even_better_sinewave_mod
Description:
Even better sinewave was an indicator developed by John F. Ehlers (see Cycle Analytics for Trader, pg. 159), in which improvement to cycle measurements completely relies on strong normalization of the waveform. The indicator aims to create an artificially predictive indicator by transferring the cyclic data swings into a sine wave. In this indicator, the modified is on the weighted moving average as a smoothing function, instead of using the super smoother, aim to be more adaptive, and the default length is set to 55 bars.
Sinewave
smoothing = (7*hp + 6*hp_1 + 5*hp_2+ 4*hp_3 + 3*hp_4 + 2*hp5 + hp_6) /28
normalize = wave/sqrt(power)
Notes:
sinewave indicator crossing over -0.9 is considered to beginning of the cycle while crossing under 0.9 is considered as an end of the cycle
line color turns to green considered as a confirmation of an uptrend, while turns red as a confirmation of a downtrend
confidence of using indicator will be much in confirmation paired with another indicator such dynamic trendline e.g. moving average
as cited within Ehlers book Cycle Analytic for Traders, the indicator will be useful if the satisfied market cycle mode and the period of the dominant cycle must be estimated with reasonable accuracy
Other Example
"Cycle" için komut dosyalarını ara
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach.
This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits.
🔎 Features
Four Filter Types
1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings.
Real world application for low pass filter - Used in power supplies to provide a clean, stable power level.
2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility.
Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity.
3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility.
Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to.
4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action.
Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else
Configurable Parameters
• Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter.
• Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay).
• Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart.
• Source Selection – Apply filters to close, open, high, low, or custom sources.
Histograms for Comparison
• BS–LP Histogram – Shows distance between Band Stop and Low Pass filters.
• BP–HP Histogram – Highlights differences between Band Pass and High Pass filters.
Histograms give the visualization of a pseudo-MACD style indicator
Visual & Informational Aids
• Customizable colors for each filter line.
• Optional zero-line for histogram reference.
• On-chart info table summarizing active filters, cutoff settings, histograms, and filter order.
📊 Use Cases
Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction.
Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns.
Noise Suppression – Deploy Band Stop to remove specific choppy frequencies.
Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
BigNuts MacroScript that overlays key events that are coming up as the US economy shifts into fiscal dominance and global liquidity may peak. The specified dates were cross referenced from many cycle theories including Benner and Kondratieff key cycle dates as well work of Michel Howell for Global liquidity cycles and Luke Gromen analysis for Marco. The script also then cross references all these dates with any key celestial events that have had previous historical significance for market timing. The celestial events are key dates to watch but can be toggled on and off.
Fourier Oscillator Suite [SeerQuant]| Fourier Oscillator Suite |
WHY THE FOURIER TRANSFORM?
The Discrete Fourier Transform (DFT) extracts dominant cyclical patterns from market price data. Fourier analysis allows for the decomposition of price movements into frequency components, distinguishing trend-driven behaviour from noise and identifying oscillatory cycles within the market. This approach is effective in detecting dominant cycles in data, filtering out random fluctuations, and providing insights into price behaviour beyond conventional indicators.
This indicator applies a Fourier transform to the selected price source, converting it into a frequency-based signal. Instead of directly working with raw price data, the transformed signal acts as a smoothed and cycle-adjusted input for multiple technical indicators, enhancing their ability to adapt to market conditions dynamically.
Once the Fourier transform is applied, the extracted signal is processed through a suite of technical indicators, which are then normalized and aggregated into a single, actionable metric.
FEATURES AND BENEFITS
✅ Multi-Factor Aggregation:
By blending volatility, momentum, and volume-based oscillators, this indicator provides a comprehensive view of market conditions.
✅ Enhanced Signal Clarity:
Fourier transformation filters noise, revealing more reliable trading signals.
✅ Adaptive Market Sensitivity:
Unlike static oscillators, the Fourier-enhanced input dynamically adjusts to price shifts.
INDICATOR COMPONENTS
The Fourier Oscillator Suite aggregates the output of the transformed signal into three primary market components:
1. Volatility-Based Metrics
Commodity Channel Index (CCI) – Measures price deviation from a moving average.
Bollinger Band %B (BB%) – Evaluates price positioning within the Bollinger Bands.
Relative Volatility Index (RVI) – Identifies periods of heightened or subdued volatility.
2. Momentum Indicators
Relative Strength Index (RSI) – Gauges trend momentum and overbought/oversold levels.
Coppock Curve – A long-term momentum oscillator, often used for detecting major trend shifts.
Momentum (MOM), TRIX, and Stochastic Momentum Index (SMI) – Further refine momentum analysis.
3. Volume-Based Oscillators
Money Flow Index (MFI) – Measures price strength relative to volume.
Volume Zone Oscillator (VZO) – Detects accumulation and distribution phases.
Elder's Force Index (EFI) & Klinger Volume Oscillator (KVO) – Assess money flow strength.
These individual metrics are first normalized within a defined period and then smoothed using the selected moving average type. The final composite signal is derived from a weighted combination of the volatility, momentum, and volume components, each of which can be customized by the user.
SETTINGS
The indicator includes an extensive set of options for users to tailor its performance:
📌 Fourier Transform Parameters
Source Selection – Choose which price input (e.g., HLC3) is used for Fourier analysis.
Fourier Period – Defines the number of cycles analyzed for signal extraction.
📌 Aggregation Settings
Normalization Period – Controls how indicator values are scaled.
Smoothing Length – Adjusts the sensitivity of moving averages applied to oscillators.
Weight Adjustments – Fine-tune the impact of volatility, momentum, and volume-based inputs on the final signal.
📌 White Noise Control
White Noise Amplitude & Period – Filters out excessive market noise to improve signal clarity.
Enable/Disable White Noise Overlay – Provides optional visualization of filtered noise levels.
📌 Custom Styling & Visual Enhancements
Selectable Color Schemes – Choose from Default, Modern, Cool, or Monochrome.
