5-Year Returns Chart BTCvsSPXvsGOLDvsNVDACompare between thes 4 assets:
BTC
NVDA
SPX
GOLD
With an initial 1000$ investment in the last 5 years each return
Tìm kiếm tập lệnh với "btc期权交割时间"
Buy And Hold Performance Screener - [JTCAPITAL]Buy And Hold Performance Screener – is a script designed to track and display multi-asset “buy and hold” performance curves and performance statistics over defined timeframes for selected symbols. It doesn’t attempt to time entries or exits; rather, it shows what would happen if one simply bought the asset at the defined start date and held it.
The indicator works by calculating in the following steps:
Start Date Definition
The script begins by reading an input for the start date. This defines the bar from which the equity curves begin.
Symbol Definitions & Close Price Retrieval
The script allows the user to specify up to ten tickers. For each ticker it uses request.security() on the “1D” timeframe to retrieve the daily close price of that symbol.
Plot Enable Inputs
For each ticker there is an input boolean controlling whether the equity curve for that ticker should be plotted.
Asset Name Cleaning
The helper function clean_name(string asset) => … takes the asset string (e.g., “CRYPTO:SOLUSD”) and manipulates it (via string splitting and replacements) to derive a cleaned short name (e.g., “SOL”). This name is used for visuals (labels, table headers).
Equity Curve Calculation (“HODL”)
The helper function f_HODL(closez) defines a variable equity that assumes a starting equity of 1 unit at the start date and then multiplies by the ratio of each bar’s close to the prior bar’s close: i.e. daily compounding of returns.
Performance Metrics Calculation
The helper function f_performance(closez) calculates, for each symbol’s close series, the percentage change of the current close relative to its close 30 days ago, 90 days ago, 180 days ago, 1 year ago (365 days), 2 years ago (730 days) and 3 years ago (1095 days).
Equity Curve Plots
For each ticker, if the corresponding plot input is true, the script assigns a plotted variable equal to the equity curve value. Its then drawing each selected equity curve on the chart, each in a distinct color.
Table Construction
If the plottable input is true, the script constructs a table and populates it with rows and column corresponding to the assigned tickers and the set 6 timeframes used for display.
Buy and Sell Conditions:
Since this is strictly a “buy-and-hold” performance screener, there are no explicit buy or sell signals generated or plotted. The script assumes: buy at the defined start_date, hold continuously to present. There are no filters, no exit logic, no take-profit or stop-loss. The benefit of this approach is to provide a clean benchmark of how selected assets would have performed if one simply adopted a passive “buy & hold” approach from a given start date.
Features and Parameters:
start_date (input.time) : Defines the date from which performance and equity curves begin.
ticker1 … ticker10 (input.symbol) : User-selectable asset symbols to include in the screener.
plot1 … plot10 (input.bool) : Boolean flags to enable/disable plotting of each asset’s equity curve.
plottable (input.bool) : Flag to enable/disable drawing the performance table.
Colored plotting + Labels for identifying each asset curve on the chart.
Specifications:
Here is a detailed breakdown of every calculation/variable/function used in the script and what each part means:
start_date
This is defined via input.time(timestamp("1 Jan 2025"), title = "Start Date"). It allows the user to pick a specific calendar date from which the equity curves and performance calculations will start.
ticker1 … ticker10
These inputs allow the user to select up to ten different assets (symbols) to monitor. The script uses each of these to fetch daily close prices.
plot1 … plot10
Boolean inputs controlling which of the ten asset equity curves are plotted. If plotX is true, the equity curve for ticker X will be visible; otherwise it will be not plotted. This gives the user flexibility to include or exclude specific assets on the chart.
Returns the cleaned asset short name.
This provides friendly text labels like “BTC”, “ETH”, “SOL”, etc., instead of full symbol codes.
The choice of distinct colours for each asset helps differentiate curves visually when multiple assets are overlaid.
Colour definitions
Variables color1…color10 are explicitly defined via color.rgb(r,g,b) to give each asset a unique colour (e.g., red, orange, yellow, green, cyan, blue, purple, pink, etc.).
What are the benefits of combining these calculations?
By computing equity curves for multiple assets from the same start date and overlaying them, you can visualise comparative performance of different assets under a uniform “buy & hold” assumption.
The performance table adds multi-horizon returns (30 D, 90 D, 180 D, 1 Y, 2 Y, 3 Y) which helps the user see both short-term and longer-term performance without having to manually compute returns.
The use of daily close data via request.security(..., "1D") removes dependency on the chart’s timeframe, thereby standardising the comparison across assets.
The equity curve and table together provide both visual (curve) and numerical (table) summaries of performance, making it easier to spot trends, divergences, and cross-asset comparisons at a glance.
Because it uses compounding (equity := equity * (closez / closez )), the curves reflect the real growth of a 1-unit investment held over time, rather than only simple returns.
The labelling of curves and the color-coding make the multi-asset overlay easier to interpret.
Using a clean start date ensures that all curves begin at the same point (1 unit at start_date), making relative performance intuitive.
Because of this, the script is useful as a benchmarking tool: rather than trying to pick entries or exit points, you can simply compare “what if I had held these assets since Jan 1 2025” (or your chosen date), and see which assets out-/under-performed in that period. It helps an investor or trader evaluate the long-term benefits of passive vs. active management, or of allocation decisions.
Please note:
The script assumes continuous daily data and does not account for dividends, fees, slippage, or tax implications.
It does not attempt to optimise timing or provide trading signals.
Returns prior to the start date are ignored (equity only begins once time >= start_date).
For newly listed assets with fewer than 365 or 730 or 1095 days of history, the longer-horizon returns may return na or misleading values.
Because it uses request.security() without specifying lookahead, and on “1D” timeframe, it complies with standard usage but you should verify there is no look-ahead bias in your particular setup.
ENJOY!
Crypto Index Price# Crypto Index Price - Indicator Description
## 📊 What is this indicator?
**Crypto Index Price** is an indicator for creating your own cryptocurrency index based on an equal-weighted portfolio. It allows you to track the overall dynamics of the cryptocurrency market through a composite index of selected assets.
## 🎯 Key Features
- **Up to 20 assets in the index** — create an index from any trading pairs
- **Equal-weighted methodology** — each asset has the same weight in the index
- **Moving average** — optional trend filter for the index
- **Flexible visualization settings** — customizable colors and line thickness
## 📈 How to Use
The indicator is displayed in a separate pane below the chart and shows:
1. **Blue line** — crypto index value
2. **Orange line** (optional) — moving average of the index
### Trading Applications:
- **Identify overall market trend** — if the index is rising, most coins are in an uptrend
- **Divergences** — divergence between your asset and the index may signal local opportunities
- **Signal confirmation** — use the index to confirm trading decisions on individual coins
- **Market condition filter** — trade longs when index is above MA, shorts when below
## ⚙️ Settings
### Assets (Symbols)
- **Asset 1-10** — main cryptocurrencies (default: BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE, TRX)
- **Asset 11-20** — additional slots for index expansion
### Visual Parameters
- **Index line color** — main line color (default: blue)
- **Line width** — from 1 to 5 pixels
- **Show moving average** — enable/disable MA
- **MA period** — moving average calculation period (default: 20)
- **MA color** — moving average line color (default: orange)
## 💡 Recommendations
- For a top coins index, use 5-10 largest cryptocurrencies by market cap
- For an altcoin index, add medium and small coins from your sector
- Use MA to filter false signals and identify the global trend
- Compare individual asset behavior with the index to find anomalies
## ⚠️ Important
The indicator uses equal-weighted methodology — each coin contributes equally regardless of price or market cap. This differs from cap-weighted indices and may provide a different market perspective.
---
*This indicator is intended for analysis and is not trading advice. Always conduct your own analysis before making trading decisions.*
---
Fib OscillatorWhat is Fib Oscillator and How to Use it?
🔶 1. Conceptual Overview
The Fib Oscillator is a Fibonacci-based relative position oscillator.
Instead of measuring momentum (like RSI or MACD), it measures where price currently sits between the recent swing high and swing low, expressed as a percentage within the Fibonacci range.
In other words:
It answers: “Where is price right now within its most recent dynamic range?”
It visualizes retracement and extension zones numerically, providing continuous feedback between 0% and 100% (and beyond if extended).
🔶 2. What the Script Does
The indicator:
Automatically detects recent high and low levels using an adaptive lookback window, which depends on ATR volatility.
Calculates the current price’s position between those levels as a percentage (0–100).
Plots that percentage as an oscillator — showing visually whether price is near the top, middle, or bottom of its recent range.
Overlays Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) as reference zones.
Generates alerts when the oscillator crosses key Fib thresholds — which can signal retracement completion, breakout potential, or pullback exhaustion.
🔶 3. Technical Flow Breakdown
(a) Inputs
Input Description Default Notes
atrLength ATR period used for volatility estimation 14 Used to dynamically tune lookback sensitivity
minLookback Minimum lookback window (candles) 20 Ensures stability even in low volatility
maxLookback Maximum lookback window 100 Limits over-expansion during high volatility
isInverse Inverts chart orientation false Useful for inverse markets (e.g. shorts or inverse BTC view)
(b) Volatility-Adaptive Lookback
Instead of using a fixed lookback, it calculates:
lookback
=
SMA(ATR,10)
/
SMA(Close,10)
×
500
lookback=SMA(ATR,10)/SMA(Close,10)×500
Then it clamps this between minLookback and maxLookback.
This makes the oscillator:
More reactive during high volatility (shorter lookback)
More stable during calm markets (longer lookback)
Essentially, it self-adjusts to market rhythm — you don’t have to constantly tweak lookback manually.
(c) High-Low Reference Points
It takes the highest and lowest points within the dynamic lookback window.
