BTC On-Chain Value Zones [MVRV]BTC Onchain Value Zones (MVRV)
Bitcoin has a cost basis. Realized Price is the average price at which every coin in circulation last moved onchain, which makes it a reasonable proxy for what the average holder actually paid. This script plots that level directly on your price chart and builds valuation zones around it.
MVRV is just price divided by Realized Price. When MVRV falls under 1, the average holder is sitting at a loss. Historically that condition has clustered around cycle lows and long accumulation ranges. When MVRV stretches well above 2.5, the market is carrying a large amount of unrealized profit, and historically that has clustered around distribution phases and cycle highs. It is a slow, structural read, not a trade trigger.
Why I rebuilt it
The common version of this idea relied on the IntoTheBlock MVRV feed. That feed stopped updating in August 2025 and PulseWire flagged it as discontinued. Scripts using it did not throw an error. They quietly froze on a stale value and kept plotting a line that meant nothing, which is worse than breaking outright.
This version calculates MVRV itself from two live feeds:
Realized Price = Realized Cap / Circulating Supply
MVRV = Price / Realized Price
Realized Cap comes from CoinMetrics and Circulating Supply from Glassnode. If either symbol is unavailable on your plan, the script falls back to an alternate ticker automatically. If supply goes dark entirely, it derives supply from market cap divided by price so the realized line keeps working rather than vanishing.
The zones
Deep buy below 0.85, meaning capitulation territory where holders are heavily underwater.
Buy below 1.0, meaning price sits under the aggregate cost basis.
Fair value between 1.0 and 2.5.
Sell above 2.5.
Euphoria above 3.5.
Every threshold is adjustable in settings. The zones are drawn in price terms, not as an oscillator, so you can see exactly what dollar level each multiple sits at right now.
Signals
Markers fire when MVRV crosses a threshold on the daily close. Triangles mark entries into the buy and sell zones, labels mark deep value and euphoria, and a circle marks the moment price reclaims its cost basis, which has historically been a useful bottom confirmation. Alerts are available for each event individually, for any buy event, for any sell event, and for a stale data feed.
Diagnostics
Two tables. The top right shows current MVRV, realized price in dollars, the active zone, how many days old the onchain data is, and which feeds are supplying it. The bottom right lists all six candidate symbols with their current values, marked green if live and red if dead. If a data provider retires a ticker two years from now, you will see it immediately instead of trusting a frozen line.
How to use it
Onchain data updates once per day, so use this on a daily chart or higher. It is built for position sizing and accumulation decisions across weeks and months, not for entries. Treat the zones as context for whatever you are already doing.
One honest caveat. MVRV peaks have declined with every cycle as Bitcoin has matured and the holder base has grown. The 3.5 euphoria level was routine in 2013 and 2017 and has been harder to reach since. Adjust the upper thresholds to fit the market you are actually trading rather than assuming past extremes will repeat.
This is for informational purposes only and is not financial advice. Indicator
Bitcoin Halving Cycle PhasesBitcoin Halving Cycle Phases is a calendar-based visual indicator that highlights approximate Bitcoin halving cycle phase zones directly on the chart.
The indicator uses historical Bitcoin halving dates and predefined calendar phase boundaries to display different cycle regions, including Halving, Bullish, Bearish, Recovery, and Pre-halving phases. Future zones are projected using an approximate cycle length and are intended only as visual calendar references.
This script does not calculate price targets, buy or sell signals, trading entries, exits, stop losses, take profits, backtest results, or financial advice. The displayed future zones are approximate calendar projections only and should not be interpreted as forecasts or guaranteed market outcomes.
The indicator is designed for educational cycle visualization and long-term market context.
Indicator
COT-Trader Seasonality - Indexed Geometric PathCOT-Trader Seasonality is a visual research indicator designed to study seasonal tendencies in futures, commodities, indices and other markets.
The script focuses on one specific question:
How has a market typically behaved throughout the calendar year when historical years are compared on a normalized basis?
Instead of averaging raw historical prices, the indicator indexes each historical year to a base value of 100 at the first available trading day of that year. This makes different years comparable across changing price regimes.
This is especially useful for markets such as commodities and futures, where long-term price levels can change significantly over time.
Methodology
The indicator uses an Indexed Geometric Seasonal Path approach:
1. Each historical year is indexed to 100 at its first available trading day.
2. Each following trading day is converted into a relative factor versus that year’s starting value.
3. For each calendar day, the geometric mean of the indexed historical factors is calculated.
4. The resulting seasonal curves are plotted on a synthetic January-to-December seasonal scale.
The geometric approach is used because price development is multiplicative. A 10% gain followed by a 10% loss does not return a market to its original level. Working with relative factors is therefore more appropriate than directly averaging absolute historical prices.
Displayed Curves
The indicator can display:
• 10Y Main Seasonal Curve
• 5Y Seasonal Curve
• 15Y Seasonal Curve
• 20Y Seasonal Curve
• Current Year / YTD indexed path
• Previous Year indexed path
• Synthetic seasonal month scale
The 10Y curve is the main reference curve. The 5Y, 15Y and 20Y curves are included as comparison views to help evaluate whether shorter-term seasonal tendencies differ from longer-term historical behavior.
The current year line stops at the latest available data point. It is not extended into the future.
How to Use
This indicator can be used to:
• compare the current year against historical seasonal tendencies
• identify periods where several seasonal curves move in a similar direction
• compare shorter-term and longer-term seasonal behavior
• study whether the current year is behaving normally or as an outlier
• support broader market research together with positioning, fundamentals, volatility and risk analysis
The month labels shown in the indicator are a synthetic seasonal month scale. They are not the same as the chart’s real time axis.
What This Indicator Does Not Do
This script does not generate buy or sell signals.
It does not predict future prices.
It does not automatically identify the best seasonal trading window.
It does not include stop-loss, take-profit, position sizing or strategy backtesting logic.
It is intended as a visual research tool, not as a standalone trading system.
