depth has evaporated and order book imbalance is driving price. Combined with body-to-range analysis indicating strong directional conviction, this metric confirms that volatility expansion reflects genuine liquidation pressure rather than random noise or low-volume chop.
*Supplementary Confirmation Metrics
Beyond the three primary detection tiers, the system analyzes additional candle characteristics that distinguish genuine liquidation events from ordinary volatility:
► Candle Strength: Measures the ratio of candle body size to total bar range. High readings (above 60%) indicate strong directional conviction where price moved decisively in one direction with minimal retracement. During liquidations, distressed traders execute market orders that drive price aggressively without the normal back-and-forth of balanced trading. Strong-bodied candles with minimal wicks confirm forced participants are accepting any available price rather than attempting to minimize slippage, validating that observed volume and price acceleration stem from liquidation pressure rather than routine trading.
► Volume Climax: Identifies when current volume reaches the highest level within recent history. Climax volume events mark terminal liquidation phases where maximum panic or squeeze intensity occurs. These extreme participation spikes typically represent the final wave of forced exits as the last remaining stops are triggered or the final shorts capitulate. For mean reversion traders, volume climax signals provide optimal reversal entry timing, as they mark maximum displacement from equilibrium when all forced sellers/buyers have been exhausted.
*Directional Classification
The system categorizes cascades into two actionable classes:
1. Short Liquidation (Bullish Cascade): Upward price movement combined with cascade patterns equals forced short covering. This occurs when aggressive spot buying (often from whales placing large market orders) or coordinated buy programs exhaust available offer liquidity, spiking price upward and triggering clustered short stop-losses. Short sellers experiencing margin pressure must buy-to-close regardless of price, creating artificial demand spikes that compound the initial buying pressure. The combination of organic buying and forced covering creates explosive upward moves as each liquidated short adds buy-side pressure, triggering additional shorts in a self-reinforcing loop. Market makers can amplify this by lifting offers ahead of forced buy orders, then selling into the exhaustion at elevated levels.
2. Long Liquidation (Bearish Cascade): Downward price movement combined with cascade patterns equals forced long liquidation. This manifests when heavy spot selling (panic sellers, large institutional unwinds, or coordinated distribution) overwhelms bid-side liquidity, breaking through support levels where long stop-losses cluster. Over-leveraged longs facing margin calls must sell-to-close at any price, generating artificial supply waves that compound the initial selling pressure. The dual force of organic selling coupled with forced long liquidation creates downward spirals where each margin call triggers additional margin calls through further price deterioration. Amplification opportunities exist by hitting bids ahead of panic selling, accumulating long positions during the capitulation, and reversing as sellers exhaust.
🟢 How to Use
1. For Mean Reversion Traders
When the indicator highlights a short liquidation cascade (green background), this signals that shorts are experiencing forced buy-to-cover pressure, often initiated by whale bids or aggressive spot buying that triggered the squeeze. Mean reversion traders can interpret this as a temporary upward dislocation from fair value. As the dashboard shows declining momentum metrics and the cascade highlighting stops, this represents a potential fade opportunity. Enter short positions expecting price to revert back toward pre-cascade levels once the forced buying exhausts and the initial large buyer completes their accumulation.
When a long liquidation cascade triggers (red background), longs are undergoing forced sell-to-close liquidation, typically catalyzed by overwhelming spot selling that breached key support levels. This creates artificial downward pressure disconnected from fundamental value, as margin-driven forced selling compounds organic sell flow. Mean reversion traders wait for the cascade to complete (dashboard transitions from active liquidation status to neutral), then enter long positions anticipating snap-back toward equilibrium pricing as panic subsides and forced sellers are exhausted.
You can also monitor the dashboard's Volume Climax indicator. When it displays "YES" during an active cascade, this suggests the liquidation is reaching its terminal phase, whether driven by the final shorts being squeezed out or the last leveraged longs capitulating. Mean reversion entries become highest probability at this point, as maximum displacement from fair value has occurred. Wait for the next 1-3 bars after climax confirmation, then enter contra-trend positions with tight stops.
The Candle Strength metric also helps validate entry timing. When candle strength readings drop significantly after maintaining elevated levels during the cascade, this divergence indicates absorption is occurring. Market makers are stepping in to provide liquidity, supporting your mean reversion thesis. Strong candle bodies during the cascade followed by weaker bodies signal the forced flow is diminishing.
2. For Momentum & Trend Following Traders
When price breaks through a significant resistance level and immediately triggers a short liquidation cascade (green background), this confirms breakout validity through forced participation. Shorts positioned against the breakout are now experiencing margin pressure from the combination of breakout momentum and potential whale buying, creating self-reinforcing buying that propels price higher. Enter long positions during the cascade or immediately after, as the forced covering provides fuel for extended momentum continuation.
Conversely, when price breaks below key support and triggers a long liquidation cascade (red background), the breakdown is validated by forced selling from trapped longs. Heavy spot selling coupled with margin liquidations creates accelerated downside momentum as liquidations cascade through clustered stop-loss levels. Enter short positions as the cascade develops, riding the combined force of organic selling and forced liquidation for extended trend moves.
3. For Sophisticated Traders & Market Makers
► Amplification Attack Execution
Sophisticated operators can exploit cascades through systematic amplification positioning. When a short liquidation is detected (green highlight activating), often initiated by whale bids absorbing offer liquidity, place aggressive buy orders to front-run and amplify the forced short covering. This exacerbates upward pressure, pushing price further from equilibrium and triggering additional clustered stops. Simultaneously begin accumulating short positions at these artificially elevated levels. As dashboard metrics indicate cascade exhaustion (volume spike declining, climax signal appearing, candle strength weakening), flatten amplification longs and hold accumulated shorts into the mean reversion.
For long liquidations (red highlight), typically catalyzed by heavy spot selling overwhelming bid depth, execute the inverse strategy. Place aggressive sell orders to compound the panic selling, amplifying downward displacement and accelerating margin call triggers. Layer long entries at depressed prices during this amplification phase as forced liquidation selling creates artificial supply. When dashboard signals cascade completion (metrics normalizing, volume climax passing), exit amplification shorts and maintain long positions for the reversal trade.
► Market Making During Liquidity Crises
During detected cascades, temporarily adjust quote placement strategy. When dashboard shows all three confirmation metrics activating simultaneously with strong candle bodies, this indicates the highest probability liquidation event, whether from whale order flow or cascading margin calls. Widen spreads dramatically to capture enhanced edge during the liquidity vacuum. Alternatively, step away from quote provision entirely on your natural inventory side (stop offering during short cascades driven by aggressive buying, stop bidding during long cascades driven by overwhelming selling) to avoid adverse selection from forced flow.
Use cascade detection to inform inventory management. During short cascades initiated by large buy orders or short squeezes, reduce existing short inventory exposure while allowing the forced buying to push price higher. Rebuild short inventory only at the inflated levels created by liquidation pressure. During long cascades where spot selling compounds leveraged liquidation, reduce long inventory and use the forced selling to reaccumulate at artificially depressed prices rather than providing stabilizing liquidity too early.
► Sequential Positioning Strategy
Advanced traders can structure trades in phases: (1) Initial amplification orders placed immediately upon cascade detection to front-run forced flow, (2) Contra-position accumulation scaled in as displacement extends and dashboard readings intensify, (3) Amplification trade exit when metrics show deceleration or candle strength weakens, (4) Contra-position hold through mean reversion, targeting pre-cascade price levels. This sequential approach extracts profit from both the dislocation phase and the subsequent equilibrium restoration.
► Risk Monitoring
If cascade highlighting persists across many consecutive bars while dashboard volume readings remain extremely elevated with sustained strong candle bodies, this suggests sustained institutional deleveraging or persistent whale activity rather than simple retail liquidation. Reduce amplification position sizing significantly, as these extended events can exhibit delayed mean reversion. Professional counter-parties may be establishing dominant positions, limiting your edge.