If isInverse = true, it flips the candle logic (useful if viewing inverse instruments like stablecoin pairs or when analyzing bearish setups invertedly).
(d) Oscillator Core
The main oscillator line:
osc
=
(
close
−
low
)
(
high
−
low
)
×
100
osc=
(high−low)
(close−low)
×100
0% = Price is at the lookback low.
100% = Price is at the lookback high.
50% = Midpoint (balanced).
Between Fibonacci percentages (23.6%, 38.2%, 61.8%, etc.), the oscillator indicates retracement stages.
(e) Fibonacci Levels as Reference
It overlays horizontal reference lines at:
0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
These act as support/resistance bands in oscillator space.
You can read it similar to how traders use Fibonacci retracements on charts, but compressed into a single line oscillator.
(f) Alerts
The script includes built-in alert conditions for crossovers at each major Fibonacci level.
You can set TradingView alerts such as:
“Oscillator crossed above 61.8%” → possible bullish continuation or breakout.
“Oscillator crossed below 38.2%” → possible pullback or correction starting.
This allows automated monitoring of fib retracement completions without manually drawing fib levels.
🔶 4. How to Use It
🔸 Visual Interpretation
Oscillator Value Zone Market Context
0–23.6% Deep Retracement Potential exhaustion of a down-move / early reversal
23.6–38.2% Shallow retracement zone Possible continuation phase
38.2–50% Mid retracement Neutral or indecisive structure
50–61.8% Key pivot region Common trend resumption zone
61.8–78.6% Late retracement Often “last pullback” area
78.6–100% Near high range Possible overextension / profit-taking
>100% Range breakout New leg formation / expansion
🔸 Practical Application Steps
Load the indicator on your chart (set overlay = false, so it’s below the main price chart).
Observe oscillator position relative to fib bands:
Use it to determine retracement depth.
Combine with structure tools:
Trend lines, swing points, or HTF market structure.
Use crossovers for timing:
Crossing above 61.8% in an uptrend often confirms breakout continuation.
Crossing below 38.2% in a downtrend signals renewed downside momentum.
For range markets, oscillator swings between 23.6% and 78.6% can define accumulation/distribution boundaries.
🔶 5. When to Use It
During Retracements: To gauge how deep the pullback has gone.
During Range Markets: To identify relative overbought/oversold positions.
Before Breakouts: Crossovers of 61.8% or 78.6% often precede impulsive moves.
In Multi-Timeframe Contexts:
LTF (15M–1H): Detect intraday retracement exhaustion.
HTF (4H–1D): Confirm major range expansions or key reversal zones.
🔶 6. Ideal Companion Indicators
The Fib Oscillator works best when contextualized with structure, volatility, and trend bias indicators.
Below are optimal pairings:
Companion Indicator Purpose Integration Insight
Market Structure MTF Tool Identify active trend direction Use Fib Oscillator only in trend direction for cleaner signals
EMA Ribbon / Supertrend Trend confirmation Align oscillator crossovers with EMA bias
ATR Bands / Volatility Envelope Validate breakout strength If oscillator >78.6% & ATR rising → valid breakout
Volume Oscillator Confirm retracement strength Volume contraction + oscillator under 38.2% → potential reversal
HTF Fib Retracement Tool Combine LTF oscillator with HTF fib confluence Powerful multi-timeframe setups
RSI or Stochastic Measure momentum relative to position RSI divergence while oscillator near 78.6% → exhaustion clue
🔶 7. Understanding the Settings
Setting Function Practical Impact
ATR Period (14) Controls volatility sampling Higher = smoother lookback adaptation
Min Lookback (20) Smallest window allowed Lower = more reactive but noisier
Max Lookback (100) Largest window allowed Higher = smoother but slower to react
Inverse Candle Chart Flips oscillator vertically Useful when analyzing bearish or inverse scenarios (e.g. short-side fib mapping)
Recommended Configs:
For scalping/intraday: ATR 10–14, lookback 20–50
For swing/position trading: ATR 14–21, lookback 50–100
🔶 8. Example Trade Logic (Practical Use)
Scenario: Uptrend on 4H chart
Oscillator drops to below 38.2% → retracement zone
Price consolidates → oscillator stabilizes
Oscillator crosses above 50% → pullback ending
Entry: Long when oscillator crosses above 61.8%
Exit: Near 78.6–100% zone or upon divergence with RSI
For Short Bias (Inverse Setup):
Enable isInverse = true to visually flip the oscillator (so lows become highs).
Use the same thresholds inversely.
🔶 9. Strengths & Limitations
✅ Strengths
Dynamic, self-adapting to volatility
Quantifies Fib retracement as a continuous function
Compact oscillator view (no clutter on chart)
Works well across all timeframes
Compatible with both trending and ranging markets
⚠️ Limitations
Doesn’t define trend direction — must be used with structure filters
Can whipsaw during choppy consolidations
The “lookback auto-adjust” may lag in sudden volatility shifts
Shouldn’t be used standalone for entries without structural confluence
🔶 10. Summary
The “Fib Oscillator” is a dynamic Fibonacci-relative positioning tool that merges retracement theory with adaptive volatility logic.
It gives traders an intuitive, quantified view of where price sits within its recent fib range, allowing anticipation of pullbacks, reversals, or breakout momentum.
Think of it as a "Fibonacci RSI", but instead of momentum strength, it shows positional depth — the vibrational location of price within its natural swing cycle.
Relative Momentum Rotation [CHE] Relative Momentum Rotation — Ranks assets by multi-horizon momentum for guided rotational selection with regime overlay
Summary
This indicator evaluates a universe of assets using a blended momentum measure across three time horizons, then ranks them to highlight top performers for potential portfolio rotation. It incorporates a regime filter to contextualize signals, tinting the background to indicate favorable or unfavorable market conditions and labeling transitions for awareness. By focusing on relative strength within a selectable universe, it helps identify leaders without relying on absolute thresholds, reducing noise from isolated trends and promoting disciplined asset switching.
Motivation: Why this design?
Traders often struggle with momentum signals that perform unevenly across market phases, such as overreacting in volatile periods or lagging in steady uptrends, leading to suboptimal rotations in multi-asset portfolios. The core idea of relative momentum rotation addresses this by comparing assets head-to-head within a defined group, blending short- and long-term changes to capture sustained strength while a regime overlay adds a macro layer to avoid fighting broader trends. This setup prioritizes peer-relative outperformance over standalone measures, aiding consistent selection in rotational strategies.
What’s different vs. standard approaches?
- Reference baseline: Traditional rate-of-change indicators track absolute price shifts over a single window, which can generate whipsaws in sideways markets or miss cross-asset opportunities.
- Architecture differences:
- Blends three distinct horizons into one composite score for a fuller momentum picture, rather than isolating one period.
- Applies ranking across a customizable universe (e.g., crypto or tech stocks) to emphasize relatives, not absolutes.
- Integrates a simple regime check via moving average crossover on a reference symbol, gating selections without overcomplicating the core logic.
- Outputs a dynamic table for visual ranking, plus subtle visual cues like background tints, instead of cluttered plots.
- Practical effect: Charts show clearer hierarchy among assets, with regime tints providing at-a-glance context—top ranks stand out more reliably in bull regimes, helping traders focus rotations without constant recalibration.
How it works (technical)
The indicator starts by assembling a list of symbols from the selected universe, including only those marked as active to keep the group focused. For each symbol, it gathers change rates over three specified horizons on a higher timeframe, blends them using user-defined weights (automatically normalized if they do not sum to one), and computes a single composite score. Scores are then ranked to select the top performers up to a set number, forming a rotation candidate list.
To add context, a regime state is determined by comparing the reference symbol's price to its moving average on daily bars—above signals a positive environment, below a negative one, with an option to invert this logic. The current chart's symbol is checked against the top list for inclusion status. All higher-timeframe data pulls are set to avoid lookahead bias, though updates may shift slightly until bars close. Persistent variables track the table state and prior regime to handle redraws efficiently, ensuring the display rebuilds only when the selection count changes.
Parameter Guide
Universe — Switches between predefined crypto or US-tech symbol sets for ranking peers. Default: Crypto. Trade-offs/Tips: Crypto for volatile assets; US-Tech for equities—match to your portfolio to avoid mismatched volatility.
Include Symbol 1–12 — Toggles individual symbols in the universe on or off. Default: Varies (true for top 10, false for extras). Trade-offs/Tips: Start with defaults for a balanced group; disable laggards to sharpen focus, but keep at least 5–8 for robust ranking.
Scoring Timeframe — Sets the aggregation period for momentum changes (e.g., monthly bars). Default: Monthly. Trade-offs/Tips: Monthly for long-term rotation; weekly for faster signals—increases noise if too short.
Weight 12m / 6m / 3m — Adjusts emphasis on long/medium/short horizons in the blend. Default: 0.50 / 0.30 / 0.20. Trade-offs/Tips: Heavier long-term for stability in trends; balance to fit asset class—test sums near 1.0 to avoid auto-normalization surprises.
ROC over MA instead of Close — Uses smoothed averages for change rates to reduce chop. Default: False. Trade-offs/Tips: Enable in noisy markets for fewer false tops; adds slight lag, so monitor for delayed rotations.
Top N to hold — Limits selections to this many highest-ranked assets. Default: 10. Trade-offs/Tips: Lower for concentrated bets (higher risk/reward); higher for diversification—align with your position sizing.
Mark current symbol if in Top N — Highlights if the chart's asset ranks in the selection. Default: True. Trade-offs/Tips: Useful for self-scanning; disable in multi-chart setups to declutter.