Bull & Bear Color Customization – Define custom colors for positive/negative momentum shifts.
Adaptive Gradient Fills – Highlights market conditions dynamically based on oscillator movements.
The Fourier Oscillator Suite is designed for advanced traders seeking a noise-reduced, multi-dimensional view of market dynamics. By incorporating Fourier-transformed signals into a broad range of oscillators, this tool offers a highly adaptive, filter-enhanced, and customizable approach to momentum and trend analysis. Whether you are a trend follower, mean reversion trader, or volume analyst, this suite provides actionable insights with enhanced clarity.
Next Moon Phases 2025Next Moon Phases 2025
This custom indicator marks both past and future moon phases with vertical lines on your chart, providing a unique way to incorporate lunar cycles into your trading strategy.
This indicator is best used on the Daily timeframe. The lunar cycle is most effective when viewed in daily bars, providing the clearest correlation between moon phases and market trends.
Key Features:
Past Moon Phases (2016–2024): Marks the key lunar phases—New Moon, First Quarter, Full Moon, and Last Quarter—with vertical lines on the chart. Perfect for backtesting and analyzing the historical relationship between moon phases and market movements.
Future Moon Phases (2025): Unlike most indicators, this tool also projects upcoming moon phases for 2025, allowing you to plan ahead and anticipate potential market reactions based on future lunar events.
Adjustable Visibility: Customize which moon phases are displayed by toggling the visibility of each phase (New Moon, First Quarter, Full Moon, Last Quarter) with a simple control.
Why Moon Phases Matter in Trading:
Many traders believe that the lunar cycle can influence market sentiment and behavior. For example:
New Moon is often associated with new beginnings and potential market reversals.
Full Moon is thought to bring increased volatility and market climaxes.
First Quarter and Last Quarter may indicate periods of consolidation or momentum shifts.
By including both past and future moon phases, this indicator allows you to examine historical data while also planning for upcoming lunar events, giving you a strategic edge for both short-term and long-term trading decisions.
E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
Ehlers Stochastic Center Of Gravity [CC]The Stochastic Center Of Gravity Indicator was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 79-80), and this is one of the many cycle scripts that I have created but not published yet because, to be honest, I don't use cycle indicators in my everyday trading. Many of you probably do, so I will start publishing my big backlog of cycle-based indicators. These indicators work best with a trend confirmation or some other confirmation indicator to pair with it. The current cycle is the length of the trend, and since most stocks generally change their underlying trend quite often, especially during the day, it makes sense to adjust the length of this indicator to match the stock you are using it on. As you can see, the indicator gives constant buy and sell signals during a trend which is why I recommend using a confirmation indicator.
I have color-coded it to use lighter colors for normal signals and darker colors for strong signals. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Global M2 Money Supply Growth (GDP-Weighted)📊 Global M2 Money Supply Growth (GDP-Weighted)
This indicator tracks the weighted aggregate M2 money supply growth across the world's four largest economies: United States, China, Eurozone, and Japan. These economies represent approximately 69.3 trillion USD in combined GDP and account for the majority of global liquidity, making this a comprehensive macro indicator for analyzing worldwide monetary conditions.
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🔧 KEY FEATURES:
📈 GDP-Weighted Aggregation
Each economy is weighted proportionally by its nominal GDP using 2025 IMF World Economic Outlook data:
• United States: 44.2% (30.62 trillion USD)
• China: 28.0% (19.40 trillion USD)
• Eurozone: 21.6% (15.0 trillion USD)
• Japan: 6.2% (4.28 trillion USD)
The weights are fully adjustable through the indicator settings, allowing you to update them annually as new IMF forecasts are released (typically April and October).
⏱️ Multiple Time Period Options
Choose between three calculation methods to analyze different timeframes:
• YoY (Year-over-Year): 12-month growth rate for identifying long-term liquidity trends and cycles
• MoM (Month-over-Month): 1-month growth rate for detecting short-term monetary policy shifts
• QoQ (Quarter-over-Quarter): 3-month growth rate for medium-term trend analysis
🔄 Advanced Offset Function
Shift the entire indicator forward by 0-365 days to test lead/lag relationships between global liquidity and asset prices. Research suggests a 56-70 day lag between M2 changes and Bitcoin price movements, but you can experiment with different offsets for various assets (equities, gold, commodities, etc.).
🌍 Individual Country Breakdown
Real-time display of each economy's M2 growth rate with:
• Current percentage change (YoY/MoM/QoQ)
• GDP weight contribution
• Color-coded values (green = monetary expansion, red = contraction)
📊 Smart Overlay Capability
Displays directly on your main price chart with an independent left-side scale, allowing you to visually correlate global liquidity trends with any asset's price action without cluttering the chart.
🔧 Customizable GDP Weights
All GDP values can be adjusted through the indicator settings without editing code, making annual updates simple and accessible for all users.
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📡 DATA SOURCES:
All M2 money supply data is sourced from ECONOMICS (Trading Economics) for consistency and reliability:
• ECONOMICS:USM2 (United States)
• ECONOMICS:CNM2 (China)
• ECONOMICS:EUM2 (Eurozone)
• ECONOMICS:JPM2 (Japan)
All values are normalized to USD using current daily exchange rates (USDCNY, EURUSD, USDJPY) before GDP-weighted aggregation, ensuring accurate cross-country comparisons.
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💡 USE CASES & APPLICATIONS:
🔹 Liquidity Cycle Analysis
Track global monetary expansion/contraction cycles to identify when central banks are coordinating loose or tight monetary policies.
🔹 Market Timing & Risk Assessment
High M2 growth (>10%) historically correlates with risk-on environments and rising asset prices across crypto, equities, and commodities. Negative M2 growth signals monetary tightening and potential market corrections.
🔹 Bitcoin & Crypto Correlation
Compare with Bitcoin price using the offset feature to identify the optimal lag period. Many traders use 60-70 day offsets to predict crypto market movements based on liquidity changes.
