CCT Pi Cycle Top/BottomPi Cycle Top/bottom: The Ultimate Market Cycle Indicator
Introduction
The Pi Cycle Top/bottom Indicator is one of the most reliable tools for identifying Bitcoin market cycle peaks and bottoms. Its effectiveness lies in the strategic combination of moving averages that historically align with major market cycle reversals. Unlike traditional moving average crossovers, this indicator applies an advanced iterative approach to pinpoint price extremes with higher accuracy.
This version, built entirely with Pine Script™ v6, introduces unprecedented precision in detecting both the Pi Cycle Top and Pi Cycle Bottom, eliminating redundant labels, optimizing visual clarity, and ensuring the indicator adapts dynamically to evolving market conditions.
What is the Pi Cycle Theory?
The Pi Cycle Top and Pi Cycle Bottom were originally introduced based on a simple yet profound discovery: key moving average crossovers consistently align with macro market tops and bottoms.
Pi Cycle Top: The crossover of the 111-day Simple Moving Average (SMA) and the 350-day SMA multiplied by 2 has historically signaled market tops with astonishing accuracy.
Pi Cycle Bottom: The intersection of the 150-day Exponential Moving Average (EMA) and the 471-day SMA has repeatedly marked significant market bottoms.
While traditional moving average strategies often suffer from lag and false signals, the Pi Cycle Indicator enhances accuracy by applying a range-based scanning methodology, ensuring that only the most critical reversals are detected.
How This Indicator Works
Unlike basic moving average crossovers, this script introduces a unique iteration process to refine the detection of Pi Cycle points. Here’s how it works:
Detecting Crossovers:
Identifies the Golden Cross (bullish crossover) and Death Cross (bearish crossover) for both the Pi Cycle Top and Pi Cycle Bottom.
Iterating Through the Cycle:
Instead of plotting a simple crossover point, this script scans the range between each Golden and Death Cross to identify the absolute lowest price (Pi Cycle Bottom) and highest price (Pi Cycle Top) within that cycle.
Precision Labeling:
The indicator dynamically adjusts label positioning:
If the price at the crossover is below the fast moving average → the label is placed on the moving average with a downward pointer.
If the price is above the fast moving average → the label is placed below the candle with an upward pointer.
This ensures optimal visibility and prevents misleading signal placement.
Advanced Pine Script v6 Features:
Labels and moving average names are only shown on the last candle, reducing chart noise while maintaining clarity.
Offers full user customization, allowing traders to toggle:
Pi Cycle Top & Bottom visibility
Moving average labels
Crossover labels
Why This Indicator is Superior
This script is not just another moving average crossover tool—it is a market cycle tracker designed for long-term investors and analysts who seek:
✔ High-accuracy macro cycle identification
✔ Elimination of false signals using an iterative range-based scan
✔ Automatic detection of market extremes without manual adjustments
✔ Optimized visuals with smart label positioning
✔ First-of-its-kind implementation using Pine Script™ v6 capabilities
How to Use It?
Bull Market Tops:
When the Pi Cycle Top indicator flashes, consider the potential for a market cycle peak.
Historically, Bitcoin has corrected significantly after these signals.
Bear Market Bottoms:
When the Pi Cycle Bottom appears, it suggests a macro accumulation phase.
These signals have aligned perfectly with historical cycle bottoms.
Final Thoughts
The Pi Cycle Top/bottom Indicator is a must-have tool for traders, investors, and analysts looking to anticipate long-term trend reversals with precision. With its refined methodology, superior label positioning, and cutting-edge Pine Script™ v6 optimizations, this is the most reliable version ever created.
Cari dalam skrip untuk "Cycle"
4-Year Cycles [jpkxyz]Overview of the Script
I wanted to write a script that encompasses the wide-spread macro fund manager investment thesis: "Crypto is simply and expression of macro." A thesis pioneered by the likes of Raoul Pal (EXPAAM) , Andreesen Horowitz (A16Z) , Joe McCann (ASYMETRIC) , Bob Loukas and many more.
Cycle Theory Background:
The 2007-2008 financial crisis transformed central bank monetary policy by introducing:
- Quantitative Easing (QE): Creating money to buy assets and inject liquidity
- Coordinated global monetary interventions
Proactive 4-year economic cycles characterised by:
- Expansionary periods (low rates, money creation)
- Followed by contraction/normalisation
Central banks now deliberately manipulate liquidity, interest rates, and asset prices to control economic cycles, using monetary policy as a precision tool rather than a blunt instrument.
Cycle Characteristics (based on historical cycles):
- A cycle has 4 seasons (Spring, Summer, Fall, Winter)
- Each season with a cycle lasts 365 days
- The Cycle Low happens towards the beginning of the Spring Season of each new cycle
- This is followed by a run up throughout the Spring and Summer Season
- The Cycle High happens towards the end of the Fall Season
- The Winter season is characterised by price corrections until establishing a new floor in the Spring of the next cycle
Key Functionalities
1. Cycle Tracking
- Divides market history into 4-year cycles (Spring, Summer, Fall, Winter)
- Starts tracking cycles from 2011 (first cycle after the 2007 crisis cycle)
- Identifies and marks cycle boundaries
2. Visualization
- Colors background based on current cycle season
- Draws lines connecting:
- Cycle highs and lows
- Inter-cycle price movements
- Adds labels showing:
- Percentage gains/losses between cycles
- Number of days between significant points
3. Customization Options
- Allows users to customize:
- Colors for each season
- Line and label colors
- Label size
- Background opacity
Detailed Mechanism
Cycle Identification
- Uses a modulo calculation to determine the current season in the 4-year cycle
- Preset boundary years include 2015, 2019, 2023, 2027
- Automatically tracks and marks cycle transitions
Price Analysis
- Tracks highest and lowest prices within each cycle
- Calculates percentage changes:
- Intra-cycle (low to high)
- Inter-cycle (previous high to current high/low)
Visualization Techniques
- Background color changes based on current cycle season
- Dashed and solid lines connect significant price points
- Labels provide quantitative insights about price movements
Unique Aspects
1. Predictive Cycle Framework: Provides a structured way to view market movements beyond traditional technical analysis
2. Seasonal Color Coding: Intuitive visual representation of market cycle stages
3. Comprehensive Price Tracking: Captures both intra-cycle and inter-cycle price dynamics
4. Highly Customizable: Users can adjust visual parameters to suit their preferences
Potential Use Cases
- Technical analysis for long-term investors
- Identifying market cycle patterns
- Understanding historical price movement rhythms
- Educational tool for market cycle theory
Limitations/Considerations
- Based on a predefined 4-year cycle model (Liquidity Cycles)
- Historic Cycle Structures are not an indication for future performance
- May not perfectly represent all market behavior
- Requires visual interpretation
This script is particularly interesting for investors who believe in cyclical market theories and want a visual, data-driven representation of market stages.
Super Cycle Low FinderHow the Indicator Works
1. Inputs
Users can adjust the cycle lengths:
Daily Cycle: Default is 40 days (within 36-44 days).
Weekly Cycle: Default is 26 weeks (182 days, within 22-31 weeks).
Yearly Cycle: Default is 4 years (1460 days).
2. Cycle Low Detection
Function: detect_cycle_low finds the lowest low over the specified period and confirms it with a bullish candle (close > open).
Timeframes: Daily lows are calculated directly; weekly and yearly lows use request.security to fetch data from higher timeframes.
3. Half Cycle Lows
Detected over half the cycle length, plotted to show mid-cycle strength or weakness.
4. Cycle Translation
Logic: Compares the position of the highest high to the cycle’s midpoint.
Output: "R" for right translated (bullish), "L" for left translated (bearish), displayed above bars.
5. Cycle Failure
Flags when a new low falls below the previous cycle low, indicating a breakdown.
6. Visualization
Cycle Lows: Diamonds below bars (yellow for daily, green for weekly, blue for yearly).
Half Cycle Lows: Circles below bars (orange, lime, aqua).
Translations: "R" or "L" above bars in distinct colors.
Failures: Downward triangles below bars (red, orange, purple).