Enable Regime Filter — Activates macro overlay using reference symbol. Default: True. Trade-offs/Tips: Core for trend-aware trading; disable for pure momentum plays, but risks counter-trend entries.
Regime Symbol — Chooses the benchmark for regime (e.g., broad index). Default: QQQ. Trade-offs/Tips: Broad market proxy like SPY for equities; swap for BTC in crypto to match universe.
SMA Length (D) — Sets the averaging window for regime comparison. Default: 100. Trade-offs/Tips: Longer for fewer flips (smoother regimes); shorter for quicker detection—default suits daily checks.
Invert (rare) — Flips the regime logic (price above average becomes negative). Default: False. Trade-offs/Tips: Only if your view inverts the benchmark; test thoroughly as it reverses all tints/labels.
Show Ranking Table — Displays the ranked list with scores and regime status. Default: True. Trade-offs/Tips: Essential for selection; position tweaks help on crowded charts.
Table X / Y — Places the table on the chart (e.g., top-right). Default: Right / Top. Trade-offs/Tips: Corner placement avoids price overlap; middle for central focus in reviews.
Dark Theme — Applies inverted colors for visibility. Default: True. Trade-offs/Tips: Matches most TradingView themes; toggle for light backgrounds without losing contrast.
Text Size — Scales table font for readability. Default: Normal. Trade-offs/Tips: Smaller for dense data; larger on big screens—impacts only last-bar render.
Background Tint by Regime — Colors the chart faintly green/red based on state. Default: True. Trade-offs/Tips: Subtle cue for immersion; disable if it distracts from price action.
Label on Regime Flip — Adds text markers at state changes. Default: True. Trade-offs/Tips: Aids journaling flips; space them by disabling in low-vol periods to cut clutter.
Reading & Interpretation
The ranking table lists top assets by position, symbol, percentage score (higher indicates stronger blended momentum), and regime status—green "ON" for favorable, red "OFF" for cautionary. Background shifts to a light teal in positive regimes (suggesting alignment for longs) or pale red in negative ones (hinting at reduced exposure). Flip labels appear as green "Regime ON" above bars or red "Regime OFF" below, marking transitions without ongoing noise. If the current symbol appears in the top rows with a solid score, it signals potential hold or entry priority within rotations.
Practical Workflows & Combinations
- Trend following: Scan the table weekly on monthly charts for top entrants; confirm with higher highs/lows in price structure before rotating in. Use regime tint as a veto—skip buys in red phases.
- Exits/Stops: Rotate out of bottom-half ranks monthly; tighten stops below recent lows during regime flips to protect against reversals. Pair with volatility filters like average true range for dynamic sizing.
- Multi-asset/Multi-TF: Defaults work across crypto/equities on daily+ timeframes; for intraday, shorten scoring to weekly but expect more interim noise. Scale universe size with portfolio count—e.g., top 5 for aggressive crypto rotations.
Behavior, Constraints & Performance
Signals update on bar close to confirm higher-timeframe data, but live bars may preview shifts from security calls, introducing minor repaint until finalized—mitigated by non-lookahead settings, though daily regime checks can lag by one session. Arrays handle up to 12 symbols efficiently, with loops capped at selection size; max bars back at 5000 supports historical depth without overload. Resource use stays low, but dense universes on very long charts may slow initial loads.
Known limits include sensitivity to universe composition (skewed groups amplify biases) and regime lag at sharp market turns, potentially delaying rotations by a period.
Sensible Defaults & Quick Tuning
Defaults assume a 10-asset crypto rotation on monthly scoring with balanced weights and QQQ regime—ideal for intermediate-term equity-like plays. For too-frequent table reshuffles, extend scoring timeframe or weight longer horizons more. If selections feel sluggish, shorten the 3-month weight or enable MA smoothing off. In high-vol environments, raise top N and SMA length for stability; for crypto bursts, drop to weekly scoring and invert regime if using a volatile proxy.
What this indicator is—and isn’t
This is a selection and visualization tool for momentum-based rotations, layering relative ranks and regime context onto charts to inform asset picks. It is not a standalone system—pair it with entry/exit rules, position sizing, and risk limits. Nor is it predictive; it reacts to past changes and may underperform in prolonged ranges or during universe gaps.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Where does it come from, specifically?
The principle of “composite momentum across multiple horizons” is common in TAA/rotation strategies. As a documented example: Keller/Butler use a composite 1/3/6/12-month momentum (“13612W”)—same idea, different windows/weights.
Robot Wealth
A practical vendor example: EPS Momentum calculates an RMR composite as a weighted mix of 12/6/3/1-month ranks (very close to “12/6/3”).
EPS Momentum
Related but not identical: StockCharts’ RRG measures the momentum rotation of relative strength—often mentioned in the same context, but it doesn’t have a fixed “12/6/3” composite.
chartschool.stockcharts.com
How is it typically computed?
ROC_12 + ROC_6 + ROC_3 (often scaled/weighted), then ranked vs. peers; the rotation periodically holds the top ranks in the portfolio. (Variants use different weights or additionally include 1-month—see the sources above.)
robotwealth.com
epsmomentum.com
Relative Valuation OscillatorRelative Valuation Oscillator (RVO) Description
The Valuation_OTC.pine script is a Relative Valuation Oscillator for TradingView that compares the current asset against a reference asset (like Bitcoin, S&P 500, or Gold) to determine if it's relatively overvalued or undervalued.
Key Features:
1. Multiple Calculation Methods:
Simple Ratio - Compares price ratio deviation from average
Percentage Difference - Direct percentage comparison between assets
Ratio Z-Score - Statistical measure (standard deviations from mean)
Rate of Change Comparison - Compares momentum/performance
Normalized Ratio - 0-100 scale centered at zero
2. Customizable Settings:
Reference asset selection (default: BTC/USDT)
Adjustable lookback period (10-500 bars)
Optional smoothing with configurable period
Overbought/oversold level thresholds (default: ±1.5)
3. Trading Signals:
Overvalued - Oscillator above overbought level (red zone)
Undervalued - Oscillator below oversold level (green zone)
Neutral - Between thresholds
Crossover alerts for key levels
Divergence detection (bullish/bearish)
4. Visual Components:
Color-coded oscillator line (green when positive, red when negative)
Optional signal line for additional smoothing
Background shading for valuation zones
Information table showing current metrics and status
Shape markers for crossovers and divergences
5. Alert Conditions:
Overvalued/undervalued alerts
Zero-line crossovers
Divergence signals
This indicator is useful for pairs trading, relative strength analysis, and identifying when an asset is trading at extremes relative to a benchmark asset.
Dot traderInterpret Signals: Green triangles indicate buy (e.g., if BTC holds $109k with bullish crossover); red triangles indicate sell (e.g., if it breaks $108k with bearish divergence).
Candle Colors: Green/bullish, red/bearish, orange/overbought (>70 RSI), blue/oversold (<30 RSI).
Alerts: Enable in TradingView for real-time notifications.
CHOCH + FVG Signals [30m Optimized]CHOCH + FVG Signals
🎯 What It Does:
This script automatically scans your chart for high-probability Smart Money Concepts (SMC) setups based on two key institutional trading principles:
Change of Character (CHOCH) – A shift in market structure signaling potential reversal
Fair Value Gap (FVG) – An imbalance zone where price moved too fast, often acting as support/resistance
When both conditions align, the script plots clear Buy (▲) and Sell (▼) signals directly on your chart — ideal for intraday trading on the 30-minute timeframe (but works on any timeframe).
✅ Key Features:
🔹 Visual Fair Value Gaps
Green shaded zones = Bullish FVGs (potential support)
Red shaded zones = Bearish FVGs (potential resistance)
Toggle on/off in settings
🔹 Smart CHOCH Detection
Detects breaks of recent swing highs/lows with proper context
Avoids false signals by confirming prior price structure
🔹 Clear Trade Signals
Green ▲ below bar = Buy signal (Bullish CHOCH + FVG confluence)
Red ▼ above bar = Sell signal (Bearish CHOCH + FVG confluence)
🔹 Customizable Filters
Option to require FVG for a signal (recommended for higher accuracy)
Adjust sensitivity via swing detection settings (default optimized for 30m)
🔹 Alert-Ready
Built-in alert conditions for instant notifications on TradingView mobile/desktop
⚙️ How to Use:
Apply to a 30-minute chart (e.g., EURUSD, Gold, NAS100, BTC)
Wait for at least 50–100 bars to load (so swing points appear)
Look for:
A green triangle (▲) → consider long entry near FVG support
A red triangle (▼) → consider short entry near FVG resistance
Confirm with price action: Wait for a strong candle close or rejection at the FVG zone
Use stop-loss below/above the FVG and target recent liquidity pools
💡 Pro Tip: Best used during high-volume sessions (e.g., London Open 7–10 AM UTC, NY Open 12:30–3:30 PM UTC).
🛠️ Settings (Inputs):
Show Fair Value Gaps
✅ Enabled
Visualize FVG zones
Max FVG History
100 bars
Prevent chart clutter
Require FVG for Signal?
✅ Enabled
Higher-quality setups (disable to test CHOCH-only)
⚠️ Important Notes:
This is a signal generator, not financial advice. Always manage risk.
Works best in trending or breaking markets — avoid during low-volatility ranges.
FVGs may get filled (tested) before price continues — patience improves results.
Backtest on historical data before live trading.
📣 Ideal For:
Retail traders learning Smart Money Concepts (SMC)
Price action traders seeking institutional-level confluence
Intraday scalpers & swing traders on 30m–1H timeframes
Risk-On / Risk-Off CompositeReal-time Risk-On / Risk-Off Composite from your four ratios:
SPY / TLT (equities vs long bonds)
HYG / LQD (high-yield vs IG credit)
HG / GOLD (copper vs gold)
BTC / GOLD (speculative vs defensive)
It:
normalizes each ratio with a z-score (so they’re comparable),
lets you weight them,
plots a composite line + histogram (up = risk-on, down = risk-off),
shows a small heat-table for each sub-signal,
and includes alert conditions for Risk-On / Risk-Off flips.