When volatility spike metrics decline while cascade highlighting continues, professional absorption is occurring. Proceed cautiously with amplification strategies, as intelligent liquidity providers are already positioning for the reversal, potentially front-running your intended reversal trade. Similarly, if large liquidation wicks appear during cascades, this indicates partial absorption is happening, suggesting more sophisticated players are taking the opposite side of distressed flow.
XAUUSD
Trading Sessions [QuantAlgo]🟢 Overview
The Trading Sessions indicator tracks and displays the four major global trading sessions: Sydney, Tokyo, London, and New York. It provides session-based background highlighting, real-time price change tracking from session open, and a data table with session status. The script works across all markets (forex, equities, commodities, crypto) and helps traders identify when specific geographic markets are active, which directly correlates with changes in liquidity and volatility patterns. Default session times are set to major financial center hours in UTC but are fully adjustable to match your trading methodology.
🟢 Key Features
→ Session Background Color Coding
Each trading session gets a distinct background color on your chart:
1. Sydney Session - Default orange, 22:00-07:00 UTC
2. Tokyo Session - Default red, 00:00-09:00 UTC
3. London Session - Default green, 08:00-16:00 UTC
4. New York Session - Default blue, 13:00-22:00 UTC
When sessions overlap, the color priority is New York > London > Tokyo > Sydney. This means if London and New York are both active, the background shows New York's color. The priority matches typical liquidity and volatility patterns where later sessions generally show higher volume.
→ Color Customization
All session colors are configurable in the Color Settings panel:
1. Click any session color input to open the color picker
2. Select your preferred color for that session
3. Use the "Background Transparency" slider (0-100) to adjust opacity. Lower values = more visible, higher values = more subtle
4. Enable "Color Price Bars" to color candlesticks themselves according to the active session instead of just the background
The Color column in the info table shows a block (█) in each session's assigned color, matching what you see on the chart background.
→ Information Table Breakdown
→ Timeframe Warning
If you're viewing a timeframe of 12 hours or higher, a red warning label appears center-screen. Session boundaries don't render accurately on high timeframes because the time() function in Pine Script can't detect intra-bar session changes when each bar spans multiple sessions. The warning tells you to switch to sub-12H timeframes (e.g., 4H, 1H, 30m, 15m, etc.) for proper session detection. You can disable this warning in Color Settings if needed, but session highlighting can be unreliable on 12H+ charts regardless.
→ Time Range Configuration
Every session's time range is editable in Session Settings:
1. Click the time input field next to each session
2. Enter time as HHMM-HHMM in 24-hour format
3. All times are interpreted as UTC
4. Modify these to account for daylight saving shifts or to define custom session periods based on your backtested optimal trading windows
For example, if your strategy performs best during London/NY overlap specifically, you could set London to 08:00-17:00 and New York to 13:00-22:00 to ensure you see the full overlap highlighted.
→ Weekdays Filter
The "Weekdays Only (Mon-Fri)" toggle controls whether sessions display on weekends:
Enabled: Sessions only show Monday-Friday and hide on Saturday-Sunday. Use this for markets that close on weekends (most equities, forex).
Disabled: Sessions display 24/7 including weekends. Use this for markets that trade continuously (crypto).
→ Table Display Options
The info table has several configuration options in Table Settings:
Visibility: Toggle "Show Info Table" on/off to display or hide the entire table.
Position: Nine position options (Top/Middle/Bottom + Left/Center/Right) let you place the table wherever it doesn't block your price action or other indicators.
Text Size: Four size options (Tiny, Small, Normal, Large) to match your screen resolution and visual preferences.
→ Color Schemes:
Mono: Black background, gray header, white text
Light: White background, light gray header, black text
Blue: Dark blue background, medium blue header, white text
Custom: Manual selection of all five color components (table background, header background, header text, data text, borders)
→ Alert Functionality
The indicator includes ten alert conditions you can access via TradingView's alert system:
Session Opens:
1. Sydney Session Started
2. Tokyo Session Started
3. London Session Started
4. New York Session Started
5. Any Session Started
Session Closes:
6. Sydney Session Ended
7. Tokyo Session Ended
8. London Session Ended
9. New York Session Ended
10. Any Session Ended
These alerts fire when sessions transition based on your configured time ranges, letting you automate monitoring of session changes without watching the chart continuously. Useful for strategies that trade specific session opens/closes or need to adjust position sizing when volatility regime shifts between sessions.
Frequency Momentum Oscillator [QuantAlgo]🟢 Overview
The Frequency Momentum Oscillator applies Fourier-based spectral analysis principles to price action to identify regime shifts and directional momentum. It calculates Fourier coefficients for selected harmonic frequencies on detrended price data, then measures the distribution of power across low, mid, and high frequency bands to distinguish between persistent directional trends and transient market noise. This approach provides traders with a quantitative framework for assessing whether current price action represents meaningful momentum or merely random fluctuations, enabling more informed entry and exit decisions across various asset classes and timeframes.
🟢 How It Works
The calculation process removes the dominant trend from price data by subtracting a simple moving average, isolating cyclical components for frequency analysis:
detrendedPrice = close - ta.sma(close , frequencyPeriod)
The detrended price series undergoes frequency decomposition through Fourier coefficient calculation across the first 8 harmonics. For each harmonic frequency, the algorithm computes sine and cosine components across the lookback window, then derives power as the sum of squared coefficients:
for k = 1 to 8
cosSum = 0.0
sinSum = 0.0
for n = 0 to frequencyPeriod - 1
angle = 2 * math.pi * k * n / frequencyPeriod
cosSum := cosSum + detrendedPrice * math.cos(angle)
sinSum := sinSum + detrendedPrice * math.sin(angle)
power = (cosSum * cosSum + sinSum * sinSum) / frequencyPeriod
Power measurements are aggregated into three frequency bands: low frequencies (harmonics 1-2) capturing persistent cycles, mid frequencies (harmonics 3-4), and high frequencies (harmonics 5-8) representing noise. Each band's power normalizes against total spectral power to create percentage distributions:
lowFreqNorm = totalPower > 0 ? (lowFreqPower / totalPower) * 100 : 33.33
highFreqNorm = totalPower > 0 ? (highFreqPower / totalPower) * 100 : 33.33
The normalized frequency components undergo exponential smoothing before calculating spectral balance as the difference between low and high frequency power:
smoothLow = ta.ema(lowFreqNorm, smoothingPeriod)
smoothHigh = ta.ema(highFreqNorm, smoothingPeriod)
spectralBalance = smoothLow - smoothHigh
Spectral balance combines with price momentum through directional multiplication, producing a composite signal that integrates frequency characteristics with price direction:
momentum = ta.change(close , frequencyPeriod/2)
compositeSignal = spectralBalance * math.sign(momentum)
finalSignal = ta.ema(compositeSignal, smoothingPeriod)
The final signal oscillates around zero, with positive values indicating low-frequency dominance coupled with upward momentum (trending up), and negative values indicating either high-frequency dominance (choppy market) or downward momentum (trending down).
🟢 How to Use This Indicator
→ Long/Short Signals: the indicator generates long signals when the smoothed composite signal crosses above zero (indicating low-frequency directional strength dominates) and short signals when it crosses below zero (indicating bearish momentum persistence).
→ Upper and Lower Reference Lines: the +25 and -25 reference lines serve as threshold markers for momentum strength. Readings beyond these levels indicate strong directional conviction, while oscillations between them suggest consolidation or weakening momentum. These references help traders distinguish between strong trending regimes and choppy transitional periods.
→ Preconfigured Presets: three optimized configurations are available with Default (32, 3) offering balanced responsiveness, Fast Response (24, 2) designed for scalping and intraday trading, and Smooth Trend (40, 5) calibrated for swing trading and position trading with enhanced noise filtration.
