Kitaran
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.
Extended-hours Volume vs AVOL// ──────────────────────────────────────────────────────────────────────────────
// Extended-Hours Volume vs AVOL • HOW IT WORKS & HOW TO TRADE IT
// ──────────────────────────────────────────────────────────────────────────────
//
// ░ What this indicator is
// ------------------------
// • It accumulates PRE-MARKET (04:00-09:30 ET) and AFTER-HOURS (16:00-20:00 ET)
// volume on intraday charts and compares that running total with the stock’s
// 21-day average daily volume (“AVOL” by default).
// • Three live read-outs are shown in the data-window/table:
//
// AH – volume traded since the 16:00 ET close
// PM – volume traded before the 09:30 ET open
// Ext – AH + PM (updates in pre-market only)
// %AVOL – Ext ÷ AVOL × 100 (updates in pre-market)
//
// • It is intended for U.S. equities but the session strings can be edited for
// other markets.
//
// ░ Why it matters
// ----------------
// Big extended-hours volume almost always precedes outsized intraday range.
// By quantifying that volume as a % of “normal” trade (AVOL), you can filter
// which gappers and news names deserve focus *before* the bell rings.
//
// ░ Quick-start trade plan (educational template – tune to taste)
// ----------------------------------------------------------------
// 1. **Scan** the watch-list between 08:30-09:25 ET.
// ► Keep charts on 1- or 5-minute candles with “Extended Hours” ✔ checked.
// 2. **Filter** by `Ext` or `%AVOL`:
// – Skip if < 10 % → very low interest
// – Flag if 20-50 % → strong interest, Tier-1 candidate
// – Laser-focus if > 50 % → crowd favourite; expect liquidity & range
// 3. **Opening Range Breakout (long example)**
// • Preconditions: Ext ≥ 20 % & price above yesterday’s close.
// • Let the first 1- or 5-min bar complete after 09:30.
// • Stop-buy 1 tick above that bar (or pre-market high – whichever higher).
// • Initial stop below that bar low (or pre-market low).
// • First target = 1R or next HTF resistance.
// 4. **Red-to-Green reversal (gap-down long)**
// • Ext ≥ 30 % but pre-market gap is negative.
// • Enter as price reclaims yesterday’s close on live volume.
// • Stop under reclaim bar; scale out into VWAP / first liquidity pocket.
// 5. **Risk** – size so the full stop is ≤ 1 R of account. Volume fade or
// loss of %AVOL slope is a reason to tighten or exit early.
//
// ░ Tips
// ------
// • AVOL look-back can be changed in the input panel (21 days ⇒ ~1 month).
// • To monitor several symbols, open a multi-chart layout and sort your
// watch-list by %AVOL descending – leaders float to the top automatically.
// • Replace colour constants with hex if the namespace ever gets shadowed.
//
// ░ Disclaimer
// ------------
// For educational purposes only. Not financial advice. Trade your own plan.
//
// ──────────────────────────────────────────────────────────────────────────────
RSI Phan Ky FullThe RSI divergence indicator is like a magnifying glass that spots gaps between price swings and momentum. When price keeps climbing but RSI quietly sags, it’s a flashing U‑turn sign: the bulls are winded, and the bears are lacing up their boots. Flip it around—price is sliding yet RSI edges higher—and you’ve got bulls secretly stockpiling. Hidden divergences shore up the trend; regular divergences hint at a pivot. Blend those signals with overbought/oversold zones, support‑resistance, and volume, and RSI divergence turns into a radar that helps traders jump in with swagger and bail out just in time.
SuperTrend CorregidoThis script implements a SuperTrend indicator based on the Average True Range (ATR). It is designed to help traders identify trend direction and potential buy/sell opportunities with visual signals on the chart.
🔧 Key Features:
ATR-Based Trend Detection: Calculates trend shifts using the ATR and a user-defined multiplier.
Buy/Sell Signals: Displays "Buy" and "Sell" labels directly on the chart when the trend changes direction.
Visual Trend Lines: Plots green (uptrend) and red (downtrend) SuperTrend lines to highlight the current market bias.
Trend Highlighting: Optionally fills the background to emphasize whether the market is in an uptrend or downtrend.
Customizable Settings:
ATR period and multiplier
Option to switch ATR calculation method
Toggle for signal visibility and trend highlighting
🔔 Alerts Included:
SuperTrend Buy Signal
SuperTrend Sell Signal
SuperTrend Direction Change
This indicator is useful for identifying entries and exits based on trend momentum and can be used across various timeframes.
Yearly History Calendar-Aligned Price up to 10 Years)Overview
This indicator helps traders compare historical price patterns from the past 10 calendar years with the current price action. It overlays translucent lines (polylines) for each year’s price data on the same calendar dates, providing a visual reference for recurring trends. A dynamic table at the top of the chart summarizes the active years, their price sources, and history retention settings.
Key Features
Historical Projections
Displays price data from the last 10 years (e.g., January 5, 2023 vs. January 5, 2024).
Price Source Selection
Choose from Open, Low, High, Close, or HL2 ((High + Low)/2) for historical alignment.
The selected source is shown in the legend table.
Bulk Control Toggles
Show All Years : Display all 10 years simultaneously.
Keep History for All : Preserve historical lines on year transitions.
