V16 Trend AnazlysisV16 - Daily Scoring Indicator Description
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V16 is a daily chart scoring indicator that evaluates whether a stock has the right conditions for a trade. Rather than giving a simple buy or sell signal, it scores the current setup out of 100 and tells you how strong the opportunity is before you commit to an entry. V16 is designed to be used first, before dropping to the 15 minute chart with V16E for the precise entry.
HOW IT WORKS
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V16 watches three core indicators simultaneously and combines them into a single score out of 100. The score updates on every bar and is displayed in a table in the top right corner of your chart. The higher the score, the stronger the setup. The colour of the score changes from red through orange, yellow and green to bright green as confidence increases.
ADX - 40 points - the foundation
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The Average Directional Index is the most heavily weighted component because without a real trend, the other indicators mean very little. ADX measures trend strength on a scale of 0 to 100. Anything below 20 is considered a ranging, choppy market where trades are unreliable. Above 25 is where a genuine trend begins.
ADX scores points in three ways:
Base Strength - how strong is the trend right now?
Above 75 = Extreme = 20 points
Above 50 = Very Strong = 16 points
Above 35 = Strong = 12 points
Above 25 = Moderate = 7 points
Above 20 = Developing = 2 points
Below 20 = No Trend = 0 points
Direction - is the trend getting stronger or weaker?
Rising strongly (3+ points vs 3 bars ago) = 12 points
Rising moderately (1-3 points) = 7 points
Flat (within 1 point) = 3 points
Falling = 0 points
DI Line Separation - how much conviction is behind the trend?
The two DI lines inside ADX show buying pressure (DI+) and selling pressure (DI-). When they are far apart and moving further apart, the trend has real conviction.
Gap 15+ and widening = 8 points
Gap 8-15 and widening = 6 points
Gap 8-15 flat = 4 points
Gap 4-8 = 2 points
Lines crossing/tangled = 0 points
RSI - 35 points - momentum and timing
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The Relative Strength Index measures momentum. V16 uses RSI in a more refined way than just watching the standard 70 and 30 levels. It uses the RSI zone, a signal line crossover, and the 50 midline to determine the quality of the momentum behind the move.
RSI scores points in two ways:
Zone - where is RSI sitting right now?
Bull control zone 65-70 = 18 points (long)
Neutral high 55-65 = 14 points (long)
Trending bull 50-55 = 8 points (long)
Overbought above 70 = 10 points (long, extended)
Neutral 45-50 = 0 points
Trending bear 40-46 = 8 points (short)
Neutral low 35-40 = 14 points (short)
Bear control 30-35 = 18 points (short)
Oversold below 30 = 10 points (short, extended)
Signal Line and 50 Cross - is momentum confirmed?
V16 applies a 9 period EMA to the RSI, creating a signal line. Crossovers of this line are meaningful entry signals. The highest scoring condition is a pullback setup - where RSI dipped below 50 and has now recovered back above it while crossing the signal line. This pattern shows the trend is healthy and buyers stepped back in at the right moment.
Pullback below 50, now recrossing above 50 and signal line = 17 points
Pullback and RSI above signal line (no fresh cross) = 13 points
Fresh cross above signal line while above 50 = 12 points
RSI above signal line, above 50 = 8 points
Cross above signal line while below 50 (early) = 4 points
(Mirror conditions apply for short signals)
DELTA - 25 points - buying and selling pressure
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Delta measures where each candle closed relative to its own high-low range. A candle that opened at the low and closed near the high shows strong buying pressure. A candle that did the opposite shows selling pressure. Delta scores points in three ways:
Zone - how strong is the pressure on this candle?
Strong buying or selling (60%+) = 10 points
Moderate buying or selling (20-60%) = 7 points
Weak (5-20%) = 3 points
Neutral (-5% to +5%) = 0 points
Direction - is pressure increasing or fading?
Rising strongly (10%+ increase) = 9 points (long)
Rising moderately (5-10%) = 6 points (long)
Flat (within 5%) = 3 points
Falling moderately = 4 points (short)
Falling strongly (10%+ decrease) = 9 points (short)
Momentum - has buying/selling been consistent over 3 bars?
Positive all 3 bars = 6 points (long)
Positive 2 of 3 bars = 3 points (long)
Mixed = 0 points
Negative 2 of 3 bars = 3 points (short)
Negative all 3 bars = 6 points (short)
SCORING BREAKDOWN
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Indicator Component Max Points
--------- --------- ----------
ADX Base strength 20
ADX Direction (vs 3 bars ago) 12
ADX DI lines + separation 8
RSI Zone 18
RSI Signal line + 50 cross 17
Delta Zone 10
Delta Direction 9
Delta Momentum (3 bars) 6
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Total 100
Score Colours:
80 - 100 = Bright green (strong setup)
60 - 79 = Green (good setup)
40 - 59 = Yellow (moderate)
20 - 39 = Orange (weak)
0 - 19 = Red (no setup)
THE TABLE - TOP RIGHT OF CHART
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V16 displays a table in the top right corner of your TradingView chart with the following rows:
ADR% Average Daily Range - how much the stock typically moves per day
LoD Location of Day - where price sits within today's range
Vol Raw volume for the current bar
RVOL Relative Volume - today's volume vs the 20 bar average
Delta Candle delta percentage and label
Trend ADX value and trend strength label
RSI RSI value and zone label
BB Bollinger Band status (Normal, Squeeze, Upper Touch, Lower Touch)
Score The combined score out of 100
SIGNAL TYPES
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When the score is active and DI lines confirm a direction, V16 identifies the type of setup:
Long Momentum
ADX strong, RSI above 50 and rising, delta positive. You are joining an existing uptrend that still has energy. Higher risk as the move has started but trend is clearly confirmed.