🔹 Macro Portfolio Allocation
Use as a regime filter to adjust portfolio exposure: increase risk assets during liquidity expansion, reduce during contraction.
🔹 Central Bank Policy Divergence
Monitor individual country metrics to identify when major central banks are pursuing divergent policies (e.g., Fed tightening while China eases).
🔹 Inflation & Economic Forecasting
Rapid M2 growth often leads inflation by 12-18 months, making this a leading indicator for future inflation trends.
🔹 Recession Early Warning
Negative M2 growth is extremely rare and has preceded major recessions, making this a valuable risk management tool.
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📊 INTERPRETATION GUIDE:
🟢 +10% or Higher
Aggressive monetary expansion, typically during crises (2001, 2008, 2020). The COVID-19 period saw M2 growth reach 20-27%, which preceded significant inflation and asset price surges. Strong bullish signal for risk assets.
🟢 +6% to +10%
Above-average liquidity growth. Central banks are providing stimulus beyond normal levels. Generally favorable for equities, crypto, and commodities.
🟡 +3% to +6%
Normal/healthy growth rate, roughly in line with GDP growth plus 2% inflation targets. Neutral environment with moderate support for risk assets.
🟠 0% to +3%
Slowing liquidity, potential tightening phase beginning. Central banks may be raising rates or reducing balance sheets. Caution warranted for high-beta assets.
🔴 Negative Growth
Monetary contraction - extremely rare. Only occurred during aggressive Fed tightening in 2022-2023. Strong warning signal for risk assets, often precedes recessions or major market corrections.
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🎯 OPTIMAL USAGE:
📅 Recommended Timeframes:
• Daily or Weekly charts for macro analysis
• Monthly charts for very long-term trends
💹 Compatible Asset Classes:
• Cryptocurrencies (especially Bitcoin, Ethereum)
• Equity indices (S&P 500, NASDAQ, global markets)
• Commodities (Gold, Silver, Oil)
• Forex majors (DXY correlation analysis)
⚙️ Suggested Settings:
• Default: YoY calculation with 0 offset for current liquidity conditions
• Bitcoin traders: YoY with 60-70 day offset for predictive analysis
• Short-term traders: MoM with 0 offset for recent policy changes
• Quarterly rebalancers: QoQ with 0 offset for medium-term trends
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📋 VISUAL DISPLAY:
The indicator plots a blue line showing the selected growth metric (YoY/MoM/QoQ), with a dashed reference line at 0% to clearly identify expansion vs. contraction regimes.
A comprehensive table in the top-right corner displays:
• Current global M2 growth rate (large, prominent display)
• Individual country breakdowns with their GDP weights
• Color-coded growth rates (green for positive, red for negative)
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🔄 MAINTENANCE & UPDATES:
GDP weights should be updated annually (ideally in April or October) when the IMF releases new World Economic Outlook forecasts. Simply adjust the four GDP input parameters in the indicator settings - no code editing required.
The relative GDP proportions between the Big 4 economies change very gradually (typically <1-2% per year), so even if you update weights once every 1-2 years, the impact on the indicator's accuracy is minimal.
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💭 TRADING PHILOSOPHY:
This indicator embodies the principle that "liquidity drives markets." By tracking the combined M2 money supply of the world's largest economies, weighted by their economic size, you gain insight into the fundamental liquidity conditions that underpin all asset prices.
Unlike single-country M2 indicators, this GDP-weighted approach captures the true global picture, accounting for the fact that US monetary policy has 2x the impact of Japanese policy due to economic size differences.
Perfect for macro-focused traders, long-term investors, and anyone seeking to understand the "tide that lifts all boats" in financial markets.
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Created for traders and investors who incorporate global liquidity trends into their decision-making process. Best used alongside other technical and fundamental analysis tools for comprehensive market assessment.
⚠️ Disclaimer: M2 money supply is a lagging macroeconomic indicator. Past correlations do not guarantee future results. Always use proper risk management and combine with other analysis methods.
Gann Master System - CompleteGann Master Trading System - Multi-Factor Confluence Indicator
Advanced implementation of W.D. Gann methodology combining Square of 9 calculations, Octave Theory projections, Time Cycle analysis, and Planetary Aspect windows into a systematic confluence-based trading system.
Key Features:
Square of 9 geometric price levels (180°, 270°, 360° rotations)
Octave Theory targets with harmonic divisions (0.5x, 1x, 2x, 4x)
Time cycle tracking with sub-cycle analysis
10 configurable planetary aspect windows (manual input from ephemeris)
Automatic swing pivot detection
Multi-factor confluence scoring (0-20+ points)
Visual signals: Blue (score 3-6), Red (7-10), Purple (11+)
Real-time info panel with factor status
Built-in alerts for high-probability setups
How It Works:
System calculates multiple Gann factors simultaneously and awards points when price aligns with key levels. Higher confluence scores indicate stronger probability of reversal. Combines objective mathematics with astronomical timing for systematic edge.
Best For: Daily/4H charts on Gold, Forex majors, Indices
Signal Frequency: 2-4 high-quality setups per month (score 11+)
Recommended Min Score: 7 for trading, 11+ for highest probability
Setup Required: Configure Square of 9 pivot, Octave base range, Time cycle start date, and planetary aspect dates. See full documentation for detailed guide.
BTC Power-Law Decay Channel Oscillator (0–100)🟠 BTC Power-Law Decay Channel Oscillator (0–100)
This indicator calculates Bitcoin’s position inside its long-term power-law decay channel and normalizes it into an easy-to-read 0–100 oscillator.
🔎 Concept
Bitcoin’s long-term price trajectory can be modeled by a log-log power-law channel.
A baseline is fitted, then an upper band (excess/euphoria) and a lower band (capitulation/fear).
The oscillator shows where the current price sits between those bands:
0 = near the lower band (historical bottoms)
100 = near the upper band (historical tops)
📊 How to Read
Oscillator > 80 → euphoric excess, often cycle tops
Oscillator < 20 → capitulation, often cycle bottoms
Works best on weekly or bi-weekly timeframes.