Hide History for All : Automatically delete old lines to update with current data.
Individual Year Settings
Toggle visibility for each year (-1 to -10) independently.
Customize color and line width for each year.
Control whether to keep or delete historical lines for specific years.
Visual Alignment Aids
Vertical lines mark yearly transitions for reference.
Polylines are semi-transparent for clarity.
Dynamic Legend Table
Shows active years, their price sources, and history status (On/Off).
Updates automatically when settings change.
How to Use
Configure Settings
Projection Years : Select how many years to display (1–10).
Price Source : Choose Open, Low, High, Close, or HL2 for historical alignment.
History Precision : Set granularity (Daily, 60m, or 15m).
Daily (D) is recommended for long-term analysis (covers 10 years).
60m/15m provides finer precision but may only cover 1–3 years due to data limits.
Adjust Visibility & History
Show Year -X : Enable/disable specific years for comparison.
Keep History for Year -X : Choose whether to retain historical lines or delete them on new year transitions.
Bulk Controls
Show All Years : Display all 10 years at once (overrides individual toggles).
Keep History for All / Hide History for All : Globally enable/disable history retention for all years.
Customize Appearance
Line Width : Adjust polyline thickness for better visibility.
Colors : Assign unique colors to each year for easy identification.
Interpret the Legend Table
The table shows:
Year : Label (e.g., "Year -1").
Source : The selected price type (e.g., "Close", "HL2").
Keep History : Indicates whether lines are preserved (On) or deleted (Off).
Tips for Optimal Use
Use Daily Timeframes for Long-Term Analysis :
Daily (1D) allows 10+ years of data. Smaller timeframes (60m/15m) may have limited historical coverage.
Compare Recurring Patterns :
Look for overlaps between historical polylines and current price to identify potential support/resistance levels.
Customize Colors & Widths :
Use contrasting colors for years you want to highlight. Adjust line widths to avoid clutter.
Leverage Global Toggles :
Enable Show All Years for a quick overview. Use Keep History for All to maintain continuity across transitions.
Example Workflow
Set Up :
Select Projection Years = 5.
Choose Price Source = Close.
Set History Precision = 1D for long-term data.
Customize :
Enable Show Year -1 to Show Year -5.
Assign distinct colors to each year.
Disable Keep History for All to ensure lines update on year transitions.
Analyze :
Observe how the 2023 close prices align with 2024’s price action.
Use vertical lines to identify yearly boundaries.
Common Questions
Why are some years missing?
Ensure the chart has sufficient historical data (e.g., daily charts cover 10 years, 60m/15m may only cover 1–3 years).
How do I update the data?
Adjust the Price Source or toggle years/history settings. The legend table updates automatically.
Bollinger Volatility AnalyzerThe Bollinger Volatility Analyzer (BVA) is a powerful enhancement of the traditional Bollinger Bands indicator, tailored to help traders identify volatility cycles and catch potential breakouts with better precision and timing. It builds upon the foundational concept of Bollinger Bands—using a moving average and standard deviation bands—but adds crucial insights into market contraction and expansion, which can be instrumental in timing entries and exits.
Here's how it works and why it's useful
At its core, the indicator calculates a moving average (called the "basis") and plots two bands—one above and one below—based on a multiple of standard deviation. These bands expand during volatile periods and contract during quiet ones. The width between these bands, normalized as a percentage of the basis, gives us a sense of how compressed or expanded the market currently is. When the band width drops below a user-defined threshold (like 2%), the script highlights this with an orange triangle below the bar. This is the "squeeze" condition, signaling a potential buildup of market energy—a kind of calm before the storm.
What makes this version of Bollinger Bands particularly powerful is that it not only detects squeezes, but also tells you when price breaks out of that squeeze range. If price closes above the upper band after a squeeze, a green "Breakout ↑" label is shown; if it closes below the lower band, a red "Breakout ↓" appears. These breakout labels act as entry signals, suggesting that volatility is returning and a directional move has begun.
This indicator is especially useful in markets that tend to alternate between consolidation and breakout phases, such as forex, crypto, and even individual stocks. Traders who look for early signs of momentum—whether for swing trading, scalping, or position building—can benefit from this tool. During a quiet market phase, the indicator warns you that a move might be coming; when the move starts, it tells you the direction.
In fast-moving markets, BVA helps filter out noise by focusing only on high-probability conditions: quiet consolidation followed by a strong breakout. It’s not a complete system by itself—it works best when paired with volume confirmation or oscillators like RSI—but as a volatility trigger and directional guide, it’s a reliable component of a trading workflow.
MA Dispersion+MA Dispersion+ — read the “breathing space” between your moving-averages
Get instant feedback on trend strength, volatility expansion and mean-reversion — across any timeframe.
MA Dispersion+ turns the humble moving-average stack into a single, easy-to-read oscillator that tells you at a glance whether price is coiling or fanning out.
🧩 What it does
Plugs into your favourite MA setup
• Pick the classic 5 / 20 / 50 / 200 lengths or disable any combination with one click.
• Choose the MA engine you trust — SMA, EMA, RMA, VWMA or WMA.
• Works on any timeframe thanks to TradingView’s security() engine.
Measures “spread”
For every bar it calculates the absolute distance of each selected MA from their average.
