SMA Strategy [MK]Overview
This strategy is a momentum-based trend-following system designed to capture sustained market moves while minimizing "whipsaws" often found in sideways markets. It utilizes a dual-SMA filter for trend direction, a precise price-crossover trigger for entry, and the Average Directional Index (ADX) to gauge market strength.
How It Works
The strategy follows a strict "Trend + Momentum + Strength" hierarchy:
1. Trend Identification (The Filter) The script uses a Fast SMA (20) and a Slow SMA (50).
Long Bias: SMA-20 > SMA-50.
Short Bias: SMA-20 < SMA-50.
2. Precise Entry (The Trigger) Unlike strategies that enter simply because the price is above a line, this script requires a Price Crossover.
Long Entry: Price must actively cross from below to above the SMA-20.
Short Entry: Price must actively cross from above to below the SMA-20.
3. Trend Strength (The ADX Gatekeeper) To solve the problem of sideways markets where moving averages run parallel, weโve integrated the ADX (Average Directional Index). The strategy will only trigger a trade if the ADX is above a user-defined threshold (default is 25), ensuring we only enter when the market is trending.
4. RSI Safety Filter To prevent "buying the top" or "selling the bottom," the RSI checks for overextended conditions. It prevents long entries if the RSI is already overbought and short entries if it is oversold.
Exit Logic
The strategy features three layers of protection:
Trend Reversal Exit: Closes the position if the price crosses back over the SMA-20 while the macro trend (SMA-20/SMA-50) has flipped.
Fixed Take Profit: A percentage-based target to lock in gains during sharp moves.
Fixed Stop Loss: A percentage-based safety net to protect capital.
Key Features
Directional Selector: Choose between "Long Only," "Short Only," or "Both."
Visual Feedback: Background colors highlight "Trending" (Green) vs "Sideways" (Red) market regimes.
Fully Customizable: All lengths and thresholds for SMAs, RSI, and ADX can be adjusted to fit different assets and timeframes.
Instructions for Use
Timeframe: This strategy is optimized for trending timeframes such as the 1-Hour (1H), 4-Hour (4H), or Daily (D). Using it on very low timeframes (1-minute or 5-minute) may increase the number of false signals due to market noise.
Asset Classes: Best suited for high-volume assets like Major Forex Pairs, Large-Cap Stocks, and Blue-Chip Cryptocurrencies.
Parameter Tuning: Use the "Strategy Tester" to find the ideal ADX Threshold for your specific asset. Volatile assets usually require a higher ADX (30+) to filter out fake breakouts.
Disclaimer
Financial Risk Warning: The script provided is for educational and informational purposes only. Trading involves significant risk, and there is always the potential for loss. Past performance, whether simulated or real, is not a guarantee of future results.
The author of this script is not a financial advisor. This indicator is not a signal service or a recommendation to buy or sell any security. Always perform your own due diligence and test any strategy thoroughly on a demo account before risking live capital. By using this script, you acknowledge that you are solely responsible for your trading decisions and any resulting financial outcomes.
Indicators and strategies
Smart Trader,Episode 1, by Ata Sabanci | Unified Matrixโ ๏ธ **CRITICAL: READ BEFORE USING** โ ๏ธ
This strategy is **100% VOLUME-BASED** and requires **Lower Timeframe (LTF) intrabar data** for accurate calculations. Please understand the following limitations before using:
**๐ DATA ACCURACY LEVELS:**
โข **1T (Tick)** โ Most accurate, real volume distribution per tick
โข **1S (1 Second)** โ Reasonably accurate approximation
โข **15S (15 Seconds)** โ Good approximation, longer historical data available
โข **1M (1 Minute)** โ Rough approximation, maximum historical data range
**โ ๏ธ BACKTEST & REPLAY LIMITATIONS:**
โข TradingView's Strategy Tester uses historical LTF data which may be limited depending on your subscription plan
โข Replay mode results may differ from live trading due to data availability
โข For longer backtest periods, use higher LTF settings (15S or 1M)
โข Not all symbols/exchanges support tick-level data
โข Crypto and Forex typically have better LTF data availability than stocks
**๐ก A NOTE ON TOOLS:**
Successful trading requires proper tools. Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable signals. Consider this when evaluating your trading infrastructure.
**WHY "EPISODE 1"?**
This strategy is titled "Episode 1" because it focuses exclusively on **Highest Buyers (HB)** โ a single but powerful concept in volume analysis.
**The Philosophy:**
A single high-volume buying event can tell us a story about market psychology:
โข Where did the biggest buyers enter?
โข How much of their power remains?
โข Are sellers consuming their advantage?
โข At what rate is the balance shifting?
By focusing on just ONE aspect of volume analysis, traders can deeply understand how a buying surge affects future price action before moving to more complex multi-factor analysis.
**The Reality:**
This script alone is approximately **2000 lines of code** โ and it only analyzes buyers. A comprehensive system covering all aspects (sellers, combined analysis, multi-timeframe correlation) would be significantly larger and computationally heavier. Breaking this into focused modules allows for:
โข Deeper understanding of each component
โข Lighter, more responsive scripts
โข Educational progression from simple to complex
**OVERVIEW**
Smart Trader EP1 is a volume-based trading strategy that tracks the balance of power between buyers and sellers through the lens of the **Highest Buyers event**. Unlike traditional indicators that rely on price patterns or mathematical formulas, this strategy analyzes *actual volume flow* to identify who is in control of the market.
The core philosophy is simple: **markets move when one side (buyers or sellers) exhausts their power while the opposing side accumulates strength.** By measuring this power shift in real-time, the strategy identifies high-probability entry and exit points.
**HOW IT WORKS**
**1. Volume Engine**
The strategy splits each candle's volume into buying volume and selling volume using intrabar data. In *Intrabar (Precise)* mode, it uses actual tick-by-tick or second-by-second data to calculate the exact buy/sell distribution. In *Geometry* mode, it approximates based on candle structure (close position within the range).
**2. Event Detection**
Within the lookback window, the strategy identifies key events:
โข **HB (Highest Buyers)** โ The candle with maximum buying volume (potential resistance when exhausted)
โข **HS (Highest Sellers)** โ The candle with maximum selling volume (potential support when exhausted)
โข **LB (Lowest Buyers)** โ The candle with minimum buying volume (buyer absence)
โข **LS (Lowest Sellers)** โ The candle with minimum selling volume (seller absence)
These events create dynamic support and resistance levels based on actual volume, not arbitrary price levels.
**3. Power Tracking (Attrition Model)**
For the Highest Buyers event (HB), the strategy tracks:
โข **Start Power (X)** โ The initial buying volume at the HB event
โข **Consumed Power (Y)** โ How much selling volume has accumulated since the event
โข **Remaining Power (Z)** โ Start Power minus Consumed Power (X - Y)
โข **Opponent Dominance** โ When Remaining Power goes negative (Z < 0), sellers have overtaken buyers
Think of it like a battle: buyers establish a position (HB), and sellers gradually consume their power. When buyers' power is exhausted (Remaining Power โค 0), sellers have taken control.
**4. Depletion Markers**
Visual markers appear on the chart when power reaches critical thresholds:
โข **๐** โ Buyers consumed 100% (Remaining = 0)
โข **๐จ** โ Buyers consumed 200% (Opponent Dominance = 100%)
โข **๐ชซ** โ Sellers consumed 100%
โข **โ ๏ธ** โ Sellers consumed 200%
**5. Cumulative Delta**
Beyond tracking power at specific events, the strategy calculates the cumulative buy volume minus sell volume since the HB event. This shows the *net flow* of money:
โข **Positive Delta** โ More buying than selling since HB (bullish pressure)
โข **Negative Delta** โ More selling than buying since HB (bearish pressure)
**6. Trend Channel**
A 5-point linear regression channel identifies the current trend:
โข **UPTREND** โ Both upper and lower channel lines slope upward
โข **DOWNTREND** โ Both lines slope downward
โข **RANGING** โ Mixed or flat slopes
The strategy also tracks where the HB event occurred within this channel (TOP, UPPER, MIDDLE, LOWER, BOTTOM) to contextualize the signal.
**7. Nearest Event Analysis**
The strategy identifies which event is closest to the current candle and analyzes the price action *after* that event:
โข How many bullish vs bearish candles followed?
โข Does post-event momentum confirm or contradict the event type?
This prevents false signals when, for example, a bearish event occurs but is immediately followed by strong bullish candles.