→ Built-in Alerts: the indicator includes three alert conditions for automated monitoring - Long Signal (momentum shifts bullish), Short Signal (momentum shifts bearish), and Signal Change (any directional transition). These alerts enable traders to receive real-time notifications without continuous chart monitoring.
→ Color Customization: four visual themes (Classic green/red, Aqua blue/orange, Cosmic aqua/purple, Custom) allow chart customization for different display environments and personal preferences.
Global Sessions by Back Ground ColorGlobal Sessions Background Color Indicator
This free TradingView tool visually highlights major global trading sessions directly on your chart using clean, professional color coding. It’s designed to help traders quickly identify periods of high liquidity and overlapping sessions, which often drive volatility and key price movements.
Features:
Session Highlights: Marks Asian, European (London), US (New York), and Overnight sessions with distinct background colors.
Overlap Detection: Special colors for overlapping sessions (e.g., London + New York).
Market Open/Close Alerts: Displays labels for major financial centers when they open or close.
Timezone-Aware: Automatically adjusts to Europe/Amsterdam (modifiable for your needs).
Clean Design: Uses a light, professional color palette for easy chart readability.
Why Use It?
Session timing is critical for spotting breakouts, reversals, and liquidity shifts. This indicator gives traders a clear visual edge without cluttering the chart—perfect for scalpers, day traders, and swing traders.
Completely free for the TradingView community – built by a trader, for traders.
How to Use the Global Sessions Indicator
This indicator automatically highlights major trading sessions on your chart using background colors. It helps you quickly identify when liquidity and volatility are likely to increase.
Color Guide:
Light Sky Blue → Asian Session (Tokyo, Sydney)
Active from 02:00 to 12:00 Amsterdam time. Often quieter but sets early trends.
Light Coral → European Session (London, Frankfurt)
Active from 09:00 to 17:30 Amsterdam time. Brings strong liquidity and trend continuation.
Light Green → US Session (New York, Chicago)
Active from 15:30 to 22:00 Amsterdam time. High volatility, major moves often occur here.
Gold/Yellow → Overnight/Wellington
Active from 23:00 to 02:00 Amsterdam time. Low liquidity, pre-Asia positioning.
Overlap Colors:
Orchid (Pinkish) → Asia + Europe Overlap
Indicates transition from Asia to London—watch for breakouts.
Light Salmon → Europe + US Overlap
The most volatile period of the day—ideal for intraday traders.
Extra Feature:
Labels show market open/close times for major financial centers (e.g., London Open, New York Close).
[AutoZone_mrkim]- Use wisely
- The indicator will automatically draw the Order Block zone for each timeframe
- It will change color if a zone is broken out
- Each timeframe will have different zone levels depending on the timeframe used
Lot Size CalculatorLot Size Calculator for Gold (XAU)
This indicator helps traders calculate the proper lot size for Gold (XAU) based on their entry, stop loss, and risk amount in USD.
You can set your entry and stop levels directly on the chart, and adjust your dollar risk from the settings panel.
The indicator measures the distance between entry and stop to calculate the position size that matches your selected risk.
A clean, customizable table displays key values such as Risk, Entry, Stop, Target, Lots, and Pips.
You can easily hide specific rows, change colors, and adjust layout options to fit your chart style.
Designed specifically for Gold traders, this tool provides a simple and visual way to manage risk directly on the chart.
Cumulative Delta_Effort vs Result_immy**Cumulative Delta Oscillator\_effort**
This script creates a “Cumulative Delta Effort vs Result” oscillator, a custom indicator designed to measure the balance between buying and selling pressure (Effort) versus actual price movement (Result).
**How It Works**
Delta Volume: Measures aggressive buying vs selling per candle.
Cumulative Delta: Tracks net buying/selling pressure over time.
Effort vs Result: Compares volume delta (effort) to price movement (result).
Oscillator: Highlights divergence between effort and result, useful for spotting absorption (high effort, low result) and exhaustion (low effort, high result).
Histogram: Visual cue for accumulation/distribution zones.
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This indicator combines volume delta (effort) and price movement (result), so it tells you how efficiently volume is moving price — a concept sometimes called effort vs. result analysis in Wyckoff or volume–spread analysis (VSA).
🔍 Concept Summary
Effort (delta volume) = how much buying/selling pressure is there (volume side).
Result (price change) = how much that effort moves price (price side).
Oscillator (Effort − Result) = how much “extra” effort is not producing movement — often showing absorption or exhaustion.
📈 How to Interpret the Signals
1\. Oscillator above Signal line → Bullish Momentum
When osc > signal, histogram turns green.
Means buying effort is stronger than price reaction — often early sign of accumulation or rising demand.
This can signal:
Possible bullish continuation if confirmed by rising prices.
Or early absorption if prices aren’t yet breaking out (smart money absorbing supply).
✅ Bullish Entry Signal:
When the oscillator crosses above the signal line (green cross) and price is near support or consolidating → potential long setup.
2\. Oscillator below Signal line → Bearish Momentum
When osc < signal, histogram turns red.
Selling effort dominates; can mean increasing supply or price exhaustion.
This often appears before:
Bearish continuation (trend strengthening)
Or upthrust/exhaustion (price rising on weak volume)
❌ Bearish Entry Signal:
When the oscillator crosses below the signal line (red cross), especially if near resistance → potential short setup.
3\. Crossovers
The alert is triggered when: ta.cross(osc, signal)
That means:
Bullish crossover: oscillator line crosses above signal → potential buy momentum shift.
Bearish crossover: oscillator line crosses below signal → potential sell momentum shift.
These work like MACD crossovers, but volume-adjusted.
4\. Zero Line
The zero line is the neutral point.
When osc crosses above zero, overall buying effort exceeds price change — market gaining strength.
When osc crosses below zero, selling pressure increases — market weakening.
→ Combining signal line crosses with zero-line crosses gives stronger confirmation.
5\. Histogram Analysis (Absorption \& Exhaustion)**
Tall green bars: rising momentum (buyers dominate)
Tall red bars: falling momentum (sellers dominate)
Shrinking bars: momentum fading — possible reversal zone.
If volume increases but price stalls, oscillator may spike while price stays flat — absorption (big players taking the opposite side).
If price surges but oscillator weakens, exhaustion — move running out of volume support.
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🧠 Practical Strategy Example
Situation What It Might Mean Possible Action
Oscillator crosses above signal near support Buyer effort increasing, price may rise Go long / close shorts
Oscillator crosses below signal near resistance Seller effort rising, price may drop Go short / take profits
Oscillator high but price flat Absorption (big players absorbing supply) Wait for breakout confirmation
Oscillator low but price flat Absorption (demand absorbing supply) Look for bullish reversal
Oscillator diverges from price Volume–price divergence Early warning of reversal
⚙️ Best Practice
Works best on volume-sensitive assets (futures, crypto, forex tick data).
**Combine with:**
Price structure (support/resistance)
Volume profile / delta footprint
Candle confirmation
We’ll go through both bullish and bearish examples so you can see how to trade with it in real market context.
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🟩 Example 1 — Bullish Setup (Long Trade)
Step 1. Context: Identify Potential Support Zone
Before relying on any indicator, find support using:
Previous swing low
Demand zone
VWAP / volume profile node
Trendline or moving average
👉 You’re looking for a place where buyers might step in.
Step 2. Wait for Oscillator Signal
Watch the oscillator panel:
The oscillator (green line) has been below the signal line (orange) → bearish phase.
Then it crosses above the signal line and the histogram turns green.
This means:
➡️ Buying “effort” is increasing faster than price reaction — momentum shift upward.