⚙️ Adjustable Parameters
Anchor date: starting point for the power-law fit (default: 2011).
Smoothing days: moving average applied to log-price (default: 365 days).
Upper / Lower multipliers: scale the bands to align with historical highs and lows.
✅ Best Use
Combine with other cycle signals (dominance ratios, macro indicators, sentiment).
Designed for long-term cycle analysis, not intraday trading.
Fractal Wave MarkerFractal Wave Marker is an indicator that processes relative extremes of fluctuating prices within 2 periodical aspects. The special labeling system detects and visually marks multi-scale turning points, letting you visualize fractal echoes within unfolding cycles dynamically.
What This Indicator Does
Identifies major and minor swing highs/lows based on adjustable period.
Uses Phi in power exponent to compute a higher-degree swing filter.
Labels of higher degree appear only after confirmed base swings — no phantom levels, no hindsight bias. What you see is what the market has validated.
Swing points unfold in a structured, alternating rhythm . No two consecutive pivots share the same hierarchical degree!
Inspired by the Fractal Market Hypothesis, this script visualizes the principle that market behavior repeats across time scales, revealing structured narrative of "random walk". This inherent sequencing ensures fractal consistency across timeframes. "Fractal echoes" demonstrate how smaller price swings can proportionally mirror larger ones in both structure and timing, allowing traders to anticipate movements by recursive patterns. Cycle Transitions highlight critical inflection points where minor pivots flip polarity such as a series of lower highs progress into higher highs—signaling the birth of a new macro trend. A dense dense clusters of swing points can indicate Liquidity Zones, acting as footprints of institutional accumulation or distribution where price action validates supply and demand imbalances.
Visualization of nested cycles within macro trend anchors - a main feature specifically designed for the chartists who prioritize working with complex wave oscillations their analysis.
111D SMA / (350D SMA * 2)Indicator: Pi Cycle Ratio
This custom technical indicator calculates a ratio between two moving averages that are used for the PI Cycle Top indicator. The PI Cycle Top indicator triggers when the 111-day simple moving average (111D SMA) crosses up with the 350-day simple moving average (350D SMA *2).
The line value is ratio is calculated as:
Line Value = 111DSMA / (350D SMA × 2)
When the 111D SMA crosses with the 350D SMA triggering the PI Cycle Top, the value of the ratio between the two lines is 1.
This visualizes the ratio between the two moving averages into a single line. This indicator can be used for technical analysis for historical and future moves.
The Investment Clock Orbital GraphThe Investment Clock Orbital Graph is an advanced visualization tool designed to help traders and investors track economic cycles using a dynamic scatter plot of GDP growth vs. CPI inflation rates.
This indicator is a fusion of two powerful TradingView indicators:
LuxAlgo ’s Relative Strength Scatter Plot – A robust scatter plot for tracking relative strength.
The Investment Clock Indicator – A cycle-based approach to market rotation. This indicator contains more information regarding The Investment Clock.
By combining these approaches, the Investment Clock Orbital Graph enables traders to visualize economic momentum and inflationary trends in a unique, orbital-style scatter plot.
Key Features & Improvements
Orbital Graph Representation – Displays GDP growth and CPI inflation as a dynamic, evolving scatter plot, showing how the economy moves through different phases.
Quadrant-Based Market Regimes – Identifies four key economic phases:
1)🔥 Overheating (High Growth, High Inflation)
2)📉 Stagflation (Low Growth, High Inflation)
3)🤒 Recovery (High Growth, Low Inflation)
4)🎈 Reflation (Low Growth, Low Inflation)
Data-Driven Analysis – Utilizes FRED (Federal Reserve Economic Data) for accurate real-world GDP & CPI data.
Trailing Path of Economic Evolution – Tracks historical economic cycles over time to show momentum and cyclical movements.
Customizable Parameters – Set sustainable GDP growth and inflation thresholds, adjust trail length, and fine-tune scatter plot resolution.
Auto-Labeled Quadrants & Revised Accurate Market Guidance – Each quadrant includes newly updated tooltips and annotations (like ETF suggestions) to help traders make informed decisions.
Live Macro Forecasting Tool – Helps traders anticipate future market conditions, rate hikes/cuts, and sector rotations.
How to Use for Trading Decisions
The Investment Clock Orbital Graph helps traders and macro investors by identifying market phases and providing insights into asset class performance during different economic conditions.
📌 Step 1: Identify the Current Quadrant
Locate the most recent point on the orbital graph to see if the economy is in Overheating, Stagflation, Recovery, or Reflation.
📌 Step 2: Forecast Market Trends
The trajectory of the points can predict upcoming economic shifts:
Overheating → Stagflation ➡️ Expect economic slowdowns, bearish stock markets.
Stagflation → Reflation ➡️ Interest rate cuts likely, bonds and defensive stocks perform well.
Reflation → Recovery ➡️ Risk-on rally, technology and cyclicals perform best.
Recovery → Overheating ➡️ Commodities surge, inflation rises, and central banks intervene.
📌 Step 3: Align Trading & Investing Strategies
🔥 Overheating – Favor commodities & energy (Oil, Industrial Stocks, Materials).
📉 Stagflation – Favor defensive assets (Cash, Utilities, Healthcare).
🤒 Recovery – Favor growth stocks (Technology, Consumer Discretionary).
🎈 Reflation – Favor bonds, value stocks, and financials.
📌 Step 4: Monitor Trends Over Time
The indicator visualizes economic movement over multiple months, allowing traders to confirm long-term trends vs. short-term noise.
The Investment Clock Orbital Graph is an essential macro trading tool, providing a real-time visualization of economic conditions. By tracking GDP growth vs. CPI inflation, traders and investors can align their portfolios with major macroeconomic shifts, predict sector rotations, and anticipate central bank policy changes.