The tighter the stack, the lower the value; the wider the fan, the higher the value.
Adds professional-grade controls
• Weighting — let short-term MAs dominate (Inverse Length), keep everything equal, or dial in your own custom weights.
• Normalisation — convert the raw distance into a percentage of price, ATR multiples, or scale by the MAs’ own mean so you can compare symbols of any price or volatility.
🔍 How traders use it
Trend confirmation – rising dispersion while price breaks out = momentum is genuine.
Volatility squeeze – dispersion parking near zero warns that a big move is loading.
Multi-TF outlook – drop one pane per timeframe (e.g. 5 m, 1 h, 1 D) and see which layer of the market is driving.
Mean-reversion plays – spikes that fade quickly often coincide with exhaustion and snap-backs.
⚙️ Quick-start
Add MA Dispersion+ to your chart.
Set the pane’s timeframe in the first input.
Tick the MA lengths you actually use.
(Optional) Pick a weighting scheme and a normaliser.
Repeat the indicator for as many timeframes as you like — each instance keeps its own settings.
✨ Why you’ll love it
Zero clutter – one orange line tells you what four separate MAs whisper.
Configurable yet bullet-proof – all lengths are hard-coded constants, so Pine never complains.
Context aware – normalisation lets you compare BTC’s $60 000 chaos with EURUSD’s four--decimals calm.
Lightweight – no labels, no drawings, no background processing — perfect for mobile and multi-pane layouts.
Give MA Dispersion+ a try and let your charts breathe — you’ll never look at moving-average ribbons the same way again.
Happy trading!
LANZ Strategy 2.0🔷 LANZ Strategy 2.0 — London Breakout Confirmation with Structural Swing Protection
LANZ Strategy 2.0 is a structured trading system that leverages the last confirmed market direction before the London session to define directional bias and manage trades based on key structural swing levels. It is tailored for intraday traders looking to capitalize on early London volatility with built-in risk management and visual clarity.
🧠 Core Components:
Directional Confirmation (Pre-London Bias): Validates the last breakout or structural move from the 15-minute timeframe before 02:15 a.m. New York time (start of the London session), establishing the expected market direction.
Time-Based Execution: Executes potential entries strictly at 02:15 a.m. NY time, using market structure to support Long or Short bias.
Dynamic Swing-Based SL System: Allows user to select between three SL protection models: First Swing (most recent structural point) Second Swing (prior level) Total Coverage (includes both swings + extra buffer) This supports flexibility based on trader profile or market conditions.
Visual Risk Mapping: All SL and TP levels are clearly plotted.
End-of-Session Management: Positions are automatically evaluated for closure at 11:45 a.m. NY time. SL, TP, or manual close outcomes are labeled accordingly.
📊 Visual Features:
Labels for 1st and 2nd swing levels upon entry.
Dynamic lines projecting SL/TP levels toward the end of the session.
Session background coloring for Pre-London, Execution, and NY sessions.
Real-time percentage outcome labels (+2.00%, -1.00%, or net % at session end).
Automatic deletion of previous visuals on new entries for clean charting.
⚙️ How It Works:
Detects last structural breakout on the 15m timeframe before 02:15 a.m. NY.
On the 02:15 a.m. candle, executes a Long or Short logic entry.
Plots corresponding SL and TP based on selected swing model.
Monitors price action: If TP or SL is hit, labels it accordingly. If no exit is hit, trade closes manually at 11:45 a.m. NY with net result shown.
Optional logic to reverse entries if market structure breaks before execution.
🔔 Alerts:
Daily execution alert at 02:15 a.m. NY (prompting manual review or action).
Optional alert logic can be extended for SL/TP hits or structure breaks.
📝 Notes:
Designed for semi-automated or discretionary intraday trading.
Best used on Forex pairs or indices with strong London session behavior.
Adjustable parameters include session hours, swing SL type, and buffer settings.
Credits:
Developed by LANZ, this script combines time-based execution with dynamic structure protection, offering a disciplined framework for participating in the London session breakout with clear visuals and risk logic.
Divergence Macro Sentiment Indicator (DMSI)The Divergence Macro Sentiment Indicator (DMSI)
Think of DMSI as your daily “mood ring” for the markets. It boils down the tug-of-war between growth assets (S&P 500, copper, oil) and safe havens (gold, VIX) into one clear histogram—so you instantly know if the bulls have broad backing or are charging ahead with one foot tied behind.
🔍 What You’re Seeing
Green bars (above zero): Risk-on conviction.
Equities and commodities are rallying while gold and volatility retreat.
Red bars (below zero): Risk-off caution.
Gold or VIX are climbing even as stocks rise—or stocks aren’t fully joined by oil/copper.
Zero line: The line in the sand between “full-steam ahead” and “proceed with care.”
📈 How to Read It
Cross-Zero Signals
Bullish trigger: DMSI flips up through zero after a red stretch → fresh long entries.
Bearish trigger: DMSI tumbles below zero from green territory → tighten stops or go defensive.
Divergence Warnings
If SPX makes new highs but DMSI is rolling over (lower green bars or red), that’s your early red flag—rallies may fizzle.
Strength Confirmation
On pullbacks, only buy dips when DMSI ≥ 0. When DMSI is deeply positive, you can be more aggressive on position size or add leverage.