Step 3. Confirm with Price
On your chart:
Candle closes above short-term resistance or above previous candle high
Ideally volume confirms (green candle with increasing volume)
✅ Bullish Entry Condition
osc crosses above signal
price closes above local resistance
Step 4. Entry \& Stop
Entry: Next candle open after confirmation cross
Stop-loss: Below recent swing low or support zone
Take profit:
2R or 3R target
or near next resistance level
🧠 Optional filter: Only take the trade if oscillator is rising from below zero (coming out of weakness).
Step 5. Manage Trade
If oscillator flattens or starts curling down → tighten stop
If it crosses below the signal again → consider exit
Example Interpretation:
Oscillator crosses above signal from -200 to +100, histogram turns green, price breaks a resistance line → strong bullish reversal → enter long.
🟥 Example 2 — Bearish Setup (Short Trade)
Step 1. Context: Find Resistance
Look for: Prior swing high
Supply zone
Major moving average
Trendline top
Step 2. Wait for Oscillator Cross Down
The oscillator (green) crosses below the signal line (orange).
Histogram turns red.
This means:
➡️ Selling effort is rising relative to price movement — bearish pressure.
Step 3. Confirm with Price
Price fails to make higher highs, or
Forms a bearish engulfing candle near resistance.
✅ Bearish Entry Condition
osc crosses below signal
price confirms with bearish candle
Step 4. Entry \& Stop
Entry: On next candle open
Stop-loss: Above resistance or recent swing high
Take profit: 2R or more or at next major support
Step 5. Exit on Opposite Signal
If oscillator crosses back above signal → momentum shift → exit short.
⚙️ Pro Tips
Tip Why It Matters
Use on 15m–4H+ charts More reliable delta signal
Combine with volume or OBV Confirms “effort” strength
Watch divergences Early reversals
Align with higher timeframe trend Avoid countertrend traps
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🧩 Quick Checklist
Step Condition Action
1 Identify zone (support/resistance) Mark area
2 Oscillator crossover Prepare order
3 Candle confirmation Enter
4 Stop-loss \& target Manage risk
5 Opposite cross Exit
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RSI EMA Crossover with Price ActionThe RSI and RSI's EMA Crossover with Price Action (1:2 Risk-Reward) strategy combines Momentum, Trend confirmation, and Basic price-action logic to generate high-probability trade setups with Proper Risk Management.
This script identifies entries when the RSI crosses a key threshold and aligns with an RSI - EMA crossover, confirming Exhaustion of a current trend and Price action confirms the Change in Trend direction. It integrates price action filters to avoid false signals during low-volatility or choppy conditions.
The strategy also includes a risk-management module, setting a fixed 1:2 risk-to-reward ratio — automatically placing a take-profit target twice the size of the stop loss. Also the Stop loss can be adjusted to nearest swing low or last 3 candles Low. to avoid Stoploss hunt.
Features
✅ RSI and EMA crossover confirmation for directional bias
✅ Basic price-action validation (optional filters)
✅ Configurable stop-loss and take-profit levels (default 1:2)
✅ Visual trade markers for entries and exits
Disclaimer: This script is intended for educational and research purposes only. It should not be considered financial advice or a guaranteed trading system. Users are encouraged to test and optimize parameters before using in live markets.
Volume Cluster Support and Resistance Levels [QuantAlgo]🟢 Overview
This indicator identifies statistically significant support and resistance levels through volume cluster analysis, isolating price zones characterized by elevated trading activity and institutional participation. By quantifying areas where volume concentration exceeded historical norms, it reveals price levels with demonstrated supply-demand imbalances that exhibit persistent influence on subsequent price action. The methodology is asset-agnostic and timeframe-independent, applicable across equities, cryptocurrencies, forex, and commodities from intraday to weekly intervals.
🟢 Key Features
1. Support and Resistance Levels
The indicator scans historical price data to identify bars where volume exceeds a user-defined threshold multiplier relative to the rolling average. For each qualifying bar, a representative price is calculated using the average of high, low, and close. Proximate price levels within a specified percentage range are then aggregated into discrete clusters using volume-weighted averaging, eliminating redundant signals. Clusters are ranked by cumulative volume to determine statistical significance. Finally, the indicator plots horizontal levels at each cluster price: support levels (green) below current price indicate zones where historical buying pressure exceeded selling pressure, while resistance levels (red) above current price mark zones where sellers historically dominated. These levels represent areas of established liquidity and price discovery, where institutional order flow previously concentrated.
The Touch Count (T) metric quantifies historical price interaction frequency, while Total Volume (TV) measures aggregate trading activity at each level, providing objective criteria for assessing level strength and trade execution decisions.
2. Volume Histogram
A histogram appears below the price chart, displaying relative volume for each bar within the lookback period, with bar height scaled to the maximum volume observed. Green bars represent up-periods (close > open) indicating buying pressure, while red bars show down-periods (close < open) indicating selling pressure. This visualization helps you confirm the validity of support/resistance levels by seeing where volume actually spiked, identify accumulation/distribution patterns, and validate breakouts by checking if they occur on above-average volume.
3. Built-in Alerts
Automated alerts trigger when price crosses below support levels or breaks above resistance levels, allowing you to monitor multiple assets without constant chart-watching.
4. Customizable Color Schemes
The indicator provides four preset color configurations (Classic, Aqua, Cosmic, Custom) optimized for visual clarity across different charting environments. Each scheme maintains consistent color mapping for support and resistance zones across both level lines and volume histogram components. The Custom configuration permits full color specification to accommodate individual charting setups, ensuring optimal visual contrast for extended analysis sessions.
Classic:
Aqua:
Cosmic:
Custom:
🟢 Pro Tips
→ Trade entry optimization: Execute long positions at support levels with high touch counts or upon confirmed resistance breakouts accompanied by above-average volume
→ Risk parameter definition: Position stop-loss orders near identified support/resistance zones with statistical significance to minimize premature exits
→ Breakout validation: Require volume confirmation exceeding historical average when price penetrates resistance to filter false breakouts
→ Level strength assessment: Prioritize levels with higher touch counts and total volume metrics for enhanced probability trade setups
→ Multi-timeframe confluence: Synthesize support/resistance levels across multiple timeframes to identify high-conviction zones where daily support aligns with 4-hour resistance structures
Weekly + Daily + H4 Sup and Res ZonesEveryday price move at a set range. Just wait at the zone for candle reversal/continuation pattern formation before entry. Always keep it simple. Patience is key. Just Pick your preferred tf zone. Daily zone highly recommended for less than 100 pips target. H4 for scalpers and Weekly for swingers.
EMA 9/50 News Confirmation Strategy v3 (Trend Aligned 3 bMin) “EMA 9/50 crossover strategy with trend filter and ATR-based targets”)
Indian Gold Festival Dates HistoricalIndian Gold Festival Dates (1975-2025)
Marks 8 major Indian festivals associated with gold buying over 50 years of historical data. Essential for analyzing seasonal patterns and cultural demand cycles in gold markets.
Festivals Included:
Dhanteras (Gold) - Most auspicious gold buying day
Diwali (Orange) - Festival of Lights
Akshaya Tritiya (Green) - "Never-ending" prosperity
Dussehra (Red) - Victory and success
Makar Sankranti (Cyan) - Solar new year
Gudi Padwa (Magenta) - Hindu New Year (Maharashtra)
Ugadi (Purple) - Hindu New Year (South India)
Navratri (Yellow) - 9-day festival
Features:
✓ 408 exact historical dates (1975-2025)
✓ Color-coded vertical lines for easy identification
✓ Toggle individual festivals on/off
✓ Adjustable line width and labels
✓ Works on all timeframes (best on daily/weekly)
Perfect for traders analyzing gold seasonality, Indian market sentiment, and cultural demand patterns. Use on XAUUSD, GC1!, or Indian gold futures.
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph
Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter.