Bitcoin Reversal PredictorOverview
This indicator displays two lines that, when they cross, signal a potential reversal in Bitcoin's price trend. Historically, the high or low of a bull market cycle often occurs near the moment these lines intersect. The lines consist of an Exponential Moving Average (EMA) and a logarithmic regression line fitted to all of Bitcoin's historical data.
Inspiration
The inspiration for this indicator came from the PI Cycle Top indicator, which has accurately predicted past bull market peaks. However, I believe the PI Cycle Top indicator may not be as effective in the future. In that indicator, two lines cross to mark the top, but the extent of the cross has been diminishing over time. This was especially noticeable in the 2021 cycle, where the lines barely crossed. Because of this, I created a new indicator that I think will continue to provide reliable reversal signals in the future.
How It Works
The logarithmic regression line is fitted to the Bitcoin (BTCUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). This results in a steadily decreasing line. The EMA oscillates above and below this regression line. Each time the two lines cross, a vertical colored bar appears, indicating that Bitcoin's price momentum is likely to reverse.
Use Cases
- Price Bottoming:
Bitcoin often bottoms out when the EMA crosses below the logarithmic regression line.
- Price Topping:
In contrast, Bitcoin often peaks when the EMA crosses above the logarithmic regression line.
- Profitable Strategy:
Trading at the crossovers of these lines can be a profitable strategy, as these moments often signal significant price reversals.
Detrended Price Oscillator [NexusSignals]Detrended Price Oscillator (DPO) is a detrended price oscillator, used in technical analysis, strips out price trends in an effort to estimate the length of price cycles from peak to peak or trough to trough.
DPO is not a momentum indicator, instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle. (cf. to investopedia)
DPO indicator made by NexusSignals components :
a filled area that allow users to see easy the trend of an asset;
a sma moving average on chart (default length is 20)
a 20 sma on oscillator, both ma's are color coded to show uptrend / downtrend
a donchian channel applied to the dpo to show breakouts, breakdowns and resistances/support, reversals
few alerts for price crossing above ma, cross above the 0 dpo line, and for cross above and below the donchian channels top and bottom
How you can use DPO indicator ?
The detrended price oscillator (DPO) can be used for measuring the distance between peaks and troughs in the indicator that may help traders to make future decisions as they can locate the most recent trough and determine when the next one may occur in the meassured distance on oscillator between peaks and troughs.
You can use the indicator to find the potential price reversals, for example when the price of an asset is in a bearish trend and the dpo is bouncing from the donchian channel bottom, that may be a potential swing low for that asset, same thing in a bullish trend when the dpo rejecting at top of donchian channel may be a trend reversal, a pullback or swing high.
When DPO is above the 0 trend is in an uptrend and when dpo is below the zero the asset is possible to move into a downtrend.
Also crosses of DPO above and below the DPO moving average may signalising a trend change.
Fourier For Loop [BackQuant]Fourier For Loop
PLEASE Read the following, as understanding an indicator's functionality is essential before integrating it into a trading strategy. Knowing the core logic behind each tool allows for a sound and strategic approach to trading.
Introducing BackQuant's Fourier For Loop (FFL) — a cutting-edge trading indicator that combines Fourier transforms with a for-loop scoring mechanism. This innovative approach leverages mathematical precision to extract trends and reversals in the market, helping traders make informed decisions. Let's break down the components, rationale, and potential use-cases of this indicator.
Understanding Fourier Transform in Trading
The Fourier Transform decomposes price movements into their frequency components, allowing for a detailed analysis of cyclical behavior in the market. By transforming the price data from the time domain into the frequency domain, this indicator identifies underlying patterns that traditional methods may overlook.
In this script, Fourier transforms are applied to the specified calculation source (defaulted to HLC3). The transformation yields magnitude values that can be used to score market movements over a defined range. This scoring process helps uncover long and short signals based on relative strength and trend direction.
Why Use Fourier Transforms?
Fourier Transforms excel in identifying recurring cycles and smoothing noisy data, making them ideal for fast-paced markets where price movements may be erratic. They also provide a unique perspective on market volatility, offering traders additional insights beyond standard indicators.
Calculation Logic: For-Loop Scoring Mechanism
The For Loop Scoring mechanism compares the magnitude of each transformed point in the series, summing the results to generate a score. This score forms the backbone of the signal generation system.
Long Signals: Generated when the score surpasses the defined long threshold (default set at 40). This indicates a strong bullish trend, signaling potential upward momentum.
Short Signals: Triggered when the score crosses under the short threshold (default set at -10). This suggests a bearish trend or potential downside risk.'
Thresholds & Customization
The indicator offers customizable settings to fit various trading styles:
Calculation Periods: Control how many periods the Fourier transform covers.
Long/Short Thresholds: Adjust the sensitivity of the signals to match different timeframes or risk preferences.
Visualization Options: Traders can visualize the thresholds, change the color of bars based on trend direction, and even color the background for enhanced clarity.
Trading Applications
This Fourier For Loop indicator is designed to be versatile across various market conditions and timeframes. Some of its key use-cases include:
Cycle Detection: Fourier transforms help identify recurring patterns or cycles, giving traders a head-start on market direction.
Trend Following: The for-loop scoring system helps confirm the strength of trends, allowing traders to enter positions with greater confidence.
Risk Management: With clearly defined long and short signals, traders can manage their positions effectively, minimizing exposure to false signals.
Final Note
Incorporating this indicator into your trading strategy adds a layer of mathematical precision to traditional technical analysis. Be sure to adjust the calculation start/end points and thresholds to match your specific trading style, and remember that no indicator guarantees success. Always backtest thoroughly and integrate the Fourier For Loop into a balanced trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future .
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
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 TradingView 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 TradingView 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
Macro Valuation Oscillator (MVO)Macro Valuation Oscillator (MVO) is a macro-relative-strength indicator that compares the current valuation of an asset against three key benchmarks: Gold, USD, and Bond. It helps visualize how the asset performs in relative macro terms over time.