**SIGNAL LOGIC**
**๐ข LONG Signal Conditions:**
โข Uptrend with positive cumulative delta and buyers accumulating
โข At channel bottom/lower with strong buyer power remaining
โข After a bearish event (HS) with bullish post-event momentum (reversal signal)
โข Ranging market with positive delta and strong power
**๐ด SHORT Signal Conditions:**
โข Downtrend with negative cumulative delta and sellers in control
โข Opponent Dominance (buyer power exhausted) with bearish momentum
โข Buyer Trap: HB at TOP in uptrend but power exhausted and delta negative
โข After a bullish event (HB) with bearish post-event momentum (trap signal)
**โณ NO_TRADE Conditions:**
โข Conflicting signals (e.g., bearish event but bullish post-momentum)
โข Ranging market without clear direction
โข Mixed power readings
โข Price position contradicts signal direction
**STRATEGY EXECUTION**
**Entry Rules:**
โข Enter LONG when signal is "LONG" and conditions are valid
โข Enter SHORT when signal is "SHORT" and conditions are valid
โข **Pyramid**: Up to 2 entries allowed in the same direction (configurable)
โข Each entry uses 10% of equity by default
โข Only one entry per confirmed candle (prevents multiple fills)
**Stop Loss (Event Line Based):**
โข **LONG positions**: Stop Loss placed below the HS line (seller support level)
โข **SHORT positions**: Stop Loss placed above the HB line (buyer resistance level)
โข A small buffer percentage is added to prevent premature stops
**Take Profit (Event Line Based):**
โข **LONG positions**: Take Profit near the HB line (buyer resistance target)
โข **SHORT positions**: Take Profit near the HS line (seller support target)
โข A small buffer percentage ensures realistic fill expectations
**Exit Rules:**
โข Exit LONG when signal changes to SHORT
โข Exit SHORT when signal changes to LONG
โข **NO_TRADE signal = HOLD** (do not exit, wait for clear direction)
โข SL/TP orders remain active regardless of signal changes
**SETTINGS GUIDE**
**โ๏ธ General Settings:**
โข *Calculation Method* โ Choose between Intrabar (Precise) or Geometry (approximation)
โข *Intrabar Resolution* โ LTF for volume data (1T, 1S, 15S, 1M)
โข *Lookback Length* โ Window for scanning events (10-150 bars)
โข *Timezone Offset* โ Adjust clock display to your local time
**๐ Matrix Display Settings:**
โข *Show Unified Matrix* โ Toggle the information dashboard
โข *Show Event Lines* โ Toggle horizontal lines at event prices
โข *Panel Size/Position* โ Customize dashboard appearance
โข *Projection Bars* โ Extend event lines into the future
โข *Depletion Threshold* โ Percentage for depletion markers (default: 100%)
**๐ท๏ธ Rank Labels Settings:**
โข *Show Rank Labels (HB/HS)* โ Display labels on highest volume candles
โข *Show Low Labels (LB/LS)* โ Display labels on lowest volume candles
โข *Ranks Count* โ Number of rankings to display (1-5)
**๐ Trend Channel Settings:**
โข *Show Trend Channel* โ Toggle the 5-point regression channel
โข *Line Color/Fill/Width/Style* โ Customize channel appearance
**๐ฏ Trade Signal Settings:**
โข *Long: Min Remaining Power %* โ Minimum buyer power for LONG signal (default: 50%)
โข *Short: Max Remaining Power %* โ Maximum power for SHORT signal (default: 30%)
โข *Opponent Dominance Threshold* โ When to consider power "exhausted" (default: 0%)
โข *Max Decay Angle* โ Maximum consumption rate for valid entries (default: 60ยฐ)
**๐ Strategy Execution Settings:**
โข *Enable Strategy* โ Turn automatic trading on/off
โข *Allow LONG/SHORT* โ Enable or disable specific directions
โข *Max Pyramid Entries* โ Maximum entries in same direction (1-3)
โข *SL Buffer %* โ Distance below/above event line for stop loss (default: 0.15%)
โข *TP Buffer %* โ Distance from event line for take profit (default: 0.05%)
**VISUAL ELEMENTS**
**Chart Labels:**
โข **#1 HB** โ Highest Buyers (rank label on candle high)
โข **#1 HS** โ Highest Sellers (rank label on candle low)
โข **#1 LB** โ Lowest Buyers (rank label on candle high)
โข **#1 LS** โ Lowest Sellers (rank label on candle low)
โข **๐ / ๐จ** โ Buyer power depletion markers
โข **๐ชซ / โ ๏ธ** โ Seller power depletion markers
**Event Lines:**
โข **Blue horizontal lines** โ HB price levels (buyer entry points)
โข **Red horizontal lines** โ HS price levels (seller entry points)
โข **Cyan lines** โ LB price levels
โข **Orange lines** โ LS price levels
โข **Dashed extensions** โ Projected levels into future bars
**Trend Channel:**
โข **Orange lines** โ Upper and lower channel boundaries (5-point regression)
โข **Orange fill** โ Channel area (90% transparency)
**Matrix Dashboard (6 rows):**
โข Row 1: Header with symbol, LTF setting, and local clock
โข Row 2: Volume snapshot (Total, Buy, Sell, Delta)
โข Row 3: Column headers
โข Row 4: Highest Buyers data (Age, Start Power, Consumed, Remaining, Decay, ETA)
โข Row 5: Highest Sellers data
โข Row 6: Signal Evaluation (Trend, Zone, Nearest Event, Signal, Reason)
**Strategy Markers:**
โข **Green triangle up** โ LONG entry
โข **Red triangle down** โ SHORT entry
โข **Faded triangles** โ Pyramid entries
โข **Colored lines** โ SL (red) and TP (green) levels when in position
**BEST PRACTICES**
**For Maximum Accuracy:**
1. Use **1T (tick)** or **1S** intrabar resolution when available
2. Trade liquid markets with good volume data (crypto majors, forex majors, high-volume stocks)
3. Use smaller lookback length (20-30) to ensure all bars have valid LTF data
4. Monitor the "Intrabar Valid Bars" counter in the matrix header
5. If you see data warnings, reduce lookback or increase LTF resolution
**For Longer Backtests:**
1. Use **15S or 1M** intrabar resolution for more historical data
2. Increase lookback length if needed
3. Understand that accuracy decreases with higher LTF settings
4. Consider using Geometry mode for very long backtests (approximation but always available)
**Understanding the Signals:**
โข Pay attention to the signal *reasoning* shown in the matrix โ it explains WHY
โข **NO_TRADE** means the system sees conflicting factors โ respect this caution
โข Event lines act as dynamic S/R โ they update as new volume events occur
โข Cumulative Delta (ฮ) often provides early warning of trend changes
**Risk Management:**
โข The default 10% per entry with max 2 pyramids = 20% maximum exposure
โข Event-line-based SL/TP provides logical levels based on actual volume events
โข Always verify signals with your own analysis before trading
**INTERPRETING THE MATRIX**
**Power Status Examples:**
โข *Remaining Power: 75%* โ Buyers still have most of their strength
โข *Remaining Power: 25%* โ Buyers nearly exhausted, watch for reversal
โข *Opponent Dominance: -50%* โ Sellers have consumed 150% of buyer power (strong bearish)
**Decay Angle:**
โข *Low angle (0-30ยฐ)* โ Slow consumption, power lasting longer
โข *High angle (60-90ยฐ)* โ Rapid consumption, expect quick exhaustion
**ETA to Parity:**
โข Shows estimated bars until Remaining Power reaches zero
โข *"Overtaken"* with ๐จ means sellers have already dominated
**LIMITATIONS & DISCLAIMER**
**Technical Limitations:**
โข Requires sufficient historical LTF data (varies by TradingView plan and symbol)
โข Intrabar (Precise) mode may show invalid data warnings on symbols with limited history
โข Strategy tester may not have access to the same LTF data as live trading
โข Maximum 500 lines and 500 labels (TradingView platform limits)
**Important Notes:**
โข This strategy focuses on **Highest Buyers only** โ it does not analyze all market factors
โข Past performance does not guarantee future results
โข Volume data quality varies significantly between symbols and exchanges
โข The strategy's signals are analytical tools, not trading recommendations
**Risk Disclaimer:**
This strategy is provided for **educational and informational purposes only**. Trading involves substantial risk of loss and is not suitable for all investors.
โข Always use proper risk management
โข Never risk more than you can afford to lose
โข Backtest results may differ significantly from live trading
โข You are solely responsible for your trading decisions
**TECHNICAL SPECIFICATIONS**
โข Pine Script Version: 6
โข Calculation: calc_on_every_tick=true, use_bar_magnifier=true
โข Default Capital: 10,000
โข Default Position Size: 10% of equity
โข Maximum Lines: 500
โข Maximum Labels: 500
โข External Library: TradingView/ta/10 (for requestUpAndDownVolume)
*Smart Trader EP1 โ Understanding Volume, One Event at a Time*
ICT Macros FuturesAll Macros Detected:
Early / Pre Market
- 02:33 โ 03:10 (NY)
- 04:03 โ 04:30
- 05:20 โ 05:40
- 05:50 โ 06:10
- 07:50 โ 08:10
- 08:20 โ 08:40
Cash Open / Morning
- 08:50 โ 09:10
- 09:20 โ 09:40
- 09:50 โ 10:10
Midday / Lunch
- 10:50 โ 11:10
- 11:50 โ 12:10
- 12:00 โ 13:30 (Lunch Hour)
Afternoon
- 13:10 โ 13:40
- 14:20 โ 14:40
- 15:15 โ 15:45
- 15:50 โ 16:10
Pulse Volume Commitment [JOAT]
Pulse Volume Commitment - Three-Dimensional Momentum Analysis
Introduction and Purpose
Pulse Volume Commitment is an open-source oscillator indicator that analyzes price action through three distinct dimensions: Quantity (candle count), Quality (body structure), and Commitment (volume-weighted quality). The core problem this indicator solves is that simple bullish/bearish candle counts miss important context. A market can have more green candles but still be weak if those candles have small bodies and low volume.
This indicator addresses that by requiring all three dimensions to align before generating strong signals, filtering out weak moves that lack conviction.
Why These Three Dimensions Work Together
Each dimension measures a different aspect of market conviction:
1. Quantity - Counts bullish vs bearish candles over the lookback period. Tells you WHO is winning the candle count battle.
2. Quality - Scores candles by body size relative to total range. Full-bodied candles (small wicks) indicate stronger conviction than doji-like candles. Tells you HOW decisively price is moving.
3. Commitment - Weights quality scores by volume. High-quality candles on high volume indicate institutional participation. Tells you WHETHER smart money is involved.