Scope and intent
• Markets. Gold and silver futures or spot, other liquid commodities, major indices
• Timeframes. Five minutes to one day. Defaults to 30min for swing pace
• Default demo used in this publication. TVC:GOLD on 30m
• Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias
• Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings
• Testability. Each component has a named input. Entry names L and S are visible in the list of trades
• Portable yardstick. Weekly ATR for stops and R multiples for targets
• Open source. Method and implementation are disclosed for community review
Method overview in plain language
You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope.
Base measures
• Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE
• Return basis. Not required
Components
• Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window
• Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat
• DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens
• Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band
Fusion rule
• All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled
Signal rule
• Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish
• Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish
• Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band
Inputs with guidance
Setup
• Symbol. Default TVC:GOLD (Correlation Asset for internal logic)
• Signal timeframe. Blank follows the chart
• Confirm timeframe. Default 1 day used by the bias block
Directional Convexity Index
• DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier
• DCX rise bars. Typical 3 to 6. Higher demands continuation
• DCX entry threshold. Typical 15 to 35. Higher avoids soft moves
• Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape
• Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence
Adaptive Volatility Envelope
• AVE window. Typical 24 to 48. Higher smooths more
• Midline type. ALMA or HMA or EMA per preference
• TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions
• Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR
• Base envelope mult. Typical 1.4 to 2.2. Width of bands
• Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands
Intermarket Bias
• Use DXY bias. Default ON
• DXY timeframe. Default 1 day
• DXY trend window. Typical 10 to 50
Risk
• Risk percent per trade. Reporting field. Keep live risk near one to two percent
• Weekly ATR. Default 14. Basis for stops
• Stop ATR weekly mult. Typical 1.5 to 3.0
• Take profit R multiple. Typical 1.5 to 3.0
• Trail with AVE band. Optional. OFF by default
Properties visible in this publication
• Initial capital. 20000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3% of the total capital available
• Pyramiding 0
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the expansion logic
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
Open source reuse and credits
• None
Mode
Public open source. Source is visible and free to reuse within TradingView House Rules
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Relative Performance Tracker [QuantAlgo]🟢 Overview
The Relative Performance Tracker is a multi-asset comparison tool designed to monitor and rank up to 30 different tickers simultaneously based on their relative price performance. This indicator enables traders and investors to quickly identify market leaders and laggards across their watchlist, facilitating rotation strategies, strength-based trading decisions, and cross-asset momentum analysis.
🟢 Key Features
1. Multi-Asset Monitoring
Track up to 30 tickers across any market (stocks, crypto, forex, commodities, indices)
Individual enable/disable toggles for each ticker to customize your watchlist
Universal compatibility with any TradingView symbol format (EXCHANGE:TICKER)
2. Ranking Tables (Up to 3 Tables)
Each ticker's percentage change over your chosen lookback period, calculated as:
(Current Price - Past Price) / Past Price × 100
Automatic sorting from strongest to weakest performers
Rank: Position from 1-30 (1 = strongest performer)
Ticker: Symbol name with color-coded background (green for gains, red for losses)
% Change: Exact percentage with color intensity matching magnitude
For example, Rank #1 has the highest gain among all enabled tickers, Rank #30 has the lowest (or most negative) return.
3. Histogram Visualization
Adjustable bar count: Display anywhere from 1 to 30 top-ranked tickers (user customizable)
Bar height = magnitude of percentage change.
Bars extend upward for gains, downward for losses. Taller bars = larger moves.
Green bars for positive returns, red for negative returns.
4. Customizable Color Schemes
Classic: Traditional green/red for intuitive interpretation
Aqua: Blue/orange combination for reduced eye strain
Cosmic: Vibrant aqua/purple optimized for dark mode
Custom: Full personalization of positive and negative colors
5. Built-In Ranking Alerts
Six alert conditions detect when rankings change:
Top 1 Changed: New #1 leader emerges
Top 3/5/10/15/20 Changed: Shifts within those tiers
🟢 Practical Applications
→ Momentum Trading: Focus on top-ranked assets (Rank 1-10) that show strongest relative strength for trend-following strategies
→ Market Breadth Analysis: Monitor how many tickers are above vs. below zero on the histogram to gauge overall market health
→ Divergence Spotting: Identify when previously leading assets lose momentum (drop out of top ranks) as potential trend reversal signals
→ Multi-Timeframe Analysis: Use different lookback periods on different charts to align short-term and long-term relative strength
→ Customized Focus: Adjust histogram bars to show only top 5-10 strongest movers for concentrated analysis, or expand to 20-30 for comprehensive overview
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
EquiSense AI Signals🇸🇦 العربي
المتنبئ الذكي المتوازن (AI v7)
وصف قصير:
مؤشر تجميعي ذكي يوازن بين الاتجاه والزخم والحجم والتذبذب وأنماط الشموع، ويحوّلها إلى نظام نقاط ونجوم يولّد إشارات شراء/بيع مؤكَّدة بتقاطع MACD. بعد الإشارة، يعرض أهدافًا ذكية (TP1/TP2/TP3) ووقف خسارة مبنيَّيْن على ATR مع رسومات مستقبلية ولوحة معلومات لإدارة الصفقة.
الإعدادات (Inputs)
الحد الأدنى للنقاط (min_score): افتراضي 6.0 — كلما ارتفع قلّت الإشارات وزادت جودتها.
الحد الأدنى للنجوم (min_stars): افتراضي 2 — فلتر لقوة الإشارة.
عدد الشموع المستقبلية (future_bars): افتراضي 15 — مدى رسم الأهداف والوقف للأمام.
استخدام الأهداف الذكية (use_ai_targets): تفعيل/إيقاف مضاعِف الذكاء الاصطناعي للأهداف والوقف.
كيف يعمل؟
يحسب المؤشر buy_score/sell_score من مجموعة عوامل: EMA8/21/50/200، RSI + متوسطه، MACD + Histogram، Stochastic، ADX/DMI، VWAP، الحجم، MTF 15m، ROC/المومنتَم، Heikin Ashi، وأنماط (ابتلاع/مطرقة/شهاب).
يحوّل الدرجات إلى نجوم (⭐⭐ إلى ⭐⭐⭐⭐⭐) حسب القوة.
تولّد الإشارة فقط إذا توفّر: درجة ≥ الحد + نجوم ≥ الحد + تقاطع MACD (صعودًا للشراء، هبوطًا للبيع).
عند الإشارة يبدأ سيناريو صفقة واحدة فقط حتى تنتهي (TP3 أو SL).
الأهداف والوقف (ذكاء اصطناعي)
تُشتق من ATR ثم تُعدَّل عبر مضاعِف AI مبني على: ATR%، الزخم (ROC)، الحجم مقابل متوسطه، قوة الاتجاه (ADX)، وعدد النجوم.
تقريبيًا:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
ماذا سترى على الشارت؟
علامات “شراء/بيع”، نجوم قرب الإشارة، خط دخول (أزرق)، وقف (أحمر منقّط)، TP1/TP2 (أخضر)، TP3 (ذهبي) مع صناديق مناطق للأهداف وخط ربط نحو الهدف النهائي.
وسم AI يعرض نسبة المضاعِف والنجوم بصريًا.
لوحة معلومات تعرض الحالة، القوة، AI%، السعر، الدرجات، وأثناء الصفقة: الدخول، TP1/TP2/TP3، والربح اللحظي.
التنبيهات (Alerts)
شرطان جاهزان: شراء وبيع عند تحقق الإشارة.
أضِف تنبيه: Right click → Add alert → اختر المؤشر → الشرط المطلوب.
أفضل الممارسات
استخدم الإطار المناسب للأصل:
سكالبينغ 5–15m: min_score 8 وmin_stars 3–4.
تأرجحي H1–H4: min_score 7 وmin_stars 3.
يومي/أسهم: min_score 6–7 وmin_stars 2–3.
فضّل التداول مع EMA200 واتجاه MTF 15m.