Long Pullback
ADX strong, RSI dipped below 50 within the last 5 bars and has now recovered back above it, delta turning positive. You are buying the dip within a healthy uptrend. Generally considered a higher quality entry with better risk-reward.
Short Momentum and Short Pullback follow the same logic in reverse.
DELTA AS A WARNING NOT A BLOCKER
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Delta does not block a signal. If ADX and RSI conditions are met, V16 still shows the score even if delta is weak or neutral. A weak delta simply reduces the total score, making the signal appear in yellow or orange rather than green. This design prevents a single choppy candle from hiding what could be a valid setup on a strong trend day. You can see the delta value in the table at all times and use it as additional context for your own judgment.
KEY SETTINGS
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Trend Settings
ADX Length Default 14
ADX Smooth Default 14
ADX Threshold Default 25 (minimum ADX to count as a trend)
RSI Settings
RSI Length Default 14
RSI Signal EMA Default 9
Pullback Window Default 5 bars (how far back to look for RSI dip below 50)
Moving Averages
MA1 EMA 9 (fast, blue)
MA2 SMA 50 (medium, orange)
MA3 SMA 200 (slow, green)
Bollinger Bands
Length Default 20
StdDev Multiplier Default 2.0
Squeeze Threshold Default 0.02
Signal History
Lookback Default 20 bars (shows L and S count in last N bars)
Display
Device Laptop or Phone (adjusts label lengths)
Text Size Tiny / Small / Normal / Large
HOW TO USE V16 WITH V16E
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Step 1 - Open V16 on the daily chart of any stock you are watching.
Step 2 - Check the score. Is it 60 or above? Is the direction clear (Long or Short)?
Step 3 - If yes, open V16E on the same stock and set the timeframe to 15M in V16E settings.
Step 4 - Watch the V16E score build in real time on the 15 minute chart.
Step 5 - When V16E fires an arrow with a score above 70 in the same direction as V16, that is your entry point.
VERSION HISTORY
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V15 - Original indicator with ADX, RSI, Delta, BB, signal history, MA plots
V15u - Delta moved from hard signal gate to warning only (first upgrade)
V16 - Full scoring system added (100 points)
- RSI signal line (9 EMA) added
- Pullback vs Momentum detection added
- Score replaces Trade row in table
- Colour gradient red to bright green
- ADX direction and DI separation scoring added
- Delta direction and momentum scoring added
- RSI zone refined with 50 midline and signal line crossover logic
- Pullback rebreak of 50 scores highest in RSI component
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London Open ToolkitLondon Open Toolkit is a session-mapping indicator built for traders who want a simple, visual framework around the London open. It highlights the Asia session range, keeps only a user-defined number of recent session boxes on the chart, projects the latest completed Asia high and low forward, and adds a small set of key reference levels: Daily Open, Previous Day High, and Previous Day Low. An optional moving average can also be displayed as a trend filter.
What it does
This script is designed to make the chart easier to read before and during the London session by focusing on a few practical reference points instead of trying to generate fully automated trade signals. It shows:
The Asia session as a shaded box
The Asia session high and low
An optional Asia midpoint
A forward projection of the most recently completed Asia high and low
Optional projected Daily Open, Previous Day High, and Previous Day Low
An optional EMA or SMA filter
A compact dashboard showing session state and simple directional context
The goal is to give a clean framework for studying liquidity around the London open, especially around the most recent Asia range.
How it works
The script uses a user-defined Asia session and time zone. While the session is active, it builds the high and low of that range in real time. When the session ends, the box and its range lines are fixed in place. The script keeps only the last N Asia sessions visible, where N is chosen by the user. The latest completed Asia range can then be projected forward so the most relevant session high and low remain visible for the active trading day.
For higher-time-frame context, the script fetches:
Daily Open
Previous Day High
Previous Day Low
These are projected forward in a cleaner style rather than drawn across large sections of chart history. This is intended to reduce clutter and keep the focus on current price action.
Why this version is intentionally simple
This indicator does not attempt to auto-detect sweep entries, reclaim candles, or trade setups. That logic was intentionally removed to keep the tool focused on chart structure and session reference levels. It is best used by traders who prefer to interpret the interaction between price and key levels themselves.
Inputs
Key settings include:
Time zone: used for session calculations
Asia Session: defines the boxed session
Keep last N days: controls how many Asia session boxes remain visible
Show Asia range box / high / low / midpoint
Project latest Asia range forward
Project Daily Open / Previous Day High / Previous Day Low
EMA/SMA type and length
Show Asia session label
These settings allow the script to stay focused on the latest session structure while keeping historical clutter under control.