Debt-Cycle vs Bitcoin-CycleDebt-Cycle vs Bitcoin-Cycle Indicator
The Debt-Cycle vs Bitcoin-Cycle indicator is a macro-economic analysis tool that compares traditional financial market cycles (debt/credit cycles) against Bitcoin market cycles. It uses Z-score normalization to track the relative positioning of global financial conditions versus cryptocurrency market sentiment, helping identify potential turning points and divergences between traditional finance and digital assets.
Key Features
Dual-Cycle Analysis: Simultaneously tracks traditional financial cycles and Bitcoin-specific cycles
Z-Score Normalization: Standardizes diverse data sources for meaningful comparison
Multi-Asset Coverage: Analyzes currencies, commodities, bonds, monetary aggregates, and on-chain metrics
Divergence Detection: Identifies when Bitcoin cycles move independently from traditional finance
21-Day Timeframe: Optimized for Long-term cycle analysis
What It Measures
Finance-Cycle (White Line)
Tracks traditional financial market health through:
Currencies: USD strength (DXY), global currency weights (USDWCU, EURWCU)
Commodities: Oil, gold, natural gas, agricultural products, and Bitcoin price
Corporate Bonds: Investment-grade spreads, high-yield spreads, credit conditions
Monetary Aggregates: M2 money supply, foreign exchange reserves (weighted by currency)
Treasury Bonds: Yield curve (2Y/10Y, 3M/10Y), term premiums, long-term rates
Bitcoin-Cycle (Orange Line)
Tracks Bitcoin market positioning through:
On-Chain Metrics:
MVRV Ratio (Market Value to Realized Value)
NUPL (Net Unrealized Profit/Loss)
Profit/Loss Address Distribution
Technical Indicators:
Bitcoin price Z-score
Moving average deviation
Relative Strength:
ETH/BTC ratio (altcoin strength indicator)
Visual Elements
White Line: Finance-Cycle indicator (positive = expansionary conditions, negative = contractionary)
Orange Line: Bitcoin-Cycle indicator (positive = bullish positioning, negative = bearish)
Zero Line: Neutral reference point
Interpretation
Cycle Alignment
Both positive: Risk-on environment, favorable for crypto
Both negative: Risk-off environment, caution warranted
Divergence: Potential opportunities or warning signals
Divergence Signals
Finance positive, Bitcoin negative: Bitcoin may be undervalued relative to macro conditions
Finance negative, Bitcoin positive: Bitcoin may be overextended or decoupling from traditional finance
Important Limitations
This indicator uses some technical and macro data but still has significant gaps:
⚠️ Limited monetary data - missing:
Funding rates (repo, overnight markets)
Comprehensive bond spread analysis
Collateral velocity and quality metrics
Central bank balance sheet details
⚠️ Basic economic coverage - missing:
GDP growth rates
Inflation expectations
Employment data
Manufacturing indices
Consumer confidence
⚠️ Simplified on-chain analysis - missing:
Exchange flow data
Whale wallet movements
Mining difficulty adjustments
Hash rate trends
Network fee dynamics
⚠️ No sentiment data - missing:
Fear & Greed Index
Options positioning
Futures open interest
Social media sentiment
The indicator provides a high-level cycle comparison but should be combined with comprehensive fundamental analysis, detailed on-chain research, and proper risk management.
Settings
Offset: Adjust the horizontal positioning of the indicators (default: 0)
Timeframe: Fixed at 21 days for optimal cycle detection
Use Cases
Macro-crypto correlation analysis: Understand when Bitcoin moves with or against traditional markets
Cycle timing: Identify potential tops and bottoms in both cycles
Risk assessment: Gauge overall market conditions across asset classes
Divergence trading: Spot opportunities when cycles diverge significantly
Portfolio allocation: Balance traditional and crypto assets based on cycle positioning
Technical Notes
Uses Z-score normalization with varying lookback periods (40-60 bars)
Applies HMA (Hull Moving Average) smoothing to reduce noise
Asymmetric multipliers for upside/downside movements in certain metrics
Requires access to FRED economic data, Glassnode, CoinMetrics, and IntoTheBlock feeds
21-day timeframe optimized for cycle analysis
Strategy Applications
This indicator is particularly useful for:
Cross-asset allocation - Decide between traditional finance and crypto exposure
Cycle positioning - Identify where we are in credit/debt cycles vs. Bitcoin cycles
Regime changes - Detect shifts in market leadership and correlation patterns
Risk management - Reduce exposure when both cycles turn negative
Disclaimer: This indicator is a cycle analysis tool and should not be used as the sole basis for investment decisions. It has limited coverage of monetary conditions, economic fundamentals, and on-chain metrics. The indicator provides directional insight but cannot predict exact timing or magnitude of market moves. Always conduct thorough research, consider multiple data sources, and maintain proper risk management in all investment decisions.
Bitcoin Cycles IndicatorBitcoin Cycles Indicator
The "Bitcoin Cycles Indicator" is designed to provide insights into the current market cycle of Bitcoin. It utilizes a combination of market cap real and total volume transfer to generate a visual representation of the market cycle.
Indicator Phases:
Cycle Lows (Green): Indicates potential low points in the cycle.
Under Valued (Aqua): Represents phases where Bitcoin might be undervalued.
Fair Market Value (Purple): Reflects periods considered to be at fair market value.
Aggressively Valued (Orange): Marks phases where Bitcoin might be aggressively valued.
Over Valued (Red): Suggests potential overvaluation of Bitcoin in the cycle.
Bitcoin Cycles can identify periods of increased risk when transaction behavior on-chain is indicative of major cycle highs. It also identifies areas of value opportunity where on-chain transaction behavior signals major cycle lows.
Historically, Bitcoin has exhibited cyclical behavior roughly every four years, coinciding with significant events known as "halvings."
While the historical correlation between Bitcoin's cycles and halving events is compelling, market dynamics are subject to change. Traders and investors should approach the market with a comprehensive strategy, incorporating multiple indicators and risk management techniques to navigate Bitcoin's evolving landscape.
Market Cycles
The Market Cycles indicator transforms market price data into a stochastic wave, offering a unique perspective on market cycles. The wave is bounded between positive and negative values, providing clear visual cues for potential bullish and bearish trends. When the wave turns green, it signals a bullish cycle, while red indicates a bearish cycle.
Designed to show clarity and precision, this tool helps identify market momentum and cyclical behavior in an intuitive way. Ideal for fine-tuning entries or analyzing broader trends, this indicator aims to enhance the decision-making process with simplicity and elegance.
Clock&Flow: Elements of Cycle Analysis 2nd partClock&Flow – Elements of Cycle Analysis (ECA) | Complete Suite
Elements of Cycle Analysis (ECA) is an advanced cyclic analysis suite designed to interpret the market through time, structure, strength, and energy, combining cycles, volatility, and participation into a single operational framework.
The suite consists of two complementary modules:
🔹ECA 1 – Cycles, Structure, and Volatility (Overlay: True)
ECA 1 is dedicated to the structural and temporal analysis of the market.
Cyclic SMAs (Cyclic Ratio) Moving averages are calibrated according to nominal cycles and timeframes to monitor multiple cycles simultaneously (from the lower cycle to the upper cycles). Crossovers between fast and slow SMAs certify the closing or transition of the cycle related to the faster SMA. The specific cycle is identified in the Info Table at the bottom right (for 15m - 1h - 2h - 1D timeframes). You can select the number of cycles to observe and the asset type to apply them to:
Index: Standard quotes (e.g., Cash sessions).
Future: Extended quotes (24h).
50-200: Classic institutional references for the medium-long term.
ATR-based Dynamic Cyclic Channels The channels represent a lower cycle and its upper counterpart; their width is determined by the observed timeframe and calculated based on average volatility (ATR). Volatility is not treated as noise but as a structural component of the cycle, essential for contextualizing excesses, compressions, and expansions.
Info Table and Quick Guide Dynamic tables automatically link SMAs, timeframes, and time cycles, providing an immediate reading of the current cyclic context.
Time Bands (Weekly / Daily) Temporal visualization helps identify cyclic pivots and rhythm transitions.
🔹 ECA 2 – Market Excesses, Strength, and Energy
ECA 2 analyzes how the market moves within the cyclic structure.