When all three align (e.g., more bullish candles + bullish quality + bullish commitment), the signal is significantly more reliable.
How the Calculations Work
Quantity Analysis:
int greenCount = 0
int redCount = 0
for i = 0 to lookbackPeriod - 1
if close > open
greenCount += 1
if close < open
redCount += 1
bool quantityBull = greenCount > redCount
Quality Analysis (body-to-range scoring):
for i = 0 to lookbackPeriod - 1
float candleBody = close - open // Signed (positive = bull)
float candleRange = high - low
float bodyQuality = candleRange > 0 ? (candleBody / candleRange * 100) * candleRange : 0.0
sumBodyQuality += bodyQuality
bool qualityBull = sumBodyQuality > 0
Signal Types
FULL BULL - All three dimensions bullish (Quantity + Quality + Commitment)
FULL BEAR - All three dimensions bearish
LEAN BULL/BEAR - 2 of 3 dimensions agree
MIXED - No clear consensus
STRONG BUY/SELL - Full confluence + ADX confirms trending market
ADX Integration
The indicator includes ADX (Average Directional Index) to filter signals:
- ADX >= 20 = TRENDING market (signals more reliable)
- ADX < 20 = RANGING market (signals may whipsaw)
Strong signals only trigger when full confluence occurs in a trending environment.
Dashboard Information
Quantity - BULL/BEAR/FLAT with green/red candle ratio
Quality - Directional bias based on body quality scoring
Commit - Volume-weighted commitment reading
ADX - Trend strength (TRENDING/RANGING)
Signal - Confluence status (FULL BULL/FULL BEAR/LEAN/MIXED)
Action - STRONG BUY/STRONG SELL/WAIT
How to Use This Indicator
For High-Conviction Entries:
1. Wait for FULL BULL or FULL BEAR confluence
2. Confirm ADX shows TRENDING
3. Enter when Action shows STRONG BUY or STRONG SELL
For Filtering Weak Setups:
1. Avoid entries when signal shows MIXED
2. Be cautious when ADX shows RANGING
3. Require at least 2 of 3 dimensions to agree
For Divergence Analysis:
1. Watch for Quantity bullish but Commitment bearish (distribution)
2. Watch for Quantity bearish but Commitment bullish (accumulation)
Input Parameters
Lookback Period (9) - Bars to analyze for all three dimensions
ADX Smoothing (14) - Period for ADX calculation
ADX DI Length (14) - Period for directional indicators
Timeframe Recommendations
15m-1H: Good for intraday momentum analysis
4H-Daily: Best for swing trading confluence
Lookback period may need adjustment for different timeframes
Limitations
Lookback period affects signal responsiveness vs reliability tradeoff
Volume data quality varies by exchange
ADX filter may cause missed entries in early trends
Works best on liquid instruments with consistent volume
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Confluence signals do not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
BTC - Cycle Integrity Index (CII) BTC - Cycle Integrity Index (CII) | RM
Are we following a calendar or a capital flow? Is the Halving still the heartbeat of Bitcoin, or has the institutional "Engine" taken over?
The most polarized debate in the digital asset space today centers on a single question: Is the 4-year Halving Cycle dead? While some market participants wait for a pre-ordained calendar countdown, the reality of 2026 suggests that visual guesswork is no longer sufficient. As institutional gravity takes hold, we cannot rely on the simple "Clock" of the past. Instead, we must audit the Integrity of the present.
The Cycle Integrity Index (CII) was engineered to move beyond simple price action and provide a clinical answer to the market's biggest mystery: "Is this trend supported by structural substance, or is it merely speculative foam?" By aggregating eight diverse Pillars into a single 0-100% score, this model uses Gaussian Distributions and Sigmoid Normalization to distinguish between professional accumulation and retail-driven chaos. We aren't guessing where we are in a cycle; we are measuring the internal health of the asset's engine in real-time.
Why these 8 Pillars?
The CII does not rely on a single indicator because the "New Era" of Bitcoin is multi-dimensional. To capture the full picture, I selected eight specific pillars that cover the three layers of market truth:
โข The Capital Layer: Global Liquidity (M2) and ETF Flows (Wall Street Absorption).
โข The Network Layer: Mining Difficulty and Security Backbone expansion.
โข The Sentiment Layer: Long-Term Holder conviction, Valuation Heat (MVRV), and Corporate Adoption (MSTR). While alternatives like the Pi Cycle or RSI exist, they are often "one-dimensional." The CII is a synthesisโa modular engine where every part validates the others.
How the Calculation Works
The CII is a sophisticated model for Bitcoin. It aggregates 8 diverse pillars into a single 0-100% score in the following way:
โข Mathematical Normalization: We don't just use raw prices. We use Gaussian Distributions to find "Institutional DNA" in drawdowns and Sigmoid (S-Curve) functions to score volatility and valuation.
โข Dynamic Weighting: The index is modular. If a data source (like a specific on-chain metric) is toggled off, the engine automatically redistributes the weight among the active sensors so the final integrity score is always balanced to 100%.
โข Multi-Source Integration: The script pulls from Global Liquidity (M2), ETF flows, Corporate Treasury premiums (MSTR), and Network Difficulty to create a truly "Full-Stack" view of the asset.
The 8 Pillars of Integrity
Pillar 1: Drawdown DNA The "Identity Crisis" Filter
โข Concept: Audits the depth of corrections to distinguish between "Institutional Floors" and "Retail Panics."
โข Logic: Historically, retail crashes reached -80%, while institutions view -20% to -25% as primary value entries.
โข Implementation: Uses a Gaussian (Normal) Distribution centered at -25%. Scores of 10/10 are awarded for holding institutional targets; scores decay as drawdowns accelerate toward legacy "crash" levels.
Basis: DNA Drawdown
Pillar 2: Volatility Regime The "Smoothness" Audit
โข Concept: Measures the "vibration" of the trend. High-integrity moves are characterized by "smooth" price action.
โข Logic: Erratic volatility signals speculative bubbles; consistent "volatility clusters" indicate professional trend-following.
โข Implementation: Calculates a Z-Score of the 14-day ATR against a 100-day benchmark. This is passed through a Sigmoid function to penalize "chaotic" price shocks while rewarding stability.
Basis: RVPM
Pillar 3: Liquidity Sync (Global M2) The Macro Heartbeat
โข Concept: Audits whether price growth is fueled by monetary expansion or internal speculative leverage.
โข Logic: True cycle integrity requires a positive correlation between Central Bank balance sheets and price action.
โข Implementation: Aggregates a custom Global Liquidity Proxy (Fed, RRP, TGA, PBoC, ECB, BoJ). It measures the Pearson Correlation between BTC and M2 with a standardized 80-day transmission lag.
Basis: Liquisync
Pillar 4: ETF Absorption (Wall Street Entry) The "Cost Basis" Defense
โข Concept: Tracks the aggregate institutional cost-basis since the January 2024 Spot ETF launch.
โข Logic: Integrity is high when the "Wall Street Floor" is defended; it fails when the aggregate position is underwater.
โข Implementation: A Cumulative VWAP engine tracking the "Big 3" (IBIT, FBTC, BITB). Scoring decays based on the percentage distance the price drifts below this institutional average entry.
Basis: Institutional Cost Corridor
Note: Turning this to OFF will significantly expand the timeframe of the indicator on the chart (otherwise it will just start in 2024)
Pillar 5: LTH Dormancy (Conviction) The HODL Floor Audit
โข Concept: Monitors the conviction of Long-Term Holders (LTH) to identify supply-side constraints.
โข Logic: Sustainable cycles require stable or increasing 1Y+ dormant supply; rapid "thawing" signals distribution.
โข Implementation: Uses Min-Max Normalization on the Active 1Y Supply over a 252-day window. A score of 10/10 indicates peak annual holding conviction.
Basis: RHODL Proxy & VDD Multiple
Pillar 6: Valuation Intensity The MVRV Heat Map
โข Concept: Measures market "overheat" by comparing Market Value to Realized Value.
โข Logic: High integrity trends rise steadily; vertical spikes in MVRV indicate "speculative foam" and bubble risk.
โข Implementation: Performs a Relative Rank Analysis of the MVRV Ratio over a 730-day window, passed through a high-steepness Sigmoid curve to identify extreme valuation anomalies.
Pillar 7: Miner Stress The Security Backbone
โข Concept: Tracks Mining Difficulty to ensure network infrastructure is expanding alongside price.
โข Logic: Difficulty expansion signals health; drops in difficulty (Miner Stress) signal capitulation and sell-side pressure.
โข Implementation: Monitors the 30-day Rate of Change (ROC) of Global Mining Difficulty. Maintains a 10/10 score during expansion; decays rapidly during network contraction.
Pillar 8: Corporate Adoption The MSTR NAV Proxy
โข Concept: Audits the MicroStrategy (MSTR) premium as a barometer for institutional demand.
โข Logic: A high premium indicates a willingness to pay a "convenience fee" for BTC exposure; a collapsing premium signals waning appetite.
โข Implementation: Calculates the Adjusted Enterprise Value (Market Cap + Debt - Cash) relative to the Net Asset Value (NAV) of its BTC holdings.
Note1: Debt and share parameters are user-adjustable to maintain accuracy as corporate balance sheets evolve.