💡 Trade Guidance & Use Cases
Trend Filter: Only take your S&P or sector-ETF long setups when DMSI is non-negative—avoids hollow rallies.
Macro Pair Trades:
Deep red DMSI: go long gold or gold miners (GLD, GDX).
Strong green DMSI: lean into cyclicals, industrials, even energy names.
Risk Management:
Scale out as DMSI fades into negative territory mid-trade.
Scale in or add to winners when it stays bullish.
Swing Confirmation: Overlay on any oscillator or price-pattern system—accept signals only when the macro tide is flowing in your favour.
🚀 Why It Works
Markets don’t move in a vacuum. When stocks rally but the “real-economy” metals and volatility aren’t cooperating, something’s off under the hood. DMSI catches those cross-asset cracks before price alone can—and gives you an early warning system for smarter entries, tighter risk, and bigger gains when the macro trend really kicks in.
Vietnamese Market Structure With CountersThis indicator is designed to track Market Structure with Swing-Low Breakdowns and Swing-High Breakups specifically tailored for the Vietnamese stock market, though it can be applied elsewhere too. By default, it uses a 10-period EMA to dynamically detect key turning points in price action and count significant breakdowns or breakups from previous swing levels.
As an open source, you can modify the source code to match your needs.
What it does:
Detects when price breaks below previous swing lows or above previous swing highs.
Plots swing levels for both highs and lows.
Displays labeled counters on the chart to show how many consecutive breakdowns or breakups have occurred.
Helps traders identify trend shifts and possible exhaustion in moves.
Why it's useful:
This tool is great for visually tracking market momentum and structure changes — especially in trending or volatile environments. It emphasizes structure over indicators, helping you understand price behavior in a simplified, intuitive way.
License:
This script is published under the Mozilla Public License 2.0. Feel free to use, modify, and contribute!
Created with care by @doqkhanh.
If you find it useful, consider leaving a comment or sharing it with others!
Bitcoin Impact AnalyzerSummary of the "Bitcoin Impact Analyzer" script, the adjustments users can make, and an explanation of what the chart and table represent:
Script Summary:
The "Bitcoin Impact Analyzer" script is designed to help traders and analysts understand the relationship between a chosen altcoin and Bitcoin (BTC). It does this by:
Fetching price data for the specified altcoin and Bitcoin.
Calculating several key comparative metrics:
Normalized Prices: Shows the percentage performance of both assets from a common starting point.
Price Correlation: Measures how similarly the two assets' prices move over a defined period.
Beta: Indicates the altcoin's volatility relative to Bitcoin.
Altcoin/BTC Ratio: Shows the altcoin's value expressed in Bitcoin.
Fetching and displaying Bitcoin Dominance (BTC.D) data.
Visualizing these metrics on the chart as distinct plots.
Displaying the current values of these key metrics in a data table on the chart for quick reference.
The script aims to provide insights into whether an altcoin is outperforming or underperforming Bitcoin, how closely its price movements are tied to Bitcoin's, and its relative volatility.
User Adjustments:
Users can customize the script's behavior through several input settings:
Symbol Inputs:
Altcoin Symbol: Users can enter the ticker symbol for any altcoin they wish to analyze (e.g., BINANCE:ETHUSDT, KUCOIN:SOLUSDT).
Bitcoin Reference Symbol: Users can specify the Bitcoin pair to use as a reference, though BINANCE:BTCUSDT is a common default.
Lookback for Correlation/Beta:
Lookback Period: This integer value (default 50 periods) determines how many past candles are used to calculate the price correlation and beta.
A shorter lookback makes the metrics more sensitive to recent price action.
A longer lookback provides a smoother, more stable indication of the longer-term relationship.
Plot Visibility Options:
Users can toggle on or off the display of each individual plot on the chart:
Normalized BTC & Altcoin Prices
Altcoin/BTC Ratio
Correlation Plot
Bitcoin Dominance (BTC.D)
Beta Plot
This allows users to focus on specific metrics and reduce chart clutter.
What the Chart Represents:
The chart visually displays the historical trends and relationships of the selected metrics:
Normalized Prices Plot: Two lines (typically orange for BTC, blue for the altcoin) show the percentage growth of each asset from the start of the loaded chart data (or the first available data point for each symbol). This makes it easy to see which asset has performed better over time on a relative basis.
Correlation Plot: A single line (purple) oscillates between -1 and +1.
Values near +1 indicate a strong positive correlation (altcoin and BTC prices tend to move in the same direction).
Values near -1 indicate a strong negative correlation (they tend to move in opposite directions).
Values near 0 indicate little to no linear relationship.
Lines at +0.7 and -0.7 are often plotted as thresholds for "strong" correlation.
Beta Plot (if enabled): A single line (teal) shows the altcoin's volatility relative to BTC.
A Beta of 1 (often marked by a dashed line) means the altcoin has, on average, the same volatility as BTC.
Beta > 1 suggests the altcoin is more volatile than BTC (moves by a larger percentage for a given BTC move).
Beta < 1 suggests the altcoin is less volatile than BTC.
Bitcoin Dominance Plot: An area plot (gray) shows the percentage of the total cryptocurrency market capitalization that Bitcoin holds. This helps understand broader market sentiment and capital flows.