Limitations
Seasonality describes historical tendencies, not certainties. Markets can deviate significantly from historical seasonal patterns due to macroeconomic conditions, weather, supply-demand shocks, positioning, volatility, futures contract rolls or other market-specific factors.
For futures and continuous contracts, historical data quality and roll methodology can influence the visual result.
The indicator should be used as one part of a broader analytical process.
Initial public release.
Features:
• Indexed geometric seasonal path calculation
• Fixed 10Y main seasonal curve
• 5Y, 15Y and 20Y comparison curves
• Current year / YTD indexed path
• Previous year indexed path
• Synthetic January-to-December seasonal month scale
• Built-in legend and methodology table
This indicator is designed for visual seasonal research and does not generate trading signals. Indicator
Bitcoin Cycle Highs and LowsOVERVIEW
The Bitcoin Cycle Highs and Lows indicator maps out the historical macro market cycle tops and bottoms of Bitcoin, dating back to 2011. In addition to serving as a visual map of historical market phases, the indicator features an algorithmic projection engine. This engine uses various statistical and geometric decay models to forecast the date and price of future macro highs and lows based on the asset's historical behaviour.
This tool is designed for macro-level market analysis, allowing traders to visualise diminishing returns, cycle duration trends, and phase retracements.
CHART ELEMENTS
When applied to a chart, the indicator plots several visual elements:
• Vertical Cycle Markers: Solid vertical lines identify the exact date of historical macro highs (Red) and macro lows (Lime).
• Price & Date Labels: Located at the anchor of each vertical line, detailing the exact recorded date and price (formatted automatically to the chart's active currency).
• Phase Arrows (Dashed Lines): Horizontal dashed lines connecting a low to the subsequent high (Bull Phase) or a high to the subsequent low (Bear Phase).
• Phase Statistics: Floating text labels positioned at the end of each Phase Arrow. These display the duration of the phase in days, the absolute price change, and the percentage move from the previous point.
PREDICTION MODELS
The indicator includes multiple distinct mathematical models for projecting future dates and prices.
Date Predictors:
• Previous bar count: Projects the next date by applying the exact duration of the most recent corresponding cycle.
• Average: Calculates the simple arithmetic average duration of all historical cycles of the same type.
• Weighted average: Averages previous cycle lengths but applies a mathematical recency bias, giving more weight to recent cycles to account for cycle duration stabilisation.
Price Predictors:
• Previous % move: Projects the next target by applying the exact percentage multiplier of the most recent corresponding cycle.
• Average: Projects the target using the geometric mean of all historical cycle multipliers, limiting the skew of extreme outliers.
• Diminishing gains: Analyses the cycle-over-cycle rate of change. It isolates peak-to-peak or trough-to-trough macro moves, calculates the historical decay in those percentage gains, and applies the decayed growth rate to project the next target.
• Fibonacci extension decay: Evaluates swing ratios by measuring the magnitude of a phase relative to the preceding phase (for example, how far a bull market extended past the previous bear market drop). It calculates the historical decay of that extension premium and applies it to the current swing.
SETTINGS AND INPUTS
• Predictions: Determines the number of future cycle highs and lows to project (0 to 9). Set to 0 to disable projections and only view historical data.
• Date predictor: Selects the algorithmic model used to project the X-axis (time) coordinate of future cycle points.
• Price predictor: Selects the algorithmic model used to project the Y-axis (price) coordinate of future cycle points.
• Bear/Bull market arrows: Toggles the visibility of the horizontal dashed lines and their accompanying statistical labels.
• Full height backgrounds: When true, vertical cycle markers extend infinitely across the Y-axis. When false, markers anchor precisely to the price level of the previous cycle phase, creating a stair-step visualisation.
• Ignore 2011 cycle: Excludes the extreme volatility and outliers of the 2011 cycle from the indicator's mathematical averages and trend decay calculations.
• Backtest # lows/highs: A testing feature that temporarily removes the most recent 1 or 2 historical cycle points from the dataset. This allows users to test the prediction models against known outcomes to evaluate their historical accuracy.
Indicator
Daubechies D4 Denoising [LB]Concept
The Daubechies D4 Wavelet Denoising indicator applies a multi‑level discrete wavelet transform using the compactly supported Daubechies D4 wavelet (Ingrid Daubechies, 1992) combined with Donoho's universal threshold (Donoho & Johnstone, 1994). It separates price into approximation (trend) and detail (noise) coefficients, attenuates noise via soft thresholding, and reconstructs a denoised price curve that directly overlays the chart.
Mathematical Foundation
The Daubechies D4 wavelet is defined by four scaling coefficients h and four wavelet coefficients g , forming quadrature mirror filters that satisfy perfect reconstruction. At each level, the input array a is circularly convolved with h and g , then downsampled by two to produce the approximation a' and detail d' :
a' = SUM_m h * a
d' = SUM_m g * a
This process is iterated J times. The universal threshold lambda is estimated for each detail array independently using the median absolute deviation (MAD) of the coefficients :
sigma = MAD / 0.6745
lambda = sigma * sqrt(2 * log N)
Soft thresholding is then applied to each detail coefficient x :
threshold(x) = sign(x) * max(|x| - lambda, 0)
Finally, the denoised signal is reconstructed by upsampling, convolution with synthesis filters, and summation of approximation and detail contributions.
What Problem Does It Solve ?
Classical moving averages and low‑pass filters eliminate noise at the cost of significant lag and do not adapt to the local structure of the data. The Daubechies D4 wavelet denoising preserves sharp transitions (edges) while removing high‑frequency noise, offering a lag‑free, adaptive smoothing that respects the multi‑scale nature of price action.
How To Interpret
Denoised line above price – the smoothed trend is stronger than the current raw price; underlying momentum remains positive despite transient dips.
Denoised line below price – the smoothed trend is weaker; price is correcting within a larger structure.
Denoised line flattening or changing direction – a regime shift may be underway; the multi‑scale trend is losing or gaining momentum.
Parameters
Source – price field to denoise (default close).
Decomposition Levels – number of wavelet decomposition iterations. Higher levels remove lower‑frequency components, producing a smoother but more slowly reacting line.
