The Investment ClockThe Investment Clock was most likely introduced to the general public in a research paper distributed by Merrill Lynch. It’s a simple yet useful framework for understanding the various stages of the US economic cycle and which asset classes perform best in each stage.
The Investment Clock splits the business cycle into four phases, where each phase is comprised of the orientation of growth and inflation relative to their sustainable levels:
Reflation phase (6:01 to 8:59): Growth is sluggish and inflation is low. This phase occurs during the heart of a bear market. The economy is plagued by excess capacity and falling demand. This keeps commodity prices low and pulls down inflation. The yield curve steepens as the central bank lowers short-term rates in an attempt to stimulate growth and inflation. Bonds are the best asset class in this phase.
Recovery phase (9:01 to 11:59): The central bank’s easing takes effect and begins driving growth to above the trend rate. Though growth picks up, inflation remains low because there’s still excess capacity. Rising growth and low inflation are the Goldilocks phase of every cycle. Stocks are the best asset class in this phase.
Overheat phase(12:01 to 2:59): Productivity growth slows and the GDP gap closes causing the economy to bump up against supply constraints. This causes inflation to rise. Rising inflation spurs the central banks to hike rates. As a result, the yield curve begins flattening. With high growth and high inflation, stocks still perform but not as well as in recovery. Volatility returns as bond yields rise and stocks compete with higher yields for capital flows. In this phase, commodities are the best asset class.
Stagflation phase (3:01 to 5:59): GDP growth slows but inflation remains high (sidenote: most bear markets are preceded by a 100%+ increase in the price of oil which drives inflation up and causes central banks to tighten). Productivity dives and a wage-price spiral develops as companies raise prices to protect compressing margins. This goes on until there’s a steep rise in unemployment which breaks the cycle. Central banks keep rates high until they reign in inflation. This causes the yield curve to invert. During this phase, cash is the best asset.
Additional notes from Merrill Lynch:
Cyclicality: When growth is accelerating (12 o'clock), Stocks and Commodities do well. Cyclical sectors like Tech or Steel outperform. When growth is slowing (6 o'clock), Bonds, Cash, and defensives outperform.
Duration: When inflation is falling (9 o'clock), discount rates drop and financial assets do well. Investors pay up for long duration Growth stocks. When inflation is rising (3 o'clock), real assets like Commodities and Cash do best. Pricing power is plentiful and short-duration Value stocks outperform.
Interest Rate-Sensitives: Banks and Consumer Discretionary stocks are interest-rate sensitive “early cycle” performers, doing best in Reflation and Recovery when central banks are easing and growth is starting to recover.
Asset Plays: Some sectors are linked to the performance of an underlying asset. Insurance stocks and Investment Banks are often bond or equity price sensitive, doing well in the Reflation or Recovery phases. Mining stocks are metal price-sensitive, doing well during an Overheat.
About the indicator:
This indicator suggests iShares ETFs for sector rotation analysis. There are likely other ETFs to consider which have lower fees and are outperforming their sector peers.
You may get errors if your chart is set to a different timeframe & ticker other than 1d for symbol/tickers GDPC1 or CPILFESL.
Investment Clock settings are based on a "sustainable level" of growth and inflation, which are each slightly subjective depending on the economist and probably have changed since the last time this indicator was updated. Hence, the sustainable levels are customizable in the settings. When I was formally educated I was trained to use average CPI of 3.1% for financial planning purposes, the default for the indicator is 2.5%, and the Medium article backtested and optimized a 2% sustainable inflation rate. Again, user-defined sustainable growth and rates are slightly subjective and will affect results.
I have not been trained or even had much experience with MetaTrader code, which is how this indicator was originally coded. See the original Medium article that inspired this indicator if you want to audit & compare code.
Hover over info panel for detailed information.
Features: Advanced info panel that performs Investment Clock analysis and offers additional hover info such as sector rotation suggestions. Customizable sustainable levels, growth input, and inflation input. Phase background coloring.
⚠ DISCLAIMER: Not financial advice. Not a trading system. DYOR. I am not affiliated with Medium, Macro Ops, iShares, or Merrill Lynch.
About the Author: I am a patent-holding inventor, a futures trader, a hobby PineScripter, and a former FINRA Registered Representative.