Note2: I just included this because I was curious about the mNAV calculation I saw in other scripts, where the printed value often does not match exactly the propagated value from the MSTR page itself. Hence, for my live calculation, we calculate the Adjusted Enterprise Value to find the "Market NAV" (mNAV). Unlike simpler scripts that only look at Market Cap vs. Bitcoin holdings, our engine accounts for the Capital Structure . We explicitly factor in the corporate debt (approx. $8.24B long-term + $7.95B convertible notes) and subtract the cash reserves (approx. $2.18B) to find the true cost Wall Street is paying for the underlying Bitcoin. Since this will ran "old" very quickly, I recommend to update in the code by yourself from time to time, or just de-select this parameter.
Interpretation Guide
โข Score 100% (The Perfect Storm): This represents a state of "Maximum Integrity." All 8 pillars are in perfect institutional alignmentโliquidity is surging, conviction is at yearly highs, and price action is perfectly smooth. This is the hallmark of a healthy, structural parabolic run.
โข 75% - 100% (High Integrity): Robust trend. Price is supported by structural demand and macro tailwinds.
โข 35% - 75% (Equilibrium): Transition zone. The market is digesting gains or waiting for a new liquidity pulse.
โข 0% - 35% (Fragile): Speculative foam. Structural support has failed.
โข Score 0% (The Ghost Trend): Absolute structural failure. All pillars (liquidity, miners, LTH, ETFs) have broken down. Note: Due to the robust nature of the Bitcoin network, the index naturally floors around 20-30% during deep bear markets, as specific pillars (like Miner Security) rarely drop to zero.
To provide a complete experience, I have included the Cycle Triad โa visualization layer consisting of the Halving, Ideal Peak, and Ideal Low. It is important to understand the role of this feature:
โข Benchmark Only (Not Calculated): The Triad is based purely on historical evidence from previous Bitcoin epochs. While the Halving is fixed anyway, the "Ideal Peak" or "Ideal Low" are not calculated or computed by the 8 pillars. These are user-adjustable temporal anchors drawn on the chart to provide a static map of the "Legacy 4-Year Cycle."
โข The Temporal Audit: The power of the CII lies in comparing the Engine (the 8 Pillars) against the Clock (the Triad) . By overlaying historical time-windows on top of our integrity math, we can see if the "New Era" is currently ahead of, behind, or perfectly in sync with the past.
โข The "Peak Divergence" Logic: Based on the specific models selected for this ECUโspecifically Volatility Decay and Valuation Heat โtraders will notice that a cycle peak often coincides with a low integrity score (Red Zone) . While the index measures structural health, a low score is a byproduct of a market that has become "too hot to handle."
โข Regime Detection: Although the primary goal is to audit the "New Era," the CII is highly effective at detecting overheated regimes. When the score drops toward the 25โ35% range, the structural floor is giving way to speculative foamโmaking it a dual-purpose tool for both cycle analysis and risk management.
Dashboard Calibration & Settings
Cycle Triad Calibration
โข Ideal Peak/Trough Window: Defines the historical "Average Days" from a Halving to the cycle top and bottom. This sets the vertical anchors for the Halving, Peak, and Low labels.
โข Show Cycle Triad: A master toggle to enable or disable the temporal lines and labels on your dashboard.
The CII Master ECU is fully modular. You can toggle individual pillars ON/OFF to focus on specific market dimensions, and calibrate the sensitivity of each sensor to match your strategic bias.
โข P1: Drawdown DNA Lookback (Weeks): Defines the window for the "Rolling High." Inst. Target (%): The specific percentage drawdown you define as "Institutional Support" (e.g., -25%).
โข P2: Volatility Regime Benchmark (Days): The historical window used to define "Normal" vs. "Abnormal" volatility.
โข P3: Liquidity Sync Corr. Window (Bars): The lookback for the Pearson Correlation calculation. Transmission Lag (Bars): The delay (standard 80 days) for Central Bank M2 to hit price.
โข P4: ETF Absorption FBTC Ticker: The data source for the ETF volume audit (Default: CBOE:FBTC).
โข P5: LTH Dormancy LTH Source: The ticker for 1Y+ Active Supply (Default: GLASSNODE:BTC_ACTIVE1Y). Norm. Window: The lookback (252 days) used to rank current conviction.
โข P6: Valuation Intensity MVRV Source: The ticker for the MVRV Ratio (Default: INTOTHEBLOCK:BTC_MVRV). Relative Window: The lookback (730 days) to calculate the valuation rank.
โข P7: Miner Stress Mining Diff: The data source for Global Mining Difficulty (Default: QUANDL:BCHAIN/DIFF).
โข P8: Corporate Adoption Shares (M) & BTC (K): The balance sheet parameters for MicroStrategy (MSTR). Update these as the company executes new purchases to maintain mNAV accuracy.
Operational Usage This index is best used on the Daily (D) (recommended - description for inputs optimized for this time-window) or Weekly (W) timeframes. While the code is optimized to fetch daily data regardless of your chart setting, the structural "Integrity" of a cycle is a macro phenomenon and should be viewed with a medium-to-long-term lens.
The Verdict: Is the 4-Year Cycle Still Alive?
Based on the data provided by the CII Master ECU, the answer remains a nuanced "Work in Progress." The evidence presents a fascinating conflict between legacy patterns and the new institutional regime:
โข The Case for the Cycle: Historically, a local "Peak" in price corresponds with a "Local Low" in our integrity indicator (Red Zone). We observed this exact phenomenon in October 2025. When viewed through the lens of the "Ideal Peak" anchor, this alignment suggests that the 4-year temporal rhythm is still exerts a massive influence on market behavior.
โข The Case for the New Era: While the timing of the October 2025 peak followed the legacy script, the intensity did not. Previous cycle tops produced far more aggressive and persistent "Red Zone" clusters. The relative brevity of the integrity breakdown suggests that the "Institutional Era" provides a much higher floor than the retail-driven bubbles of 2017 and 2021.
โข The Institutional Floor: Our data shows that while "Tops" still resemble the 4-year cycle, the "Lows" now reflect a regime of constant institutional absorption. This suggests that the brutal 80% drawdowns of the past may be replaced by the "Institutional DNA" of Pillar 1.
Final Outlook: As we move through 2026, the ultimate test lies in the Q3/Q4 window. While classical theory demands a "Cycle Low" during this period, the CII will be our primary auditor. We cannot definitively say the cycle is dead, but we can say it has evolved. We will not know if the 4-year low will manifest until the model either flags a total structural breakdown or confirms that the institutional "Floor" has permanently shifted the rhythm of the asset.
Tags: Bitcoin, Institutional, Macro, On-chain, Liquidity, MSTR, ETF, Cycle
Note to Moderators: This script is a "Master Index" that aggregates several quantitative models I have previously published on this platform (including DNA Drawdown, RVPM, and Liquisync). I am the original author of the logic and source code referenced in the "Basis" sections of the description.
The Setup Factory - Swing Data TSF - Swing data
Useful intraday updated data for swing traders
Interpretation and summary:
1. 20D Avg $ Vol: The average daily dollar volume (Price ร Volume) over the last 20 trading days.
2. Live $ Vol: The total dollar volume accumulated during the current daily bar so far.
3. Relative Vol %: Today's volume progress compared to the average amount of volume typically accumulated by this exact minute over the last 20 days.
4. Projected Vol %: A prediction of the final daily volume total, calculated by applying today's current rate of outperformance (Buzz) to the full-day average.
5. Continuous Volume Buzz: The percentage difference between today's current volume and the historical average for this specific time window (e.g., how far "ahead of schedule" the stock is).
6. Volume Pace (15m): A comparison of the last 15 minutes of volume against the average 15-minute speed of the day so far (excluding the opening 15-minute surge).
7. Daily ATR %: The 14-day average daily price range (volatility) expressed as a percentage of the current stock price.
8. Dist. Today Low: The percentage distance between the current price and todayโs lowest point.
9. Dist. Prior Low: The percentage distance between the current price and yesterdayโs lowest point.
NewsTypesLibrary "NewsTypes" Provides the based library for the news system
f_hhmmToMs(_hhmm)
โโParameters:
โโโโ _hhmm (int)
f_addNews(_d, _hhmm, _tid, _dArr, _tArr, _idArr)
โโParameters:
โโโโ _d (string)
โโโโ _hhmm (int)
โโโโ _tid (int)
โโโโ _dArr (array)
โโโโ _tArr (array)
โโโโ _idArr (array)
f_addNewsMs(_d, _ms, _tid, _dArr, _tArr, _idArr)
โโParameters:
โโโโ _d (string)
โโโโ _ms (int)
โโโโ _tid (int)
โโโโ _dArr (array)
โโโโ _tArr (array)
โโโโ _idArr (array)
f_loadTypeSevByTypeId()
Predictive ZLEMA NavigatorThis is an advanced trend-following indicator that combines Zero-Lag Exponential Moving Averages (ZLEMA) with predictive crossover analysis to identify high-probability trade entries with exceptional timing precision.