Excesses and Divergences (Cyclic Stochastic) An oscillator calibrated on the same cyclic ratio as the suite. Crossovers between the lower cycle (blue) and upper cycle (red) signal potential phase changes. In areas of excess, divergences often confirm the closing and restart of a cycle.
Directional Movement System (DMS) The ADX measures the strength of the movement, while +DI and -DI indicate direction. A simultaneous crossover of ADX, +DI, and -DI signals imminent acceleration, even before the strength is fully expressed.
Market Pulse – Real Market Energy The Market Pulse measures the amount of real energy moving through the market by relating three factors:
Price Velocity
Normalized Volume
Volatility (ATR relative to price)
These three factors are combined multiplicatively: if one is missing, the impulse weakens. The zero line represents a state of energy equilibrium; values above or below indicate a real imbalance (bullish or bearish). Note: Market Pulse is not a classic oscillator and should not be interpreted as overbought or oversold; it is used to evaluate the energetic quality of a movement.
Operational Convergence
The maximum operational effectiveness of the ECA suite is achieved when all modules converge on the same market phase.
When cyclic timing, volatility, price structure, trend strength, and movement energy align, the context signals a high-probability operational phase. The system is applicable to any timeframe or asset because it is not bound by dogmatic or subjective interpretations of technical or fundamental analysis; instead, it leverages what is actually happening in the market. Major chart patterns and Volume Profile (technically not includable in this specific suite) provide further confirmation.
Under these conditions, the signal does not originate from a single indicator but from the consistency of the entire system: time, volatility, and energy moving in the same direction.
Entries should always be accompanied by proper risk management.
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Clock&Flow – Elements of Cycle Analysis (ECA) | Suite Completa
Elements of Cycle Analysis (ECA) è una suite avanzata di analisi ciclica progettata per leggere il mercato attraverso tempo, struttura, forza ed energia, combinando cicli, volatilità e partecipazione in un unico framework operativo.
La suite è composta da due moduli complementari:
🔹 ECA 1 – Cicli, Struttura e Volatilità (overlay true)
ECA 1 è dedicato all’analisi strutturale e temporale del mercato.
SMA cicliche (ratio ciclica)
Le medie mobili sono calibrate in funzione dei cicli nominali e del timeframe per monitorare più cicli simultaneamente (dal ciclo inferiore fino ai cicli superiori).
Gli incroci tra SMA veloci e lente certificano la chiusura o transizione del ciclo correlato alla SMA più veloce. Il ciclo in questione è segnalato nella info table in basso a destra (per i time frame 15’ - 1h - 2h - 1D) Puoi selezionare il numero dei cicli da osservare e su quali asset applicarle (Index = quotazioni standard / Future = quotazioni estese / 50-200 i classici riferimenti istituzionali per il medio-lungo periodo
Canali ciclici dinamici basati su ATR
I canali rappresentano un ciclo inferiore e il suo superiore, l’ampiezza è data dal time frame osservato e calcolata sulla volatilità media (ATR).
La volatilità non è trattata come rumore, ma come componente strutturale del ciclo, utile per contestualizzare eccessi, compressioni ed espansioni.
Info Table e Quick Guide
Tabelle dinamiche collegano automaticamente SMA, timeframe e cicli temporali, fornendo una lettura immediata del contesto ciclico in corso.
Time Bands (Weekly / Daily)
La visualizzazione temporale aiuta a individuare pivot ciclici e transizioni di ritmo.
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
🔹 ECA 2 – Eccessi, Forza ed Energia del Mercato
ECA 2 analizza come il mercato si muove all’interno della struttura ciclica.
Eccessi e divergenze (Stochastic ciclico)
Oscillatore calibrato sulla stessa ratio ciclica della suite.
Gli incroci tra ciclo inferiore (blu) e superiore (rosso) segnalano potenziali cambi di fase; in area di eccesso, le divergenze certificano spesso la chiusura e ripartenza del ciclo.
Directional Movement System (DMS)
L’ADX misura la forza del movimento, mentre +DI e –DI ne indicano la direzione.
L’incrocio simultaneo di ADX, +DI e –DI segnala un’accelerazione imminente, anche in assenza di forza già espressa.
Market Pulse – Energia reale del mercato
Il Market Pulse misura quanta energia reale sta attraversando il mercato mettendo in relazione:
velocità del prezzo
volume normalizzato
volatilità (ATR rapportato al prezzo)
I tre fattori sono combinati in modo moltiplicativo: se uno manca, l’impulso si indebolisce.
La linea dello zero rappresenta una condizione di equilibrio energetico; valori sopra o sotto indicano uno sbilanciamento reale, rialzista o ribassista.
Il Market Pulse non è un oscillatore classico e non va interpretato in termini di ipercomprato o ipervenduto: serve a valutare la qualità energetica del movimento.
La massima efficacia operativa della suite ECA si ottiene quando tutti i moduli convergono sulla stessa fase di mercato.
Quando tempi ciclici, volatilità, struttura del prezzo, forza del trend ed energia del movimento risultano allineati, il contesto segnala una fase ad alta probabilità operativa.
È applicabile su qualunque time frame o asset perché non è vincolato a dogmatiche e soggettive interpretazioni di analisi tecnica - fondamentale ma sfrutta ciò che realmente sta accadendo sul mercato.
I principali pattern grafici e il Volume Profile (in questa suite tecnicamente non inseribili) forniscono ulteriori conferme e/o indicazioni.
In queste condizioni il segnale non nasce da un singolo indicatore, ma dalla coerenza dell’intero sistema: tempo, volatilità ed energia si muovono nella stessa direzione.
Gli ingressi vanno sempre accompagnati da una corretta gestione del rischio.
Clock&Flow: Elements of Cycle Analysis 1st partClock&Flow – Elements of Cycle Analysis (ECA) | Complete Suite
Elements of Cycle Analysis (ECA) is an advanced cyclic analysis suite designed to interpret the market through time, structure, strength, and energy, combining cycles, volatility, and participation into a single operational framework.
The suite consists of two complementary modules:
🔹 ECA 1 – Cycles, Structure, and Volatility (Overlay: True)
ECA 1 is dedicated to the structural and temporal analysis of the market.
Cyclic SMAs (Cyclic Ratio) Moving averages are calibrated according to nominal cycles and timeframes to monitor multiple cycles simultaneously (from the lower cycle to the upper cycles). Crossovers between fast and slow SMAs certify the closing or transition of the cycle related to the faster SMA. The specific cycle is identified in the Info Table at the bottom right (for 15m - 1h - 2h - 1D timeframes). You can select the number of cycles to observe and the asset type to apply them to:
Index: Standard quotes (e.g., Cash sessions).
Future: Extended quotes (24h).
50-200: Classic institutional references for the medium-long term.
ATR-based Dynamic Cyclic Channels The channels represent a lower cycle and its upper counterpart; their width is determined by the observed timeframe and calculated based on average volatility (ATR). Volatility is not treated as noise but as a structural component of the cycle, essential for contextualizing excesses, compressions, and expansions.
Info Table and Quick Guide Dynamic tables automatically link SMAs, timeframes, and time cycles, providing an immediate reading of the current cyclic context.
Time Bands (Weekly / Daily) Temporal visualization helps identify cyclic pivots and rhythm transitions.
🔹 ECA 2 – Market Excesses, Strength, and Energy
ECA 2 analyzes how the market moves within the cyclic structure.
Excesses and Divergences (Cyclic Stochastic) An oscillator calibrated on the same cyclic ratio as the suite. Crossovers between the lower cycle (blue) and upper cycle (red) signal potential phase changes. In areas of excess, divergences often confirm the closing and restart of a cycle.
Directional Movement System (DMS) The ADX measures the strength of the movement, while +DI and -DI indicate direction. A simultaneous crossover of ADX, +DI, and -DI signals imminent acceleration, even before the strength is fully expressed.
Market Pulse – Real Market Energy The Market Pulse measures the amount of real energy moving through the market by relating three factors:
Price Velocity
Normalized Volume
Volatility (ATR relative to price)
These three factors are combined multiplicatively: if one is missing, the impulse weakens. The zero line represents a state of energy equilibrium; values above or below indicate a real imbalance (bullish or bearish). Note: Market Pulse is not a classic oscillator and should not be interpreted as overbought or oversold; it is used to evaluate the energetic quality of a movement.