Window Length (power of 2) – analysis window size. Must be a power of two for the dyadic decomposition; the indicator automatically adjusts to the largest valid power of two if an invalid value is entered.
Reference
Daubechies I., "Ten Lectures on Wavelets", Society for Industrial and Applied Mathematics, 1992.
Donoho D.L. & Johnstone I.M., "Ideal Spatial Adaptation by Wavelet Shrinkage", Biometrika, Vol. 81, No. 3, pp. 425‑455, 1994. Indicator
Pi Cycle Top OscillatorOverview
The Pi Cycle Top Oscillator is an advanced, adaptive iteration of the classic Pi Cycle Top indicator, reimagined as a continuous risk metric. While the original indicator famously predicted Bitcoin’s macro peaks by waiting for a binary crossover of the 111-day SMA and the 2x 350-day SMA, this script translates the relationship between these two moving averages into a normalized 0 to 1 oscillator, providing both buy and sell signals.
As an asset matures, its volatility historically compresses. In the 2021 cycle, the classic moving averages barely touched, meaning future cycles might never see a pure crossover due to the law of diminishing returns. This oscillator solves that problem by replacing the rigid crossover requirement with dynamic, regression-based boundaries.
Tip
Hide the Bitcoin price chart to clearly view the metric in the main chart pane:
How it Works
Instead of waiting for a binary signal, this indicator calculates the exact mathematical ratio between the two moving averages:
ratio = ta.sma(close, 111) / (ta.sma(close, 350) * 2)
Using historical extremes of this ratio, the script projects two dynamic boundaries:
Top Boundary: A logarithmic regression curve that accounts for historical volatility decay, descending over time.
Bottom Boundary: A linear regression line representing macro bottoms.
The current ratio is then normalized between these two converging lines, producing a continuous Risk metric.
Key Features
Continuous Risk Scale: Unlike the classic indicator which is either "on" or "off", this oscillator provides a constant reading from 0 (historical bottom) to 1 (probable macro top).
Volatility Adjusted: The logarithmic top line factors in macro volatility decay, ensuring the indicator remains relevant in future cycles even if a classic crossover never occurs.
Visual Chart Feedback: The main chart automatically highlights price bars in Green when Risk falls below your custom Buy Zone Level, and Red when Risk exceeds your Sell Zone Level.
Dual Display Modes: Use the indicator settings to toggle between the normalized 0-1 "Oscillator" view and the raw "Fit Lines" view to see the actual ratio and regression curves.
How to Use
This tool is designed for macro-level portfolio risk management rather than short-term trading.
Accumulation: Readings near or below 0.1 historically correlate with macro bottoms, presenting potential long-term accumulation zones.
Distribution: Readings near or above 0.9 indicate severe market overheating, signaling potential distribution zones.
You can adjust the Buy and Sell zone thresholds in the indicator settings to fit your personal risk tolerance.
Limitations
Bitcoin Exclusive: This indicator is designed strictly for analyzing Bitcoin. Its mathematical model is based entirely on Bitcoin's historical macro cycles and is not applicable to other cryptocurrencies or traditional assets.
No Guaranteed Extremes: There are no guarantees that the oscillator will reach the upper or lower boundaries in future cycles, nor that it will remain strictly within the 0 to 1 range. For example, during the 2025 cycle, the oscillator never reached the theoretical sell zone, demonstrating that market dynamics can and do shift.
Static Curve Fitting: The regression curves for the upper and lower boundaries were fitted using the global tops and bottoms of the 111-day and 2x 350-day SMA ratio prior to 2023. The resulting equation coefficients are hardcoded directly into the script. As new macro extremes form in the future, these boundary models may eventually require a new approximation to maintain their accuracy.
Indicator
Sine Wave Cycle Oscillator [HT]Overview:
This oscillator identifies the dominant market cycle in real time using John Ehlers' Hilbert Transform and Homodyne Discriminator — a signal-processing technique adapted from radio engineering. Rather than using a fixed bar count to simulate a sine wave, the indicator measures the market's own oscillatory rhythm bar-by-bar, producing a phase-accurate sine wave that stays synchronized with actual price cycles as they expand and contract.
How It Works:
Adaptive Cycle Detection (Hilbert Transform)
Price is passed through a multi-stage signal processing pipeline:
4-bar weighted smooth — reduces noise before analysis-
Hilbert detrend — strips the DC trend component, isolating the cyclic portion
In-phase (I1) / Quadrature (Q1) decomposition — constructs a phasor representation of price
90° phase advance — produces jI and jQ for phasor rotation
Phasor addition — yields the corrected I2/Q2 complex pair
Homodyne Discriminator — computes the instantaneous cycle period from the rate of phase change between consecutive bars
Adaptive period — clamped between 6 and 50 bars, double-smoothed for stability
The result is a live dominant cycle period that updates every bar and is displayed in the info table.
Instantaneous Phase Engine
From the I1/Q1 phasor, the indicator derives a continuous phase angle (0°–360°) that tracks where price currently sits within its cycle — no fixed-length assumption, no lag from windowing.
Sine wave — sin(phase), EMA-smoothed for display clarity
Lead sine — cos(phase) = exactly 90° ahead of the main wave, acting as an early-warning signal for turns
Signals:
Strong signals require both conditions to fire simultaneously (table) — the highest-conviction setup. Early warnings give traders advance notice of a potential turn before the zero-line confirms. Weak signals flag zero-line crossings that lack lead-sine confirmation and should be treated with caution.
Visual Elements:
Sine wave — colour-coded green above zero, red below, with a matching fill
Lead sine — plotted in blue, always one quarter-cycle ahead
±0.8 bands — mark the 90° and 270° peak zones where cycle reversals are most likely
Background shading — highlights three key phase zones:
🟢 80°–100° — approaching upside peak
🟡 170°–190° — mid-cycle reversal zone
🔴 260°–280° — approaching downside peak
Label markers — L (Strong Buy) and S (Strong Sell) plotted directly on the oscillator panel; triangles mark early warnings
Info Table (Top-Right)
Field Description Dom Cycle Current adaptive period in bars (Homodyne Discriminator output)
Angle Instantaneous phase angle in degrees
Phase Named cycle stage: Cycle Start / Uptrend Peak / Reversal / Downtrend Peak Signal Current bar's signal classification
Legend rows Cross / color change logic reference and phase reference guide
Settings:
Parameter Default Description Smoothing 3EMA length applied to the raw sine wave before plotting
The cycle period requires no manual input — it is derived entirely from the market via the Hilbert Transform engine.