How to use it
A common way to use the script is:
Let the Asia session complete
Use the projected Asia high and low as current-day reference levels
Watch how price behaves around those levels into London
Use Daily Open, Previous Day High, and Previous Day Low as additional context
Optionally use the moving average as a simple trend filter
This script is best treated as a visual session framework, not a standalone decision engine.
Notes and limitations
This is a chart-structuring tool, not a strategy or a promise of performance.
It does not place trades or generate automatic alerts for entries.
It is intended to help with observation and session mapping.
Session behaviour can vary by market, symbol, and time zone settings, so users should confirm that their inputs match the market they trade.
Open-source note
This script is published so users can inspect the logic directly, understand how the session levels are built, and adapt the workflow for their own research. Trading View notes that open-source publications are governed by its script publishing rules and House Rules. Penunjuk

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Multi-Factor Return Attribution / Fundamental AnalysisHere's the updated post with ORCL woven in:
Multi-Factor Return Attribution (MFRA)
Every stock return is a mix of forces. Part of the move comes from the broad market lifting or dragging everything with it. Part comes from capital rotating into or out of the sector. Part comes from flows specific to the sub-industry. And whatever's left โ the piece none of those explain โ is the stock's own fundamental or idiosyncratic signal.
MFRA decomposes equity returns into exactly these four layers: Broad Market, Sector, Sub-Sector, and Idiosyncratic, using a rolling orthogonalized regression framework that runs directly on your chart.
The default configuration ships with **ORCL** (Oracle) as the stock, **SPY** as the market proxy, **XLK** as the sector ETF, and **IGV** (software sub-sector) as the sub-industry ETF โ but every symbol is configurable to any equity/ETF combination.
How It Works
The indicator takes four price feeds as input. Daily returns are computed for each, then transformed into orthogonal factors using a Gram-Schmidt-style subtraction chain โ the sector factor becomes XLK return minus SPY return, the sub-sector factor becomes IGV return minus XLK return. This ensures each layer captures only incremental information, with no double-counting between levels.
A rolling OLS regression (configurable window, default 21 days) solves a full 4ร4 normal equation system on every bar, estimating an intercept (alpha) and three slope coefficients (betas) against the orthogonalized factors. These betas represent the stock's current sensitivity to each layer of the return hierarchy. The residual โ total return minus the sum of all factor contributions โ isolates the idiosyncratic component: moves driven by earnings, guidance, analyst revisions, or anything else unique to the name.
The decomposition is exact. On every bar, the four attributed components sum precisely to the stock's total return. Nothing is lost, nothing is fabricated.
Reading It: ORCL as an Example
Oracle sits at an interesting intersection โ it's a mega-cap tech name with exposure to cloud infrastructure, enterprise software, and database, which means its returns get pulled by broad market risk (SPY), tech sector rotation (XLK), and software-specific flows (IGV) simultaneously. MFRA separates all of that.
When ORCL rallies on a day the entire market is up, the stacked histogram shows a large cyan (Broad Market) bar โ most of the move was just beta. But when Oracle moves on an AI infrastructure deal, a cloud revenue beat, or a Larry Ellison keynote and neither SPY nor XLK nor IGV moved proportionally, the magenta (Idiosyncratic) component dominates. That's the stock's own story, isolated from everything systematic.
If tech is rotating into software names specifically โ IGV outperforming XLK which is outperforming SPY โ you'll see the green (Sub-Sector) layer stacking up, telling you Oracle is riding a sub-industry wave, not generating alpha on its own.
The snapshot table in the top right gives you the exact numbers: how many percentage points of ORCL's recent return came from each source, the current betas, Rยฒ, and daily alpha in basis points.
What Each Component Tells You
- Broad Market (cyan) โ How much of the stock's move is just beta to the index. When this dominates, the stock is being carried by macro sentiment, not its own story.
- Sector Flows (orange) โ Capital rotating into or out of the sector beyond what the broad market explains. Large sector contributions during flat market days reveal pure sector rotation trades.
- Sub-Sector Flows (green) โ Thematic or sub-industry-specific moves beyond sector-level flow. For ORCL, this captures software/cloud momentum (IGV) that's distinct from broader tech (XLK).
- Fundamental / Idiosyncratic (magenta) โ The residual. This is the stock's own signal โ the return component that none of the systematic factors explain. Persistent idiosyncratic contribution suggests a name-specific catalyst is in play. Sudden spikes often align with earnings, news, or positioning shifts.
Four Chart Views
*Rolling Decomposition* โ Stacked histogram showing the N-day rolling sum of each component's contribution (in percentage points), with positive and negative values stacked independently from the zero line. A white line traces total return for reference.
*Cumulative Attribution* โ Same stacking logic, but cumulated from the start of the visible history. Shows how much of ORCL's total performance over the period came from each source โ useful for answering "was this a beta trade or an alpha trade?"
*Rolling Betas* โ Time series of the three regression coefficients. Tracks how ORCL's factor sensitivities evolve. A market beta rising above 1.0 means the name is becoming more aggressive than SPY; a sector beta collapsing toward zero means Oracle is decoupling from XLK.