Operational Convergence
The maximum operational effectiveness of the ECA suite is achieved when all modules converge on the same market phase.
When cyclic timing, volatility, price structure, trend strength, and movement energy align, the context signals a high-probability operational phase. The system is applicable to any timeframe or asset because it is not bound by dogmatic or subjective interpretations of technical or fundamental analysis; instead, it leverages what is actually happening in the market. Major chart patterns and Volume Profile (technically not includable in this specific suite) provide further confirmation.
Under these conditions, the signal does not originate from a single indicator but from the consistency of the entire system: time, volatility, and energy moving in the same direction.
Entries should always be accompanied by proper risk management.
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Clock&Flow – Elements of Cycle Analysis (ECA) | Suite Completa
Elements of Cycle Analysis (ECA) è una suite avanzata di analisi ciclica progettata per leggere il mercato attraverso tempo, struttura, forza ed energia, combinando cicli, volatilità e partecipazione in un unico framework operativo.
La suite è composta da due moduli complementari:
🔹 ECA 1 – Cicli, Struttura e Volatilità (overlay true)
ECA 1 è dedicato all’analisi strutturale e temporale del mercato.
SMA cicliche (ratio ciclica)
Le medie mobili sono calibrate in funzione dei cicli nominali e del timeframe per monitorare più cicli simultaneamente (dal ciclo inferiore fino ai cicli superiori).
Gli incroci tra SMA veloci e lente certificano la chiusura o transizione del ciclo correlato alla SMA più veloce. Il ciclo in questione è segnalato nella info table in basso a destra (per i time frame 15’ - 1h - 2h - 1D) Puoi selezionare il numero dei cicli da osservare e su quali asset applicarle (Index = quotazioni standard / Future = quotazioni estese / 50-200 i classici riferimenti istituzionali per il medio-lungo periodo
Canali ciclici dinamici basati su ATR
I canali rappresentano un ciclo inferiore e il suo superiore, l’ampiezza è data dal time frame osservato e calcolata sulla volatilità media (ATR).
La volatilità non è trattata come rumore, ma come componente strutturale del ciclo, utile per contestualizzare eccessi, compressioni ed espansioni.
Info Table e Quick Guide
Tabelle dinamiche collegano automaticamente SMA, timeframe e cicli temporali, fornendo una lettura immediata del contesto ciclico in corso.
Time Bands (Weekly / Daily)
La visualizzazione temporale aiuta a individuare pivot ciclici e transizioni di ritmo.
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
🔹 ECA 2 – Eccessi, Forza ed Energia del Mercato
ECA 2 analizza come il mercato si muove all’interno della struttura ciclica.
Eccessi e divergenze (Stochastic ciclico)
Oscillatore calibrato sulla stessa ratio ciclica della suite.
Gli incroci tra ciclo inferiore (blu) e superiore (rosso) segnalano potenziali cambi di fase; in area di eccesso, le divergenze certificano spesso la chiusura e ripartenza del ciclo.
Directional Movement System (DMS)
L’ADX misura la forza del movimento, mentre +DI e –DI ne indicano la direzione.
L’incrocio simultaneo di ADX, +DI e –DI segnala un’accelerazione imminente, anche in assenza di forza già espressa.
Market Pulse – Energia reale del mercato
Il Market Pulse misura quanta energia reale sta attraversando il mercato mettendo in relazione:
velocità del prezzo
volume normalizzato
volatilità (ATR rapportato al prezzo)
I tre fattori sono combinati in modo moltiplicativo: se uno manca, l’impulso si indebolisce.
La linea dello zero rappresenta una condizione di equilibrio energetico; valori sopra o sotto indicano uno sbilanciamento reale, rialzista o ribassista.
Il Market Pulse non è un oscillatore classico e non va interpretato in termini di ipercomprato o ipervenduto: serve a valutare la qualità energetica del movimento.
La massima efficacia operativa della suite ECA si ottiene quando tutti i moduli convergono sulla stessa fase di mercato.
Quando tempi ciclici, volatilità, struttura del prezzo, forza del trend ed energia del movimento risultano allineati, il contesto segnala una fase ad alta probabilità operativa.
È applicabile su qualunque time frame o asset perché non è vincolato a dogmatiche e soggettive interpretazioni di analisi tecnica - fondamentale ma sfrutta ciò che realmente sta accadendo sul mercato.
I principali pattern grafici e il Volume Profile (in questa suite tecnicamente non inseribili) forniscono ulteriori conferme e/o indicazioni.
In queste condizioni il segnale non nasce da un singolo indicatore, ma dalla coerenza dell’intero sistema: tempo, volatilità ed energia si muovono nella stessa direzione.
Gli ingressi vanno sempre accompagnati da una corretta gestione del rischio.
Benner Cycles📜 Overview
The Benner Cycles indicator is a visually intuitive overlay that maps out one of the most historically referenced market timing models—Samuel T. Benner’s Cycles—directly onto your chart. This tool highlights three distinct types of market years: Panic, Peak, and Buy years, based on the rhythmic patterns first published by Benner in the late 19th century.
Benner's work is legendary among financial historians and cycle theorists. His original charts, dating back to the 1800s, remarkably anticipated economic booms, busts, and recoveries by following repeating year intervals. This modern adaptation brings that ancient rhythm into your TradingView workspace.
🔍 Background
Samuel T. Benner (1832–1913) was an Ohioan ironworks businessman and farmer who, after losing everything in the Panic of 1873, sought to uncover the secrets of economic cycles. His work led to the famous Benner's Cycle Chart, which forecasts business activity using repeatable intervals of panic, prosperity, and opportunity.
Benner’s method was based on a combination of numerological, agricultural, and empirical observations—not unlike early forms of technical and cyclical analysis. His legacy survives through a set of three rotating intervals for each market condition.
George Tritch was the individual responsible for preserving and publishing Samuel T. Benner’s economic cycle charts after Benner's death. While Benner was the original creator of the Benner Cycle, Tritch is known for reproducing and circulating the Benner chart in the early 20th century, helping it gain broader recognition among traders, economists, and financial historians.
🛠️ Features
Overlay Background Highlights shades the chart background to reflect the current year's cycle type
Configurable Year Range defines your own historical scope using Start Year and End Year
Fully Customizable Colors & Opacity
Live Statistics Table (optional) displays next projected Panic, Peak, and Buy years as well as current year’s market phase
Cycle Phase Logic (optional) prioritizes highlighting in order of Panic > Peak > Buy if overlaps occur
📈 Use Cases
Macro Timing Tool – Use the cycle phases to align with broader economic rhythms (especially useful for long-term investors or cycle traders).
Market Sentiment Guide – Panic years may coincide with recessions or major selloffs; Buy years may signal deep value or accumulation opportunities.
Overlay for Historical Studies – Perfect for comparing past major market movements (e.g., 1837, 1929, 2008) with their corresponding cycle phase. See known limitations below.
Forecasting Reference – Identify where we are in the repeating Benner rhythm and prepare for what's likely ahead.
⚠️ Limitations
❗ Not Predictive in Isolation: Use in conjunction with other tools.
❗ Calendar-Based Only: This indicator is strictly time-based and does not factor in price action, volume, or volatility.
❗ Historical Artifact, Not a Guarantee
❗ Data Availability: This indicator's historical output is constrained by the available price history of the underlying ticker. Therefore, it cannot display cycles prior to the earliest candle on the chart.
Dominant Cycle Detection OscillatorThis is a Dominant Cycle Detection Oscillator that searches multiple ranges of wavelengths within a spectrum. Choose one of 4 different dominant cycle detection methods (MESA MAMA cycle, Pearson Autocorrelation, Discreet Fourier Transform, and Phase Accumulation) to determine the most dominant cycles and see the historical results. Straight lines can indicate a steady dominant cycle; while Wavy lines might indicate a varying dominant cycle length. The steadier the cycle, the easier it may be to predict future events in that cycle (keep the log scale in mind when considering steadiness). The presence of evenly divisible (or harmonic) cycle lengths may also indicate stronger cycles; for example, 19, 38, and 76 dominant lengths for the 2x, 4x, and 8x cycles. Practically, a trader can use these cycle outputs as the default settings for other Hurst/cycle indicators. For example, if you see dominant cycle oscillator outputs of 38 & 76 for the 4x and 8x cycle respectively, you might want to test/use defaults of 38 & 76 for the 4x & 8x lengths in the bandpass, diamond/semi-circle notation, moving average & envelope, and FLD instead of the defaults 40 & 80 for a more fine-tuned analysis.