Notes & Best Practices:
Works on any symbol and timeframe; the adaptive period adjusts automatically
Most reliable on liquid instruments with clear cyclic behavior (indices, major FX pairs, large-cap equities)
Combine Strong signals with trend context from a higher timeframe for best results — this oscillator excels at timing entries within a known trend, not at predicting trend direction itself
The lead sine can precede actual turns by several bars; wait for the zero-line confirmation on lower-conviction setups
Ref:
Based on the work of John F. Ehlers — Cybernetic Analysis for Stocks and Futures (2004)
Disclaimer: This indicator is for educational purposes only. Always practice proper risk management and combine with your own analysis before making trading decisions. Happy trading.
Indicator
Rolling SSA Oscillator [LuxAlgo]The Rolling SSA Oscillator indicator is a cycle-analysis tool that utilizes Singular Spectrum Analysis (SSA) to decompose price action into its most significant periodic components, providing a real-time view of underlying market rhythms. Unlike traditional lagging oscillators, this script uses eigendecomposition to isolate dominant trends and noise-reduced oscillations for better market timing.
🔶 USAGE
The indicator provides two primary components derived from the price's spectral signature: a Long-Term Periodic component and a Short-Term Periodic component. These can be used to identify trend direction, cyclical reversals, and momentum exhaustion.
🔹 Trading Signals
Trend Direction: When the Long-Term Periodic component (solid line) is above the zero level and colored green, the primary underlying cycle is in an upward phase. Conversely, a red line below zero indicates a downward phase.
Cycle Crosses: Traders can look for the Short-Term Periodic component (dotted line) crossing the Long-Term component or the zero line to anticipate shorter-term shifts in momentum.
Normalization: When the "Normalize" setting is enabled, the components are scaled relative to their combined absolute magnitude. This is particularly useful for identifying extreme cycle peaks regardless of absolute price volatility.
🔶 DETAILS
Singular Spectrum Analysis (SSA) is a powerful non-parametric technique used in time-series analysis. This indicator implements a rolling version of SSA through the following mathematical steps:
Embedding: The price data is mapped into a trajectory matrix using the "Window" length defined in the settings.
Decomposition: A covariance matrix is computed, followed by eigendecomposition to find the eigenvalues and eigenvectors.
Grouping & Reconstruction: The eigenvectors are sorted by their energy (eigenvalues). The script specifically reconstructs the first two components to form the Long-Term trend/cycle and the subsequent two components to form the Short-Term cycle.
Because this script uses matrix.eigenvalues() and matrix.eigenvectors() , it requires significant computation. The "Window" input determines the "resolution" of the cycles; a larger window can capture longer-term rhythms but increases the lag and computational load.
🔶 SETTINGS
Window: Controls the embedding dimension (L). This defines the maximum cycle length the indicator can effectively resolve.
Long Term Periodic: Toggles the visibility of the primary trend-following cycle (Components 1 & 2).
Short Term Periodic: Toggles the visibility of the faster, more reactive cycle (Components 3 & 4).
Normalize: If enabled, adjusts the output so that the combined amplitude of both components stays within a consistent range, making it easier to spot cyclical extremes.
🔹 Dashboard
Dashboard: Toggles the on-screen statistics table.
Position: Determines where the dashboard is displayed (Top Right, Bottom Right, or Bottom Left).
Size: Adjusts the text size within the dashboard.
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Indicator
Vertical Event Lines - BTC Halving & Custom DatesThis indicator plots vertical lines and labels for Bitcoin halving dates and any custom events you define directly on the price chart.
It is designed as a clean, lightweight event-timeline overlay so you can instantly see where key dates occur relative to price action.
Main features
Built-in Bitcoin halving dates (2012, 2016, 2020, 2024), plus 8 additional custom event slots with freely configurable date/time, name and color.
Vertical lines are positioned using xloc.bar_time , ensuring each event is anchored to the exact timestamp in the chart’s timeframe and timezone.
Past and current events:
A label is created once, on the first bar that crosses the event time, and placed near the bar’s high for consistent readability across symbols and timeframes.
Future events:
A separate label is shown at the bottom of the chart, making future dates clearly visible even to the right of the last bar. These labels update only on the most recent bar to keep the script efficient.
Flexible styling:
Global controls for line width, line style and label size, with per-event color selection and optional per-event overrides of global width and style.
How to use
Add the script to any chart (BTC or other symbols). It works on all timeframes.
Use the Global settings to configure default line style, line width and label appearance (size, orientation, text color).
In each Event X section, enable the event and set:
Date/time in YYYY-MM-DD HH:MM format
Event name
Color
Optional custom width/style
When scrolling through time:
Events left of the last bar show a vertical line and a one-time label at the crossing bar.
Events right of the last bar show a vertical line and a bottom label that remains visible in the future.
This script is intended as a visual reference tool only .
It does not generate trading signals, alerts or backtests. Indicator
Indicator
Moon Declination & More [BlueprintResearch]🌒 MOON DECLINATION & MORE
A comprehensive lunar declination visualization showing Moon, Sun, and node declinations, with phase coloring, zodiac sign tracking, and future projections.
Part of the Blueprint Research open-source ephemeris project.
█ WHAT'S INCLUDED
• Moon Declination — The Moon's angular distance from the celestial equator, oscillating rapidly (~27 days)
• Sun Declination — Optional overlay showing the Sun's seasonal declination (±23.4°)
• Node Declinations — North (☊) and South (☋) node lines forming the Moon's orbital envelope
• Future Projections — Project all lines up to 500 bars into the future
• Zodiac Crossing Markers — Indicates when the North Node reaches a particular zodiac degree. Keep in mind, nodes move through the zodiac in reverse.