Key Features:
1. Zero-Lag Technology
Utilizes ZLEMA calculation to eliminate the inherent lag found in traditional EMAs
Provides faster response to price movements while maintaining smooth trend identification
Default periods (34/89) align with Fibonacci sequence for natural market rhythm detection
2. Predictive Crossover System
Unique algorithm forecasts upcoming Golden Cross and Death Cross events before they occur
Displays estimated bars until next crossover, giving traders advance preparation time
Helps avoid late entries by signaling trend changes up to 200 bars in advance
3. Visual Direction Arrows
Color-coded projection arrows show the momentum trajectory of both fast and slow ZLEMAs
Adjustable projection length allows customization for different trading timeframes
Instantly identifies whether trends are strengthening or weakening
4. Multi-Layer Signal Confirmation
Clear crossover points marked with circles and confirmation ticks
Dynamic fill coloring between MAs for instant trend bias recognition
Bullish signals (green/blue) and bearish signals (orange/red) prevent confusion
Performance Characteristics:
Strengths:
Reduced Whipsaws: ZLEMA's lag reduction minimizes false signals in ranging markets
Early Detection: Predictive algorithm provides 10-50 bar advance warning of trend changes
Versatile Application: Works across all timeframes (1-minute to daily) and asset classes
Visual Clarity: Clean interface prevents information overload while maintaining comprehensive data
Optimal Use Cases:
Swing trading on 4H-Daily timeframes
Trend confirmation for breakout strategies
Portfolio rotation timing based on momentum shifts
Works exceptionally well on trending assets (crypto, indices, trending stocks)
Trading Approach:
Enter long on Golden Cross confirmation with upward direction arrows
Exit or reverse on Death Cross with downward momentum projection
Use prediction labels to scale into positions before actual crossover
Combine with volume analysis for enhanced confirmation
Built-in Alert System: Automated notifications for both bullish and bearish crossovers ensure you never miss a trading opportunity.
This indicator bridges the gap between reactive and predictive trading, giving you the speed of ZLEMA with the foresight of trend projection analysis.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice.Happy Trading
Current & Prior Day OHLC Levels# Current & Prior Day OHLC Levels with 15-Minute Opening Range
## Overview
This comprehensive indicator plots key price levels for futures and stock traders, displaying Current Day levels, Prior Day levels, and the 15-Minute Opening Range. These levels serve as critical support and resistance zones that professional traders monitor throughout the trading session.
## Key Features
### Current Day Levels (Session-Based)
- **Current Open**: The opening price of the current trading session
- **Current High**: The highest price reached during the current session (updates in real-time)
- **Current Low**: The lowest price reached during the current session (updates in real-time)
The indicator properly recognizes **futures trading sessions**, which begin at their respective session start times (not midnight). For example, most equity index futures sessions begin at 6:00 PM ET the previous day, ensuring accurate session-based tracking for overnight and globex trading.
### Prior Day Levels
- **Prior Open**: Opening price from the previous trading session
- **Prior High**: High of the previous trading session
- **Prior Low**: Low of the previous trading session
- **Prior Close**: Closing price from the previous trading session
Prior day levels are some of the most widely watched technical levels in trading, often acting as psychological support and resistance zones where price action tends to react.
### 15-Minute Opening Range (NY Session)
- **OR High**: The high of the first 15 minutes after New York market open (9:30-9:45 AM ET)
- **OR Low**: The low of the first 15 minutes after New York market open (9:30-9:45 AM ET)
The opening range concept is a popular day trading strategy. The first 15 minutes often establishes the tone for the day, with these levels frequently serving as breakout or breakdown points. The indicator tracks these levels in real-time as they form, then locks them in after 9:45 AM ET.
## Visual Design
### Smart Line Extension
- Lines extend **left** to the exact bar that created each level (e.g., the bar that made the high)
- Lines extend **right** by a configurable number of bars (default: 50 bars)
- No infinite line extension cluttering your chart
### Intelligent Label Placement
- Labels positioned **above** highs and opens
- Labels positioned **below** lows
- Adjustable offset to position labels optimally for your timeframe
- Optional price display in labels (e.g., "Current High: 5,950.00")
- Semi-transparent label backgrounds for clean chart appearance
## Customization Options
### Individual Level Controls
Each level (Current Open, High, Low, Prior Open, High, Low, Close, OR High, OR Low) can be:
- Toggled on/off independently
- Assigned a custom color
- Given its own line style (Solid, Dashed, or Dotted)
- Adjusted for line width (1-5 pixels)
### Default Styling
- **Current Day**: Solid lines (Gold for Open, Green for High, Red for Low)
- **Prior Day**: Dashed lines (Steel Blue for Open, Dark Cyan for High, Crimson for Low, Slate Blue for Close)
- **Opening Range**: Dotted lines (Cyan for High, Tomato for Low)
This default styling provides clear visual distinction between level types while remaining professional and easy to read.
### Label Customization
- Toggle all labels on/off
- Show or hide price values in labels
- Adjust label offset (distance from current bar)
- Five label size options: Tiny, Small, Normal, Large, Huge
### Line Extension Control
- Configurable right extension (0-500 bars)
- Adjust based on your chart timeframe and preference
## Best Use Cases
### Futures Traders
The indicator's session-aware design makes it perfect for futures markets, properly handling:
- Electronic trading hours (Globex)
- Session rollovers at 5:00 PM or 6:00 PM ET (depending on contract)
- Overnight price action
### Day Traders
- Use Opening Range levels for breakout/breakdown strategies
- Monitor Current High/Low for intraday trend identification
- Watch Prior Day levels for profit targets and stop placement
### Swing Traders
- Prior Day High/Low often act as key decision points
- Prior Close serves as an important reference level
- Current Day levels help with intraday entry/exit timing
### Multi-Timeframe Analysis
Works on any intraday timeframe:
- 1-minute for scalping
- 5-minute for active day trading
- 15-minute or 30-minute for swing entries
- 1-hour for position context
## Technical Details
### Session Detection
- Uses TradingView's built-in session detection for accurate daily boundaries
- Properly handles futures contracts with non-midnight session starts
- New York timezone detection for Opening Range (9:30 AM ET)
### Real-Time Updates
- Current High and Low update dynamically as price moves
- Opening Range levels update live during the 9:30-9:45 AM window
- Lines redraw on each bar to maintain accurate positioning
### Performance
- Maximum 500 lines and 500 labels to ensure smooth chart performance
- Efficient line/label deletion and recreation on session changes
- Minimal computational overhead
## Tips for Optimal Use
1. **Adjust Line Extension**: For lower timeframes (1-min, 5-min), reduce right extension to 20-30 bars. For higher timeframes (1-hour), increase to 100+ bars.
2. **Combine with Price Action**: These levels work best when combined with candlestick patterns, volume analysis, and order flow.
3. **Watch for Level Tests**: Price often tests these levels multiple times before breaking through or reversing.
4. **Opening Range Breakouts**: Many traders wait for price to break and close above OR High or below OR Low before entering directional trades.
5. **Prior Day Levels as Targets**: Use Prior High as an upside target and Prior Low as a downside target for intraday trades.
## Compatibility
- Works on all instruments (Futures, Stocks, Forex, Crypto)
- Optimized for intraday timeframes (1-min to 1-hour)
- Best results on liquid instruments with clear session boundaries
- Designed specifically with ES, NQ, YM, and RTY futures traders in mind
## Credits
Ported from NinjaTrader indicators with enhanced features and TradingView-specific optimizations. Original concept based on classic technical analysis principles used by professional traders worldwide.
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*Note: These levels are for informational and educational purposes only. Past performance does not guarantee future results. Always practice proper risk management.*
Multi-Filter Slope Master Pro CareCAdvanced EMA Slope Analyzer with Smart Filters
Key Features:
๐ Core Analysis
Tracks slopes of 3 EMAs (9, 20, 50)
Multiple slope calculation methods
Requires price + slope confirmation for signals
๐ก๏ธ Smart Filters
Multi-timeframe trend confirmation
Volume-based signal weighting
Trading session restriction
๐ Visual Dashboard
Interactive data tables (multiple layouts)
Real-time trend strength histogram
Color-coded signal markers
Customizable themes & positions
๐ Output
Individual EMA signals (Bullish/Bearish/Neutral)
Combined trend strength score
Overall market bias indicator
Chart alerts for signal changes
Purpose: Identify high-probability trend movements by filtering out noise through multiple confirmation layers.
OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)ไปฅไธๆฏไธบๆจๅฎๅถ็ **OBV Apex: DBDR (Donchian-Bollinger Dual Resonance)** ๆๆ ๅ่ฏญ็ฎไปใ
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## ๆๆ ็ฎไป / Indicator Overview
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** ๆฏไธๆฌพไธไธบๆๆ้ซๆฆ็่ถๅฟๅ่ฝฌๅๆณขๅจ็็ๅ่่ฎพ่ฎก็ๅฐ็ซฏ้ไปทๆๆ ใๅฎๆ็ ดไบไผ ็ปๆๆ ๅไธ็ปดๅบฆ็ๅฑ้๏ผๅฐๅบไบ็ปๅฏนไปทๆ ผๅบ้ด็**ๅๅฅๅฎ้้้ป่พ**ไธๅบไบ็ป่ฎกๅญฆๆฆ็ๅๅธ็**ๅธๆๅธฆๅจ่ฝ้ป่พ**ๆทฑๅบฆ่ๅ๏ผๆจๅจไธบไบคๆ่
ๆไพโ่ทจ็ปดๅบฆๅ
ฑๆฏโ็ๅณ็ญไพๆฎใ
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** is a cutting-edge volume-price indicator designed to capture high-probability trend reversals and volatility breakouts. It breaks the limitations of single-dimensional indicators by integrating **Donchian Channel logic** (based on absolute price ranges) with **Bollinger Band momentum logic** (based on statistical probability distribution), providing traders with a "cross-dimensional resonance" framework for decision-making.