Muting the oscillator's historical lines and overlaying the indicator on the chart can visually cue a trader to the cycle lengths without taking up extra panes. The DFT Cycle lengths with muted historical lines have been overlayed on the chart in the photo.
The y-axis scale for this indicator's pane (just the oscillator pane, not the chart) most likely needs to be changed to logarithmic to look normal, but it depends on the search ranges in your settings. There are instructions in the settings. In the photo, the MESA MAMA scale is set to regular (not logarithmic) which demonstrates how difficult it can be to read if not changed.
In the Spectral Analysis chapter of Hurst's book Profit Magic, he recommended doing a Fourier analysis across a spectrum of frequencies. Hurst acknowledged there were many ways to do this analysis but recommended the method described by Lanczos. Currently in this indicator, the closest thing to the method described by Lanczos is the DFT Discreet Fourier Transform method.
Shoutout to @lastguru for the dominant cycle library referenced in this code. He mentioned that he may add more methods in the future.
deKoder | Business Cycle vs BitcoinThis indicator overlays Bitcoin's detrended momentum with the US ISM Manufacturing PMI (a key business cycle proxy) to visually dissect the relationship between crypto cycles and broader economic health.
Inspired by ongoing debates in crypto macro analysis (e.g., "Is there a 4-year halving cycle, or is it just the business cycle?" ), it highlights potential lead-lag dynamics - challenging the popular view that PMI strictly leads Bitcoin rallies and tops.
Key Features
• BTC Momentum Wave (Yellow/Orange Line):
Detrended deviation from Bitcoin's long-term "fair value" (24-month SMA).
Formula: ((close / sma(close, 24)) * 100 - 100) * 0.15
- Positive (yellow): BTC overvalued relative to trend | bullish momentum
- Negative (orange): Undervalued relative to trend | bearish momentum
• PMI Wave (Teal/Red Line):
ISM Manufacturing PMI centered at zero (raw PMI - 50, scaled ×3 for alignment).
- Positive (teal): Expansion (>50 raw) — economic tailwinds.
- Negative (red): Contraction (<50 raw) — headwinds, often linked to risk-off in assets.
• S&P 500 Momentum (White Line, Optional):
Similar deviation for SPX, showing how equities bridge BTC's volatility and PMI's smoothness.
• Divergence Highlights (Bar & Background Colors):
- Teal/Green Zones : BTC momentum positive while PMI negative → BTC signaling early recovery (potential lead by 1-3+ months at bottoms).
- Maroon/Red Zones : BTC momentum negative while PMI positive → BTC warning of rollovers (early bear signals).
- Neutral: No color — aligned cycles.
• Overlaid SMA on Price Chart :
24-month SMA for BTC (teal when price above, red when below) — quick fair value reference.
How to Interpret: Does BTC Lead the Business Cycle?
The chart flips the common meme ( "No 4-year cycle, it's just the business cycle" ) by visually emphasising BTC's potential as a forward-looking signal .
Historical cycles (2013–2025) show:
• BTC Leads at Bottoms : E.g., 2018–2019 and 2022 troughs — BTC momentum crosses positive 2–4 months before PMI, as speculative traders price in liquidity easing/recoveries ahead of manufacturing data.
• Coincident or BTC-Led at Tops : Peaks align closely (e.g., 2017, 2021), with PMI rollovers often coinciding or slightly leading the initial BTC euphoria fade. BTC then rolls over before PMI confirms later.
• Why? Markets are anticipatory (6–12 months forward), while PMI is a lagged survey snapshot. BTC, as a high-beta risk asset, amplifies early sentiment shifts before they hit factory orders/employment.
Inputs & Customization
• BTC Source (Default: BITSTAMP:BTCUSD)
• Fair Value MA Length (Default: 24 months)
• Show S&P (Default: False)
• PMI Multiplier (Default: 3.0)
• BTC Momentum Multiplier (Default: 0.15)
• Cap BTC Momentum at ±100 (Default: True)
• Toggle Early Cross Arrows, Bar/Background Deviation Colors, Difference Histogram
XRP Cycle Timing 42XRP Cycle Timing (42) is a time-based market structure indicator designed to visualize recurring cycle behavior using evenly spaced timing nodes. It focuses on when potential structural transitions occur rather than predicting price direction outright.
The indicator projects repeating cycle points across past, current, and future market phases, allowing traders to study rhythm, symmetry, and temporal alignment in price action.
How It Works
The script divides market activity into repeating cycles of fixed length (default: 42 bars) and marks six internally consistent timing points within each cycle. These points are plotted as vertical guides and labeled numerically (1–6).
Optional timing windows highlight tolerance zones around each cycle point, helping users observe how price interacts with these recurring time intervals.
In addition, the indicator can display HIT markers when short-term momentum conditions align with a cycle point. These events are intended as contextual confirmations, not trade signals.
Intended Use
This indicator is best used to:
Study market rhythm and repetition
Compare current price behavior to prior cycles
Identify late-cycle vs early-cycle conditions
Provide time-based context alongside other tools such as trend, momentum, or volatility indicators
It is not a standalone trading system and should be used in conjunction with other forms of analysis.
Asset-Specific Settings (Important)
⚠️ Current default settings are optimized specifically for XRP.
The cycle length, internal timing points, and momentum sensitivity were calibrated using XRP historical behavior.
While the indicator can be applied to other assets, optimal results typically require manual adjustment of:
Cycle length
Timing point spacing
Momentum confirmation settings
Different assets often exhibit different temporal structures, so users are encouraged to experiment and adapt settings accordingly.
Customization
Users can:
Adjust cycle length and timing points
Toggle past, current, and future cycle projections
Enable or disable timing windows
Enable or disable HIT confirmations
Modify visual styling for clarity
These options allow the indicator to be adapted to different timeframes, market conditions, and personal workflows.
Notes
This script focuses on time structure, not price targets.
Future cycle projections are for visual reference only and do not imply future price direction.
All drawings update dynamically with new market data.
Disclaimer
This indicator is provided for educational and analytical purposes only. It does not constitute financial advice. Trading involves risk, and users are responsible for their own decisions.
SemiCircle Cycle Notation PivotsFor decades, traders have sought to decode the rhythm of the markets through cycle theory. From the groundbreaking work of HM Gartley in the 1930s to modern-day cycle trading tools on TradingView, the concept remains the same: markets move in repeating waves with larger cycles influencing smaller ones in a fractal-like structure, and understanding their timing gives traders an edge to better anticipate future price movements🔮.
Traditional cycle analysis has always been manual, requiring traders to painstakingly plot semicircles, diamonds, or sine waves to estimate pivot points and time reversals. Drawing tools like semicircle & sine wave projections exist on TradingView, but they lack automation—forcing traders to adjust cycle lengths by eye, often leading to inconsistencies.
This is where SemiCircle Cycle Notation Pivots indicator comes in. Semicircle cycle chart notation appears to have evolved as a practical visualization tool among cycle theorists rather than being pioneered by a single individual; some key influences include HM Gartley, WD Gann, JM Hurst, Walter Bressert, and RayTomes. Built upon LonesomeTheBlue's foundational ZigZag Waves indicator , this indicator takes cycle visualization to the next level by dynamically detecting price pivots and then automatically plotting semicircles based on real-time cycle length calculations & expected rhythm of price action over time.
Key Features:
Automated Cycle Detection: The indicator identifies pivot points based on your preference—highs, lows, or both—and plots semicircle waves that correspond to Hurst's cycle notation.
Customizable Cycle Lengths: Tailor the analysis to your trading strategy with adjustable cycle lengths, defaulting to 10, 20, and 40 bars, allowing for flexibility across various timeframes and assets.
Dynamic Wave Scaling: The semicircle waves adapt to different price structures, ensuring that the visualization remains proportional to the detected cycle lengths and aiding in the identification of potential reversal points.