█ CONCEPTS
Declination measures how far north or south a celestial body appears from the celestial equator. The Moon's declination oscillates rapidly, while its maximum range shifts slowly over the 18.6-year nodal cycle.
Node Declination Envelope:
The North (☊) and South (☋) node lines mark the envelope of the Moon's orbit—the theoretical maximum northern and southern declinations the Moon can reach.
Lunar Standstills:
The 18.6-year nodal cycle determines when the Moon reaches its most extreme declinations. During a major standstill, the Moon can exceed ±28° declination. During a minor standstill, the Moon's range is limited to approximately ±18°.
Out-of-Bounds (OOB):
When the Moon moves beyond ±23.44° declination, it exceeds the Sun's maximum reach and is considered "Out of Bounds."
█ COLORING OPTIONS
Phase Coloring (Moon)
Color the Moon's declination line by lunar phase:
• New Moon (0-90°): Slate silver
• First Quarter (90-180°): Mint
• Full Moon (180-270°): Bright gold
• Last Quarter (270-360°): Soft violet
Zodiac Sign Coloring (Nodes)
Color the node lines by their zodiac sign. When enabled, a color legend appears at the top, showing all 12 signs for reference.
█ ZODIAC FEATURES
Zodiac Sign Coloring
Color the North and South Node lines according to their zodiac sign positions.
Zodiac Crossing
Marks when the North Node crosses a specific zodiac degree. Select any sign and degree (0-29) to track. The North Node moves retrograde through the zodiac over an 18.6-year cycle.
█ RESEARCH FEATURES
Standstill Thresholds
Horizontal reference lines at key declination levels:
• ±28.6° Major Standstill (peak of the 18.6-year cycle)
• ±18.3° Minor Standstill (trough of the cycle)
• ±23.4° Out-of-Bounds threshold
OOB Highlighting
Optional background shading when the Moon exceeds the OOB threshold.
Node Equatorial Crossings
Crosshair markers indicate when the node's declination crosses 0° (equatorial passage).
Reference Line Labels
Labels at projection endpoints with an adjustable offset for readability.
█ FEATURES
• Moon declination with optional lunar phase coloring
• Sun declination overlay
• North and South node declinations (☊ and ☋)
• Future projections up to 500 bars
• Zodiac sign coloring with a color legend
• Zodiac degree-crossing markers
• Node equatorial-crossing markers
• Out-of-Bounds background highlighting
• Reference line labels with offset control
• Customizable line widths and colors
• Informative tooltips for all settings
• Works on all timeframes
█ HOW TO USE
1 — Add the indicator to your chart
2 — Configure which elements to display (Moon, Sun, Nodes)
3 — Enable future projections to view upcoming declination values
4 — Enable Zodiac coloring to track node sign positions
5 — Set a Zodiac Crossing degree to mark when the North Node crosses that point
6 — Enable Standstill Thresholds to show reference lines
7 — Toggle phase coloring to visualize the lunar cycle
█ THEORY
Lunar Theory: ELP2000-82 by Chapront-Touzé & Chapront
Solar Theory: VSOP87 for Sun position and phase calculation
Reference: Meeus, "Astronomical Algorithms" (2nd Ed., 1998)
█ LIMITATIONS
• Truncated ELP2000-82 theory (~10 arcseconds precision)
• Future projections assume consistent bar timing
• Phase coloring uses 4 phases (not the 8 traditional phases)
• Mean nodes only (no perturbation corrections)
█ OPEN SOURCE
Blueprint Research Ephemeris Libraries:
• lib_elp2000_moon — Lunar position and mean node calculations
• lib_vsop_core — Solar position and coordinate utilities
• lib_ephemeris — Unified planetary API
Third-Party Libraries:
• hsvColor by @kaigouthro — HSV color utilities (MPL 2.0)
© 2025-2026 BlueprintResearch (Javonnii) • CC BY-NC-SA 4.0
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Indicator
Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R)
Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg.
“Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits.
Core Idea
This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model.
It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections.
A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio.
Default Properties & Risk Assumptions
The backtest uses realistic but conservative defaults:
// Default properties used for backtesting
strategy(
"Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)",
overlay = true,
initial_capital = 10000, // realistic account size
default_qty_type = strategy.percent_of_equity,
default_qty_value = 1, // 1% risk per trade
commission_type = strategy.commission.cash_per_contract,
commission_value = 0.005, // example stock commission
slippage = 0 // see notes below
)
Account size: 10,000 (can be changed to match your own account).
Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with PulseWire’s recommendations.
Commission: 0.005 cash per contract/share as a realistic example for stock trading.
Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker.
Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable.
1. Full Fractal Wave Engine
The script builds and maintains four pivot streams using ATR-adaptive fractals:
Primary Degree (Macro Trend):
Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines.
Intermediate Degree (Trading Degree):
Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ).
Minor Degree (Micro Structure):
Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c).
ABC Corrections (Optional):
When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines.
Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions.
2. Theory Rules & Strict Mode
Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use.
Strict Mode: Enforces key Elliott constraints:
Wave 3 not shorter than waves 1 and 5.
No invalid W4 overlap with W1 (for standard impulses).
ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up.
3. Trend Filter & Pivots
EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter.
Price above EMA → Only long setups are considered.
Price below EMA → Only short setups are considered.
ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes.
4. Dynamic Risk Management (Guaranteed R/R Engine)
The trading engine is designed around risk, not just pattern recognition:
ATR-Based Stop:
Stop-loss is placed at:
Entry ± ATR × Multiplier (user-configurable, default 2.0).
This anchors risk to current volatility.
Minimum Reward:Risk Ratio:
For each setup, the script:
Computes the distance from entry to stop (risk).
Projects a take-profit target at risk × min_rr_ratio away from entry.
Only accepts the setup if risk is positive and the required R:R ratio is achievable.
Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design.
“Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability.
5. Trading Logic – W3–W4–W5 Pattern
The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern:
Bullish structure:
Sequence of pivots forms a higher-high / higher-low pattern.