Puell Multiple Variants [OperationHeadLessChicken]Overview
This script contains three different, but related indicators to visualise Bitcoin miner revenue.
The classical Puell Multiple : historically, it has been good at signaling Bitcoin cycle tops and bottoms, but due to the diminishing rewards miners get after each halving, it is not clear how you determine overvalued and undervalued territories on it. Here is how the other two modified versions come into play:
Halving-Corrected Puell Multiple : The idea is to multiply the miner revenue after each halving with a correction factor, so overvalued levels are made comparable by a horizontal line across cycles. After experimentation, this correction factor turned out to be around 1.63. This brings cycle tops close to each other, but we lose the ability to see undervalued territories as a horizontal region. The third variant aims to fix this:
Miner Revenue Relative Strength Index (Miner Revenue RSI) : It uses RSI to map miner revenue into the 0-100 range, making it easy to visualise over/undervalued territories. With correct parameter settings, it eliminates the diminishing nature of the original Puell Multiple, and shows both over- and undervalued revenues correctly.
Example usage
The goal is to determine cycle tops and bottoms. I recommend using it on high timeframes, like monthly or weekly . Lower than that, you will see a lot of noise, but it could still be used. Here I use monthly as the example.
The classical Puell Multiple is included for reference. It is calculated as Miner Revenue divided by the 365-day Moving Average of the Miner Revenue . As you can see in the picture below, it has been good at signaling tops at 1,3,5,7.
The problems:
- I have to switch the Puell Multiple to a logarithmic scale
- Still, I cannot use a horizontal oversold territory
- 5 didn't touch the trendline, despite being a cycle top
- 9 touched the trendline despite not being a cycle top
Halving-Corrected Puell Multiple (yellow): Multiplies the Puell Multiple by 1.63 (a number determined via experimentation) after each halving. In the picture below, you can see how the Classical (white) and Corrected (yellow) Puell Multiples compare:
Advantages:
- Now you can set a constant overvalued level (12.49 in my case)
- 1,3,7 are signaled correctly as cycle tops
- 9 is correctly not signaled as a cycle top
Caveats:
- Now you don't have bottom signals anymore
- 5 is still not signaled as cycle top
Let's see if we can further improve this:
Miner Revenue RSI (blue):
On the monthly, you can see that an RSI period of 6, an overvalued threshold of 90, and an undervalued threshold of 35 have given historically pretty good signals.
Advantages:
- Uses two simple and clear horizontal levels for undervalued and overvalued levels
- Signaling 1,3,5,7 correctly as cycle tops
- Correctly does not signal 9 as a cycle top
- Signaling 4,6,8 correctly as cycle bottoms
Caveats:
- Misses two as a cycle bottom, although it was a long time ago when the Bitcoin market was much less mature
- In the past, gave some early overvalued signals
Usage
Using the example above, you can apply these indicators to any timeframe you like and tweak their parameters to obtain signals for overvalued/undervalued BTC prices
You can show or hide any of the three indicators individually
Set overvalued/undervalued thresholds for each => the background will highlight in green (undervalued) or red (overvalued)
Set special parameters for the given indicators: correction factor for the Corrected Puell and RSI period for Revenue RSI
Show or hide halving events on the indicator panel
All parameters and colours are adjustable
Gold–Bitcoin Correlation (Offset Model) by KManus88This indicator analyzes the correlation between Gold (XAU/USD) and Bitcoin (BTC/USD) using a time-offset model adjustable by the user.
The goal is to detect cyclical leads or lags between both assets, highlighting how capital flows into Gold may precede or follow movements in the crypto market.
Key Features:
Dynamic correlation calculation between Gold and Bitcoin.
Adjustable offset in days (default: 107) to fine-tune the temporal shift.
Automatic labels and on-chart visualization.
Compatible with multiple timeframes and logarithmic scales.
Interpretation:
Positive correlation suggests synchronized trends between both assets.
Negative correlation signals divergence or rotation of liquidity.
The time-offset parameter helps estimate when a shift in Gold could later reflect in Bitcoin.
Recommended use:
For macro-financial and global liquidity cycle analysis.
As a complementary tool in cross-asset momentum strategies.
© 2025 – Developed by KManus88 | Inspired by monetary correlation studies and global liquidity cycles.
This script is for educational purposes only and does not constitute financial advice.
Fair Value Lead-Lag Model [BackQuant]Fair Value Lead-Lag Model
A cross-asset model that estimates where price "should" be relative to a chosen reference series, then tracks the deviation as a normalized oscillator. It helps you answer two questions: 1) is the asset rich or cheap vs its driver, and 2) is the driver leading or lagging price over the next N bars.
Concept in one paragraph
Many assets co-move with a macro or sector driver. Think BTC vs DXY, gold vs real yields, a stock vs its sector ETF. This tool builds a rolling fair value of the charted asset from a reference series and shows how far price is above or below that fair value in standard deviation units. You can shift the reference forward or backward to test who leads whom, then use the deviation and its bands to structure mean-reversion or trend-following ideas.
What the model does
Reference mapping : Pulls a reference symbol at a chosen timeframe, with an optional lead or lag in bars to test causality.
Fair value engine : Converts the reference into a synthetic fair value of the chart using one of four methods:
Ratio : price/ref with a rolling average ratio. Good when the relationship is proportional.
Spread : price minus ref with a rolling average spread. Good when the relationship is additive.
Z-Score : normalizes both series, aligns on standardized units, then re-projects to price space. Good when scale drifts.
Beta-Adjusted : rolling regression style. Uses covariance and variance to compute beta, then builds a fair value = mean(price) + beta * (ref − mean(ref)).
Deviation and bands : Computes a z-scored deviation of price vs fair value and plots sigma bands (±1, ±2, ±3) around the fair value line on the chart.
Correlation context : Shows rolling correlation so you can judge if deviations are meaningful or just noise when co-movement is weak.
Visuals :
Fair value line on price chart with sigma envelopes.
Deviation as a column oscillator and optional line.
Threshold shading beyond user-set upper and lower levels.
Summary table with reference, deviation, status, correlation, and method.
Why this is useful
Mean reversion framework : When correlation is healthy and deviation stretches beyond your sigma threshold, probability favors reversion toward fair value. This is classic pairs logic adapted to a driver and a target.
Trend confirmation : If price rides the fair value line and deviation stays modest while correlation is positive, it supports trend persistence. Pullbacks to negative deviation in an uptrend can be buyable.
Lead-lag discovery : Shift the reference forward by +N bars. If correlation improves, the reference tends to lead. Shift backward for the reverse. Use the best setting for planning early entries or hedges.
Regime detection : Large persistent deviations with falling correlation hint at regime change. The relationship you relied on may be breaking down, so reduce confidence or switch methods.
How to use it step by step
Pick a sensible reference : Choose a macro, index, currency, or sector driver that logically explains the asset’s moves. Example: gold with DXY, a semiconductor stock with SOXX.
Test lead-lag : Nudge Lead/Lag Periods to small positive values like +1 to +5 to see if the reference leads. If correlation improves, keep that offset. If correlation worsens, try a small negative value or zero.
Select a method :
Start with Beta-Adjusted when the relationship is approximately linear with drift.
Use Ratio if the assets usually move in proportional terms.
Use Spread when they trade around a level difference.
Use Z-Score when scales wander or volatility regimes shift.
Tune windows :
Rolling Window controls how quickly fair value adapts. Shorter equals faster but noisier.
Normalization Period controls how deviations are standardized. Longer equals stabler sigma sizing.
Correlation Length controls how co-movement is measured. Keep it near the fair value window.
Trade the edges :
Mean reversion idea : Wait for deviation beyond your Upper or Lower Threshold with positive correlation. Fade back toward fair value. Exit at the fair value line or the next inner sigma band.
Trend idea : In an uptrend, buy pullbacks when deviation dips negative but correlation remains healthy. In a downtrend, sell bounces when deviation spikes positive.
Read the table : Deviation shows how many sigmas you are from fair value. Status tells you overvalued or undervalued. Correlation color hints confidence. Method tells you the projection style used.
Reading the display
Fair value line on price chart: the model’s estimate of where price should trade given the reference, updated each bar.
Sigma bands around fair value: a quick sense of residual volatility. Reversions often target inner bands first.
Deviation oscillator : above zero means rich vs fair value, below zero means cheap. Color bins intensify with distance.
Correlation line (optional): scale is folded to match thresholds. Higher values increase trust in deviations.
Parameter tips
Start with Rolling Window 20 to 30, Normalization Period 100, Correlation Length 50.
Upper and Lower Threshold at ±2.0 are classic. Tighten to ±1.5 for more signals or widen to ±2.5 to focus on outliers.
When correlation drifts below about 0.3, treat deviations with caution. Consider switching method or reference.
If the fair value line whipsaws, increase Rolling Window or move to Beta-Adjusted which tends to be smoother.
Playbook examples
Pairs-style reversion : Asset is +2.3 sigma rich vs reference, correlation 0.65, trend flat. Short the deviation back toward fair value. Cover near the fair value line or +1 sigma.
Pro-trend pullback : Uptrend with correlation 0.7. Deviation dips to −1.2 sigma while price sits near the −1 sigma band. Buy the dip, target the fair value line, trail if the line is rising.
Lead-lag timing : Reference leads by +3 bars with improved correlation. Use reference swings as early cues to anticipate deviation turns on the target.