Altcoin/BTC Ratio Plot: A line (fuchsia) shows the price of the altcoin denominated in BTC.
An upward trend means the altcoin is gaining value against Bitcoin (outperforming).
A downward trend means the altcoin is losing value against Bitcoin (underperforming).
What the Table Represents:
The data table, typically located in the bottom-right corner of the chart, provides a snapshot of the current values for the most important calculated metrics. It includes:
Altcoin: The ticker symbol of the analyzed altcoin.
Bitcoin Ref: The ticker symbol of the Bitcoin reference.
Correlation (lookback): The current correlation coefficient between the altcoin and BTC, based on the specified lookback period. The value is color-coded (e.g., green for strong positive, red for strong negative).
Beta (lookback): The current beta value of the altcoin relative to BTC, based on the specified lookback period. The value may be color-coded to highlight significantly high or low volatility.
BTC.D Current: The current Bitcoin Dominance percentage.
ALT/BTC Ratio: The current price of the altcoin expressed in Bitcoin.
The table offers a quick, at-a-glance summary of the present market dynamics between the two assets without needing to interpret the lines on the chart for their exact current values.
Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
Candle Rating (1–5)This “Candle Rating (1–5)” indicator measures where each bar’s close sits within its own high-low range and assigns a simple strength score:
Range Calculation
It computes the candle’s total range (high − low) and finds the close’s position as a percentage of that range (0 = close at low, 1 = close at high).
Five-Point Rating
1 (Strong Buy): Close in the top 20% of the range
2 (Moderate Buy): 60–80%
3 (Neutral): 40–60%
4 (Moderate Sell): 20–40%
5 (Strong Sell): Bottom 20%
Visual Feedback
It plots the numeric rating above each bar (colored green → red), giving you an at-a-glance read of candle momentum and potential reversal strength across any timeframe.
Parsifal.Swing.TrendScoreThe Parsifal.Swing.TrendScore indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
________________________________________
The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
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The Parsifal.Swing.TrendScore – Specifics
The Parsifal.Swing.TrendScore module combines short-term trend data with information about the current swing state, derived from raw price data and classical technical indicators. It provides an indication of how well the short-term trend aligns with the prevailing swing, based on recent market behavior.
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How Swing.TrendScore Works
The Swing.TrendScore calculates a swing score by collecting data within a bin (i.e., a single candle or time bucket) that signals an upside or downside swing. These signals are then aggregated together with insights from classical swing indicators.
Additionally, it calculates a short-term trend score using core technical signals, including:
• The Z-score of the price's distance from various EMAs
• The slope of EMAs
• Other trend-strength signals from additional technical indicators
These two components—the swing score and the trend score—are then combined to form the Swing.TrendScore indicator, which evaluates the short-term trend in context with swing behavior.
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How to Interpret Swing.TrendScore
The trend component enhances Swing.TrendScore’s ability to provide stronger signals when the short-term trend and swing state align.
It can also override the swing score; for example, even if a mean reversion appears to be forming, a dominant short-term trend may still control the market behavior.
This makes Swing.TrendScore particularly valuable for:
• Short-term trend-following strategies
• Medium-term swing trading
Unlike typical swing indicators, Swing.TrendScore is designed to respond more to medium-term swings rather than short-lived fluctuations.
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Behavior and Chart Representation
The Swing.TrendScore indicator fluctuates within a range, as most of its components are range-bound (though Z-score components may technically extend beyond).
• Historically high or low values may suggest overbought or oversold conditions
• The chart displays:
o A fast curve (orange)
o A slow curve (white)
o A shaded background representing the market state
• Extreme values followed by curve reversals may signal a developing mean reversion
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TrendScore Background Value
The Background Value reflects the combined state of the short-term trend and swing:
• > 0 (shaded green) → Bullish mode: swing and short-term trend both upward
• < 0 (shaded red) → Bearish mode: swing and short-term trend both downward
• The absolute value represents the confidence level in the market mode
Notably, the Background Value can remain positive during short downswings if the short-term trend remains bullish—and vice versa.
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How to Use the Parsifal.Swing.TrendScore
Several change points can act as entry triggers or aids:
• Fast Trigger: change in slope of the fast signal curve
• Trigger: fast line crosses slow line or the slope of the slow signal changes
• Slow Trigger: change in sign of the Background Value
Examples of these trigger points are illustrated in the accompanying chart.
Additionally, market highs and lows aligning with the swing indicator values may serve as pivot points in the evolving price process.
________________________________________
As always, this indicator should be used in conjunction with other tools and market context in live trading.
While it provides valuable insight and potential entry points, it does not predict future price action.
Instead, it reflects recent tendencies and should be used judiciously.
________________________________________
Extensions
The aggregation of information—whether derived from bins or technical indicators—is currently performed via simple averaging. However, this can be modified using alternative weighting schemes, based on:
• Historical performance
• Relevance of the data
• Specific market conditions
Smoothing periods used in calculations are also modifiable. In general, the EMAs applied for smoothing can be extended to reflect expectations based on relevance-weighted probability measures.
Since EMAs inherently give more weight to recent data, this allows for adaptive smoothing.
Additionally, EMAs may be further extended to incorporate negative weights, akin to wavelet transform techniques.