Automated Cycle Detection: Dynamically identifies price pivot points and automatically adjusts offsets based on real-time cycle length calculations, ensuring precise semicircle wave alignment with market structure.
Color-Coded Cycle Tiers: Each cycle tier is distinctly color-coded, enabling quick differentiation and a clearer understanding of nested market cycles.
Market Cycle Phases IndicatorOverview
The Market Cycle Phases Indicator is a powerful tool designed to help traders identify and visualize the different phases of market cycles. By distinguishing between Accumulation, Uptrend, Distribution, and Downtrend phases, this indicator provides a clear and color-coded representation of market conditions, aiding in better decision-making and strategy development. It is especially useful for long-term investors to observe and understand market cycles over extended periods. The phases are color-coded for easy identification: Green for Accumulation, Blue for Uptrend, Yellow for Distribution, and Red for Downtrend.
Key Features
Identifies four key market phases: Accumulation, Uptrend, Distribution, and Downtrend
Uses a combination of moving averages and volatility measures
Color-coded background for easy visualization of market phases
Adjustable parameters for moving average length, volatility length, and volatility threshold
Plots the moving average and Average True Range (ATR) for reference
Suitable for both short-term trading and long-term investing
Concepts Underlying the Calculations
The calculations behind the Market Cycle Phases Indicator are straightforward, combining the principles of moving averages and volatility measures:
Moving Average (MA): A simple moving average is used to determine the overall trend direction.
Average True Range (ATR): This measures market volatility over a specified period.
Volatility Threshold: A multiplier is applied to the ATR to distinguish between high and low volatility conditions.
How It Works
The indicator first calculates a moving average (MA) of the closing prices and the Average True Range (ATR) to measure market volatility. Based on the position of the price relative to the MA and the current volatility level, the indicator determines the current market phase:
Accumulation Phase: Price is below the MA, and volatility is low (Green background). This phase often indicates a period of consolidation and potential buying interest before an uptrend.
Uptrend Phase: Price is above the MA, and volatility is high (Blue background). This phase represents a strong upward movement in price, often driven by increased buying activity.
Distribution Phase: Price is above the MA, and volatility is low (Yellow background). This phase suggests a period of consolidation at the top of an uptrend, where selling interest may start to increase.
Downtrend Phase: Price is below the MA, and volatility is high (Red background). This phase indicates a strong downward movement in price, often driven by increased selling activity.
How Traders Can Use It
Traders can use the Market Cycle Phases Indicator to:
Identify potential entry and exit points based on market phase transitions.
Confirm trends and avoid false signals by considering both trend direction and volatility.
Develop and refine trading strategies tailored to specific market conditions.
Enhance risk management by recognizing periods of high and low volatility.
Observe long-term market cycles to make informed investment decisions.
Example Usage Instructions
Add the Market Cycle Phases Indicator to your chart.
Adjust the input parameters as needed:
Base Length: Default is 50.
Volatility Length: Default is 14.
Volatility Threshold: Default is 1.5.
Observe the color-coded background to identify the current market phase
Use the identified phases to inform your trading decisions:
Consider buying during the Accumulation or Uptrend phases.
Consider selling or shorting during the Distribution or Downtrend phases.
Combine with other indicators and analysis techniques for comprehensive market insights.
By incorporating the Market Cycle Phases Indicator into your trading toolkit, you can gain a clearer understanding of market dynamics and enhance your ability to navigate different market conditions, making it a valuable asset for long-term investing.
Cycle-Synced Channel Breakout📌 Cycle-Synced Channel Breakout – Detect Breakouts Confirmed by Candles and Momentum Cycles
📖 Overview
The Cycle-Synced Channel Breakout indicator is a precision breakout detection tool that combines the power of:
• Adaptive Keltner Channels
• Dominant Cycle Period Analysis (Ehlers-inspired)
• Candlestick Pattern Recognition (Engulfing)
This multi-layered approach helps identify true breakout opportunities by filtering out noise and false signals, making it ideal for swing traders and intraday traders seeking high-probability directional moves.
⚙️ How It Works
1. Keltner Channel Envelope
A dynamic volatility channel based on the EMA and ATR defines the upper and lower bounds of price movement.
2. Engulfing Candle Detection
The script detects strong bullish and bearish engulfing patterns, which often signal trend reversals or momentum continuations.
3. Dominant Cycle Momentum (Ehlers-inspired)
Using a smoothed power oscillator derived from a detrended price series, the indicator assesses whether momentum is accelerating during the breakout — filtering out weak moves.
4. Signal Confirmation Logic
A signal is only shown when:
• An engulfing pattern is detected, and
• Price breaks out of the Keltner Channel, and
• Momentum (cycle power) is rising
5. Visual Feedback
• Breakout signals are plotted with “BUY” or “SELL” labels
• Faded green/red background highlights confirmed breakouts
• Optional display of engulfing candles with triangle markers
⸻
🛠️ Key Features
• ✅ Adaptive Keltner Channels
• ✅ Bullish/Bearish Engulfing Candle Recognition
• ✅ Ehlers-style Cycle Momentum Confirmation
• ✅ Background highlights for confirmed breakouts
• ✅ Optional candle pattern visualization
• ✅ Lightweight and Pine v6 compatible
⸻
🧪 Inputs
• Keltner Length – EMA period for channel basis
• Multiplier – Multiplied with ATR to determine band width
• Cycle Lookback – Used to calculate smoothed cycle power
• Show Engulfing Candles? – Toggles candlestick signals
• Show Breakout Signals? – Toggles breakout labels and backgrounds
⸻
🧠 How to Use
• Look for “BUY” or “SELL” labels when:
• An engulfing candle breaks through the Keltner Channel
• Cycle momentum confirms strength behind the move
• The background color will faintly highlight the breakout direction.
• Use in combination with other trend or volume indicators for added confluence.
🔒 Notes
• This indicator is not repainting.
• It is designed for educational and research purposes only.
• Works across all timeframes and asset classes (stocks, crypto, forex, etc.)
Bitcoin Cycle High/Low with functional Alert [heswaikcrypt]Introduction
Just as machines are fine-tuned for maximum efficiency, trading indicators must evolve to meet the demands of ever-changing markets.
Credit goes to the initial author, @NoCreditsLeft I only improved the existing Pi-cycle indicator with a functional alert and included a bull mode indicator in the script. The alert can help you get a live alert at candle close when the cycle tops, bottoms, and the potential bull phase switch occurs.
Philip Swift’s Pi Cycle Top Indicator is a brilliant example of leveraging mathematical relationships to signal critical turning points in Bitcoin’s price cycles. Historically, it has identified market and local tops with some relative accuracy, often within three days, as demonstrated in all the previous bull run cycles.
At its core, the Pi Cycle Indicator derives its name from the mathematical constant π (pi), achieved by using simple moving averages (MAs) in a specific ratio: 𝜋 = Long MA/short MA
The Bull mode switch is calculated using a crossover of the short exponentia moving average and the long moving average.
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Knowing when Bitcoin reaches its top—and receiving timely alerts about it—is crucial for successful trading. The indicator is designed to signal;
Potential Bitcoin tops: Purple label
Potential Bitcoin bottoms : green Label, and
Parabolic swing : Yellow diamond shape (relating to the market switching to a potential bull mode)
"Please note: This indicator is tailored for Bitcoin using historical data analysis and should not be considered definitive. However accurate it might be."
Setting alerts
To set the alert conditions, select any alert function call to get alert whenever the conditions are met. The script is configured on dialy TF; you can set it on 1D or weekly TF.
Enjoy and Trade smartly
Lunar Cycle Tracker - (Moon + 3 Mercury Retrogrades)This script overlays the lunar and Mercury retrograde cycles directly onto your chart, helping traders visualize natural timing intervals that may influence market behavior.
Key Features:
🌑 New Moon & Full Moon Markers:
Vertical lines and labels indicate new and full moon events each month. You can fully customize their colors.
🌗 Last Quarter Moon Fill:
A soft pink background highlights the last quarter moon phase (from 7.4 days after the full moon to the next new moon).
🪐 Three Mercury Retrograde Zones:
Highlight up to three retrograde periods per year with customizable date inputs and background color. Great for spotting potential reversal or volatility windows.