Price is above the EMA trend filter.
A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode).
Entry (Long – W4 Pullback):
The “height” of W3 is measured.
Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg.
ATR-based stop is placed below entry.
Take-profit is projected to satisfy min Reward:Risk.
Bearish structure:
Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down).
Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price.
6. Orders & Execution
Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”).
Exits: A single strategy.exit() is attached to each entry with:
Take-profit at the projected minimum R:R target.
Stop-loss at ATR-based level.
One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained.
7. Visual Guide on the Chart
Wave Labels:
Primary: ①,②,③,④,⑤, ⒶⒷⒸ
Intermediate: (1)…(5), (A)(B)(C)
Minor: i…v, a b c
Trend EMA: Single blue EMA showing the dominant trend.
Setup Boxes:
Green transparent box → long entry zone.
Red transparent box → short entry zone.
Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price.
8. How to Use This Strategy
Attach the strategy to your chart
Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list.
Start with the default settings
Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.).
Study the wave map
Zoom in and out and look at the three wave degrees:
Blue circles → Primary degree (big picture trend).
Teal (1)…(5) → Intermediate degree (swing structure).
Red i…v → Minor degree (micro waves).
Use this to understand how the engine is interpreting the Elliott structure on your symbol.
Watch for valid setups
Look for the coloured boxes and labels:
Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend.
Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend.
Only trades in the direction of the EMA trend filter are allowed by the strategy.
Check the Reward:Risk of each idea
For each setup, inspect:
Limit entry price.
ATR-based stop level.
Projected take-profit level.
Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it.
Backtest and evaluate
Open the Strategy Tester:
Verify you have a decent sample size (ideally 100+ trades).
Check drawdowns, average trade, win-rate and R:R distribution.
Change markets and timeframes to see where the logic behaves best.
Adapt to your own risk profile
If you plan to use it live:
Set Initial Capital to your real account size.
Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade).
Set commission and slippage to realistic broker values.
Re-run the backtest after every major change.
Use as a framework, not a signal machine
Treat this as a structured Elliott/R:R framework:
Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals.
Optionally hide some wave degrees or ABC labels if you want a cleaner chart.
Combine the system’s structure with your own trade management and discretion.
Best Practices & Limitations
This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis.
All wave counts are algorithmic and can differ from a manual analyst’s interpretation.
Like any backtest, results depend heavily on:
Symbol and timeframe.
Sample size (more trades are better).
Realistic commission/slippage settings.
The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance.
No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework.
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
Strategy
Pi Cycle BTC Top + Pre-Alert BandsPi Cycle BTC Top + Pre-Alert Bands is an advanced implementation of the classic Pi Cycle Top model, designed for Bitcoin cycle analysis on higher timeframes (especially 1D BTCUSD/BTCUSD·INDEX).
The original Pi Cycle Top uses two moving averages:
• 111-day SMA (short MA)
• 350-day SMA ×2 (long MA)
A Pi Top is signaled when the 111 SMA crosses above the 350×2 SMA. Historically, this has occurred near major BTC cycle highs.
This script extends that idea with a 3-step early-warning sequence:
• Pi Green – early compression: short/long MA ratio crosses upward into the green band (convergence from below is required).
• Pi Yellow – mid-cycle warning: only fires if a valid Green has already occurred in the same cycle.
• Pi Cycle Top – final top: the classic Pi Cycle cross, limited to one top signal per cycle. After a top, no new Yellow or Top signals can appear until a new Green event starts the next cycle.
Background shading shows the active phase (Green / Yellow / late-cycle zone), so you can see at a glance where BTC is within its Pi-based macro structure.
All logic is non-repainting: request.security() uses lookahead_off and no future data is accessed.
Typical use
This indicator is intended as a macro-cycle timing and risk-awareness tool, not a stand-alone entry system. Many traders use it to:
• Watch for Pi Green as the start of a potential late-cycle advance.
• Treat Pi Yellow as a rising-risk environment and tighten risk management.
• Use the Pi Cycle Top as a historical high-risk zone where large profit-taking or hedging may be considered.
Always combine this with your own analysis (trend, volume, on-chain, macro) before making decisions.
How to set alerts
Add the indicator to your chart (1D BTCUSD or BTCUSD·INDEX recommended).
Click Alerts → Condition → Pi Cycle BTC Top + Pre-Alert Bands.
Choose one of:
• Pi Cycle – Green Pre-Alert (early convergence)
• Pi Cycle – Yellow Pre-Alert (after Green only)
• Pi Cycle – TOP (Single per Cycle, after Green)
Use “Once per bar close” for higher-timeframe reliability.
Disclaimer
This tool is for educational and analytical purposes only. The Pi Cycle concept is based on historical behavior and does not guarantee future results. This is not financial advice; always do your own research and manage risk appropriately. Indicator
Gann Square of 144 (Master Price & Time)🔹 What this tool does
Draws a 144-unit square in price & time (0 → 144)
Plots all key horizontal & vertical levels:
0, 18, 36, 48, 54, 72, 90, 96, 108, 126, 144
Highlights the main 1/2 level (72) as thick midline
Marks 1/3 and 2/3 (48 & 96) as special harmonic levels
Draws internal diagonals (0–144, 144–0 and sub-squares)
Plots an 8-ray Gann fan from the 0-point (0 → 36 / 72 / 108 / 144 etc.)
Keeps price–time ratio consistent inside the box:
the 1×1 angle has a fixed slope = price_per_bar
The idea: once the square is calibrated to a major swing, you can study how price respects these angles and harmonic zones over time.
🔧 Inputs & how to set it up correctly
Choose your timeframe
Works best on Daily and Weekly charts.
Use one timeframe consistently when calibrating the square.
Start offset (bars back)
Start offset (bars back) shifts the whole square left/right.
Increase the value to move the square further into the past, decrease it to move it closer to the current bars.
Box width (bars)
Box width (bars) = how many bars the square spans horizontally.
Bigger value = projects the structure further into the future.
Example: 288 bars ≈ 2×144 units in time, 720 bars for longer-term projection, etc.