Caveats
The model assumes a stable relationship over the chosen windows. Structural breaks, policy shocks, and index rebalances can invalidate recent history.
Correlation is descriptive, not causal. A strong correlation does not guarantee future convergence.
Do not force trades when the reference has low liquidity or mismatched hours. Use a reference timeframe that captures real overlap.
Bottom line
This tool turns a loose cross-asset intuition into a quantified, visual fair value map. It gives you a consistent way to find rich or cheap conditions, time mean-reversion toward a statistically grounded target, and confirm or fade trends when the driver agrees.
Luxy Adaptive MA Cloud - Trend Strength & Signal Tracker V2Luxy Adaptive MA Cloud - Professional Trend Strength & Signal Tracker
Next-generation moving average cloud indicator combining ultra-smooth gradient visualization with intelligent momentum detection. Built for traders who demand clarity, precision, and actionable insights.
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WHAT MAKES THIS INDICATOR SPECIAL?
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Unlike traditional MA indicators that show static lines, Luxy Adaptive MA Cloud creates a living, breathing visualization of market momentum. Here's what sets it apart:
Exponential Gradient Technology
This isn't just a simple fill between two lines. It's a professionally engineered gradient system with 26 precision layers using exponential density distribution. The result? An organic, cloud-like appearance where the center is dramatically darker (15% transparency - where crossovers and price action occur), while edges fade gracefully (75% transparency). Think of it as a visual "heat map" of trend strength.
Dynamic Momentum Intelligence
Most MA clouds only show structure (which MA is on top). This indicator shows momentum strength in real-time through four intelligent states:
- 🟢 Bright Green = Explosive bullish momentum (both MAs rising strongly)
- 🔵 Blue = Weakening bullish (structure intact, but momentum fading)
- 🟠 Orange = Caution zone (bearish structure forming, weak momentum)
- 🔴 Deep Red = Strong bearish momentum (both MAs falling)
The cloud literally tells you when trends are accelerating or losing steam.
Conditional Performance Architecture
Every calculation is optimized for speed. Disable a feature? It stops calculating entirely—not just hidden, but not computed . The 26-layer gradient only renders when enabled. Toggle signals off? Those crossover checks don't run. This makes it one of the most efficient cloud indicators available, even with its advanced visual system.
Zero Repaint Guarantee
All signals and momentum states are based on confirmed bar data only . What you see in historical data is exactly what you would have seen trading live. No lookahead bias. No repainting tricks. No signals that "magically" appear perfect in hindsight. If a signal shows in history, it would have triggered in real-time at that exact moment.
Educational by Design
Every single input includes comprehensive tooltips with:
- Clear explanations of what each parameter does
- Practical examples of when to use different settings
- Recommended configurations for scalping, day trading, and swing trading
- Real-world trading impact ("This affects entry timing" vs "This is visual only")
You're not just getting an indicator—you're learning how to use it effectively .
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THE GRADIENT CLOUD - TECHNICAL DETAILS
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Architecture:
26 precision layers for silk-smooth transitions
Exponential density curve - layers packed tightly near center (where crossovers happen), spread wider at edges
75%-15% transparency range - center is highly opaque (15%), edges fade gracefully (75%)
V-Gradient design - emphasizes the action zone between Fast and Medium MAs
The Four Momentum States:
🟢 GREEN - Strong Bullish
Fast MA above Medium MA
Both MAs rising with momentum > 0.02%
Action: Enter/hold LONG positions, strong uptrend confirmed
🔵 BLUE - Weak Bullish
Fast MA above Medium MA
Weak or flat momentum
Action: Caution - bullish structure but losing strength, consider trailing stops
🟠 ORANGE - Weak Bearish
Medium MA above Fast MA
Weak or flat momentum
Action: Warning - bearish structure developing, consider exits
🔴 RED - Strong Bearish
Medium MA above Fast MA
Both MAs falling with momentum < -0.02%
Action: Enter/hold SHORT positions, strong downtrend confirmed
Smooth Transitions: The momentum score is smoothed using an 8-bar EMA to eliminate noise and prevent whipsaws. You see the true trend , not every minor fluctuation.
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FLEXIBLE MOVING AVERAGE SYSTEM
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Three Customizable MAs:
Fast MA (default: EMA 10) - Reacts quickly to price changes, defines short-term momentum
Medium MA (default: EMA 20) - Balances responsiveness with stability, core trend reference
Slow MA (default: SMA 200, optional) - Long-term trend filter, major support/resistance
Six MA Types Available:
EMA - Exponential; faster response, ideal for momentum and day trading
SMA - Simple; smooth and stable, best for swing trading and trend following
WMA - Weighted; middle ground between EMA and SMA
VWMA - Volume-weighted; reflects market participation, useful for liquid markets
RMA - Wilder's smoothing; used in RSI/ADX, excellent for trend filters
HMA - Hull; extremely responsive with minimal lag, aggressive option
Recommended Settings by Trading Style:
Scalping (1m-5m):
Fast: EMA(5-8)
Medium: EMA(10-15)
Slow: Not needed or EMA(50)
Day Trading (5m-1h):
Fast: EMA(10-12)
Medium: EMA(20-21)
Slow: SMA(200) for bias
Swing Trading (4h-1D):
Fast: EMA(10-20)
Medium: EMA(34-50)
Slow: SMA(200)
Pro Tip: Start with Fast < Medium < Slow lengths. The gradient works best when there's clear separation between Fast and Medium MAs.
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CROSSOVER SIGNALS - CLEAN & RELIABLE
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Golden Cross ⬆ LONG Signal
Fast MA crosses above Medium MA
Classic bullish reversal or trend continuation signal
Most reliable when accompanied by GREEN cloud (strong momentum)
Death Cross ⬇ SHORT Signal
Fast MA crosses below Medium MA
Classic bearish reversal or trend continuation signal
Most reliable when accompanied by RED cloud (strong momentum)
Signal Intelligence:
Anti-spam filter - Minimum 5 bars between signals prevents noise
Clean labels - Placed precisely at crossover points
Alert-ready - Built-in ALERTS for automated trading systems
No repainting - Signals based on confirmed bars only
Signal Quality Assessment:
High-Quality Entry:
Golden Cross + GREEN cloud + Price above both MAs
= Strong bullish setup ✓
Low-Quality Entry (skip or wait):
Golden Cross + ORANGE cloud + Choppy price action
= Weak bullish setup, likely whipsaw ✗
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REAL-TIME INFO PANEL
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An at-a-glance dashboard showing:
Trend Strength Indicator:
Visual display of current momentum state
Color-coded header matching cloud color
Instant recognition of market bias
MA Distance Table:
Shows percentage distance of price from each enabled MA:
Green rows : Price ABOVE MA (bullish)
Red rows : Price BELOW MA (bearish)
Gray rows : Price AT MA (rare, decision point)
Distance Interpretation:
+2% to +5%: Healthy uptrend
+5% to +10%: Getting extended, caution
+10%+: Overextended, expect pullback
-2% to -5%: Testing support
-5% to -10%: Oversold zone
-10%+: Deep correction or downtrend
Customization:
4 corner positions
5 font sizes (Tiny to Huge)
Toggle visibility on/off
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HOW TO USE - PRACTICAL TRADING GUIDE
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STRATEGY 1: Trend Following
Identify trend : Wait for GREEN (bullish) or RED (bearish) cloud
Enter on signal : Golden Cross in GREEN cloud = LONG, Death Cross in RED cloud = SHORT
Hold position : While cloud maintains color
Exit signals :
• Cloud turns ORANGE/BLUE = momentum weakening, tighten stops
• Opposite crossover = close position
• Cloud turns opposite color = full reversal
STRATEGY 2: Pullback Entries
Confirm trend : GREEN cloud established (bullish bias)
Wait for pullback : Price touches or crosses below Fast MA
Enter when : Price rebounds back above Fast MA with cloud still GREEN
Stop loss : Below Medium MA or recent swing low
Target : Previous high or when cloud weakens
STRATEGY 3: Momentum Confirmation
Your setup triggers : (e.g., chart pattern, support/resistance)
Check cloud color :
• GREEN = proceed with LONG
• RED = proceed with SHORT
• BLUE/ORANGE = skip or reduce size
Use gradient as confluence : Not as primary signal, but as momentum filter
Risk Management Tips:
Never enter against the cloud color (don't LONG in RED cloud)
Reduce position size during BLUE/ORANGE (transition periods)
Place stops beyond Medium MA for swing trades
Use Slow MA (200) as final trend filter - don't SHORT above it in uptrends
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PERFORMANCE & OPTIMIZATION
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Tested On:
Crypto: BTC, ETH, major altcoins
Stocks: SPY, AAPL, TSLA, QQQ
Forex: EUR/USD, GBP/USD, USD/JPY
Indices: S&P 500, NASDAQ, DJI
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TRANSPARENCY & RELIABILITY
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Educational Focus:
Detailed tooltips on every input
Clear documentation of methodology
Practical examples in descriptions
Teaches you why , not just what
Open Logic:
Momentum calculation: (Fast slope + Medium slope) / 2
Smoothing: 8-bar EMA to reduce noise
Thresholds: ±0.02% for strong momentum classification
Everything is transparent and explainable
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COMPLETE FEATURE LIST
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Visual Components:
26-layer exponential gradient cloud
3 customizable moving average lines
Golden Cross / Death Cross labels
Real-time info panel with trend strength
MA distance table
Calculation Features:
6 MA types (EMA, SMA, WMA, VWMA, RMA, HMA)
Momentum-based cloud coloring
Smoothed trend strength scoring
Conditional performance optimization
Customization Options:
All MA lengths adjustable
All colors customizable (when gradient disabled)
Panel position (4 corners)
Font sizes (5 options)
Toggle any feature on/off
Signal Features:
Anti-spam filter (configurable gap)
Clean, non-overlapping labels
Built-in alert conditions
No repainting guarantee
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IMPORTANT DISCLAIMERS
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This indicator is for educational and informational purposes only
Not financial advice - always do your own research
Past performance does not guarantee future results
Use proper risk management - never risk more than you can afford to lose
Test on paper/demo accounts before using with real money
Combine with other analysis methods - no single indicator is perfect
Works best in trending markets; less effective in choppy/sideways conditions
Signals may perform differently in different timeframes and market conditions
The indicator uses historical data for MA calculations - allow sufficient lookback period
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CREDITS & TECHNICAL INFO
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Version: 2.0
Release: October 2025
Special Thanks:
TradingView community for feedback and testing
Pine Script documentation for technical reference
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SUPPORT & UPDATES
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Found a bug? Comment below with:
Ticker symbol
Timeframe
Screenshot if possible
Steps to reproduce
Feature requests? I'm always looking to improve! Share your ideas in the comments.