*R-Squared* โ The model's explanatory power over time. High Rยฒ means ORCL is moving in lockstep with its systematic factors. Low Rยฒ means idiosyncratic forces dominate โ exactly when single-stock analysis matters most.
Practical Use Cases
Pre-earnings, check whether ORCL's recent run is broad-market-driven or idiosyncratic โ the answer changes how you size and hedge the position. During sector rotations, isolate whether Oracle is participating because of tech/software flows or its own fundamentals. After a large move, decompose it immediately: was it SPY, XLK, IGV, or Oracle itself? That distinction determines whether the move is likely to mean-revert or persist.
Configuration
All four symbols are configurable โ swap ORCL for any stock, change the sector/sub-sector ETFs to match. OLS window controls regression lookback (default 21 days). Rolling decomposition window controls the summation period for the histogram view (default 5 days). Snapshot table can be toggled on or off.
Methodology Note
The orthogonalization is a simplified Gram-Schmidt procedure applied to return differences rather than a full iterative projection. This is deliberate โ it produces clean, interpretable factor layers (market โ sector excess โ sub-sector excess) without the numerical overhead of a full QR decomposition, and the resulting attribution remains exact. The regression is solved via direct 4ร4 matrix inversion using cofactor expansion, with no external library dependencies. Penunjuk

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[Anwar] : BTC Trend Strategy V2 (Fixed + ADX Working)๐ Strategy Description
This strategy is a trend-following, pullback-based trading system designed for Bitcoin. It combines multiple indicatorsโEMA (trend), ADX (trend strength), ATR (volatility), and RSI (momentum)โto identify high-probability trade setups. Trades are taken only when the broader trend aligns across timeframes, and entries occur on controlled pullbacks rather than chasing price. Risk is managed using ATR-based stop losses and trailing exits, allowing the strategy to adapt dynamically to market volatility.
๐ Why This Works
The strategy works because it focuses on trading with the market, not against it:
Trend alignment (HTF + EMA) ensures trades follow the dominant market direction
ADX filter removes weak or sideways conditions, avoiding low-quality trades
Pullback entries improve timing and reduce buying/selling at extremes
Volatility filter (ATR) avoids dead markets and enhances movement capture
Trailing stops allow profits to run during strong Bitcoin trends
Together, these elements create a system that reduces noise, improves trade quality, and captures larger moves, which is essential in a volatile market like Bitcoin. Strategi

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Multi-Indicator DashboardTrend Dashboard Description
Trend Dashboard is a multi-indicator market analysis tool designed to combine several widely used technical signals into one clean on-chart panel. Instead of loading separate indicators for momentum, trend, volatility, and volume confirmation, this script brings them together into a compact dashboard that helps traders evaluate overall market conditions at a glance.
The goal of the indicator is to reduce chart clutter while still preserving the most useful information from a broader technical workflow. It allows traders to monitor multiple dimensions of price action in one place, making it easier to confirm setups, avoid conflicting signals, and build a faster read on trend quality.
The dashboard currently includes the following components:
MACD
Displays the MACD line and signal line, along with a bullish or bearish reading based on whether the MACD line is above or below the signal line. This helps identify momentum direction and possible trend continuation or weakening momentum.
RSI
Displays the current RSI value and classifies it as Bullish, Bearish, Overbought, or Oversold. Overbought and oversold levels are user-configurable, with common defaults of 70 and 30. This helps traders quickly identify momentum strength as well as potential exhaustion zones.
EMA Trend
Uses a fast EMA and slow EMA structure, along with current price position, to classify trend conditions more clearly than a simple crossover. The dashboard labels the trend as:
Strong Uptrend
Weak Uptrend
Weak Downtrend
Strong Downtrend
This gives traders a more nuanced understanding of whether price is aligned with trend structure or temporarily pulling back against it.
Stochastic
Displays smoothed %K and %D values and classifies the condition as Bullish, Bearish, Overbought, or Oversold. Overbought and oversold thresholds are configurable, with common defaults of 80 and 20. This helps highlight short-term momentum shifts and possible reversal zones.
ATR
Displays the current Average True Range and compares it against its recent average to determine whether volatility is relatively high or low. This gives context around market expansion and contraction, which can be useful for trade timing, stop placement, and breakout evaluation.
OBV
Displays On-Balance Volume alongside its moving average and classifies the current state as Accumulation or Distribution. This adds a volume-confirmation layer to the dashboard and helps traders assess whether buying or selling pressure is supporting the current market move.
Why Use This Indicator
Trend Dashboard is useful for traders who want a broader market read without stacking multiple panes and overlays across the chart. It is especially helpful for:
quickly checking alignment between momentum and trend
spotting overbought and oversold conditions
confirming whether volatility is expanding or contracting
seeing whether volume is supporting price action
reducing the need to manage several separate indicators
By combining these tools into one structured panel, the script can act as a pre-trade checklist or a general market condition monitor.
Customization
The script includes adjustable inputs for all major calculations, including:
MACD fast, slow, and signal lengths
RSI length, bullish threshold, overbought level, and oversold level
EMA fast and slow lengths
Stochastic length, smoothing values, overbought level, and oversold level
ATR length and ATR comparison lookback
OBV moving average length
dashboard table position
This allows the indicator to be adapted for different assets, timeframes, and trading styles.