خفّض المخاطرة وقت الأخبار العالية.
التزم بإدارة مخاطر ثابتة (مثلاً 1% لكل صفقة).
حدود مهمة
الأفضل انتظار إغلاق الشمعة لتأكيد التقاطعات وتجنّب تغيّرها.
صفقة واحدة في المرة بفضل حالة in_trade.
يستخدم request.security مع lookahead_off لإطار 15m؛ التزم بالتقييم عند الإغلاق.
أسئلة شائعة
هل يستخدم منفردًا؟ نعم، لكن مع مناطق سعرية/ترند وخطة مخاطر يصبح أقوى.
لماذا تختلف الأهداف؟ لأن مضاعِف AI يكيّف TP/SL مع ظروف السوق.
إخلاء مسؤولية
هذه أداة تحليلية تعليمية وليست نصيحة استثمارية. اختبر الإعدادات تاريخيًا والتزم بالمخاطرة المناسبة.
ملاحظة للمبرمجين
Pine Script v6، متغيرات var لحفظ الحالة، تنظيف الرسومات على الشمعة الأخيرة، مع حدود مرتفعة للرسوم لتجنّب الأخطاء.
🇬🇧 English
Balanced Smart Predictor (AI v7)
Short description:
A smart, ensemble-style indicator that blends trend, momentum, volume, volatility, and candle patterns into a score & star system that produces Buy/Sell signals confirmed by MACD crosses. After a signal, it projects smart targets (TP1/TP2/TP3) and a stop-loss derived from ATR, with forward drawings and a control panel for trade management.
Inputs
Minimum Score (min_score): default 6.0 — higher = fewer but stronger signals.
Minimum Stars (min_stars): default 2 — extra filter for strength.
Future Bars (future_bars): default 15 — how far targets/SL are drawn ahead.
Use AI Targets (use_ai_targets): toggle the AI multiplier for TP/SL.
How it works
Computes buy_score/sell_score from: EMA8/21/50/200, RSI & its MA, MACD & Histogram, Stochastic, ADX/DMI, VWAP, Volume, 15m MTF tilt, ROC/Momentum, Heikin Ashi, and candle patterns (engulfing/hammer/shooting star).
Converts scores into Stars (⭐⭐ to ⭐⭐⭐⭐⭐) via tiered thresholds.
Signals fire only when: Score ≥ minimum + Stars ≥ minimum + MACD cross (up = Buy, down = Sell).
On a signal, one active trade is managed until TP3 or SL is reached.
Targets & Stop (AI-driven)
Targets and SL are ATR-based, then adjusted by an AI multiplier derived from: ATR%, momentum (ROC), relative volume, trend strength (ADX), and star rating.
Approximate formulas:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
What you’ll see on chart
“Buy/Sell” markers with small Star labels, an Entry line (blue), SL (red dotted), TP1/TP2 (green), TP3 (gold) with shaded target boxes and a guide line towards the final target.
A central AI badge showing the multiplier % and star rating.
A top-right Panel showing status, strength, AI%, price, scores, and during trades: entry, TP1/TP2/TP3, and live P/L.
Alerts
Two ready-made conditions: Buy and Sell when the respective signal triggers.
Add alert: Right click → Add alert → choose the indicator → select condition.
Best practices
Match timeframe to instrument:
Scalping 5–15m: min_score 8, min_stars 3–4.
Swing H1–H4: min_score 7, min_stars 3.
Daily/Equities: min_score 6–7, min_stars 2–3.
Prefer trades with EMA200 and 15m MTF trend alignment.
De-risk around major news.
Use fixed risk per trade (e.g., 1%).
Important notes
Prefer bar close confirmation to avoid mid-bar MACD flips.
Single trade at a time via the in_trade state.
15m MTF uses request.security with lookahead_off; evaluate at close for consistency.
FAQ
Use it standalone? You can, but it’s stronger when combined with S/R zones/trendlines and solid risk management.
Why do targets vary? The AI multiplier adapts TP/SL to current market conditions.
Disclaimer
This is an analytical/educational tool, not financial advice. Always backtest and use appropriate risk management.
Developer note
Built in Pine Script v6, uses var for trade state, clears drawings on the last bar to keep the chart tidy, and raises drawing limits to avoid runtime errors.
Supply & Demand Zones [QuantAlgo]🟢 Overview
The Supply & Demand (Support & Resistance) Zones indicator identifies price levels where significant buying and selling pressure historically emerged, using swing point analysis and pattern recognition to mark high-probability reversal and continuation areas. Unlike conventional support/resistance tools that draw arbitrary horizontal lines, this indicator can automatically detect structural zones, offering traders systematic entry and exit levels where institutional order flow likely congregates across any market or timeframe.
🟢 How to Use
# Zone Types:
Green/Demand Zones: Support areas where buying pressure historically emerged, representing potential long entry opportunities where price may bounce or consolidate before moving higher. These zones mark levels where buyers previously overcame sellers.
Red/Supply Zones: Resistance areas where selling pressure historically dominated, indicating potential short entry opportunities where price may reverse or stall before declining. These zones identify levels where sellers previously overwhelmed buyers.
# Zone Pattern Types:
Wick Rejection Zones: Zones created from candles with exceptionally long wicks showing violent price rejection. A demand rejection occurs when price drops sharply but closes well above the low, forming a long lower wick (relative to the total candle range) that demonstrates buyers aggressively defending that level. A supply rejection shows price spiking higher but closing well below the high, with the long upper wick proving sellers rejected that price aggressively. These zones often represent major institutional orders that absorbed significant market pressure. The rejection wick ratio setting controls how prominent the wick must be (higher ratios require more dramatic rejections and produce fewer but higher-quality zones).
Continuation Demand Zones: Areas where price rallied upward, paused in a brief consolidation base, then rallied again. This pattern confirms strong buying continuation (the consolidation represents profit-taking or minor pullbacks that failed to attract meaningful selling). When price returns to these zones, buyers who missed the initial rally often provide support, making them high-probability long entries within established uptrends. These zones follow the classic Rally-Base-Rally structure, demonstrating that buyers remain in control even during temporary pauses.
Reversal Demand Zones: Zones where price dropped, formed a consolidation base, then reversed into a rally. This structure marks potential trend reversals or major swing lows where buyers finally overwhelmed sellers after a decline. The base period represents accumulation by stronger hands, and these zones frequently appear at market bottoms or as significant pullback support within larger uptrends, signaling shifts in market control. These zones follow the Drop-Base-Rally pattern, showing the moment when selling pressure exhausted and buying interest emerged.
Continuation Supply Zones: Areas where price dropped, consolidated briefly, then dropped again. This pattern demonstrates strong selling continuation (the pause represents temporary buying attempts that failed to generate meaningful recovery). When price returns to these zones, sellers who missed the initial decline often provide resistance, creating short entry opportunities within established downtrends. These zones follow the Drop-Base-Drop structure, confirming that sellers maintain dominance even during temporary consolidations.
Reversal Supply Zones: Zones where price rallied upward, formed a consolidation base, then reversed into a decline. This formation identifies potential trend reversals or major swing highs where sellers overcame buyers after an advance. The base period often represents distribution by institutional participants, and these zones commonly appear at market tops or as key pullback resistance within larger downtrends, marking transfers of market control from buyers to sellers. These zones follow the Rally-Base-Drop pattern, capturing the transition point when buying exhaustion meets aggressive selling.
# Zone Mitigation Methods:
Wick Mitigation: Zones become invalidated immediately upon first contact by any wick. This assumes zones work only on their initial test, reflecting the belief that institutional orders concentrated at these levels get completely filled on first touch. Best for traders seeking only the highest-probability, untested zones and willing to accept that zones invalidate frequently in volatile markets. When price touches a zone boundary with even a single wick, that zone is considered "used up" and becomes mitigated.