When the MVO line for Gold (yellow) moves below the neutral zone (0), it reflects relative weakness against gold. When it rises above +80, it indicates relative strength or potential overheating compared to gold. The same concept applies to USD (blue) and Bond (purple) lines.
The indicator highlights macro-rotation behavior, showing periods when assets outperform (green) or underperform (red) in relative value. It is mainly intended for daily charts, providing a clear visual framework for assessing long-term macro relationships and timing within broader market cycles.
Grandoc's MTF SeparatorsOverviewThis indicator, known as Grandoc's MTF Separators, draws vertical lines to mark key period boundaries across multiple timeframes (MTF—standing for "Multi-Timeframe," which allows visualization of higher-timeframe structures like daily or weekly pivots directly on lower-timeframe charts, such as 15-minute views). It helps traders align intraday decisions with broader market cycles. Additionally, it includes optional session open/close lines and closing price ranges for major forex sessions (Sydney, Tokyo, Frankfurt, London, New York). By combining customizable timeframe separators with session-specific visuals, it provides a comprehensive tool for multi-timeframe analysis without cluttering the chart. The script is optimized for efficiency, using arrays to manage drawings and respect TradingView's limits.© grandoc
Created: October 12, 2025
Last Modified: October 12, 2025
Version: 1.4 (Improved: Added Frankfurt session with independent toggles for open/close lines and closing range)Key FeaturesMulti-Timeframe (MTF) Separators: Configurable lines for up to four timeframes (e.g., daily, weekly, monthly), plotted as vertical lines extending across the chart. Supports periods from seconds to years—ideal for spotting MTF confluences, like a weekly open aligning with a London session start.
Session Management: Independent toggles for open/close lines and 30-minute closing ranges for five major sessions. Opens use dotted lines by default; closes use solid lines. Frankfurt session added for European traders.
Customization: Select reference points (session start or midnight day start), timezones, colors, line styles, and lookback limits to control visibility and performance.
Efficiency: Arrays limit drawings to user-defined lookback periods, preventing overload on historical data.
Originality and UsefulnessThis script extends standard timeframe detection by integrating session visuals with granular controls, including the new Frankfurt session for better European market coverage. Unlike generic separators, it uses a modular drawSeparator() function for consistent rendering across MTF and sessions, reducing code redundancy. Closing ranges highlight volatility in the final 30 minutes of each session, serving as dynamic support/resistance—unique for session-based strategies.Ideal for forex traders on instruments like EURUSD futures, where aligning intraday trades with higher-timeframe pivots and session transitions reduces noise. For instance, on a 15-minute EURUSD futures chart, daily separators mark session-aligned opens, while London closing ranges flag potential reversal zones before New York handover. The MTF aspect shines here: A weekly separator (orange solid line) crossing a NY open (blue dotted) signals a high-probability setup.How It WorksMulti-Timeframe SeparatorsDetection: Uses ta.change(time(tf, sess, tzz)) to identify period starts, where tf is the timeframe string (e.g., "1D"), sess is "0000-0000" for day-midnight or empty for session-start, and tzz is the timezone.
Drawing: On change, drawSeparator() creates a vertical line via line.new(x1=x_time, x2=x_time, y1=open, y2=open + syminfo.mintick, extend=extend.both). The mintick offset ensures it's a line, not a point. Lines extend both ways for full visibility.
Management: Pushed to dedicated arrays (e.g., sepArray1); excess trimmed with array.shift() and line.delete() based on lookback.
Visibility: Only plots if higher timeframe (timeframe.in_seconds(tf) > timeframe.in_seconds()).
Session Open and Close LinesDetection: For each session (e.g., Sydney: "2200-0700:1234567"), inSession = not na(time(timeframe.period, sessionStr, sessionTz)). Opens trigger on inSession and not inSession ; closes on not inSession and inSession .
Drawing Opens: Calls drawSeparator(true, sessionColor, sessionOpenWidth, sessionOpenStyle, sessionLookback, sessLinesArray) at time (bar open time). Uses global dotted style/width by default for easy identification of new sessions.
Drawing Closes: Similar call, but at time_close (previous bar close) for precise end-time alignment. Uses global solid style/width. All shared in one sessLinesArray for unified trimming.
Navigation Benefit: Dotted opens act as "entry gates" for session momentum; solid closes as "exit signals." Colors differentiate sessions (e.g., green for Sydney), enabling quick scans—e.g., spot Tokyo open overlaps on EURUSD futures for Asian bias.
Closing RangesDetection: For each closing window (e.g., London: "1630-1700:1234567"), inClose = not na(time(timeframe.period, closeStr, sessionTz)).
Tracking: On entry (inClose and not inClose ), initializes high/low at current bar's values and stores bar_index. During session, updates with math.max/min(nz(var, high/low), high/low).
Drawing: On exit (not inClose and inClose ), creates box.new(left=startBar, right=bar_index-1, top=high, bottom=low, border_color=sessionColor, bgcolor=color.new(sessionColor, 80)). 80% transparency for subtle shading; border matches session color.
Management: Pushed to rangeBoxesArray; trimmed like lines. Only draws if toggle enabled (defaults off to avoid clutter).
Navigation Benefit: Ranges visually encapsulate end-of-session volatility—e.g., on EURUSD futures, a tight NY range signals low-risk continuation, while wide ones warn of gaps. Ideal for range-break trades or as next-session S/R.
All session elements use the dedicated sessionTz for consistency, independent of separator timezone.Installation and UsageAdd via TradingView's Public Library (search "Grandoc's MTF Separators").
Settings Navigation: Separators (#1-4): Toggle/enable timeframes (e.g., D1 default); lookback hidden for simplicity.
Style: Per-separator colors/widths/styles (hidden widths); global open/close styles for sessions.
Preferences: "Session" vs. "Day" reference (tooltips explain EURUSD example); timezone (hidden, Day-only).
Session Settings: Unified timezone for all sessions.
Open Lines (g4): Per-session toggles (all on default).