Best Use Cases
This dashboard can be useful for:
trend traders looking for alignment across multiple signals
swing traders wanting a quick technical summary
intraday traders monitoring momentum, volatility, and volume confirmation
traders who want a more organized chart layout with fewer separate indicators
Notes
This script is intended as a decision-support tool, not a standalone trading system. Like all indicators, it works best when interpreted in market context and combined with price structure, support and resistance, and risk management.
If you want, I can also turn this into:
a polished TradingView public-library description
a shorter โAboutโ version
a feature list with bullet formatting for publication
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Larry Williams Valuation Index [tradeviZion]Stop guessing whether an asset is "cheap" or "expensive." Based on the legendary methodology developed by Larry Williams in 1990 (the WillVal Index), this upgraded indicator measures the true intrinsic valuation of an asset by comparing it against key macroeconomic correlations.
While price tells you what the market is paying right now, Valuation tells you what the asset is actually worth. This isn't just a standard WVI script. We have engineered it into a comprehensive macro-dashboard that evaluates the asset against three universal benchmarks (like the Dollar, Gold, and Treasuries) PLUS a dynamic, auto-detecting Sector ETF.
๐ Exclusive Features
1. Auto-Sector Relative Strength (The Game Changer)
By default, the script compares your current asset against 3 primary symbols (e.g., DXY, GC1!, ZB1!).
The 4th Asset: The script features a built-in "Sector Brain." It automatically reads the sector of the stock you are viewing (e.g., Technology, Financials, Healthcare) and pulls the data for the corresponding Sector ETF (XLK, XLF, XLV, etc.). This tells you instantly if Apple is undervalued compared to the broader Tech sector!
2. Macro-Locked Calculation (1D)
Valuation is a macro concept, not a 5-minute scalping tool. To protect you from intraday noise, the core mathematical engine is strictly locked to the Daily (1D) Timeframe. You can trade on the 1-minute or 1-hour chart, and the indicator will silently calculate the true daily valuation in the background.
3. Adaptive vs. Fixed Thresholds
Manual Levels: Use the classic Larry Williams fixed thresholds (e.g., Overvalued > 85, Undervalued < 15).
Auto Levels: Markets change. Turn on Auto Levels to let the script dynamically calculate the overbought/oversold thresholds based on recent price extremes, smoothed by a custom multiplier.
4. Multi-Security Consensus Alerts
Reduce false signals. The built-in alert system allows you to require a consensus. For example, you can set the alerts to trigger a "Buy" signal ONLY if at least 3 out of the 4 tracked securities are showing an "Undervalued" reading simultaneously.
5. Clean Visual Dashboard
A sleek, customizable on-chart table displays the exact valuation score (0-100 scale) and the current status (Over, Under, or Normal) for all four correlated assets. The indicator lines change color dynamically when entering extreme valuation zones.
โ๏ธ How the Math Works
The WillVal methodology doesn't just look at price. It takes the ratio of the current asset against a correlated security, applies a dual Exponential Moving Average (EMA) momentum oscillator to identify trends, and then normalizes the result on a 0-100 scale using a historical lookback period (default is 156 bars, representing roughly 3 years of data).
๐ก How to Trade It
Undervalued (Green Zone): When the index drops below the lower threshold (e.g., 15), the asset is historically cheap compared to its correlations. Look for bullish setups or accumulation zones.
Overvalued (Red Zone): When the index rises above the upper threshold (e.g., 85), the asset is historically expensive. This is a warning sign to tighten stop losses, take profits, or look for bearish distribution.
Note: Valuation indicates extreme conditions, but extreme conditions can persist. Always pair valuation readings with price action confirmation (like Order Blocks, VWAP, or trendline breaks) before executing a trade. Penunjuk

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Sessions + Prev + PDH/PDL + Killzones SuiteDescription
This indicator is designed to provide time-based and price-based market context by combining session ranges with commonly referenced prior levels into a single, unified framework.
The purpose of the script is contextual analysis, not signal generation.
What the script does
The script tracks and plots the following elements directly on the price chart:
โข High and Low ranges for multiple trading sessions (Asia, London, New York morning, and New York afternoon)
โข High and Low levels from the previous occurrence of each session
โข Prior Day High (PDH) and Prior Day Low (PDL)
โข Optional session โkillzoneโ boxes that visually mark active session time windows
All calculations are performed using time-based session boundaries and price extrema (high/low) within those windows.
Why these components are combined
Sessions, previous session levels, and prior day levels are frequently analyzed together by discretionary traders because they represent:
โข Where liquidity formed earlier in the day or previous day
โข Where price previously paused, expanded, or reversed
โข Natural reference points for intraday structure and range analysis
Instead of plotting these elements using multiple separate scripts, this indicator integrates them into one consistent framework so that all levels are calculated using the same timezone, session logic, and display rules.
This avoids mismatched session times, duplicate levels, or conflicting calculations that can occur when multiple scripts are used simultaneously.