Close Mitigation: Zones remain valid through wick penetration but become invalidated only when a candle closes through the zone boundary. This method allows price to briefly probe the zone with wicks while requiring actual commitment (a close) for invalidation. Suitable for traders who recognize that zones can withstand initial tests and prefer filtering out false breakouts caused by temporary volatility or liquidity hunts. A zone stays active as long as candles close within or outside it, regardless of wick penetration, until a close occurs beyond the boundary.
Full Body Mitigation: Zones stay valid until an entire candle body exists completely beyond the zone boundary, meaning both the open and close must be outside the zone. This approach maintains zone validity through partial penetrations, accommodating the reality that institutional zones can absorb considerable price action before exhausting. Ideal for volatile markets or traders who believe zones represent price ranges rather than precise levels, and who want zones to persist through aggressive but ultimately rejected breakout attempts. Only when both the open and close of a candle are beyond the zone does it become mitigated.
🟢 Pro Tips for Trading and Investing
→ Preset Selection: Choose presets matching your preferred timeframe - Scalping (M1-M30) for aggressive detection on minute charts, Intraday (H1-H12) for balanced filtering on hourly timeframes, or Swing Trading (1D+) for strict filtering on daily charts. Each preset automatically optimizes swing length, zone strength, and max zone counts for the selected timeframe.
→ Input Calibration: Adjust Swing Length based on market speed (lower values 3-7 for fast markets, higher values 12-20 for slower markets). Set Minimum Zone Strength according to asset volatility (0.05-0.15% for low-volatility assets, 0.25-0.5% for high-volatility assets). Tune Rejection Wick Ratio higher (0.6-0.8) for strict wick filtering or lower (0.3-0.5) to capture more subtle rejections.
→ Zone Pattern Toggle Strategy: Pattern types are mutually exclusive - enable Continuation OR Reversal patterns for each zone type, not both together. Recommended combinations: For trend trading, enable Rejection + Continuation (2-4 toggles total). For reversal trading, enable Rejection + Reversal (2-4 toggles). For scalping, enable only Rejection zones (1-2 toggles). Maximum 3-4 active toggles provides optimal chart clarity. A simple Wick Rejection toggle can also work on virtually any market and timeframe.
→ Mitigation Method Selection: Use Wick mitigation in clean trending markets for strict zone invalidation on first touch. Use Close mitigation in moderate volatility to filter out temporary spikes. Use Full Body mitigation in highly volatile markets to keep zones active through whipsaws and false breakouts.
→ Alert Configuration: Utilize built-in alerts for new zone creation, zone touches, and zone breaks. New zone alerts notify when fresh supply/demand areas form. Zone touch alerts signal potential entry opportunities as price reaches zones. Zone break alerts indicate when levels fail, signaling possible trend acceleration or structure changes.
GOLDSNIPERThe Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading.
Aug 6
Release Notes
The Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading
Aug 13
Release Notes
The Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading.
3 days ago
Release Notes
The Gold Sniper Indicator is a precision TradingView tool for scalping and intraday trading Gold (XAUUSD).
It is built around a break-and-retest strategy with clear trade management: 10 pip Stop Loss, 20 pip TP1, and 35 pip TP2.
The indicator automatically:
• Plots institutional key levels and supply & demand zones
• Detects breakout and retest opportunities in real time
• Provides stop loss and take profit levels for structured, disciplined trading
Whether you’re a scalper or day trader, Gold Sniper helps you catch high-probability setups on XAUUSD with precise risk-to-reward ratios (1:1 and 1:3).
Fisher Transform Trend Navigator [QuantAlgo]🟢 Overview
The Fisher Transform Trend Navigator applies a logarithmic transformation to normalize price data into a Gaussian distribution, then combines this with volatility-adaptive thresholds to create a trend detection system. This mathematical approach helps traders identify high-probability trend changes and reversal points while filtering market noise in the ever-changing volatility conditions.
🟢 How It Works
The indicator's foundation begins with price normalization, where recent price action is scaled to a bounded range between -1 and +1:
highestHigh = ta.highest(priceSource, fisherPeriod)
lowestLow = ta.lowest(priceSource, fisherPeriod)
value1 = highestHigh != lowestLow ? 2 * (priceSource - lowestLow) / (highestHigh - lowestLow) - 1 : 0
value1 := math.max(-0.999, math.min(0.999, value1))
This normalized value then passes through the Fisher Transform calculation, which applies a logarithmic function to convert the data into a Gaussian normal distribution that naturally amplifies price extremes and turning points:
fisherTransform = 0.5 * math.log((1 + value1) / (1 - value1))
smoothedFisher = ta.ema(fisherTransform, fisherSmoothing)
The smoothed Fisher signal is then integrated with an exponential moving average to create a hybrid trend line that balances statistical precision with price-following behavior:
baseTrend = ta.ema(close, basePeriod)
fisherAdjustment = smoothedFisher * fisherSensitivity * close
fisherTrend = baseTrend + fisherAdjustment
To filter out false signals and adapt to market conditions, the system calculates dynamic threshold bands using volatility measurements:
dynamicRange = ta.atr(volatilityPeriod)
threshold = dynamicRange * volatilityMultiplier
upperThreshold = fisherTrend + threshold
lowerThreshold = fisherTrend - threshold
When price momentum pushes through these thresholds, the trend line locks onto the new level and maintains direction until the opposite threshold is breached:
if upperThreshold < trendLine
trendLine := upperThreshold
if lowerThreshold > trendLine
trendLine := lowerThreshold
🟢 Signal Interpretation
Bullish Candles (Green): indicate normalized price distribution favoring bulls with sustained buying momentum = Long/Buy opportunities
Bearish Candles (Red): indicate normalized price distribution favoring bears with sustained selling pressure = Short/Sell opportunities
Upper Band Zone: Area above middle level indicating statistically elevated trend strength with potential overbought conditions approaching mean reversion zones
Lower Band Zone: Area below middle level indicating statistically depressed trend strength with potential oversold conditions approaching mean reversion zones
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant developments without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency and clarity
Configuration Presets: Three parameter sets available - Default (balanced settings), Scalping (faster response with higher sensitivity), and Swing Trading (slower response with enhanced smoothing)
Color Customization: Four color schemes including Classic, Aqua, Cosmic, and Custom options for personalized chart aesthetics
Laguerre Filter Trend Navigator [QuantAlgo]🟢 Overview
The Laguerre Filter Trend Navigator employs advanced polynomial filtering mathematics to smooth price data while minimizing lag, creating a responsive yet stable trend-following system. Unlike simple moving averages that apply equal weight to historical data, the Laguerre filter uses recursive calculations with exponentially weighted polynomials to extract meaningful directional signals from noisy market conditions. Combined with dynamic volatility-adjusted boundaries, this creates an adaptive framework for identifying high-probability trend reversals and continuations across all tradable instruments and timeframes.
🟢 How It Works
The indicator leverages Laguerre polynomial filtering, a mathematical technique originally developed for digital signal processing applications. The core mechanism processes price data through four cascaded filter stages (L0, L1, L2, L3), each applying the gamma coefficient to recursively smooth incoming information while preserving phase relationships. This multi-stage architecture eliminates random fluctuations more effectively than traditional moving averages while responding quickly to genuine directional shifts.
The gamma coefficient serves as the primary smoothing control, determining how aggressively the filter dampens noise versus tracking price movements. Lower gamma values reduce smoothing and increase filter responsiveness, while higher values prioritize stability over reaction speed. Each filter stage compounds this effect, creating progressively smoother output that converges toward true underlying trend direction.
Surrounding the filtered price line, the algorithm constructs adaptive boundaries using dynamic volatility regime measurements. These calculations quantify current market turbulence independently of direction, expanding during active trading periods and contracting during quiet phases. By multiplying this volatility assessment by a user-defined scaling factor, the system creates self-adjusting bands that automatically conform to changing market conditions without manual intervention.