在腳本中搜尋"Cycle"
[blackcat] L3 Improved Dual Ehlers BPF for Volatility DetectionOVERVIEW
This script implements an advanced L3 Improved Dual Ehlers Bandpass Filter (BPF) for volatility detection, combining both L1 and L2 calculation methods to create a comprehensive trading signal. The script leverages John Ehlers' sophisticated digital signal processing techniques to identify market cycles and extract meaningful trading signals from price action. By combining multiple cycle detection methods and filtering approaches, it provides traders with a powerful tool for identifying trend changes, momentum shifts, and potential reversal points across various market conditions and timeframes. The L3 approach uniquely combines the outputs of both L1 (01 range) and L2 (-11 range) methods, creating a signal that ranges from -1~2 and provides enhanced sensitivity to market dynamics.
FEATURES
🔄 Dual Calculation Methods: Choose between L1 (01 range), L2 (-11 range), or combine both for L3 signal (-1~2 range) to match your trading style
📊 Multiple Cycle Detection: Seven different dominant cycle calculation methods including HoDyDC (Hilbert Transform Dominant Cycle), PhAcDC (Phase Accumulation Dominant Cycle), DuDiDC (Duane Dominant Cycle), CycPer (Cycle Period), BPZC (Bandpass Zero Crossing), AutoPer (Autocorrelation Period), and DFTDC (Discrete Fourier Transform Dominant Cycle)
🎛️ Flexible Mixing Options: Six sophisticated mixing methods including weighted averaging, simple sum, difference extraction, dominant-only, subdominant-only, and adaptive mixing that adjusts based on signal strength
🌊 Bandpass Filtering: Precise bandwidth control for both dominant and subdominant filters, allowing fine-tuning of frequency response characteristics
📈 Advanced Divergence Detection: Robust algorithm for identifying bullish and bearish divergences with customizable lookback periods and range constraints
🎨 Comprehensive Visualization: Extensive customization options for all signals, colors, plot styles, and display elements
🔔 Comprehensive Alert System: Built-in alerts for divergence signals, zero line crosses, and various market conditions
📊 Real-time Cycle Information: Optional display of dominant and subdominant cycle periods for educational purposes
🔄 Adaptive Signal Processing: Dynamic adjustment of parameters based on market conditions and volatility
🎯 Multiple Signal Outputs: Simultaneous generation of L1, L2, and L3 signals for different trading strategies
HOW TO USE
Select Calculation Method: Choose between "l1" (01 range), "l2" (-11 range), or "both" (L3, -1~2 range) in the Calculation Method settings based on your preferred signal characteristics
Configure Cycle Detection: Select your preferred Dominant Cycle Method from the seven available options and adjust the Cycle Part parameter (0.1-0.9) to fine-tune cycle sensitivity
Set Subdominant Parameters: Configure the subdominant cycle either as a ratio of the dominant cycle or as a fixed period, depending on your analysis approach
Adjust Filter Bandwidth: Fine-tune the bandwidth settings for both dominant and subdominant filters (0.1-1.0) to control the frequency response and signal smoothing
Choose Mixing Method: Select how to combine the filters - weighted averaging for balance, sum for maximum sensitivity, difference for trend isolation, or adaptive mixing for dynamic response
Configure Smoothing: Select from SMA, EMA, or HMA smoothing methods with adjustable length (1-20 bars) to reduce noise in the final signal
Customize Visualization: Enable/disable individual plots, divergence detection, zero line, fill areas, and customize all colors to match your chart preferences
Set Divergence Parameters: Configure lookback ranges (5-60 bars) for divergence detection to match your trading timeframe and style
Monitor Signals: Watch for crosses above/below zero line and divergence patterns, paying attention to signal strength and consistency
Set Up Alerts: Configure alerts for divergence signals, zero line crosses, and other market conditions to stay informed of trading opportunities
LIMITATIONS
The script requires the dc_ta library from blackcat1402 for several advanced cycle calculation methods (HoDyDC, PhAcDC, DuDiDC, CycPer, BPZC, AutoPer, DFTDC)
L1 method operates in 01 range while L2 method uses -11 range, requiring different interpretation approaches
Combined L3 signal ranges from -1~2 when both methods are selected, creating unique signal characteristics that traders must adapt to
Divergence detection accuracy depends on proper lookback period settings and market volatility conditions
Performance may be impacted with very long lookback ranges (>60 bars) or when multiple plots are simultaneously enabled
The script is designed for non-overlay use and may not display correctly on certain chart types or with conflicting indicators