Bottom price
Bottom price is your 0-level in price.
Usually set this to a major swing low (cycle low, bear market low, important pivot).
The bottom-left corner of the square conceptually sits at:
(start_offset_bar, bottom_price)
Price per bar (slope 1×1) (if your version has this input)
This defines the slope of the 1×1 angle (main Gann angle).
Recommended way to set it:
Pick a major impulsive move from Swing Low → Swing High.
Measure:
Price range = High − Low
Number of bars between them.
Compute:
price_per_bar = price_range / number_of_bars
Use that as your 1×1 value in the input.
Now the main diagonal from 0 to 144 represents the true Gann 1×1 for that swing.
Important: The 1×1 angle is mathematically correct (price-per-bar), even if it does not always look like a perfect 45° line visually in PulseWire due to chart scaling.
📖 How to read the Square of 144
Horizontal levels
0 = anchor price (bottom)
18, 36, 48, 54, 72, 90, 96, 108, 126, 144 = key price harmonics
72 (1/2) often acts as major support/resistance
48 & 96 (1/3 and 2/3) are strong “vibration” levels
Vertical levels
Same units but in time (bars).
When important pivots in price occur near these verticals, you get time–price confluence.
Midlines (1/2)
The thick horizontal and vertical lines at 72 mark the center of the square.
Crossings around these often signal important cycle turns.
1/3 & 2/3 zones (48–54 and 90–96)
These narrow bands are powerful reversal / decision zones.
Price often reacts strongly there or accelerates if they break.
Gann fan from 0-point
These rays represent major trends:
1×1 equivalent (main diagonal)
Faster & slower angles (e.g. 2×1, 1×2, etc depending on configuration)
If price breaks one fan angle cleanly, it often “falls” or “climbs” toward the next one.
🎯 Practical use cases
Project future support/resistance zones based on a major low.
See where price is in the square: early in the cycle (0–36), mid (around 72), or late (108–144).
Watch how price respects:
midlines (72),
1/3 and 2/3 bands (48–54, 90–96),
and the fan angles from 0.
Combine with your own price action / Fibonacci / trend tools – this is not a signal generator, but a time–price map.
⚠️ Notes & limitations
This tool is for educational & analytical purposes only.
It does not generate buy/sell signals.
Visual 45° angles in PulseWire can change when you zoom or rescale the chart.
→ The script keeps the internal price-per-bar logic stable, even if the drawing looks steeper/flatter when zooming.
Always confirm zones with price action, volume, and higher timeframe context. Indicator
Market Regime IndexThe Market Regime Index is a top-down macro regime nowcasting tool that offers a consolidated view of the market’s risk appetite. It tracks 32 of the world’s most influential markets across asset classes to determine investor sentiment by applying trend-following signals to each independent asset. It features adjustable parameters and a built-in alert system that notifies investors when conditions transition between Risk-On and Risk-Off regimes. The selected markets are grouped into equities (7), fixed income (9), currencies (7), commodities (5), and derivatives (4):
Equities = S&P 500 E-mini Index Futures, Nasdaq-100 E-mini Index Futures, Russell 2000 E-mini Index Futures, STOXX Europe 600 Index Futures, Nikkei 225 Index Futures, MSCI Emerging Markets Index Futures, and S&P 500 High Beta (SPHB)/Low Beta (SPLV) Ratio.
Fixed Income = US 10Y Treasury Yield, US 2Y Treasury Yield, US 10Y-02Y Yield Spread, German 10Y Bund Yield, UK 10Y Gilt Yield, US 10Y Breakeven Inflation Rate, US 10Y TIPS Yield, US High Yield Option-Adjusted Spread, and US Corporate Option-Adjusted Spread.
Currencies = US Dollar Index (DXY), Australian Dollar/US Dollar, Euro/US Dollar, Chinese Yuan/US Dollar, Pound Sterling/US Dollar, Japanese Yen/US Dollar, and Bitcoin/US Dollar.
Commodities = ICE Brent Crude Oil Futures, COMEX Gold Futures, COMEX Silver Futures, COMEX Copper Futures, and S&P Goldman Sachs Commodity Index (GSCI) Futures.
Derivatives = CBOE S&P 500 Volatility Index (VIX), ICE US Bond Market Volatility Index (MOVE), CBOE 3M Implied Correlation Index, and CBOE VIX Volatility Index (VVIX)/VIX.
All assets are directionally aligned with their historical correlation to the S&P 500. Each asset contributes equally based on its individual bullish or bearish signal. The overall market regime is calculated as the difference between the number of Risk-On and Risk-Off signals divided by the total number of assets, displayed as the percentage of markets confirming each regime. Green indicates Risk-On and occurs when the number of Risk-On signals exceeds Risk-Off signals, while red indicates Risk-Off and occurs when the number of Risk-Off signals exceeds Risk-On signals.
Bullish Signal = (Fast MA – Slow MA) > (ATR × ATR Margin)
Bearish Signal = (Fast MA – Slow MA) < –(ATR × ATR Margin)
Market Regime = (Risk-On signals – Risk-Off signals) ÷ Total assets
This indicator is designed with flexibility in mind, allowing users to include or exclude individual assets that contribute to the market regime and adjust the input parameters used for trend signal detection. These parameters apply to each independent asset, and the overall regime signal is smoothed by the signal length to reduce noise and enhance reliability. Investors can position according to the prevailing market regime by selecting factors that have historically outperformed under each regime environment to minimise downside risk and maximise upside potential:
Risk-On Equity Factors = High Beta > Cyclicals > Low Volatility > Defensives.
Risk-Off Equity Factors = Defensives > Low Volatility > Cyclicals > High Beta.
Risk-On Fixed Income Factors = High Yield > Investment Grade > Treasuries.
Risk-Off Fixed Income Factors = Treasuries > Investment Grade > High Yield.
Risk-On Commodity Factors = Industrial Metals > Energy > Agriculture > Gold.
Risk-Off Commodity Factors = Gold > Agriculture > Energy > Industrial Metals.