Customization:
Moon event dates and colors
Manual input for Mercury retrograde periods (year, month, day)
Full compatibility with all timeframes (1H, 4H, daily, etc.)
Great for astro-cycle traders, Gann-based analysts, or anyone who respects time symmetry in the markets.
Fully customizable & works across all timeframes.
This tool was created by AngelArt as part of a larger astro-market model using lunar timing and planetary retrogrades for cycle-based market analysis.
Goertzel Cycle Period [Loxx]Goertzel Cycle Period is an indicator that uses Goertzel algorithm to extract the cycle period of ticker's price input to then be injected into advanced, adaptive indicators and technical analysis algorithms.
The following information is extracted from: "MESA vs Goertzel-DFT, 2003 by Dennis Meyers"
Background
MESA which stands for Maximum Entropy Spectral Analysis is a widely used mathematical technique designed to find the frequencies present in data. MESA was developed by J.P Burg for his Ph.D dissertation at Stanford University in 1975. The use of the MESA technique for stocks has been written about in many articles and has been popularized as a trading technique by John Ehlers.
The Fourier Transform is a mathematical technique named after the famed French mathematician Jean Baptiste Joseph Fourier 1768-1830. In its digital form, namely the discrete-time Fourier Transform (DFT) series, is a widely used mathematical technique to find the frequencies of discrete time sampled data. The use of the DFT has been written about in many articles in this magazine (see references section).
Today, both MESA and DFT are widely used in science and engineering in digital signal processing. The application of MESA and Fourier mathematical techniques are prevalent in our everyday life from everything from television to cell phones to wireless internet to satellite communications.
MESA Advantages & Disadvantage
MESA is a mathematical technique that calculates the frequencies of a time series from the autoregressive coefficients of the time series. We have all heard of regression. The simplest regression is the straight line regression of price against time where price(t) = a+b*t and where a and b are calculated such that the square of the distance between price and the best fit straight line is minimized (also called least squares fitting). With autoregression we attempt to predict tomorrows price by a linear combination of M past prices.
One of the major advantages of MESA is that the frequency examined is not constrained to multiples of 1/N (1/N is equal to the DFT frequency spacing and N is equal to the number of sample points). For instance with the DFT and N data points we can only look a frequencies of 1/N, 2/N, Ö.., 0.5. With MESA we can examine any frequency band within that range and any frequency spacing between i/N and (i+1)/N . For example, if we had 100 bars of price data, we might be interested in looking for all cycles between 3 bars per cycle and 30 bars/ cycle only and with a frequency spacing of 0.5 bars/cycle. DFT would examine all bars per cycle of between 2 and 50 with a frequency spacing constrained to 1/100.
Another of the major advantages of MESA is that the dominant spectral (frequency) peaks of the price series, if they exist, can be identified with fewer samples than the DFT technique. For instance if we had a 10 bar price period and a high signal to noise ratio we could accurately identify this period with 40 data samples using the MESA technique. This same resolution might take 128 samples for the DFT. One major disadvantage of the MESA technique is that with low signal to noise ratios, that is below 6db (signal amplitude/noise amplitude < 2), the ability of MESA to find the dominant frequency peaks is severely diminished.(see Kay, Ref 10, p 437). With noisy price series this disadvantage can become a real problem. Another disadvantage of MESA is that when the dominant frequencies are found another procedure has to be used to get the amplitude and phases of these found frequencies. This two stage process can make MESA much slower than the DFT and FFT . The FFT stands for Fast Fourier Transform. The Fast Fourier Transform(FFT) is a computationally efficient algorithm which is a designed to rapidly evaluate the DFT. We will show in examples below the comparisons between the DFT & MESA using constructed signals with various noise levels.
DFT Advantages and Disadvantages.
The mathematical technique called the DFT takes a discrete time series(price) of N equally spaced samples and transforms or converts this time series through a mathematical operation into set of N complex numbers defined in what is called the frequency domain. Why would we what to do that? Well it turns out that we can do all kinds of neat analysis tricks in the frequency domain which are just to hard to do, computationally wise, with the original price series in the time domain. If we make the assumption that the price series we are examining is made up of signals of various frequencies plus noise, than in the frequency domain we can easily filter out the frequencies we have no interest in and minimize the noise in the data. We could then transform the resultant back into the time domain and produce a filtered price series that hopefully would be easier to trade. The advantages of the DFT and itís fast computation algorithm the FFT, are that it is extremely fast in calculating the frequencies of the input price series. In addition it can determine frequency peaks for very noisy price series even when the signal amplitude is less than the noise amplitude. One of the disadvantages of the FFT is that straight line, parabolic trends and edge effects in the price series can distort the frequency spectrum. In addition, end effects in the price series can distort the frequency spectrum. Another disadvantage of the FFT is that it needs a lot more data than MESA for spectral resolution. However this disadvantage has largely been nullified by the speed of today's computers.
Goertzel algorithm attempts to resolve these problems...
What is the Goertzel algorithm?
The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of the individual terms of the discrete Fourier transform (DFT). It is useful in certain practical applications, such as recognition of dual-tone multi-frequency signaling (DTMF) tones produced by the push buttons of the keypad of a traditional analog telephone. The algorithm was first described by Gerald Goertzel in 1958.
Like the DFT, the Goertzel algorithm analyses one selectable frequency component from a discrete signal. Unlike direct DFT calculations, the Goertzel algorithm applies a single real-valued coefficient at each iteration, using real-valued arithmetic for real-valued input sequences. For covering a full spectrum, the Goertzel algorithm has a higher order of complexity than fast Fourier transform (FFT) algorithms, but for computing a small number of selected frequency components, it is more numerically efficient. The simple structure of the Goertzel algorithm makes it well suited to small processors and embedded applications.
The main calculation in the Goertzel algorithm has the form of a digital filter, and for this reason the algorithm is often called a Goertzel filter
Where is Goertzel algorithm used?
This package contains the advanced mathematical technique called the Goertzel algorithm for discrete Fourier transforms. This mathematical technique is currently used in today's space-age satellite and communication applications and is applied here to stock and futures trading.
While the mathematical technique called the Goertzel algorithm is unknown to many, this algorithm is used everyday without even knowing it. When you press a cell phone button have you ever wondered how the telephone company knows what button tone you pushed? The answer is the Goertzel algorithm. This algorithm is built into tiny integrated circuits and immediately detects which of the 12 button tones(frequencies) you pushed.
Future Additions:
Bartels test for cycle significance, testing output cycles for utility
Hodrick Prescott Detrending, smoothing
Zero-Lag Regression Detrending, smoothing
High-pass or Double WMA filtering of source input price data
References:
1. Burg, J. P., ëMaximum Entropy Spectral Analysisî, Ph.D. dissertation, Stanford University, Stanford, CA. May 1975.
2. Kay, Steven M., ìModern Spectral Estimationî, Prentice Hall, 1988
3. Marple, Lawrence S. Jr., ìDigital Spectral Analysis With Applicationsî, Prentice Hall, 1987
4. Press, William H., et al, ìNumerical Receipts in C++: the Art of Scientific Computingî,
Cambridge Press, 2002.
5. Oppenheim, A, Schafer, R. and Buck, J., ìDiscrete Time Signal Processingî, Prentice Hall,
1996, pp663-634
6. Proakis, J. and Manolakis, D. ìDigital Signal Processing-Principles, Algorithms and
Applicationsî, Prentice Hall, 1996., pp480-481
7. Goertzel, G., ìAn Algorithm for he evaluation of finite trigonometric seriesî American Math
Month, Vol 65, 1958 pp34-35.
Hybrid, Zero lag, Adaptive cycle MACD [Loxx]TASC's March 2008 edition Traders' Tips includes an article by John Ehlers titled "Measuring Cycle Periods," and describes the use of bandpass filters to estimate the length, in bars, of the currently dominant price cycle.
What are Dominant Cycles and Why should we use them?
Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode.
There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility.
We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month.
When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth .
Indicator Features
-Zero lag or Regular MACD/signal calculation
- Fixed or Band-pass Dominant Cycle for MACD and Signal MA period inputs
-10 different moving average options for both MACD and Signal MA calculations
-Separate Band-pass Dominant Cycle calculations for both MACD and Signal MA calculations
- Slow-to-Fast Band-pass Dominant Cycle input to tweak the ratio of MACD MA input periods as they relate to each other
Schaff Trend Cycle (STC) - t0rdn3Schaff Trend Cycle (STC)
By t0rdn3 (original STC by , now with more descriptive naming)
Description
The Schaff Trend Cycle (STC) is a momentum-based oscillator that combines the speed of a fast EMA crossover with cyclical normalization. Developed by Doug Schaff, it identifies market turning points more responsively than MACD or RSI.
How It Works
1. EMA Difference : Calculates the difference between two EMAs of the source series (default: close).
2. Cycle Percentage : Normalizes that difference to a 0–100 range over the cycle period.
3. Smoothing : Applies exponential smoothing twice—first to the cycle percentage, then to its normalized cycles—to reduce noise.
4. Final STC Line : Produces a smoothed oscillator oscillating between 0 and 100.
Alerts
- "STC turned down above 75" : Fires once when STC makes a local peak above the upper threshold ( 75 ).
- "STC turned up below 25" : Fires once when STC makes a local trough below the lower threshold ( 25 ).
Inputs
Cycle Period : 12 — Lookback in bars for normalization
Fast EMA Length : 26 — Period of the fast EMA
Slow EMA Length : 50 — Period of the slow EMA
Smoothing Factor : 0.5 — Exponential smoothing coefficient (0–1)
Usage
Readings above 75 indicate an overbought cycle; readings below 25 indicate an oversold cycle. Crossings of the 50 midline can confirm trend direction:
- STC rising through 50 → bullish shift
- STC falling through 50 → bearish shift
Combine STC with price action or other trend filters to improve signal quality. You can adjust the cycle period and EMA lengths to match different timeframes or instruments.
Market Cycle IndicatorThe Market Cycle Indicator is a tool that integrates the elements of RSI, Stochastic RSI, and Donchian Channels. It is designed to detect market cycles, enabling traders to enter and exit the market at the most opportune times.
This indicator provides a unique perspective on the market, combining multiple strategies into one unified and weighted approach. By factoring in the inputs from each of these popular technical analysis methods, it offers a more holistic view of the market trends and cycles.
Parameter Details:
Donchian Channels (DCO):
- donchianPeriod: Sets the period for the Donchian Channel calculation. Default is set to 14.
- donchianSmoothing: Sets the smoothing factor for the Donchian Channel calculation. Default is set to 3.
- donchianPrice: Selects the price type to be used in the Donchian Channel calculation. Default is set to the closing price.
Relative Strength Index (RSI):
- rsiPeriod: Sets the period for the RSI calculation. Default is set to 14.
- rsiSmoothing: Sets the smoothing factor for the RSI calculation. Default is set to 3.
- rsiPrice: Selects the price type to be used in the RSI calculation. Default is set to the closing price.
Stochastic RSI (StochRSI):
- srsiPeriod: Sets the period for the Stochastic RSI calculation. Default is set to 20.
- srsiSmoothing: Sets the smoothing factor for the Stochastic RSI calculation. Default is set to 3.
- srsiK: Sets the period for the %K line in the Stochastic RSI calculation. Default is set to 5.
- srsiD: Sets the period for the %D line in the Stochastic RSI calculation. Default is set to 5.
- srsiPrice: Selects the price type to be used in the Stochastic RSI calculation. Default is set to the closing price.
Weights:
- rsiWeight: Sets the weight for the RSI in the final aggregate calculation. Default is set to 1.
- srsiWeight: Sets the weight for the Stochastic RSI in the final aggregate calculation. Default is set to 1.
- dcoWeight: Sets the weight for the Donchian Channel in the final aggregate calculation. Default is set to 1.
Limits:
- limitHigh: Sets the upper limit for the indicator. Default is set to 80.
- limitLow: Sets the lower limit for the indicator. Default is set to 20.
By customizing these parameters, users can tweak the indicator to align with their own trading strategies and risk tolerance levels. Whether you're a novice or an experienced trader, the Comprehensive Market Cycle Indicator provides valuable insights into the market's behavior.
Uses library HelperTA
Hurst Cycle Channel Clone [LazyBear]Cycle Channel is loosely based on Hurst's nested channels. Basic idea is to identify and highlight the shorter cycles, in the context of higher degree cycles.
This indicator plots the shorter term (red) & medium term (green) cycles as channels. Some things to note:
As you can see the red channel keeps moving with in the bounds of green channel. When green breaches red channel, it usually signifies extreme market condition.
Both red & green channels provide support/resistance levels. Also, the green channel provides S/R levels to the inner red channel.
Movement of red channel with reference to green highlights reversal points, reducing momentum et al. For ex., point "(x)" in the chart shows how red channel failed to reach the upper green channel line and highlighted the local top.
Use this just like other bands/channels. I have more indicators derived from this idea, will post them later.
Some more examples:
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MSFT 1M:
DXY 1M:
IWM 1M:
More info:
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cyclicwave.blogspot.com
List of my free indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
(Support doc: bit.ly)
Cryptolabs Global Liquidity Cycle Momentum IndicatorCryptolabs Global Liquidity Cycle Momentum Indicator (LMI-BTC)
This open-source indicator combines global central bank liquidity data with Bitcoin price movements to identify medium- to long-term market cycles and momentum phases. It is designed for traders who want to incorporate macroeconomic factors into their Bitcoin analysis.
How It Works
The script calculates a Liquidity Index using balance sheet data from four central banks (USA: ECONOMICS:USCBBS, Japan: FRED:JPNASSETS, China: ECONOMICS:CNCBBS, EU: FRED:ECBASSETSW), augmented by the Dollar Index (TVC:DXY) and Chinese 10-year bond yields (TVC:CN10Y). This index is:
- Logarithmically scaled (math.log) to better represent large values like central bank balances and Bitcoin prices.
- Normalized over a 50-period range to balance fluctuations between minimum and maximum values.
- Compared to prior-year values, with the number of bars dynamically adjusted based on the timeframe (e.g., 252 for 1D, 52 for 1W), to compute percentage changes.
The liquidity change is analyzed using a Chande Momentum Oscillator (CMO) (period: 24) to measure momentum trends. A Weighted Moving Average (WMA) (period: 10) acts as a signal line. The Bitcoin price is also plotted logarithmically to highlight parallels with liquidity cycles.
Usage
Traders can use the indicator to:
- Identify global liquidity cycles influencing Bitcoin price trends, such as expansive or restrictive monetary policies.
- Detect momentum phases: Values above 50 suggest overbought conditions, below -50 indicate oversold conditions.
- Anticipate trend reversals by observing CMO crossovers with the signal line.
It performs best on higher timeframes like daily (1D) or weekly (1W) charts. The visualization includes:
- CMO line (green > 50, red < -50, blue neutral), signal line (white), Bitcoin price (gray).
- Horizontal lines at 50, 0, and -50 for improved readability.
Originality
This indicator stands out from other momentum tools like RSI or basic price analysis due to:
- Unique Data Integration: Combines four central bank datasets, DXY, and CN10Y as macroeconomic proxies for Bitcoin.
- Dynamic Prior-Year Analysis: Calculates liquidity changes relative to historical values, adjustable by timeframe.
- Logarithmic Normalization: Enhances visibility of extreme values, critical for cryptocurrencies and macro data.
This combination offers a rare perspective on the interplay between global liquidity and Bitcoin, unavailable in other open-source scripts.
Settings
- CMO Period: Default 24, adjustable for faster/slower signals.
- Signal WMA: Default 10, for smoothing the CMO line.
- Normalization Window: Default 50 periods, customizable.
Users can modify these parameters in the Pine Editor to tailor the indicator to their strategy.
Note
This script is designed for medium- to long-term analysis, not scalping. For optimal results, combine it with additional analyses (e.g., on-chain data, support/resistance levels). It does not guarantee profits but supports informed decisions based on macroeconomic trends.
Data Sources
- Bitcoin: INDEX:BTCUSD
- Liquidity: ECONOMICS:USCBBS, FRED:JPNASSETS, ECONOMICS:CNCBBS, FRED:ECBASSETSW
- Additional: TVC:DXY, TVC:CN10Y