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## ๆ ธๅฟๅ่ฝไธ่ง่ง่ฏๅซ / Key Features & Visual Identification
### **1. ๆบ่ฝๅ่ฒไธป็บฟ / Intelligent Multi-Color Main Line**
ๆๆ OBV ไธป็บฟๆ นๆฎๅฝๅๅจ่ฝ็ถๆๅฎๆถๅๆข้ข่ฒใ
* **็ฝ่ฒ (ๆ็ซฏๅบ)**๏ผๅฝ OBV ่งฆ็ขฐๆๅบ็ ดๅๅฅๅฎ้้่ฝจ้ๆถๅไธบ็ฝ่ฒ๏ผๆ็คบๅจ่ฝ่ฟๅ
ฅ่ถ
ไนฐๆ่ถ
ๅ็ๆ็ซฏๅบๅใ
* **็ปฟ่ฒ/็บข่ฒ (่ถๅฟๅบ)**๏ผไปฃ่กจ OBV ็ช็ ดไบไธญ่ฝจ็ผๅฒๅบ๏ผ็กฎ่ฎคไบๅฝๅ็ไธๆถจๆไธ่ท่ถๅฟใ
* **้ป่ฒ (ๅช้ณๅบ)**๏ผOBV ๅคไบ็ผๅฒๅบๅ
้จ๏ผๆ็คบๅธๅบๅคไบ้่กๆๆ ๆนๅ้ถๆฎตใ
The main OBV line switches colors in real-time based on momentum states.
* **White (Extreme)**: Turns white when OBV touches or pierces Donchian boundaries, signaling extreme overbought/oversold momentum.
* **Green/Red (Trend)**: Indicates OBV has broken out of the mid-rail buffer, confirming an uptrend or downtrend.
* **Yellow (Noise)**: OBV stays within the buffer zone, suggesting a sideways or directionless market.
### **2. ๆณขๅจ็ๆคๅ่ๆฏ / Volatility Squeeze Background**
ๅฝๅๅฅๅฎ้้ๅคงๅน
ๆถ็ช๏ผไปฃ่กจๅธๅบ่ฟๅ
ฅ่ๅ้ถๆฎตใๆญคๆถ็ฆปๆฃๅบๅ๏ผDispersion Area๏ผไผๅไธบ**ๆทฑ็ดซ่ฒ**๏ผ่ฟๆฏๅณๅฐๅ็ๅคง็บงๅซๅ็็้่ฆ่ง่งไฟกๅทใ
When the Donchian Channel narrows significantly, it represents a market accumulation phase. The Dispersion Area turns **Deep Purple**, providing a crucial visual signal for an impending major volatility breakout.
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## ่ฏฆ็ป็จๆณ่ฏดๆ / Detailed Usage Instructions
### **1. ้ป่พๅ
ฑๆฏๆๅท (โญ) ็ๅฎๆๆไน / Strategic Meaning of the Resonance Star (โญ)**
่ฟๆฏๆฌๆๆ ๆๅ
ทไปทๅผ็ๆ ธๅฟไฟกๅทใ
* **ๅบ็กไฟกๅท (R/H)**๏ผๅฝๅๅฅๅฎ็ณป็ปๆฃๆตๅฐ็ปๆๆง่็ฆปๆถไบง็ใ
* **ๅ
ฑๆฏไฟกๅท (โญ)**๏ผไป
ๅฝๅๅฐ้่็ๅธๆๅธฆ็ฎๆณไนๅๆถๆฃๆตๅฐ้ป่พ่็ฆปๆถ๏ผไฟกๅทๅๆไผ้ๅธฆ โญใ
* **็จๆณ**๏ผๆฎ้ R ไฟกๅทไป
ไปฃ่กจไปทๆ ผ็ปๆ็่กฐ็ซญ๏ผ่ **Rโญ** ๅไปฃ่กจ็ฉบ้ด็ปๆไธๆณขๅจ็ๅจ่ฝ็**ๅ้่กฐ็ซญ**ใๅจๅฎๆไธญ๏ผๅธฆๆๆๅท็ไฟกๅทๅ
ทๆๆ้ซ็ๅ่ฝฌๆๅ็๏ผๆฏๆธ้กถๆๅบ็ๆ ธๅฟๅ่ใ
This is the most valuable core signal of the indicator.
* **Basic Signals (R/H)**: Generated when the Donchian system detects structural divergence.
* **Resonance Signal (โญ)**: A star is appended only when the hidden Bollinger Band algorithm also detects logical divergence simultaneously.
* **Usage**: A standard R signal represents structural exhaustion, while **Rโญ** signifies **dual exhaustion** of both space structure and volatility momentum. In practice, signals with stars offer significantly higher reversal success rates.
### **2. ้กถ็น็ๅ็ญ็ฅ (็ช็ ดไบคๆ) / The Apex Explosion Strategy (Breakout)**
* **่งๅฏ**๏ผๅฏปๆพ่ๆฏๅบ็ฐๆ็ปญ**ๆทฑ็ดซ่ฒ**ๅกซๅ
็ๅบๅ๏ผๆคๅๆ๏ผใ
* **ๅ
ฅๅบ**๏ผๅฝ OBV ไธป็บฟ็ฑ้ป่ฝฌ็ปฟ๏ผๅคๅคด็ช็ ด๏ผๆ็ฑ้ป่ฝฌ็บข๏ผ็ฉบๅคด็ช็ ด๏ผๅนถ่ฑ็ฆป็ดซ่ฒๅบๅๆถ๏ผๆฏ็ๅๆง่กๆ
็่ตทๅง็นใ
* **Observation**: Look for areas with continuous **Deep Purple** background filling (Squeeze phase).
* **Entry**: When the OBV line shifts from yellow to green (Bullish breakout) or red (Bearish breakout) and exits the purple zone, it marks the start of an explosive trend.
### **3. ๅ้ๅ
ฑๆฏๅ่ฝฌ็ญ็ฅ (ๅ่ฝฌไบคๆ) / Double Resonance Reversal Strategy**
* **็กฎ่ฎคๆกไปถ**๏ผOBV ไธป็บฟๅไธบ**็ฝ่ฒ**่ฟๅ
ฅๆ็ซฏๅบ๏ผ้ๅๅบ็ฐๅธฆๆ **โญ** ็่็ฆปๆ ็ญพใ
* **่พ
ๅฉ็กฎ่ฎค**๏ผ่งๅฏ KDJ ๆ ็ญพใๅฆๆๅ
ฑๆฏๆๅทๅบ็ฐๅ๏ผKDJ ไบง็้กบๅฟ็ๅคงๅ **B (Buy)** ๆ **S (Sell)** ๆ ็ญพ๏ผๅๅ่ฝฌ็็กฎๅฎๆง่ฟไธๆญฅๅขๅผบใ
* **Confirmation**: The OBV line turns **White** (Extreme zone), followed by a divergence label with a **โญ**.
* **Secondary Confirmation**: Monitor KDJ labels. If an uppercase **B (Buy)** or **S (Sell)** appears after the resonance star, the certainty of the reversal is further enhanced.
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## ไธไธๆญฅๅปบ่ฎฎ / Next Step
ๆจ็ฐๅจๅฏไปฅๆ นๆฎๆญค็ฎไป่ฟ่กๅฎ็ๅค็ใๅฆๆๆจ้่ฆๆๅฐ**่ญฆๆฅ้ป่พ (Alerts)** ่ฟไธๆญฅ็ปๅ๏ผไพๅฆ้ๅฏนโๅธฆๆๅท็่็ฆปโ่ฎพ็ฝฎไธ้จ็ๆจ้ๆ้๏ผ่ฏท้ๆถๅ่ฏๆใ
You can now use this overview for backtesting. If you need me to further refine the **Alert logic**, such as setting specific push notifications for "Divergence with Star," please let me know.
Dual VWAP + Dual ATR % BandsScript is adjusted for 5min time frame, can play around setting to adjust accordingly.
It has
Vwap regular
Vwap with adjustable time period
Bands based on ATR value, ie (if ATR is 10, one can adjust band to VWap+ATR %( adjustable)
ATR% can be adjusted to include daily ATR values in addition to current day ATR based on chart time frame.
The bands can be tied to regular VWAP or period VWAP
Regards
RSI adaptive zones with divergencesThis script is modified version of Adaptive RSI,
Thanks to creator of the script, modification is made by cloude code.
Adaptive RSIThe Adaptive RSI is a new version of the famous RSI that can adapt to environments and produce both Mean Reverting & Trend Following signals.
The Benefits
- Adaptive behaviour can allow fast entries while also filtering false signals
- Provides signals for both catching high/low value zones and trends
- Very good trend catching in trending environments
- Visualization provides Overbought/Oversold signal highlighting of more restrictive (diamonds) and less restrictive type (background), divergence between smoothed and basic RSI, Adaptive RSI values and bar coloring.
- Works well on BINANCE:BNBUSD
The Idea
The main idea is to give the RSI a more adaptive approach to do the market, so it can speed it up during potential oppurtunities and slow down during more dangerous environments.
This would theoreticly allow it to be a lot more versatile and provide a more accurate set of signals. On top of that, the adaptive approach could not only provide great entries but also exits when following the indicator mean-reverting style.
How it works
The indicator sets up 3 conditions, the more of them are true, the more aggressive approach will be chosen. This allows the indicator to shift speed, adapt to any environment and avoid too many false signals.
Then it uses a smoothing to improve accuracy, that is adaptive in the same way as the RSI itself.
It also has a option for a special ROC-weighted source, which however I do not recommend using unless you understand coding & know how it works.
Hope you enjoy Gs!
Please keep in mind no indicator is perfect and that every indicator has flaws
Momentum Regime and Confluence EngineThe Momentum Regime and Confluence Engine is a momentum-based indicator designed to help traders understand trend context, alignment, and timingโwithout relying on price prediction or repainting logic.
Instead of telling you what to buy or sell, this tool answers three critical questions:
Which timeframe is in control?