How the script works (high-level)
โข Each session is defined using user-selectable session times and timezone
โข During a session, the script tracks the highest and lowest traded price
โข When a session ends, its final high and low are stored as the โprevious sessionโ levels
โข PDH and PDL are calculated using the completed trading day
โข Lines and labels are anchored to the bars where levels are formed, rather than extending indefinitely
โข Optional display filters allow users to show only the current trading day to reduce chart clutter
No forward-looking logic, prediction, alerts, or trade execution logic is included.
How to use it
This script is intended to be used as a visual reference tool to help traders:
โข Identify session boundaries and intraday ranges
โข Observe how price reacts near prior session highs and lows
โข Assess where price is trading relative to PDH and PDL
โข Maintain consistent session timing across different timezones
The script does not provide trade entries, exits, alerts, or performance claims.
Important notes
โข This indicator does not generate buy or sell signals
โข It does not predict future price movement
โข It is not a trading strategy
โข All decisions remain the responsibility of the user
Disclaimer
This script is provided for educational and informational purposes only.
It does not constitute financial advice. Trading involves risk, and users should apply appropriate risk management and personal judgment when using any technical tool. Penunjuk

NQ Swing Command Intraday NQ Swing Command โ Intraday (15m/30m/1h)
A structured intraday trading system built for the Nasdaq-100 Index (NQ), designed to capture clean swing moves using multi-timeframe confluence. This script aligns 15m execution with 30m confirmation and 1H directional bias, giving traders a clear framework for timing entries within the broader market structure.
The strategy focuses on identifying trend continuation and reversal zones, combining price action, momentum, and key levels to deliver high-probability setups. Whether you're trading pullbacks, breakouts, or intraday swings, this system helps filter noise and keep you trading in sync with market flow.
Built for consistency and discipline, NQ Swing Command is ideal for traders looking to:
*Follow structured, rule-based setups
*Improve entry timing across multiple timeframes
*Capture intraday swings with confidence
*Stay aligned with overall market direction
A clean, no-fluff approach to mastering intraday movement on NQ. Penunjuk

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Moon Boys BTC Production Cost Daily137
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Moon Boys BTC PRODUCTION COST DAILY
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Track Bitcoin's real-time production cost using comprehensive electricity consumption data and mining economics to identify macro support/resistance zones.
โโโ OVERVIEW โโโ
This indicator calculates Bitcoin's actual cost of production by combining Cambridge Bitcoin Electricity Consumption Index (CBECI) data with electricity pricing models across different mining eras. It reveals where miners are profitable or underwater, providing crucial macro-level support zones that have historically acted as psychological and economic floors.
Perfect for:
โข Identifying long-term accumulation zones
โข Understanding miner profitability and capitulation risk
โข Spotting macro support levels during bear markets
โข Gauging healthy vs. overheated price levels
โข Planning dollar-cost averaging strategies
โโโ KEY FEATURES โโโ
๐ COMPREHENSIVE HISTORICAL DATA
โโ 378 data points spanning 2011-2026
โโ Complete CBECI electricity consumption dataset
โโ Verified accuracy: all dates and values cross-checked
โโ Updates every ~14 days with new CBECI releases
โก ELECTRICITY COST MODELING
โโ Pre-June 2019: $0.05/kWh (Early mining era)
โโ Pre-April 2021: $0.04/kWh (China dominance period)
โโ Post-May 2021: $0.05/kWh (China exodus, Western migration)
โโ Post-April 2024: $0.05/kWh (Post-4th halving era)
โโ Fully customizable for scenario analysis
๐ฏ DUAL COST CURVES
โโ Red line: Pure electricity cost per BTC
โโ Purple line: Total production cost (electricity + operations)
โโ Green line: Miner price (spot + transaction fee revenue)
โโ Pink fill: Zones where miners are losing money
๐ AUTOMATIC HALVING ADJUSTMENTS
โโ Integrates all Bitcoin halvings (2012, 2016, 2020, 2024)
โโ Block reward automatically adjusts: 50 โ 25 โ 12.5 โ 6.25 โ 3.125
โโ Accurate per-day BTC production calculations
๐ฐ PROFIT MARGIN TRACKING
โโ Annual profit margin labels (optional)
โโ Shows miner profitability percentage
โโ Appears on chart at electricity cost level
โโ Calculated using 365-day moving average
โโโ HOW TO READ IT โโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ INDICATOR โ MEANING โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ ๐ข Green Line โ Miner Price (BTC price + fee revenue)โ