Modern Economic Eras DashboardOverview
This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison.
Data Sources & Indicators
All data is loaded monthly from official FRED series and rescaled to improve readability:
🔵 Real GDP (FRED:GDP): Total output of the U.S. economy.
🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation.
⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP.
🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force.
🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices.
🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries.
🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled.
Historical Crashes
The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context.
Era Classification
Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder.
Best Use Cases
✅ Long-term macro investors studying structural market behavior
✅ Educators and analysts explaining economic transitions
✅ Portfolio managers aligning strategy with macroeconomic phases
✅ Traders using history for cycle timing and risk assessment
Technical Notes
Designed for monthly timeframe, though it works on weekly.
Uses close price and standard request.security calls for consistency.
Max labels/lines configured for broader history (from 1860s to present).
All plotted series are rescaled manually for better visibility.
Originality
This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
LANZ Strategy 3.0🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Strategy with Execution Window Logic
LANZ Strategy 3.0 is a rule-based trading system that utilizes the Asian session range to project Fibonacci levels and manage entries during a defined execution window. Designed for Forex and index traders, this strategy focuses on structured price behavior around key levels before the New York session.
🧠 Core Components:
Asian Session Range Mapping: Automatically detects the high, low, and midpoint during the Asian session.
Fibonacci Level Projection: Projects configurable Fibonacci retracement and extension levels based on the Asian range.
Execution Window Logic: Uses the 01:15 NY candle as a reference to validate potential reversals or continuation setups.
Conditional Entry System: Includes logic for limit order entries (buy or sell) at specific Fib levels, with reversal logic if price breaks structure before execution.
Risk Management: Entry orders are paired with dynamic SL and TP based on Fibonacci-based distances, maintaining a risk-reward ratio consistent with intraday strategies.
📊 Visual Features:
Asian session high/low/mid lines.
Fibonacci levels: Original (based on raw range) and Optimized (user-adjustable).
Session background coloring for Asia, Execution Window, and NY session.
Labels and lines for entry, SL, and TP targets.
Dynamic deletion of untriggered orders after execution window expires.
⚙️ How It Works:
The script calculates the Asian session range.
Projects Fibonacci levels from the range.
Waits for the 01:15 NY candle to close to validate a signal.
If valid, a limit entry order (BUY or SELL) is plotted at the selected level.
If price structure changes (e.g., breaks the high/low), reversal logic may activate.
If no trade is triggered, orders are cleared before the NY session.
🔔 Alerts:
Alerts trigger when a valid setup appears after 01:15 NY candle.
Optional alerts for order activation, SL/TP hit, or trade cancellation.
📝 Notes:
Intended for semi-automated or discretionary trading.
Best used on highly liquid markets like Forex majors or indices.
Script parameters include session times, Fib ratios, SL/TP settings, and reversal logic toggle.
Credits:
Developed by LANZ, this script merges traditional session-based analysis with Fibonacci tools and structured execution timing, offering a unique framework for morning volatility plays.
LANZ Strategy 4.0🔷 LANZ Strategy 4.0 — Trend Impulse Detection with Risk Management
LANZ Strategy 4.0 is a multi-indicator trend strategy designed for short to medium-term trading on any asset or timeframe. It combines Parabolic SAR, Supertrend, ADX, and time zone highlighting to detect and confirm trend impulses, while managing entries with dynamic Stop Loss (SL) and Take Profit (TP) levels.
🧠 Core Components:
Parabolic SAR: Identifies short-term trend reversals.
Supertrend: Highlights trend continuation zones.
ADX Filter: Ensures trend strength by filtering entries when ADX exceeds a defined threshold.
Impulse Detection Logic: Detects and confirms movement impulses with a counter, only generating trade signals on confirmed sequences.
Risk Management: Calculates dynamic SL/TP with a default risk-reward ratio of 1:2, minimum SL of 4 pts, and maximum of 12 pts.
📊 Visual Features:
Trend lines from Supertrend and SAR.
Colored background zones for different sessions (Asia, NY).
Labels and lines for entry, SL, and TP.
Movement number labels help visualize impulse progression.
Alerts when a new impulse is confirmed.
⚙️ How It Works:
The strategy waits for a confirmed impulse (i.e., change in SAR + Supertrend + ADX filter).
Once a valid impulse is confirmed:
A trade signal (BUY/SELL) is shown.
SL and TP levels are calculated and drawn.
The script monitors live price to determine if SL or TP is hit.
Impulse counter advances to label movement progression.
🔔 Alerts:
You will receive an alert each time a new valid impulse is confirmed, indicating a potential trading opportunity.
📝 Notes:
Script is intended for discretionary or assisted trading, not automated execution.
Works best during active sessions with visible trend direction.
You can adjust ATR period, multiplier, SL padding, and impulse thresholds.
Credits:
Developed by LANZ combines established technical indicators and original impulse-count logic.
Parsifal.Swing.FlowThe Parsifal.Swing.Flow indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
________________________________________
The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
________________________________________
The Parsifal.Swing.Flow – Specifics
The Parsifal.Swing.Flow module aggregates price and trading flow data per bin (a "bin" refers to a single candle or time bucket) and smooths this information over recent historical data to reflect ongoing market dynamics.