Is short-term momentum aligned or counter-trend?
When is momentum likely to change?
๐น Core Concept (Simple Explanation)
Markets move in cycles of momentum.
This indicator visualizes those cycles across Weekly and Daily timeframes and places them into a single, easy-to-read view.
Weekly momentum defines the broader market regime
Daily momentum shows shorter-term pressure inside that regime
Projection provides an early visual guide for potential momentum shifts
๐ข๐ด Momentum Lines (%K / %D)
The indicator uses two smooth momentum lines:
Green line โ rising momentum pressure
Red line โ declining momentum pressure
These lines move between 0 and 100:
Near 0 โ downside momentum is exhausted
Near 100 โ upside momentum is exhausted
When green is above red, momentum is improving.
When red is above green, momentum is weakening.
๐ฅ๐ฉ Weekly Context Background (Primary Trend)
The background color represents the Weekly momentum regime:
Green โ Weekly bullish context
Red โ Weekly bearish context
Gray โ Neutral / transitional phase
Weekly context changes slowly by design and uses hysteresis logic, meaning it will not flip back and forth near a crossover. Momentum must prove itself before the regime changes.
This helps reduce false signals and whipsaws.
๐ข๐ด Daily Context Overlay (Timing Layer)
A lighter background overlay shows Daily momentum context:
Reacts faster than the weekly layer
Can temporarily move against the weekly trend
Highlights pullbacks, relief rallies, and short-term shifts
Examples:
Weekly red + Daily green โ short-term bounce in a downtrend
Weekly green + Daily red โ pullback in an uptrend
๐ Projection & โProjected Crossโ
The indicator includes an optional momentum projection:
It analyzes a historical momentum pattern
Maps that behavior forward in time
Displays a projected path for the momentum lines
A โProjected Crossโ label marks where a momentum crossover is likely to occur if similar conditions repeat.
Projections are scenarios, not guarantees.
They are intended as early awareness, not signals.
๐ท Weekly Context Tag
A small on-screen tag displays the current Weekly regime:
W Context: Bull
W Context: Bear
W Context: Neutral
This provides quick confirmation without needing to interpret colors alone.
๐งญ How to Use This Indicator
Start with the Weekly background
Identify the dominant market regime.
Check the Daily overlay
Look for alignment or counter-trend behavior.
Watch for projected momentum shifts
Prepare for volatility or transition.
Use price for confirmation
Momentum often shifts before price reacts.
โ
Best Use Cases
Identifying trend regime and momentum bias
Avoiding trades against higher-timeframe pressure
Timing pullbacks and momentum reversals
Staying objective during market noise
โ ๏ธ Important Notes
This indicator does not predict price
It does not generate buy/sell signals
It is a context and timing tool, not a standalone strategy
Final Thought
The Momentum Regime and Confluence Engine is designed to help traders see who is in control, who is pushing back, and when momentum is likely to changeโbefore price makes it obvious.
Log Trend Channel Enhanced**Log Trend Channel Enhanced (LTC+)**
A logarithmic regression channel with 11 deviation bands and comprehensive statistical metrics.
**Features:**
- Logarithmic regression trendline from customizable start date
- 11 parallel bands at ยฑ0.5ฯ, ยฑ1ฯ, ยฑ1.5ฯ, ยฑ2ฯ, ยฑ2.5ฯ standard deviations
- Color-coded zones (green = undervalued, red = overvalued)
**Metrics displayed:**
- Rยฒ (goodness of fit)
- Pearson correlation
- Implied CAGR (annualized return from trendline)
- Distance from trend (%)
- Current ฯ position
- Channel position (%)
- Historical percentile rank
**Usage:**
Ideal for long-term trend analysis on assets with exponential growth patterns. Use on log-scale charts for best visualization. Green zones near -2ฯ historically indicate accumulation opportunities; red zones near +2ฯ suggest distribution phases.
**Settings:**
- Adjustable start date (default: 1 year ago)
- Customizable colors and line widths
- Optional deviation labels
- Configurable future projection
M15 Impulse FVG EntryM15 Impulse FVG Entry
M15 Impulse FVG Entry is a minimalist price-action tool designed to highlight structured entry contexts using impulse candles, decision zones, and Fair Value Gap (FVG) logic.
โธป
Core Logic
1. M15 Impulse Candle
A strong M15 candle is identified using ATR expansion and body-to-range ratio.
This candle defines a decision zone (High / Low).
2. IN Candle
Only the first candle that forms fully inside the decision zone after the M15 impulse is considered.
This candle acts as the structural reference.
3. OUT Candle
Price must break cleanly outside the zone.
The previous candle must already close outside the zone.
No reversal is allowed through the IN candle extreme.
4. FVG Entry Context
The gap between the IN candle and the OUT candle forms the Fair Value Gap.
A midpoint between IN and OUT can be used as a potential entry reference.
โธป
What This Script Shows
โข M15 โ Impulse candle marker
โข Zone โ High / Low of the impulse candle
โข IN โ First valid candle inside the zone
โข OUT โ Valid breakout candle
โธป
Design Philosophy
โข No BUY / SELL bias
โข No alerts, no automation
โข No indicator stacking
โข Clean and chart-friendly
This script provides market context and structure only .
Risk management and execution rules remain the traderโs responsibility.
Smart Reversal [Scalping-Algo]โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Smart Reversal
This indicator identifies potential reversal points using a two-step confirmation method that I developed for my own scalping. Unlike typical reversal indicators that rely on RSI oversold/overbought or simple candlestick patterns, this uses a different approach.
๐น HOW IT WORKS
The logic is based on two phases:
Phase 1 - Anchor Detection:
The indicator looks for candles where price closes beyond ALL previous candles in the lookback period. For a bullish setup, the close must be below the lows of the last N candles (default 20). This isn't just a "lower low" - it's an extreme extension where price has broken below every single candle in the range. I also require this candle to have above-average volume (2x the 20-period average) to confirm real selling pressure, not just a gap or low-liquidity move.
Phase 2 - Confirmation:
After an anchor forms, I wait for price to reverse and close above the anchor candle's high (for buys) or below the anchor's low (for sells). This must happen within 3 bars. If price makes a new extreme instead, the setup cancels.
๐น SIGNAL QUALITY SCORING
Each signal gets a score from 3/5 to 5/5:
- 3/5: Basic confirmation occurred
- 4/5: Anchor or confirmation had strong volume
- 5/5: Both volume conditions met + aligned with 200 EMA trend
I focus on 4/5 and 5/5 signals personally.
๐น WHAT YOU SEE ON CHART
- Green/Red boxes: Active setup waiting for confirmation
- B or S labels: Confirmed signals with quality score
- Dashboard: Shows current status and volume condition
๐น SETTINGS
- Bars to Check: How many candles for the breakout comparison (default 20)
- Confirmation Window: Bars allowed after anchor for confirmation (default 3)
- Volume thresholds: Adjustable multipliers for anchor (2x) and confirmation (1.2x)
๐น SUGGESTED USE
- Works on any timeframe, but I use it mainly on 5-15 min charts
- Better results when combined with key support/resistance levels
- Avoid trading during high-impact news
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
EMA Slope Checker Pro CareCAn enhanced momentum analysis indicator that measures the rate of change of key EMAs (9, 20, 50) with a fully customizable data table. It provides real-time slope calculations, visual trend direction arrows, and a professional-grade information panel that can be positioned, resized, and color-customized to match any trading background or screen layout.
Perfect for momentum traders who need quick, at-a-glance EMA slope information with maximum visibility and customization options.
5Min Dashboard + 1Min Footprint (mit Dashboard-Ampel)This dashboard combines multiple key trading indicators for the 5-minute chart and adds a 1-minute Footprint analysis. It provides a quick overview of the strongest signals without micro-volume affecting the Buy/Sell rating.
Features:
EMA9/21 Cross โ fast trend cross detection
Williams %R โ overbought/oversold signals
MACD โ trend direction on the 5-minute timeframe, optimized for day trading
VWAP โ price relative to volume-weighted average
ADX Filter โ identifies trend strength, helps avoid sideways markets
Footprint 1-Minute Signal โ highlights high Buy/Sell volume zones (support/resistance)
Dashboard Signals โ clear Buy/Sell/Neutral status with scores
Overlay Plots: EMA9, EMA21, VWAP, Footprint cumulative delta, and support/resistance zones
Advantages:
Fast visualization of all key indicators in one panel
Signal lights and arrows simplify quick decision-making
Flexible timeframes: 5-min for trading decisions, 1-min footprint for micro-market movements
Open Source: fully viewable, transparent, and customizable code
Disclaimer / Legal Notice:
This indicator is for analysis purposes only.
Not financial advice; no guarantee of profits.
Trading is at the user's own risk.
Users should conduct their own testing before executing real trades.
OTM Adaptive Kalman CloudOTM โข Adaptive Kalman Cloud โ User Guide
OTM โข Adaptive Kalman Cloud is a trend + momentum visual tool built around two Adaptive Kalman filters (Fast & Slow). It prints a directional cloud that reacts quickly when the market shifts, but stays smooth enough to keep you out of chop.