Risk-On Currency Factors = Cryptocurrencies > Foreign Currencies > US Dollar.
Risk-Off Currency Factors = US Dollar > Foreign Currencies > Cryptocurrencies.
In summary, the Market Regime Index is a comprehensive macro risk-management tool that identifies the current market regime and helps investors align portfolio risk with the market’s underlying risk appetite. Its intuitive, color-coded design makes it an indispensable resource for investors seeking to navigate shifting market conditions and enhance risk-adjusted performance by selecting factors that have historically outperformed. While it has proven historically valuable, asset-specific characteristics and correlations evolve over time as market dynamics change. Indicator
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Cyclic Reversal Engine [AlgoPoint]Overview
Most indicators focus on price and momentum, but they often ignore a critical third dimension: time. Markets move in rhythmic cycles of expansion and contraction, but these cycles are not fixed; they speed up in trending markets and slow down in choppy conditions.
The Cyclic Reversal Engine is an advanced analytical tool designed to decode this rhythm. Instead of relying on static, lagging formulas, this indicator learns from past market behavior to anticipate when the current trend is statistically likely to reach its exhaustion point, providing high-probability reversal signals.
It achieves this by combining a sophisticated time analysis with a robust price-action confirmation.
How It Works: The Core Logic
The indicator operates on a multi-stage process to identify potential turning points in the market.
1. Market Regime Analysis (The Brain): Before analyzing any cycles, the indicator first diagnoses the current "personality" of the market. Using a combination of the ADX, Choppiness Index, and RSI, it classifies the market into one of three primary regimes:
- Trending: Strong, directional movement.
- Ranging: Sideways, non-directional chop.
- Reversal: An over-extended state (overbought/oversold) where a turn is imminent.
2. Adaptive Cycle Learning (The "Machine Learning" Aspect): This is the indicator's smartest feature. It constantly analyzes past cycles by measuring the bar-count between significant swing highs and swing lows. Crucially, it learns the average cycle duration for each specific market regime. For example, it learns that "in a strong trending market, a new swing low tends to occur every 35 bars," while "in a ranging market, this extends to 60 bars."
3. The Countdown & Timing Signal: The indicator identifies the last major swing high or low and starts a bar-by-bar countdown. Based on the current market regime, it selects the appropriate learned cycle length from its memory. When the bar count approaches this adaptive target, the indicator determines that a reversal is "due" from a timing perspective.
4. Price Confirmation (The Trigger): A signal is never generated based on timing alone. Once the timing condition is met (the cycle is "due"), the indicator waits for a final price-action confirmation. The default confirmation is the RSI entering an extreme overbought or oversold zone, signaling momentum exhaustion. The signal is only triggered when Time + Price Confirmation align.
How to Use This Indicator
- The Dashboard: The panel in the bottom-right corner is your command center.
- Market Regime: Shows the current market personality analyzed by the engine.
- Adaptive Cycle / Bar Count: This is the core of the indicator. It shows the target cycle length for the current regime (e.g., 50) and the current bar count since the last swing point (e.g., 45). The background turns orange when the bar count enters the "due zone," indicating that you should be on high alert for a reversal.
- BUY/SELL Signals: A label appears on the chart only when the two primary conditions are met:
The timing is right (Bar Count has reached the Adaptive Cycle target).
The price confirms exhaustion (RSI is in an extreme zone).
A BUY signal suggests a downtrend cycle is likely complete, and a SELL signal suggests an uptrend cycle is likely complete.
Key Settings
- Pivot Lookback: Controls the sensitivity of the swing point detection. Higher values will identify more significant, longer-term cycles.
- Market Regime Engine: The ADX, Choppiness, and RSI settings can be fine-tuned to adjust how the indicator classifies the market's personality.
- Require Price Confirmation: You can toggle the RSI confirmation on or off. It is highly recommended to keep it enabled for higher-quality signals. Indicator
Chandelier Exit Oscillator [LuxAlgo]The Chandelier Exit Oscillator is a technical analysis tool that provides insights into potential trend reversals, momentum shifts, and trend continuation patterns, helping traders pinpoint optimal exit points for both long and short positions.
By calculating trailing stop levels based on a multiple of the Average True Range (ATR), the oscillator visually indicates when prices move above or below these critical stop levels.
This script uniquely combines the Chandelier Exit indicator with an oscillator format, equipping traders with a versatile tool that leverages ATR-based levels for enhanced trend analysis.
🔶 USAGE
Displaying the Chandelier Exit as an oscillator allows traders to gauge trend momentum and strength, recognize potential reversals, and refine their market insights.
The Timeframe option specifies the timeframe used for calculations, enabling multi-timeframe analysis and allowing traders to align the indicator’s signals with broader or narrower market trends.
The Chandelier Exit Oscillator allows users to select between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
The Chandelier Exit Overlay allows users to enable or disable the display of Chandelier Exit levels directly on the price chart. When enabled, this overlay plots trailing stop levels for both long and short positions, helping traders visually monitor potential exit points and trend boundaries alongside the price action.
The Trend-based Bar Color feature allows users to color the bars on the price chart according to the current trend direction. This visual differentiation aids in quicker decision-making and provides a clearer understanding of market dynamics.
🔶 SETTINGS
🔹 Chandelier Exit Settings
Timeframe: Sets the timeframe for calculations, allowing multi-timeframe analysis.
ATR Length: Defines the number of bars used for calculating the Average True Range (ATR), which helps in setting Chandelier Exit levels.
ATR Multiplier: Adjusts the sensitivity of the Chandelier Exit lines based on the ATR. Higher values make the indicator more conservative, while lower values make it more responsive.
🔹 Chandelier Exit Oscillator
Chandelier Exit Oscillator: Allows users to choose between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
Oscillator Smoothing: Controls the level of smoothing applied to the oscillator. Higher smoothing values filter out minor fluctuations.
🔹 Chandelier Exit Overlay
Chandelier Exit Overlay: Enables or disables the display of Chandelier Exit levels directly on the price chart.
Trend-based Bar Colors: Allows users to color bars based on trend direction, enhancing the visual analysis of market direction.
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