Questions? Check the tooltips first (hover over any input) - most answers are there. If still stuck, ask in comments.
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Happy Trading!
Remember: The best indicator is the one you understand and use consistently. Take time to learn how the cloud behaves in different market conditions. Practice on paper before going live. Trade smart, manage risk, and may the trends be with you! 🚀
Friday’s Close – Futures Weekend AnchorPurpose:
This indicator highlights the US futures weekend close price — the exact level where CME markets end trading on Friday at 4:00 PM CT / 5:00 PM ET.
It’s designed primarily for crypto traders who want to compare weekend market behavior to the traditional finance (TradFi) close.
Why it matters:
Crypto trades 24/7, but global liquidity and sentiment still pivot around the Friday futures close. During the weekend, crypto can “drift” relative to traditional markets — this line shows exactly where the week ended for Wall Street, giving you a clean reference point until futures reopen on Sunday evening.
Features
Precise Friday close capture (CME weekend close minute, not just daily bar)
Works on any ticker — especially useful for BTC, ETH, or other crypto assets
Adjustable for time zone (New York / Chicago / custom)
Option to select prior weeks with weekOffset
Draws a single clean line from Friday’s close forward — no clutter, no vertical stitches
Optional right-edge label with the close value and timestamp
Usage Tips
Keep the chart’s timezone in sync with your anchor (America/New_York = 5 PM ET, America/Chicago = 4 PM CT).
Use weekOffset = 1 to view last week’s Friday close.
Combine with volume, funding, or open interest indicators to see how weekend moves relate to the TradFi close.
Ideal for weekend analysis — shows whether crypto is trading rich or cheap vs. the Friday benchmark before futures reopen.
Recommended For
Crypto traders, analysts, and quant enthusiasts who monitor TradFi–crypto decoupling or weekend premium behavior.
Liquidity Index with Advanced Statistical NormalizationLiquidity Index with Advanced Statistical Normalization
An open-source TradingView indicator for analyzing global liquidity cycles using robust statistical methods
Overview
This Pine Script indicator combines multiple macroeconomic data sources to construct a composite liquidity index that tracks global financial conditions. It employs advanced statistical techniques typically found in quantitative finance research, adapted for real-time charting.
Key Features
📊 Multi-Source Data Integration
- Federal Reserve Components: Fed Funds Rate, Reverse Repo (RRP), Treasury General Account (TGA)
- PBOC Components: China M2 Money Stock adjusted by CNY/USD exchange rate
- Volatility Index: MOVE Index (bond market volatility)
🔬 Advanced Statistical Methods
1. Theil-Sen Estimator: Robust trend detection resistant to outliers
2. Triple Normalization:
- Z-score normalization
- MAD (Median Absolute Deviation) normalization
- Quantile normalization via inverse normal CDF
3. Multi-Timeframe Analysis: Short (8-bar) and long (34-bar) windows with blended composite
📈 Signal Processing
- Log-transformation for non-linear relationships
- Smoothing via customizable SMA
- Composite signal averaging across normalization methods
Why This Approach?
Traditional liquidity indicators often suffer from:
- Sensitivity to outliers in economic data
- Assumption of normal distributions
- Single-timeframe bias
This script addresses these issues by:
- Using median-based robust statistics (Theil-Sen, MAD)
- Applying multiple normalization techniques
- Blending short and long-term perspectives
Customization Options
short_length // Short window (default: 8)
long_length // Long window (default: 34)
show_short // Display short composite
show_long // Display long composite
show_blended // Display blended signal
smoothing_length // SMA smoothing period (default: 10)
How to Use
1. Liquidity Expansion (positive values): Risk-on environment, favorable for asset prices
2. Liquidity Contraction (negative values): Risk-off environment, potential market stress
3. Divergences: Compare indicator direction vs. price action for early warnings
Potential Improvements
Community members are encouraged to enhance:
- Additional data sources (ECB balance sheet, BOJ operations, etc.)
- Alternative normalization methods (robust scaling, rank transformation)
- Machine learning integration (LSTM forecasting, regime detection)
- Alert conditions for liquidity inflection points
- Volatility-adjusted weighting schemes
Technical Notes
- Uses request.security() for multi-symbol data fetching
- All calculations handle missing data via nz() functions
- Median-based statistics computed via array operations
- Custom inverse CDF approximation (no external libraries required)
Contributing
This is a foundation for liquidity analysis. Potential extensions:
- LLM Integration: Use language models to parse Fed/PBOC meeting minutes and adjust weights dynamically
- Sentiment Layer: Incorporate crypto funding rates or options skew
- Adaptive Parameters: Auto-tune window lengths based on market regime
- Cross-Asset Validation: Backtest signals against BTC, equities, bonds
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License: Open source - modify and redistribute freelyDisclaimer: For educational purposes only. Not financial advice.
High Volume Arrow Signals (Ajustável)The High Volume Arrow Signals (Adjustable) indicator is a professional technical analysis tool designed to clearly pinpoint moments when trading volume significantly exceeds its recent average, signaling potential institutional pressure, strong conviction, or market exhaustion.
Its primary function is to overlay confirmation signals directly onto the price bars without altering the original candle colors.
Strategic Application
This indicator is most effective when used as a confluence tool to confirm moves initiated by price action or other indicators:
Breakout Confirmation: An arrow plotted during a price range breakout suggests the move has genuine volume conviction.
Reversal Identification: A Buy arrow appearing at a key support level (or a Sell arrow at resistance) indicates strong volume rejection and a potential turning point.
The adjustable multiplier ensures users can fine-tune the indicator to the specific volatility and volume characteristics of assets like BTC and ETH across different timeframes.
Jensen Alpha RS🧠 Jensen Alpha RS (J-Alpha RS)
Jensen Alpha RS is a quantitative performance evaluation tool designed to compare multiple assets against a benchmark using Jensen’s Alpha — a classic risk-adjusted return metric from modern portfolio theory.
It helps identify which assets have outperformed their benchmark on a risk-adjusted basis and ranks them in real time, with optional gating and visual tools. 📊
✨ Key Features
• 🧩 Multi-Asset Comparison: Evaluate up to four assets simultaneously.
• 🔀 Adaptive Benchmarking: TOTALES mode uses CRYPTOCAP:TOTALES (total crypto market cap ex-stablecoins). Dynamic mode automatically selects the strongest benchmark among BTC, ETH, and TOTALES based on rolling momentum.
• 📐 Jensen’s Alpha Calculation: Uses rolling covariance, variance, and beta to estimate α, showing how much each asset outperformed its benchmark.
• 📈 Z-Score & Consistency Metrics: Z-Score highlights statistical deviations in alpha; Consistency % shows how often α has been positive over a chosen window.
• 🚦 Trend & Zero Gates: Optional filters that require assets to be above EMA (trend) and/or have α > 0 for confirmation.
• 🏆 Leaders Board Table: Displays α, Z, Rank, Consistency %, and Gate ✓/✗ for all assets in a clear visual layout.
• 🔔 Dynamic Alerts: Get notified whenever the top alpha leader changes on confirmed (non-repainting) data.
• 🎨 Visual Enhancements: Smooth α with an SMA or color bars by the current top-performing asset.
🧭 Typical Use Cases
• 🔄 Portfolio Rotation & Relative Strength: Identify which assets consistently outperform their benchmark to optimize capital allocation.
• 🧮 Alpha Persistence Analysis: Gauge whether a trend’s performance advantage is statistically sustainable.
• 🌐 Market Regime Insight: Observe how asset leadership rotates as benchmarks shift across market cycles.
⚙️ Inputs Overview
• 📝 Assets (1–4): Select up to four tickers for evaluation.
• 🧭 Benchmark Mode: Choose between static TOTALES or Dynamic auto-selection.
• 📏 Alpha Settings: Adjustable lookback, smoothing, and consistency windows.
• 🚦 Gates: Optional trend and alpha filters to refine results.
• 🖥️ Display: Enable/disable table and customize colors.
• 🔔 Alerts: Toggle notifications on leadership changes.
🔎 Formula Basis
Jensen’s Alpha (α) is estimated as:
α = E − β × E
where β = Cov(Ra, Rb) / Var(Rb), and Ra/Rb represent asset and benchmark returns, respectively.
A positive α indicates outperformance relative to the risk-adjusted benchmark expectation. ✅
⚠️ Disclaimer
This script is for educational and analytical purposes only.