What it shows
Fast Kalman = short-term direction / impulse
Slow Kalman = trend baseline / structure bias
Cloud = the โstateโ of the market (trend vs reversal vs chop)
How to read it
Bullish state
Cloud is bull color
Fast is above Slow (or Fast slope is rising if using slope mode)
Best trades: pullbacks into the cloud + continuation
Bearish state
Cloud is bear color
Fast is below Slow (or Fast slope is falling)
Best trades: pullbacks into the cloud + continuation
Transition / reversal
Cloud flips color after Fast/Slow relationship changes
Treat first flip as warning, confirmation comes from structure/liquidity (your SMC tool)
Settings that matter (donโt overcomplicate it)
1) Lengths
Fast (8โ13): quicker signals, more noise
Slow (21โ55): cleaner bias, fewer flips
Typical: 8 / 21 (fast scalps) or 13 / 34 (cleaner trend)
2) Color Mode
Fast>Slow: best for trend bias (simple + reliable)
Fast Slope: more responsive, can flip earlier in chop
3) Timeframe + Wait for Close
Set a higher TF (ex: 1H) to use it as bias
Turn on Wait for timeframe closes to stop HTF repaint-style flicker
4) Cloud Thickness
Thickness Mult is visual only (makes the cloud easier to see)
Doesnโt change the Kalman calculationโjust visibility
5) Spread (Visual Helper)
Spread is visual only to separate lines when volatility is low
Use ATR spread for most markets
Best way to use it (simple rules)
Only trade in the cloud direction
Entries: wait for price to pull back into/near the cloud, then continue
Exits: when cloud flips against you OR momentum dies and structure breaks
Combine with your SMC: use the cloud as bias, SMC as entry trigger
Recommended presets
Gold / BTC (5mโ15m)
Fast 8, Slow 21
Color mode: Fast>Slow
Thickness: 1.6โ2.2
Spread: ATR, 14, amount 0.10โ0.25 depending on volatility
Vimal's Super Intraday Combo // ยฉ Vimal โ Super Intraday Combo Signal (v6)
//@version=6
indicator("Vimal's Super Intraday Combo (RSI + MACD + BB + EMA + VWAP + Stoch)", overlay=true)
// ---------- Inputs ----------
groupTrend = "Trend & Benchmarks"
emaLen = input.int(20, "EMA length", minval=5, group=groupTrend)
useVWAP = input.bool(true, "Use VWAP filter", group=groupTrend)
groupMom = "Momentum"
rsiLen = input.int(14, "RSI length", minval=5, group=groupMom)
rsiBuy = input.int(55, "RSI buy threshold", minval=40, maxval=70, group=groupMom)
rsiSell = input.int(45, "RSI sell threshold", minval=30, maxval=60, group=groupMom)
stochLen = input.int(14, "Stoch length", minval=5, group=groupMom)
stochSignal = input.int(3, "Stoch signal length", minval=1, group=groupMom)
stochBuyLvl = input.int(20, "Stoch oversold level", minval=1, maxval=50, group=groupMom)
stochSellLvl = input.int(80, "Stoch overbought level", minval=50, maxval=99, group=groupMom)
groupMACD = "MACD"
macdFast = input.int(12, "MACD fast", minval=3, group=groupMACD)
macdSlow = input.int(26, "MACD slow", minval=5, group=groupMACD)
macdSignalLen = input.int(9, "MACD signal", minval=3, group=groupMACD)
groupBB = "Bollinger Bands"
bbLen = input.int(20, "BB length", minval=5, group=groupBB)
bbMult = input.float(2.0, "BB multiplier", minval=1.0, maxval=4.0, step=0.1, group=groupBB)
bbSqueezeLook = input.int(20, "Squeeze lookback", minval=10, group=groupBB)
groupLogic = "Signal Logic"
strictMode = input.bool(false, "Strict mode (all filters must agree)", group=groupLogic)
riskFilter = input.bool(true, "Avoid chasing far outside upper band", group=groupLogic)
maxBandDistPc = input.float(0.30, "Max distance above upper band (%) for buys", minval=0.05, step=0.05, group=groupLogic)
minBandDistPc = input.float(0.30, "Max distance below lower band (%) for sells", minval=0.05, step=0.05, group=groupLogic)
// ---------- Core calculations ----------
ema = ta.ema(close, emaLen)
vwap = ta.vwap(close)
rsi = ta.rsi(close, rsiLen)
k = ta.sma(ta.stoch(close, high, low, stochLen), 1)
d = ta.sma(k, stochSignal)
= ta.macd(close, macdFast, macdSlow, macdSignalLen)
basis = ta.sma(close, bbLen)
dev = bbMult * ta.stdev(close, bbLen)
bbUpper = basis + dev
bbLower = basis - dev
bbWidth = (bbUpper - bbLower) / basis
squeeze = bbWidth < ta.lowest(bbWidth, bbSqueezeLook)
// ---------- Conditions ----------
trendUp = close > ema
trendDown = close < ema
vwapUp = not useVWAP or close >= vwap
vwapDown = not useVWAP or close <= vwap
rsiBull = rsi >= rsiBuy
rsiBear = rsi <= rsiSell
stochBull = ta.crossover(k, d) and k < stochBuyLvl
stochBear = ta.crossunder(k, d) and k > stochSellLvl
macdBull = macdLine > macdSignal and macdHist > 0
macdBear = macdLine < macdSignal and macdHist < 0
bbBreakUp = ta.crossover(close, bbUpper)
bbBreakDn = ta.crossunder(close, bbLower)
// Risk control: avoid chasing too far outside bands
distAboveUpper = (close - bbUpper) / close
distBelowLower = (bbLower - close) / close
okBuyDistance = not riskFilter or distAboveUpper <= maxBandDistPc
okSellDistance = not riskFilter or distBelowLower <= minBandDistPc
// ---------- Scoring ----------
bullScore = (trendUp ? 1 : 0) + (vwapUp ? 1 : 0) + (rsiBull ? 1 : 0) + (stochBull ? 1 : 0) + (macdBull ? 1 : 0) + ((bbBreakUp or (close > basis and not squeeze)) ? 1 : 0)
bearScore = (trendDown ? 1 : 0) + (vwapDown ? 1 : 0) + (rsiBear ? 1 : 0) + (stochBear ? 1 : 0) + (macdBear ? 1 : 0) + ((bbBreakDn or (close < basis and not squeeze)) ? 1 : 0)
minAgree = strictMode ? 6 : 4
buy = bullScore >= minAgree and okBuyDistance
sell = bearScore >= minAgree and okSellDistance
// ---------- Plots (ensures indicator outputs) ----------
plot(ema, "EMA", color=color.new(color.yellow, 0), linewidth=2)
plot(vwap, "VWAP", color=color.new(color.orange, 20), linewidth=1)
plot(bbUpper,"BB Upper",color=color.new(color.teal, 0))
plot(basis, "BB Basis",color=color.new(color.gray, 60))
plot(bbLower,"BB Lower",color=color.new(color.teal, 0))
plotshape(buy, title="BUY", style=shape.labelup, color=color.new(color.lime, 0), text="BUY", location=location.belowbar, size=size.tiny)
plotshape(sell, title="SELL", style=shape.labeldown, color=color.new(color.red, 0), text="SELL", location=location.abovebar, size=size.tiny)
bgcolor(buy ? color.new(color.lime, 92) : sell ? color.new(color.red, 92) : na)
// ---------- Alerts ----------
alertcondition(buy, title="BUY signal (combo)", message="BUY: Multi-indicator agreement reached.")
alertcondition(sell, title="SELL signal (combo)", message="SELL: Multi-indicator agreement reached.")
// ---------- Optional table ----------
var tbl = table.new(position.top_right, 3, 7, border_color=color.new(color.white, 70))
if barstate.islast
table.cell(tbl, 0, 0, "Metric", text_color=color.white)
table.cell(tbl, 1, 0, "Bull", text_color=color.lime)
table.cell(tbl, 2, 0, "Bear", text_color=color.red)
table.cell(tbl, 0, 1, "Trend (EMA)")
table.cell(tbl, 1, 1, trendUp ? "โ
" : "โ", text_color=color.lime)
table.cell(tbl, 2, 1, trendDown? "โ
" : "โ", text_color=color.red)
table.cell(tbl, 0, 2, "VWAP")
table.cell(tbl, 1, 2, vwapUp ? "โ
" : "โ", text_color=color.lime)
table.cell(tbl, 2, 2, vwapDown ? "โ
" : "โ", text_color=color.red)
table.cell(tbl, 0, 3, "RSI")
table.cell(tbl, 1, 3, rsiBull ? "โ
" : "โ", text_color=color.lime)
table.cell(tbl, 2, 3, rsiBear ? "โ
" : "โ", text_color=color.red)
table.cell(tbl, 0, 4, "Stoch")
table.cell(tbl, 1, 4, stochBull? "โ
" : "โ", text_color=color.lime)
table.cell(tbl, 2, 4, stochBear? "โ
" : "โ", text_color=color.red)
table.cell(tbl, 0, 5, "MACD + BB")
table.cell(tbl, 1, 5, (macdBull or bbBreakUp) ? "โ
" : "โ", text_color=color.lime)
table.cell(tbl, 2, 5, (macdBear or bbBreakDn) ? "โ
" : "โ", text_color=color.red)
table.cell(tbl, 0, 6, "Score", text_color=color.white)
table.cell(tbl, 1, 6, str.tostring(bullScore), text_color=color.lime)
table.cell(tbl, 2, 6, str.tostring(bearScore), text_color=color.red)
Swing High Low Liquidity Pools with Purge CriteriaThis Pine Script indicator plots dynamic liquidity pool levels from swing highs/lows using two configurable sensitivities (short-term and longer-term), extends lines until breached by a percentage threshold, and displays horizontal All-Time High (ATH) and All-Time Low (ATL) lines. User can choose to hide liquidity pool levels that are no longer active.
Recommended for higher time frames like daily and weekly.