Close Lines (g7): Per-session toggles (all on default).
Closing Ranges (g5): Per-session toggles (all off default—enable for S/R focus).
Session Times (g8): Edit strings (e.g., adjust for DST on EURUSD futures).
Colors & Lookback (g6): Session colors; shared lookback limits.
Apply to EURUSD futures (e.g., 15-min chart) with defaults: See green daily dots, orange weekly solids, session opens/closes in theme colors.
Pro Tip: On futures, set "Session" reference and exchange TZ for accurate rollover alignment; enable ranges for close-of-day liquidity plays. For MTF depth, layer #3 (monthly) over intraday for long-term bias.
LimitationsLines/ranges may cluster on low-timeframe charts; increase lookback or disable lower separators.
Session times are UTC defaults; manual DST tweaks needed for futures like EURUSD.
Time-based; avoid non-standard charts (e.g., Renko).
No built-in alerts—use TradingView's on line/box conditions.
Example Chart Open-source for community reuse (credit © grandoc). Published October 12, 2025. Questions? Comment below!
Hurst‑Millard FLD Normalized 2.0 – Signals "Hurst-Millard FLD Normalized 2.0 – Signals" indicator. It analyzes price data using a combination of moving averages (MAs) and the Hurst exponent to decompose price movements into trend, swing, and noise components, generating buy and sell signals. Here's a brief overview of its functionality:Inputs and Modes:Offers Auto Mode (cycle-based) and Manual Mode for configuring three moving averages: Long-Term (LT), Mid-Term (MT), and Short-Term (ST).
Auto Mode calculates MA lengths and offsets based on user-defined target cycle lengths (e.g., LT: 400 bars, MT: 100 bars, ST: 25 bars) with predefined offset ratios (0.2, 0.333, 0.5 respectively).
Manual Mode allows direct input of MA lengths and offsets.
Moving Averages:Computes Simple Moving Averages (SMAs) for LT, MT, and ST based on the closing price.
Applies forward-shifting to simulate future price behavior (e.g., maLongFwd shifts the LT MA by the specified offset).
Decomposition:Trend: Derived from the forward-shifted LT MA (maLongFwd).
Swing: Calculated as the difference between MT and LT MAs, scaled as a percentage of the closing price and amplified (using ATR or a manual factor).
Noise: Calculated as the difference between ST and MT MAs, similarly scaled and amplified.
Hurst Exponent:Estimates the Hurst exponent to measure the persistence or mean-reversion of the noise component.
Uses a 50-bar lookback period, smoothed with a 5-period SMA.
Signal Generation:Generates buy signals when the noise component is less than the swing component and their difference is within a user-defined proximity threshold (default: 25% of swing).
Generates sell signals when noise exceeds swing within the same threshold.
Signals are plotted as diamond shapes at the calculated proximity price level.
Visualization:Plots the trend, swing, and noise components as lines with customizable colors and gradient intensity based on their relative strength.
Optional debugging plots for raw forward-shifted MAs and proximity thresholds.
Displays a periodic debug table (every 100 bars) showing key metrics like close price, MAs, trend, swing, noise, Hurst exponent, and more.
Additional Features:Supports ATR-based amplification for scaling swing and noise.
Allows customization of signal colors, diamond offsets, and proximity thresholds.
Includes debugging options to visualize raw MAs and proximity bands.
In summary, this indicator uses cycle-based or manually configured MAs to break down price action into trend, swing, and noise, calculates the Hurst exponent for noise analysis, and generates buy/sell signals based on the relationship between swing and noise within a proximity threshold. It’s designed for traders to identify potential trend reversals or continuations.
QLitCycle QuarterlyQLITCYCLE
QLitCycle is an intraday cycle visualization tool that divides each trading day into multiple segments, helping traders identify time-based patterns and recurring market behaviors. By splitting the day into distinct periods, this indicator allows for better analysis of intraday rhythms, cycle alignment, and time-specific market tendencies.
It can be applied to various markets and timeframes, but is most effective on intraday charts where precise time segmentation can reveal valuable insights.
Dividers Timeframe/Session/Calendar-Based [ARTech]Dividers Timeframe/Session/Calendar-Based
This indicator provides customizable visual dividers for multiple timeframes, trading sessions, and calendar-based periods (daily, weekly, monthly). It helps traders visually separate chart areas by key time boundaries without cluttering the chart with price lines.
Key Features:
Multi-Timeframe Dividers: Select up to 4 timeframes (e.g., 60 min, 4 hours, daily, weekly) to display customizable lines marking the start of each timeframe’s candle.
Session Dividers: Define up to 4 trading sessions with user-defined time zones, colors, and active weekdays. The indicator highlights the session’s highest and lowest price range using a box, and compares the session’s opening and closing prices. Based on this comparison, it displays a green or red emoji to indicate bullish or bearish sessions, making it easy to identify session momentum visually.
Calendar-Based Dividers: Enable daily, weekly, or monthly background color zones, with individual toggles and color settings for each day, week, or month. Perfect for visually distinguishing trading periods.
Why use this indicator?
Divider Indicator helps keep your chart organized by visually segmenting timeframes, sessions, and calendar periods, aiding in better analysis of price action relative to important time boundaries.
How to Use
███████ Timezone ███████
A valid timezone name exactly as it appears in the chart’s lower-right corner (e.g. New York, London).
A valid UTC offset in ±H:MM or ±HH:MM format. Hours: 0–14 (zero-padded or not, e.g. +1:30, +01:30, -0:00). Minutes: Must be 00, 15, 30, or 45.
Examples;
UTC → ✅ Valid
Exchange → ✅ Valid
New York → ✅ Valid
London → ✅ Valid
Berlin → ✅ Valid
America/New York → ❌ Invalid. (Use "New York" instead)
+1:30 → ✅ Valid offset with single-digit hour
+01:30 → ✅ Valid offset with zero-padded hour
-05:00 → ✅ Valid negative offset
-0:00 → ✅ Valid zero offset
+1:1 → ❌ Invalid (minute must be 00, 15, 30, or 45)
+2:50 → ❌ Invalid (minute must be 00, 15, 30, or 45)
+15:00 → ❌ Invalid (hour must be 14 or below)
███████ Timeframe ███████
Use this section to display vertical divider lines at the opening of higher timeframe candles (e.g., 1H, 4H, Daily, Weekly). This helps visually separate price action according to larger market structures.