It is NOT a signal. 🚫📉
It does not constitute financial advice, trading signals, or investment recommendations. 💬
The author is not responsible for any financial losses or trading decisions made based on this indicator. 🙏
Always perform your own analysis and use proper risk management. 🛡️
QUANTUM MOMENTUMOverview
Quantum Momentum is a sophisticated technical analysis tool designed to help traders identify relative strength between assets through advanced momentum comparison. This cyberpunk-themed indicator visualizes momentum dynamics between your current trading symbol and any comparison asset of your choice, making it ideal for pairs trading, crypto correlation analysis, and multi-asset portfolio management.
Key Features
📊 Multi-Asset Momentum Comparison
Dual Symbol Analysis: Compare momentum between your chart symbol and any other tradable asset
Real-Time Tracking: Monitor relative momentum strength as market conditions evolve
Difference Visualization: Clear histogram display showing which asset has stronger momentum
🎯 Multiple Momentum Calculation Methods
Choose from four different momentum calculation types:
ROC (Rate of Change): Traditional percentage-based momentum measurement
RSI (Relative Strength Index): Oscillator-based momentum from 0-100 range
Percent Change: Simple percentage change over the lookback period
Raw Change: Absolute price change in native currency units
📈 Advanced Trend Filtering System
Enable optional trend filters to align momentum signals with prevailing market direction:
SMA (Simple Moving Average): Classic trend identification
EMA (Exponential Moving Average): Responsive trend detection
Price Action: Identifies trends through higher highs/lows or lower highs/lows patterns
ADX (Average Directional Index): Measures trend strength with customizable threshold
🎨 Futuristic Cyberpunk Design
Neon Color Scheme: Eye-catching cyan, magenta, and matrix green color palette
Glowing Visual Effects: Enhanced visibility with luminescent plot lines
Dynamic Background Shading: Subtle trend state visualization
Real-Time Data Table: Sleek information panel displaying current momentum values and trend status
How It Works
The indicator calculates momentum for both your current chart symbol and a comparison symbol (default: BTC/USDT) using your selected method and lookback period. The difference between these momentum values reveals which asset is exhibiting stronger momentum at any given time.
Positive Difference (Green): Your chart symbol has stronger momentum than the comparison asset
Negative Difference (Pink/Red): The comparison asset has stronger momentum than your chart symbol
When the trend filter is enabled, the indicator will only display signals that align with the detected market trend, helping filter out counter-trend noise.
Settings Guide
Symbol Settings
Compare Symbol: Choose any tradable asset to compare against (e.g., major indices, cryptocurrencies, forex pairs)
Momentum Settings
Momentum Length: Lookback period for momentum calculations (default: 14 bars)
Momentum Type: Select your preferred momentum calculation method
Display Options
Toggle visibility of current symbol momentum line
Toggle visibility of comparison symbol momentum line
Toggle visibility of momentum difference histogram
Optional zero line reference
Trend Filter Settings
Use Trend Filter: Enable/disable trend-based signal filtering
Trend Method: Choose from SMA, EMA, Price Action, or ADX
Trend Length: Period for trend calculations (default: 50)
ADX Threshold: Minimum ADX value to confirm trend strength (default: 25)
Best Use Cases
✅ Pairs Trading: Identify divergences in momentum between correlated assets
✅ Crypto Market Analysis: Compare altcoin momentum against Bitcoin or Ethereum
✅ Stock Market Rotation: Track sector or index relative strength
✅ Forex Strength Analysis: Monitor currency pair momentum relationships
✅ Multi-Timeframe Confirmation: Use alongside other indicators for confluence
✅ Mean Reversion Strategies: Spot extreme momentum divergences for potential reversals
Visual Indicators
⚡ Cyan Line: Your chart symbol's momentum
⚡ Magenta Line: Comparison symbol's momentum
📊 Green/Pink Histogram: Momentum difference (positive = green, negative = pink)
▲ Green Triangle: Bullish trend detected (when filter enabled)
▼ Red Triangle: Bearish trend detected (when filter enabled)
◈ Yellow Diamond: Neutral/sideways trend (when filter enabled)
Pro Tips
💡 Look for crossovers between the momentum lines as potential trade signals
💡 Combine with volume analysis for stronger confirmation
💡 Use momentum divergence (price making new highs/lows while momentum doesn't) for reversal signals
💡 Enable trend filter during ranging markets to reduce false signals
💡 Experiment with different momentum types to find what works best for your trading style
Technical Requirements
TradingView Pine Script Version: v6
Chart Type: Works on all chart types
Indicator Placement: Separate pane (overlay=false)
Data Requirements: Needs access to comparison symbol data
Fury by Tetrad Fury by Tetrad
What it is:
A rules-based Bollinger+RSI strategy that fades extremes: it looks for price stretching beyond Bollinger Bands while RSI confirms exhaustion, enters countertrend, then exits at predefined profit multipliers or optional stoploss. “Ultra Glow” visuals are purely cosmetic.
How it works — logic at a glance
Framework: Classic Bollinger Bands (SMA basis; configurable length & multiplier) + RSI (configurable length).
Long entries:
Price closes below the lower band and RSI < Long RSI threshold (default 28.3) → open LONG (subject to your “Market Direction” setting).
Short entries:
Price closes above the upper band and RSI > Short RSI threshold (default 88.4) → open SHORT.
Profit exits (price targets):
Uses simple multipliers of the strategy’s average entry price:
Long exit = `entry × Long Exit Multiplier` (default 1.14).
Short exit = `entry × Short Exit Multiplier` (default 0.915).
Risk controls:
Optional pricebased stoploss (disabled by default) via:
Long stop = `entry × Long Stop Factor` (default 0.73).
Short stop = `entry × Short Stop Factor` (default 1.05).
Directional filter:
“Market Direction” input lets you constrain entries to Market Neutral, Long Only, or Short Only.
Visuals:
“Ultra Glow” draws thin layered bands around upper/basis/lower; these do not affect signals.
> Note: Inputs exist for a timebased stop tracker in code, but this version exits via targets and (optional) price stop only.
Why it’s different / original
Explicit extreme + momentum pairing: Entries require simultaneous band breach and RSI exhaustion, aiming to avoid entries on gardenvariety volatility pokes.
Deterministic exits: Multiplier-based targets keep results auditable and reproducible across datasets and assets.
Minimal, unobtrusive visuals: Thin, layered glow preserves chart readability while communicating regime around the Bollinger structure.
Inputs you can tune
Bollinger: Length (default 205), Multiplier (default 2.2).
RSI: Length (default 23), Long/Short thresholds (28.3 / 88.4).
Targets: Long Exit Mult (1.14), Short Exit Mult (0.915).
Stops (optional): Enable/disable; Long/Short Stop Factors (0.73 / 1.05).
Market Direction: Market Neutral / Long Only / Short Only.
Visuals: Ultra Glow on/off, light bar tint, trade labels on/off.
How to use it
1. Timeframe & assets: Works on any symbol/timeframe; start with liquid majors and 60m–1D to establish baseline behavior, then adapt.
2. Calibrate thresholds:
Narrow/meanreverting markets often tolerate tighter RSI thresholds.
Fast/volatile markets may need wider RSI thresholds and stronger stop factors.
3. Pick realistic targets: The default multipliers are illustrative; tune them to reflect typical mean reversion distance for your instrument/timeframe (e.g., ATRinformed profiling).
4. Risk: If enabling stops, size positions so risk per trade ≤ 1–2% of equity (max 5–10% is a commonly cited upper bound).
5. Mode: Use Long Only or Short Only when your discretionary bias or higher timeframe model favors one side; otherwise Market Neutral.
Recommended publication properties (for backtests that don’t mislead)
When you publish, set your strategy’s Properties to realistic values and keep them consistent with this description:
Initial capital: 10,000 (typical retail baseline).
Commission: ≥ 0.05% (adjust for your venue).
Slippage: ≥ 2–3 ticks (or a conservative pertrade value).
Position sizing: Avoid risking > 5–10% equity per trade; fixedfractional sizing ≤ 10% or fixedcash sizing is recommended.
Dataset / sample size: Prefer symbols/timeframes yielding 100+ trades over the tested period for statistical relevance. If you deviate, say why.
> If you choose different defaults (e.g., capital, commission, slippage, sizing), explain and justify them here, and use the same settings in your publication.
Interpreting results & limitations
This is a countertrend approach; it can struggle in strong trends where band breaches compound.
Parameter sensitivity is real: thresholds and multipliers materially change trade frequency and expectancy.
No predictive claims: Past performance is not indicative of future results. The future is unknowable; treat outputs as decision support, not guarantees.
Suggested validation workflow
Try different assets. (TSLA, AAPL, BTC, SOL, XRP)
Run a walkforward across multiple years and market regimes.
Test several timeframes and multiple instruments. (30m Suggested)
Compare different commission/slippage assumptions.
Inspect distribution of returns, max drawdown, win/loss expectancy, and exposure.
Confirm behavior during trend vs. range segments.
Alerts & automation
This release focuses on chart execution and visualization. If you plan to automate, create alerts at your entry/exit conditions and ensure your broker/venue fills reflect your slippage/fees assumptions.
Disclaimer
This script is provided for educational and research purposes. It is not investment advice. Trading involves risk, including the possible loss of principal. © Tetrad Protocol.
Order Flow RSI - Price / CVD / OIOrder Flow RSI blends three powerful market perspectives — Price , Cumulative Volume Delta (CVD) , and Open Interest (OI) — into one unified RSI-style oscillator.
It reveals momentum and imbalance across these data streams and highlights situations where participation, liquidity, and positioning disagree — moments that often precede reversals.
What it does
The indicator converts:
Price → RSI (classic momentum),
CVD → RSI (buy/sell pressure balance),
OI → RSI (position expansion/contraction)
…then plots all three RSIs together on the same 0–100 scale.
A fourth Consensus RSI (average of any two or all three) can optionally be shown to simplify the view.