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How Swing.Flow Works
For each bin, individual data points—called "bin-infolets"—are collected. Each infolet reflects the degree and direction of trading flow, offering insight into buying and selling pressure.
The module processes this data in two steps:
1. Aggregation:
All bin-infolet values within a bin are averaged to produce a single bin-flow value.
2. Smoothing:
The resulting bin-flow values are then smoothed across multiple bins, typically using short-term EMAs.
The outcome is a dynamic representation of the current swing state based on recent trading flow activity.
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How to Interpret Swing.Flow
• Range-bound but not a true oscillator:
While individual bin-infolets are range-bound, the Swing.Flow indicator itself is not a classical oscillator.
• Overbought/Oversold Signals:
Historically high or low values in Swing.Flow may signal overbought or oversold conditions.
• Chart Representation:
o A fast curve (orange)
o A slow curve (white)
o A shaded background that illustrates overall market state
• Mean Reversion Signals:
Extreme curve values followed by reversals may indicate the onset of a mean reversion in price.
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Flow Background Value
The Flow Background Value represents the net state of trading flow:
• > 0 (green shading) → Bullish mode
• < 0 (red shading) → Bearish mode
• The absolute value reflects the confidence level in the current trend direction
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How to Use the Parsifal.Swing.Flow
Several change points can act as entry point triggers:
• Fast Trigger:
A change in the slope of the fast signal curve
• Trigger:
The fast line crossing the slow line or a change in the slope of the slow signal
• Slow Trigger:
A change in the sign of the Background Value
These triggers are visualized in the accompanying chart.
Additionally, market highs and lows that align with the swing indicator values can serve as pivot points for the ongoing price process.
________________________________________
As always, this indicator is best used in conjunction with other indicators and market information.
While Parsifal.Swing.Flow offers valuable insight and potential entry points, it does not predict future price action.
Rather, it reflects the most recent market tendencies, and should therefore be applied with discretion.
________________________________________
Extensions
• Aggregation Method:
The current approach—averaging all infolets—can be replaced by alternative weighting schemes, adjusted according to:
o Historical performance
o Relevance of data
o Specific market conditions
• Smoothing Period:
The EMA-based smoothing period can be varied. In general, EMAs can be enhanced to reflect relevance-weighted probability measures, giving greater importance to recent data for a more adaptive and dynamic response.
• Advanced Smoothing:
EMAs can be further extended to include negative weights, similar to wavelet transform techniques, allowing even greater flexibility in smoothing methodologies.
Parsifal.Swing.RSIThe Parsifal.Swing.RSI indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module facilitates judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These swings within the trend are inherently tradable.
They can be approached:
• One-sidedly, in alignment with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions.
Note: In strong trends, mean reversions often appear as sideways consolidations, making one-sided trades more robust.
________________________________________
The Parsifal Swing Suite
The suite provides insights into current swing states and offers various entry point triggers.
All modules act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., the RSI, which ranges from 0 to 100%).
________________________________________
The Parsifal.Swing.RSI – Specifics
The Parsifal.Swing.RSI is the simplest module in the suite. It uses variations of the classical RSI, explicitly combining:
• RSI: 14-period RSI of the market
• RSIMA: 14-period EMA of the RSI
• RSI21: 14-period RSI of the 21-period EMA of the market
• RSI21MA: 14-period EMA of RSI21
Component Behavior:
• RSI: Measures overbought/oversold levels but reacts very sensitively to price changes.
• RSIMA: Offers smoother directional signals, making it better for assessing swing continuation. Its slope and sign changes are more reliable indicators than pure RSI readings.
• RSI21: Based on smoothed prices. In strong trends, it reaches higher levels and reacts more smoothly than RSI.
• RSI21MA: Further smooths RSI21, serving as a medium-term swing estimator and a signal line for RSI21.
When RSI21 exceeds RSI, it indicates trend strength.
• In uptrends, RSI21 > RSI, with larger exceedance = stronger trend
• In downtrends, the reverse holds
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Indicator Construction
The Swing RSI combines:
• RSI and RSIMA → short-term swings
• RSI21 and RSI21MA → medium-term swings
This results in:
• A fast swing curve, derived from RSI and RSI21
• A slow swing curve, derived from RSIMA and RSI21MA
This setup is smoother than RSI/RSIMA alone but more responsive than using RSI21/RSI21MA alone.
________________________________________
Background Value
The Background Value reflects the overall market state, derived from RSI21:
• > 0: shaded green → bullish mode
• < 0: shaded red → bearish mode
• The absolute value reflects confidence in the current mode
________________________________________
How to Use the Parsifal.Swing.RSI
Several change points can act as entry triggers:
• Fast Trigger: change in slope of the fast signal curve
• Trigger: fast line crossing slow line or change in slow signal's slope
• Slow Trigger: change in sign of the Background Value
Examples of these triggers are shown in the chart.
Additionally, market highs and lows aligned with swing values can serve as pivot points in evolving price movements.
________________________________________
As always, this indicator should be used alongside other tools and information in live trading.
While it provides valuable insights and potential entry points, it does not predict future price action.
It reflects the latest tendencies and should be used judiciously.