1. Enable a Timeframe:
Turn on one or more timeframes (e.g., 60, 240, D, W) by checking their respective toggle boxes.
2. Lines Mark Candle Opens:
Each active timeframe will draw a vertical line at the start of its candle , making it easier to align intraday moves with larger timeframe shifts.
3. Customize Line Style:
For each timeframe, you can individually set:
Line Style: Solid, dashed, or dotted.
Line Width: From 1 to 10 pixels.
Line Color: Pick any color to match your chart theme.
Opacity: Use transparent colors to avoid overwhelming the chart.
4. Use Multiple Timeframes Together:
You can enable multiple timeframe dividers simultaneously. To maintain clarity:
Use distinct colors for each timeframe.
Use thinner or dotted lines for lower timeframes and bolder lines for higher ones.
Match line style and color intensity to reflect timeframe importance. (e.g., a thick green solid line for Weekly, a thin gray dotted line for 1H)
5. Visual Tip:
These dividers are especially useful for identifying higher timeframe candle opens during intraday trading, spotting breaks above/below previous candle ranges, or aligning session-based strategies with higher timeframe trends.
███████ Session ███████
Use this section to visually highlight specific trading sessions (e.g., London, New York, Tokyo, Sydney) on your chart using time zones, session ranges, and optional weekday filters. This helps focus your analysis on active market hours.
1. Enable a Session:
Activate up to 4 separate trading sessions. Each session can be named (e.g., "London") and customized independently.
2. Set Session Time and Days:
Define session time using the hhmm-hhmm format. (e.g., 0800-1700)
Select which days of the week the session applies to (Sunday through Saturday)
Set your preferred time zone (UTC, Exchange, etc.) from the global settings.
3. Session Box Drawing:
For each active session, the indicator will:
Draw a background-colored box from the session’s start to end time.
Stretch the box to fit the highest and lowest price within that time window.
Draw an outline using customizable border style and width.
4. Session Labels and Directional Hints:
Optionally display the session’s name as a label.
The indicator compares the session’s opening and closing prices . Based on the result:
📈 Green emoji shows a bullish session (close >= open)
📉 Red emoji shows a bearish session (close < open)
5. Display Options:
Show all sessions, only the last session, or a specific number of previous sessions.
Customize label size, location (top/bottom), and whether it appears inside or outside the box.
Adjust background opacity to blend the sessions neatly into your chart.
6. Visual Tip:
Session boxes are particularly useful for:
Spotting repeated highs/lows during active trading hours.
Recognizing session-based breakouts or consolidations.
Comparing performance across different markets and time zones.
███████ Calendar-Based ███████
This section helps you visually segment your chart based on calendar periods: daily, weekly, and monthly. You can enable background color highlighting for individual days, weeks, or months to better track price movements within these time frames.
1. Enable Daily, Weekly, or Monthly Highlighting:
Toggle on the options for Daily, Weekly, and/or Monthly highlighting according to your needs.
2. Select Specific Days, Weeks, or Months:
For Daily, enable any combination of days (up to 7) to color-code.
For Weekly, enable up to 5 weeks per month to cover partial weeks.
For Monthly, enable up to 12 months with individual toggles and colors.
3. Customize Colors for Each Period:
Assign distinct colors to each day, week, or month for easy differentiation. Choose hues that stand out but avoid colors that are too close in tone for adjacent periods.
4. Background Opacity:
Adjust the opacity level of the background coloring to ensure it complements your chart without obscuring price data.
5. Handling Partial Weeks and Overlaps:
The weekly highlighting accounts for months that span 4 to 6 weeks by allowing toggles up to 5 weeks, including weeks that may partially overlap with previous or next months.
6. Visual Tip:
Calendar-based backgrounds are excellent for:
Quickly identifying price behavior within specific calendar units.
Comparing price action across days, weeks, or months.
Spotting seasonal trends or recurring patterns tied to calendar cycles.
CirclesCircles - Support & Resistance Levels
Overview
This indicator plots horizontal support and resistance levels based on W.D. Gann's mathematical approach of dividing 360 degrees by 2 and by 3. These divisions create natural price magnetism points that have historically acted as significant support and resistance levels across all markets and timeframes.
How It Works
360÷2 Levels (Blue): 5.63, 11.25, 33.75, 56.25, 78.75, etc.
360÷3 Levels (Red): 7.5, 15, 30, 37.5, 52.5, 60, 75, etc.
Both Levels (Yellow): 22.5, 45, 67.5, 90, 112.5, 135, 157.5, 180 - These are "doubly strong" as they appear in both calculations
Key Features
Auto-Scaling: Automatically adjusts for any price range (from $0.001 altcoins to $100K+ Bitcoin)
Manual Scaling: Choose from 0.001x to 1000x multipliers or set custom values
Full Customization: Colors, line widths, styles (solid/dashed/dotted)
Historical View: Option to show all levels regardless of current price
Clean Display: Adjustable label positioning and line extensions
Use Cases
Identify potential reversal zones before price reaches them
Set profit targets and stop losses at key mathematical levels
Confirm breakouts when price decisively moves through major levels
Works on all timeframes and all markets (stocks, crypto, forex, commodities)
Gann Theory
W.D. Gann believed that markets move in mathematical harmony based on geometric angles and time cycles. These 360-degree divisions represent natural balance points where price often finds support or resistance, making them valuable for both short-term trading and long-term analysis.
Perfect for traders who use:
Support/Resistance trading
Fibonacci levels
Pivot points
Mathematical/geometric analysis
Multi-timeframe analysis