Core logic
CVD engine – based on TradingView’s native volume-delta request.
Modes: Continuous (default, smooth line), Anchored (resets each session), Rolling window.
Open Interest – pulled automatically from the symbol’s “_OI” feed; aligns to chart timeframe for real-time flow.
RSI calculation – standard RSI applied to each data stream, optionally smoothed (SMA / EMA / RMA / WMA / VWMA).
Signals – optional background highlights when:
All three RSIs are overbought (red) or oversold (green), or
Any pair show opposite extremes (e.g., price overbought + OI oversold).
Consensus RSI – arithmetic mean of the selected RSIs, summarizing overall market tone.
Inputs overview
CVD settings: anchor period, lower-TF delta, mode, rolling length
RSI lengths: separate for price, CVD, OI
Smoothing: type + period applied to all RSIs at once
Consensus: choose which RSIs to average
Signals: enable/disable each combination; optional alerts
Levels: adjustable OB/MID/OS (default 70 / 50 / 30)
Visuals: fill between active RSIs, background highlights, level lines, colors in Style tab
How to read it
All 3 overbought (red): broad exhaustion → possible correction
All 3 oversold (green): broad depletion → possible bounce
Opposite pairs: divergence between price and participation
Price↑ but OI↓ (red) → weak rally, fading participation
Price↓ but CVD↑ (green) → hidden accumulation
Combine with structure and volume profile for confirmation.
Notes
Works best on assets with full CVD + OI data (futures, BTC, etc.).
Use Continuous CVD for smooth RSI, Anchored for session analysis.
Smoothing 2–5 EMA is a good starting point to reduce noise.
All styling (colors, line types, thickness) is adjustable in the Style tab.
Limitations & caveats
CVD requires accurate tick/volume/delta data from your data feed. Performance may differ across instruments.
OI availability varies by exchange / symbol. Where OI is absent, pairwise OI signals are not evaluated.
This indicator is a tool — it generates signals of interest, not guaranteed profitable trades. Backtest and combine with your risk rules.
Smoothing introduces lag; longer smoothing reduces noise but delays signals.
Order Flow RSI bridges traditional momentum analysis and order-flow context — giving a multi-dimensional view of when markets are truly stretched or quietly reloading.
Sometimes it works, sometimes it doesn't.
ALMASTO – Pro Trend & Momentum (v1.1)ALMASTO — Pro Trend & Momentum Strategy
Description:
This strategy is designed for precision trading in both Forex (FX) and Crypto markets.
It combines multi-timeframe trend confirmation (EMA200), momentum filters (RSI, MACD, ADX), and ATR-based dynamic risk management.
ALMASTO — Pro Trend & Momentum Strategy automatically manages take-profit levels, stop-loss, and breakeven adjustments once TP1 is reached — providing a structured and emotion-free trading approach.
Optimal Use
Works best on lower timeframes (5m–15m) with strong liquidity sessions.
Optimized for pairs like EURUSD, XAUUSD, and BTCUSDT.
Built for trend-following setups and momentum reversals with high volatility confirmation.
Recommended Settings
🔹 Forex – 5m
EMA Fast = 34, EMA Slow = 200, HTF = 1H
RSI (14): Long ≥ 55 / Short ≤ 45
MACD (8 / 21 / 5), ADX Len 10 / Min 27
ATR Len 7, Stop Loss = ATR × 2.1
TP1 = 1.1 RR, TP2 = 2.3 RR
Session = 07:00–11:00 & 12:30–16:00 (Exchange Time)
Risk = 0.8% per trade
🔹 Forex – 15m
EMA Fast = 50, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 53 / Short ≤ 47
MACD (12 / 26 / 9), ADX Min 24
ATR Len 10, SL = ATR × 1.9
TP1 = 1.2 RR, TP2 = 2.6 RR
Risk = 1.0% per trade
🔹 Crypto – 5m (BTC/USDT)
EMA Fast = 34, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 56 / Short ≤ 44
MACD (8 / 21 / 5), ADX Min 30
ATR Len 7, SL = ATR × 2.2
TP1 = 1.0 RR, TP2 = 2.5 RR
Session = 00:00–06:00 & 12:00–22:00 (UTC)
Risk = 0.5% per trade
Core Features
✅ Auto breakeven after TP1
✅ Dual take-profit system (1:1 & 1:2 RR)
✅ ATR-based stop & trailing logic
✅ Filters for session time, volume, and volatility
✅ Candle-body vs ATR size filter to avoid noise
✅ Optional cooldown between trades
Important Notes
Use bar close confirmation only (barstate.isconfirmed) to avoid repainting on lower timeframes.
Adjust commission (0.01–0.03%) and slippage (1–2 ticks) in Strategy Tester for realistic results.
Avoid low-liquidity hours (after 21:00 UTC for FX / after midnight for crypto).
Backtest using realistic broker data (e.g., BlackBull Markets / Bybit / Binance Futures).
Best results occur during London & New York sessions with moderate volatility.
⚠️ Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice.
Use proper risk management and test thoroughly before using on live accounts.
Developed by KING FX Labs
Built and optimized by Yousef Almasto — combining advanced price-action logic, multi-timeframe EMA structure, and volatility-adaptive ATR management.
Tested across Forex, Gold, and Crypto markets to ensure consistent performance and minimal drawdown.
📈 “Precision Trading. Zero Emotion. Pure Momentum.”
Overleverage Short Screener Alert Overleverage Short Screener Alert Guide (inspired by a posting "an on-chain trader nicknamed "Calm Order King" has reportedly made over $10 million in porfit this month - mainly by shorting BTC and SOL at precise reversal points", this script tries to guess his work.
🎯 Purpose of the Script
The script aims to identify potential **shorting opportunities** in derivatives markets (Perpetual Futures).
It looks for a setup often associated with a "long squeeze" or "blow-off top" by checking three criteria simultaneously: **High Excitement**, **Liquidity Buildup**, and the start of a **Price Dip**.
***
### 🛠️ Customize Inputs (Settings)
Access the indicator's settings window to adjust the following values:
Funding Rate Threshold (%):** Controls the required bar momentum (proxy for excitement). *Adjust between 0.01 and 0.05.*
OI MA Period:** Sets the lookback period for the Open Interest/Volume trend. *Use 7 to 14.*
OI Spike % Above MA:** Defines how far above its trend the Volume/OI must be to signal high liquidity buildup. *Try 20.0 to 50.0.*
Price Drop % From X-Period High:** Sets the minimum percentage drop required from the recent high to confirm the setup. *Use 3.0 to 7.0.*
High Timeframe:** The period used to calculate the "recent high." *Use '7D' (7 Days) or '1D' (1 Day).*
***
🔔 Reading the Signal and Setting Alerts
Visual Signal (Short\_Alert):** A **red triangle down** will appear at the top of the indicator pane when all three conditions are met. The background will also turn light red.
Signal Confirmation:**
* The **FR Proxy % (Blue Line)** must be **above** its blue threshold line.
* The **OI Spike % (Orange Line)** must be **above** its orange threshold line.
* The **Price Drop % (Fuchsia Line)** must be **below** its fuchsia threshold line.
Setting Alerts:**
1. Click the **"Alert"** button (bell icon) on the chart.
2. Set the **Condition** to the indicator's name: **"Overleverage Short Screener Alert
3. Set the specific condition to: **"Overleverage Short Alert"**.
4. The default alert message includes the current percentage values for all three factors for quick review.
1m Scalping ATR (with SL & Zones)A universal ATR indicator that anchors volatility to your stop-loss.
Read any market (FX, JPY pairs, Gold/Silver, indices, crypto) consistently—regardless of pip/point conventions and timeframe.
Why this indicator?
Classic ATR is absolute (pips/points) and feels different across markets/TFs. ATR Takeoff normalizes ATR to your stop-loss in pips and highlights clear zones for “quiet / ideal / too volatile,” so you instantly know if a 10-pip SL fits current conditions.
Key features
Auto pip detection (FX, JPY, XAU/XAG, indices, BTC/ETH).
Selectable ATR source: chart timeframe or fixed ATR TF (e.g., “15”, “30”, “60”).
Display modes:
Percent of SL – ATR relative to SL in %, great for M1 (typical 10–30%).
Multiple of SL – ATR as a multiple of SL (e.g., 0.6× / 1.0× / 1.2×).
Panel zones:
Green = “Ready for takeoff” (≤ Low), Yellow = reference (Mid), Red = too volatile (≥ High).
Status badge (top-right): Quiet / ATR ok / Wild, current ATR/SL value, ATR TF used.
Direction-agnostic: Works the same for longs and shorts.
Inputs (at a glance)
Length / Smoothing (RMA/SMA/EMA/WMA): ATR base settings.
Your Stop-Loss (Pips): Reference SL (e.g., 10).
ATR Timeframe (empty = chart): Use chart TF or a fixed TF.
Display Mode: “Percent of SL” or “Multiple of SL.”
Low/Mid/High (Percent Mode): Zone thresholds in % of SL.
Low/Mid/High (Multiple Mode): Zone thresholds in ×SL.
Recommended defaults
Length 14, Smoothing RMA, SL 10 pips
Display Mode: Percent of SL
Low/Mid/High (%): 15 / 20 / 25
ATR Timeframe: empty (= chart) for reactive, or “30” for smoother M30 context with M1 entries.
How to use
Set SL (pips). 2) Choose display mode. 3) Optionally pick ATR TF.
Interpretation:
≤ Low (green): setups allowed.
≈ Mid (yellow): neutral reference.
≥ High (red): too volatile → adjust SL/size or wait.
Note: Auto-pip relies on common ticker naming; verify on exotic symbols.
Disclaimer: For research/education. Not financial advice.