โ (above purple) โ โ Miners profitable, healthy market โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ ๐ข Green Line โ Price below production cost โ
โ (below purple) โ โ Miner capitulation zone โ
โ โ โ Strong historical buy signal โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ ๐ด Red Line โ Pure electricity cost per BTC โ
โ โ โ Absolute minimum mining cost โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ ๐ฃ Purple Line โ Total production cost โ
โ โ โ Break-even for miners (60% elec) โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ ๐ธ Pink Fill โ Below-cost territory โ
โ โ โ Miners selling at a loss โ
โ โ โ Historical accumulation zone โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโ TRADING APPLICATIONS โโโ
๐ป BEAR MARKET BOTTOMS
โ Price touching or breaking below production cost = high probability bottom
โ Extended periods below cost = miner capitulation
โ Historical bottoms: Nov 2011, Jan 2015, Dec 2018, Nov 2022
โ Strongest buy signal in macro Bitcoin investing
๐ BULL MARKET HEALTH CHECKS
โ Distance above production cost = market heat level
โ 100-200% above cost = healthy bull market
โ 500%+ above cost = euphoric/bubble territory
โ Use as take-profit reference points
๐ ACCUMULATION STRATEGY
โ DCA when price approaches production cost
โ Increase buy size when price drops below cost
โ Maximum allocation when 10-20% below cost
โ Layer entry as margin shows negative percentages
โ๏ธ SUPPORT/RESISTANCE ZONES
โ Production cost acts as macro support in downtrends
โ Often becomes resistance after prolonged bear markets
โ Price reclaiming cost = bullish structural shift
โ Failed reclaims = continued weakness
๐ HALVING CYCLE ANALYSIS
โ Cost doubles after each halving (supply cut)
โ Price typically consolidates near new cost basis
โ Historic pattern: break above cost = new bull cycle
โ Track 6-12 months post-halving for trend confirmation
โโโ SETTINGS GUIDE โโโ
โก ELECTRICITY COST ASSUMPTIONS (USD/kWh)
โโ Pre-June 2019 (0.05): Early mining era, hobby miners
โโ Pre-China Exodus 2021 (0.04): Cheap Chinese hydropower
โโ Post-May 2021 (0.05): Western migration, higher costs
โโ Post-April 2024 (0.05): Current era post-4th halving
๐ก Adjust these for "what if" scenarios or local costs
๐ฐ ELECTRICITY PERCENTAGE (Default: 60%)
โโ Electricity as % of total mining costs
โโ Remaining 40% = hardware, labor, rent, maintenance
โโ Lower % = higher total cost (more conservative)
โโ Typical range: 50-70%
๐จ VISUAL TOGGLES
โโ Plot BTC Miner Price: Show/hide green line
โ โโ Includes transaction fee revenue per BTC
โโ Plot Production Cost Curves: Show/hide red & purple lines
โโ Plot Annual Profit Margin Labels: Show/hide margin %
โโ Appears annually (Jan 1st) and on last bar
โโโ HOW IT WORKS โโโ
1. ELECTRICITY CONSUMPTION DATA
โข Cambridge Bitcoin Electricity Consumption Index (CBECI)
โข Actual network-wide energy usage in TWh (terawatt-hours)
โข Updated bi-weekly with real hash rate data
โข 378 historical data points (Aug 2011 - Jan 2026)
2. COST CALCULATION FORMULA
Electricity Cost per BTC =
(TWh per year / 365.25 days) ร
(10^9 to convert to kWh) /
(BTC mined per day) ร
(Electricity price per kWh)
Total Cost per BTC =
Electricity Cost / (Electricity % of total costs)
3. BTC MINED PER DAY
Blocks per day (144) ร Block reward
โข 2009-2012: 50 BTC/block = 7,200 BTC/day
โข 2012-2016: 25 BTC/block = 3,600 BTC/day
โข 2016-2020: 12.5 BTC/block = 1,800 BTC/day
โข 2020-2024: 6.25 BTC/block = 900 BTC/day
โข 2024+: 3.125 BTC/block = 450 BTC/day
4. MINER PRICE METRIC
Spot close price + (Transaction fees per day / BTC mined per day)
โข Currently simplified with fees = 0
โข Shows true revenue per BTC for miners
5. PROFIT MARGIN CALCULATION
((Miner Price / Total Cost) - 1) ร 100
โข Smoothed with 365-day SMA
โข Shows sustainable annual profitability
โโโ BEST PRACTICES โโโ
โ
DO:
โข Use on DAILY timeframe for accuracy (designed for daily data)
โข Combine with on-chain metrics (SOPR, MVRV, Puell Multiple)
โข Layer with traditional TA for entry/exit timing
โข Understand this is AVERAGE global cost (varies by miner)
โข Use as macro filter, not short-term trading signal
โข Check profit margins during capitulation events
โ DON'T:
โข Use as sole indicator for short-term trades
โข Ignore that efficient miners have much lower costs
โข Forget that cost is constantly rising (hash rate + difficulty)
โข Assume price can't go below cost (it can temporarily)
โข Trade based only on cost - liquidity events can wick lower
โข Expect instant reversals at cost levels
โโโ HISTORICAL PERFORMANCE โโโ
Major Bitcoin bottoms near/below production cost:
๐
November 2011
Price: ~$2 | Cost: ~$5
โ 60% below cost, -95% drawdown
โ Bottom signal โ
๐
January 2015
Price: ~$150 | Cost: ~$180
โ 17% below cost, -85% drawdown
โ Bottom signal โ
๐
December 2018
Price: ~$3,200 | Cost: ~$3,500
โ 9% below cost, -84% drawdown
โ Bottom signal โ
๐
November 2022
Price: ~$15,500 | Cost: ~$17,000
โ 9% below cost, -77% drawdown
โ Bottom signal โ
Pattern: When price trades below production cost, accumulation zone.