6 Moving Averages Difference TableIndicator Summary: 6 Moving Averages Difference Table (6MADIFF)
This TradingView indicator calculates and plots up to six distinct moving averages (MAs) directly on the price chart. Users have extensive control over each MA, allowing selection of:
Type: SMA, EMA, WMA, VWMA, HMA, RMA
Length: Any positive integer
Color: User-defined
Visibility: Can be toggled on/off
A core feature is the on-chart data table, designed to provide a quick overview of the relationships between the MAs and the price. This table displays:
$-MA Column: The absolute difference between the user-selected Input Source (e.g., Close, Open, HLC3) and the current value of each MA.
MA$ Column: The actual calculated price value of each MA for the current bar.
MA vs. MA Matrix: A grid showing the absolute difference between every possible pair of the calculated MAs (e.g., MA1 vs. MA2, MA1 vs. MA3, MA2 vs. MA5, etc.).
Customization Options:
Input Source: Select the price source (Open, High, Low, Close, HL2, HLC3, OHLC4) used for all MA calculations and the price difference column.
Table Settings: Control the table's visibility, position on the chart, text size, decimal precision for displayed values, and the text used for the column headers ("$-MA" and "MA$").
Purpose:
This indicator is useful for traders who utilize multiple moving averages in their analysis. The table provides an immediate, quantitative snapshot of:
How far the current price is from each MA.
The exact value of each MA.
The spread or convergence between different MAs.
This helps in quickly assessing trend strength, potential support/resistance levels based on MA clusters, and the relative positioning of short-term versus long-term averages.
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Bitcoin Monthly Seasonality [Alpha Extract]The Bitcoin Monthly Seasonality indicator analyzes historical Bitcoin price performance across different months of the year, enabling traders to identify seasonal patterns and potential trading opportunities. This tool helps traders:
Visualize which months historically perform best and worst for Bitcoin.
Track average returns and win rates for each month of the year.
Identify seasonal patterns to enhance trading strategies.
Compare cumulative or individual monthly performance.
🔶 CALCULATION
The indicator processes historical Bitcoin price data to calculate monthly performance metrics
Monthly Return Calculation
Inputs:
Monthly open and close prices.
User-defined lookback period (1-15 years).
Return Types:
Percentage: (monthEndPrice / monthStartPrice - 1) × 100
Price: monthEndPrice - monthStartPrice
Statistical Measures
Monthly Averages: ◦ Average return for each month calculated from historical data.
Win Rate: ◦ Percentage of positive returns for each month.
Best/Worst Detection: ◦ Identifies months with highest and lowest average returns.
Cumulative Option
Standard View: Shows discrete monthly performance.
Cumulative View: Shows compounding effect of consecutive months.
Example Calculation (Pine Script):
monthReturn = returnType == "Percentage" ?
(monthEndPrice / monthStartPrice - 1) * 100 :
monthEndPrice - monthStartPrice
calcWinRate(arr) =>
winCount = 0
totalCount = array.size(arr)
if totalCount > 0
for i = 0 to totalCount - 1
if array.get(arr, i) > 0
winCount += 1
(winCount / totalCount) * 100
else
0.0
🔶 DETAILS
Visual Features
Monthly Performance Bars: ◦ Color-coded bars (teal for positive, red for negative returns). ◦ Special highlighting for best (yellow) and worst (fuchsia) months.
Optional Trend Line: ◦ Shows continuous performance across months.
Monthly Axis Labels: ◦ Clear month names for easy reference.
Statistics Table: ◦ Comprehensive view of monthly performance metrics. ◦ Color-coded rows based on performance.
Interpretation
Strong Positive Months: Historically bullish periods for Bitcoin.
Strong Negative Months: Historically bearish periods for Bitcoin.
Win Rate Analysis: Higher win rates indicate more consistently positive months.
Pattern Recognition: Identify recurring seasonal patterns across years.
Best/Worst Identification: Quickly spot the historically strongest and weakest months.
🔶 EXAMPLES
The indicator helps identify key seasonal patterns
Bullish Seasons: Visualize historically strong months where Bitcoin tends to perform well, allowing traders to align long positions with favorable seasonality.
Bearish Seasons: Identify historically weak months where Bitcoin tends to underperform, helping traders avoid unfavorable periods or consider short positions.
Seasonal Strategy Development: Create trading strategies that capitalize on recurring monthly patterns, such as entering positions in historically strong months and reducing exposure during weak months.
Year-to-Year Comparison: Assess how current year performance compares to historical seasonal patterns to identify anomalies or confirmation of trends.
🔶 SETTINGS
Customization Options
Lookback Period: Adjust the number of years (1-15) used for historical analysis.
Return Type: Choose between percentage returns or absolute price changes.
Cumulative Option: Toggle between discrete monthly performance or cumulative effect.
Visual Style Options: Bar Display: Enable/disable and customize colors for positive/negative bars, Line Display: Enable/disable and customize colors for trend line, Axes Display: Show/hide reference axes.
Visual Enhancement: Best/Worst Month Highlighting: Toggle special highlighting of extreme months, Custom highlight colors for best and worst performing months.
The Bitcoin Monthly Seasonality indicator provides traders with valuable insights into Bitcoin's historical performance patterns throughout the year, helping to identify potentially favorable and unfavorable trading periods based on seasonal tendencies.