The trend-following engine monitors price position relative to these volatility-adjusted boundaries. When the upper band falls below the current trend line, the system shifts downward to track bearish momentum. Conversely, when the lower band rises above the trend line, it elevates to follow bullish movement. These crossover events trigger color transitions between bullish (green) and bearish (red) states, providing clear visual confirmation of directional changes validated by volatility-normalized thresholds.
🟢 How to Use
Green/Bullish Trend Line: Laguerre filter positioned in upward trajectory, indicating momentum-confirmed conditions favorable for establishing or maintaining long positions (buy)
Red/Bearish Trend Line: Laguerre filter trending downward, signaling regime-validated environment suitable for initiating or holding short positions (sell)
Rising Green Line: Accelerating bullish filter with expanding separation from price lows, demonstrating strengthening upward momentum and increasing confidence in trend persistence with optimal long entry timing
Declining Red Line: Steepening bearish filter creating growing distance from price highs, revealing intensifying downside pressure and enhanced probability of continued decline with favorable short positioning opportunities
Flattening Trends: Horizontal or oscillating filter movement regardless of color suggests directional uncertainty where price action contradicts filter positioning, potentially indicating consolidation phases or impending volatility expansion requiring cautious trade management
🟢 Pro Tips for Trading and Investing
→ Preset Selection Framework: Match presets to your trading style - Scalping preset employs aggressive gamma (0.4) with tight volatility bands (1.0x) for rapid signal generation on sub-15-minute charts, Day Trading preset balances responsiveness and stability for hourly timeframes, while Swing Trading preset maximizes smoothing (0.8 gamma) with wide bands (2.5x) to filter intraday noise on daily and weekly charts.
→ Gamma Coefficient Calibration: Adjust gamma based on market personality - reduce values (0.3-0.5) for highly liquid, fast-moving assets like major currency pairs and tech stocks where quick filter adaptation prevents lag-induced losses, increase values (0.7-0.9) for slower instruments or trending markets where excessive sensitivity generates false reversals and whipsaw trades.
→ Volatility Period Optimization: Tailor the volatility measurement window to information cycles. Deploy shorter lookback periods (7-10) for instruments with rapid regime changes like individual equities during earnings seasons, standard periods (14-20) for balanced assessment across general market conditions, and extended periods (21-30) for commodities and indices exhibiting persistent volatility characteristics.
→ Band Width Multiplier Adaptation: Scale boundary distance to current market phase. Contract multipliers (1.0-1.5) during range-bound consolidations to capture early breakout signals as soon as genuine momentum emerges, expand multipliers (2.0-3.0) during trending markets or high-volatility events to avoid premature exits caused by normal retracement activity rather than authentic reversals.
→ Multi-Timeframe Filter Alignment: Implement the indicator across multiple timeframes, using higher intervals (4H/Daily) to identify primary trend direction via filter slope and lower intervals (15min/1H) for precision entry timing when filter colors align, ensuring trades flow with dominant momentum while optimizing execution at favorable price levels.
→ Alert-Driven Systematic Execution: Configure trend change alerts to capture every filter-validated directional shift from bullish to bearish conditions or vice versa, enabling consistent signal response without continuous chart monitoring and eliminating emotional decision-making during critical transition moments.
Bayesian Trend Navigator [QuantAlgo]🟢 Overview
The Bayesian Trend Navigator uses Bayesian statistics to continuously update trend probabilities by combining long-term expectations (prior beliefs) and short-term observations (likelihood evidence), rather than relying solely on recent price data like many conventional indicators. This mathematical framework produces robust directional signals that naturally balance responsiveness with stability, making it suitable for traders and investors seeking statistically-grounded trend identification across diverse market environments and asset types.
🟢 How It Works
The indicator operates on Bayesian inference principles, a statistical method for updating beliefs when new evidence emerges. The system begins by establishing a prior belief - a long-term trend expectation calculated from historical price behavior. This represents the "baseline hypothesis" about market direction before considering recent developments.
Simultaneously, the algorithm collects recent market evidence through short-term trend analysis, representing the likelihood component. This captures what current price action suggests about directional momentum independent of historical context.
The core Bayesian engine then combines these elements using conjugate normal distributions and precision weighting. It calculates prior precision (inverse variance) and likelihood precision, combining them to determine a posterior precision. The resulting posterior mean represents the mathematically optimal trend estimate given both historical patterns and current reality. This posterior calculation includes intervals derived from the posterior variance, providing probabilistic confidence bounds around the trend estimate.
Finally, volatility-based standard deviation bands create adaptive boundaries around the Bayesian estimate. The trend line adjusts within these constraints, generating color transitions between bullish (green) and bearish (red) states when the posterior calculation crosses these probabilistic thresholds.
🟢 How to Use
Green/Bullish Trend Line: Posterior probability favoring upward momentum, indicating statistically favorable conditions for long positions (buy)
Red/Bearish Trend Line: Posterior probability favoring downward momentum, signaling mathematically supported timing for short positions (sell)
Rising Green Line: Strengthening bullish posterior as new evidence reinforces upward beliefs, showing increasing probabilistic confidence in trend continuation with favorable long entry conditions
Declining Red Line: Intensifying bearish posterior with accumulating downside evidence, indicating growing statistical certainty in downtrend persistence and optimal short positioning opportunities
Flattening Trends: Diminishing posterior confidence regardless of color suggests equilibrium between prior beliefs and contradictory evidence, potentially signaling consolidation or insufficient statistical clarity for high-conviction trades
🟢 Pro Tips for Trading and Investing
→ Preset Configuration Strategy: Deploy presets based on your trading horizon - Scalping preset maximizes evidence weight (0.8) for rapid Bayesian updates on 1-15 minute charts, Default preset balances prior and likelihood for general applications, while Swing Trading preset equalizes weights (0.5/0.5) for stable inference on hourly and daily timeframes.
→ Prior Weight Adjustment: Calibrate prior weight according to market regime - increase values (0.5-0.7) in stable trending markets where historical patterns remain predictive, decrease values (0.2-0.3) during regime changes or news-driven volatility when recent evidence should dominate the posterior calculation.
→ Evidence Period Tuning: Modify the evidence period based on information flow velocity. Use shorter periods (5-8 bars) for assets with continuous price discovery like cryptocurrencies, medium periods (10-15) for liquid stocks, and longer periods (15-20) for slower-moving markets to ensure adequate likelihood sample size.
→ Likelihood Weight Optimization: Adjust likelihood weight inversely to market noise levels. Higher values (0.7-0.8) work well in clean trending conditions where recent data is reliable, while lower values (0.4-0.6) help during choppy periods by maintaining stronger reliance on established prior beliefs.
→ Multi-Timeframe Bayesian Confluence: Apply the indicator across multiple timeframes, using higher timeframes (Daily/Weekly) to establish prior belief direction and lower timeframes (Hourly/15-minute) for likelihood-driven entry timing, ensuring posterior probabilities align across temporal scales for maximum statistical confidence.
→ Standard Deviation Multiplier Management: Adapt the multiplier to match current uncertainty levels. Use tighter multipliers (1.0-1.5) during low-volatility consolidations to capture early trend emergence, and wider multipliers (2.0-2.5) during high-volatility events to avoid premature signals caused by statistical noise rather than genuine posterior shifts.
→ Variance-Based Position Sizing: Monitor the implicit posterior variance through trend line stability - smooth consistent movements indicate low uncertainty warranting larger positions, while erratic fluctuations suggest high statistical uncertainty calling for reduced exposure until clearer probabilistic convergence emerges.
→ Alert-Based Probabilistic Execution: Utilize trend change alerts to capture every statistically significant posterior shift from bullish to bearish states or vice versa without constantly monitoring the charts.
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
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🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
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🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
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🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
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⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