โโโ TECHNICAL NOTES โโโ
โข Built with Pine Script v5
โข Data source: Cambridge Centre for Alternative Finance (CBECI) Updated Quaterly by Request
โข All dates/values verified against official CSV dataset
โข Electricity price adjusts based on major mining regime shifts
โข Uses series variables for proper historical calculation
โข Forward-fills data between CBECI update periods
โข Accounts for all 4 halvings in BTC history
โโโ DATA PERIODS EXPLAINED โโโ
๐ญ PRE-JUNE 2019 ($0.05/kWh)
Early mining era, distributed hobby miners, average global cost
๐จ๐ณ JUNE 2019 - APRIL 2021 ($0.04/kWh)
China dominance period, cheap hydropower in Sichuan/Yunnan
๐ MAY 2021 - APRIL 2024 ($0.05/kWh)
China ban, Western migration, renewable energy transition
๐ฎ POST-APRIL 2024 ($0.05/kWh)
4th halving, institutional mining, current era
โโโ UNDERSTANDING MINING ECONOMICS โโโ
โก ELECTRICITY = 60% OF COST (Default)
โโ Largest variable expense for miners
โโ Directly tied to hash rate and difficulty
๐ง OTHER COSTS = 40%
โโ ASIC hardware (depreciation)
โโ Facility rent and cooling
โโ Labor and maintenance
โโ Internet and infrastructure
โโ Insurance and legal
๐ฐ REVENUE SOURCES
โโ Block subsidy (newly minted BTC)
โโ Transaction fees (variable, usually 2-10% of revenue)
๐ MINER BEHAVIOR
โข Profitable: Accumulate BTC, expand operations
โข Break-even: Hold BTC, maintain operations
โข Unprofitable: Forced selling, potential capitulation
โโโ ADVANCED USE CASES โโโ
๐ฌ SCENARIO ANALYSIS
โ Adjust electricity costs to model different regions
โ US miners: $0.05-0.07/kWh
โ Nordic miners: $0.02-0.04/kWh
โ Middle East: $0.01-0.03/kWh
๐ COMBINE WITH ON-CHAIN DATA
โ Miner Net Position Change (selling pressure)
โ Hash Ribbons (miner capitulation indicator)
โ Difficulty Ribbon (hash rate compression)
โ Puell Multiple (miner revenue extremes)
๐ฏ MULTI-TIMEFRAME CONFLUENCE
โ Weekly chart: macro trend and cost support
โ Daily chart: precise entry/exit near cost
โ 4H chart: short-term reactions at cost levels
๐ CORRELATION TRADING
โ Miner stocks (MARA, RIOT, CLSK) vs BTC cost
โ When BTC < cost, miner stocks typically -30-50%
โ Energy prices (oil, nat gas) affect mining costs
โโโ LIMITATIONS & CONSIDERATIONS โโโ
โ ๏ธ AVERAGE COST, NOT ACTUAL
โข Large miners with PPAs have costs as low as $0.02-0.03/kWh
โข Inefficient miners may have costs 2-3x the average
โข This shows network-wide average for reference
โ ๏ธ ELECTRICITY PRICE ASSUMPTIONS
โข Static periods vs. dynamic energy markets
โข Renewable energy % growing = lower average cost over time
โข Geographic distribution matters (Texas vs. Kazakhstan)
โ ๏ธ DOESN'T INCLUDE
โข ASIC efficiency improvements (more hash/watt)
โข Stranded energy and flare gas mining
โข Government subsidies or penalties
โข Seasonal variations (wet/dry seasons)
โ ๏ธ LAGGING INDICATOR
โข CBECI data updates every ~14 days
โข Historical data, not forward-looking
โข Cost always rises, but at variable rate
โโโ DISCLAIMER โโโ
This indicator visualizes Bitcoin's estimated global average production cost based on publicly available electricity consumption data and modeled pricing assumptions. It does NOT:
โข Guarantee future price movements or bottoms
โข Account for individual miner profitability variations
โข Include all operational costs (simplified to electricity %)
โข Predict miner capitulation or selling pressure
โข Constitute financial advice or buy/sell signals
Production cost is A REFERENCE POINT, not a hard floor. Price can and has traded below cost during extreme capitulation events. Market liquidity, macro conditions, and sentiment often override cost-basis logic in the short term.
Always conduct your own research and use proper risk management.
๐ EDUCATIONAL USE ONLY | NOT FINANCIAL ADVICE
โโโ RESOURCES โโโ
Cambridge Bitcoin Electricity Consumption Index (CBECI)
โ ccaf.io/cbnsi/cbeci
Bitcoin Mining Economics
โ insights.braiins.com/en/
Block Reward Halving Schedule
โ bitcoinblockhalf.com/
Difficulty & Hash Rate Charts
โ blockchain.com/charts/difficulty
Understanding ASIC Mining
โ academy.binance.com/en/articles/what-is-an-asic-miner
Mining Profitability Calculator
โ coinwarz.com/mining/bitcoin/calculator
On-Chain Miner Metrics
โ cryptoquant.com/
Energy & Mining Data
โ hashrateindex.com/
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Built for the Bitcoin community ๐
Because understanding the cost of production is fundamental analysis ๐
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Penunjuk

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