Adaptive mixing method requires careful threshold tuning to avoid excessive signal fluctuation
Cycle detection algorithms may produce unreliable results during low volatility or highly choppy market conditions
The script assumes regular price data and may not perform optimally with irregular or gapped price sequences
NOTES
The script implements advanced mathematical calculations including bandpass filters, Hilbert transforms, and various cycle detection algorithms developed by John Ehlers
For optimal results, experiment with different cycle detection methods and bandwidth settings across various market conditions and timeframes
The adaptive mixing method automatically adjusts weights based on signal strength, providing dynamic response to changing market conditions
Divergence detection works best when the "Plot Divergence" option is enabled and when combined with other technical analysis tools
Zero line crosses can indicate potential trend changes or momentum shifts, especially when confirmed by volume or other indicators
The script includes commented code for cycle information display that can be enabled if you want to monitor cycle periods in real-time
Different calculation methods may perform better in different market environments - L1 tends to be smoother while L2 is more sensitive
The subdominant cycle helps filter out noise and provides additional confirmation for signals generated by the dominant cycle
Bandwidth settings control the filter's frequency response - lower values provide more smoothing while higher values increase sensitivity
Mixing methods offer different approaches to combining signals - weighted averaging is generally most reliable for most trading applications
THANKS
Special thanks to John Ehlers for his pioneering work in cycle analysis and digital signal processing for financial markets. This script implements and significantly improves upon his bandpass filter methodology, incorporating multiple advanced techniques from his extensive body of work. Also heartfelt thanks to blackcat1402 for the dc_ta library that provides essential cycle calculation methods and for maintaining such a valuable resource for the Pine Script community. Additional appreciation to the TradingView platform for providing the tools and environment that make sophisticated technical analysis accessible to traders worldwide. This script represents a collaborative effort in advancing the field of algorithmic trading and technical analysis.
CCI with Subjective NormalizationCCI (Commodity Channel Index) with Subjective Normalization
This indicator computes the classic CCI over a user-defined length, then applies a subjective mean and scale to transform the raw CCI into a pseudo Z‑score range. By adjusting the “Subjective Mean” and “Subjective Scale” inputs, you can shift and rescale the oscillator to highlight significant tops and bottoms more clearly in historical data.
1. CCI Calculation:
- Uses the standard formula \(\text{CCI} = \frac{\text{price} - \text{SMA(price, length)}}{0.015 \times \text{mean deviation}}\) over a user-specified length (default 500 bars).
2. Subjective Normalization:
- After CCI is calculated, it is divided by “Subjective Scale” and offset by “Subjective Mean.”
- This step effectively re-centers and re-scales the oscillator, helping you align major lows or highs at values like –2 or +2 (or any desired range).
3. Usage Tips:
- CCI Length controls how far back the script measures average price and deviation. Larger values emphasize multi-year cycles.
- Subjective Mean and Scale let you align the oscillator’s historical lows and highs with numeric levels you prefer (e.g., near ±2).
- Adjust these parameters to fit your particular market analysis or to match known cycle tops/bottoms.
4. Plot & Zero Line:
- The indicator plots the normalized CCI in yellow, along with a zero line for quick reference.
- Positive values suggest price is above its long-term mean, while negative values suggest it’s below.
This approach offers a straightforward momentum oscillator (CCI) combined with a customizable normalization, making it easier to spot historically significant overbought/oversold conditions without writing complex code yourself.
[blackcat] L2 Ehlers Autocorrelation Periodogram V2OVERVIEW
The Ehlers Autocorrelation Periodogram is a sophisticated technical analysis tool that identifies market cycles and their dominant frequencies using autocorrelation and spectral analysis techniques.
BACKGROUND
Developed by John F. Ehlers and detailed in his book "Cycle Analytics for Traders" (2013), this indicator combines autocorrelation functions with discrete Fourier transforms to extract cyclic information from price data.
FUNCTION
The indicator works through these key steps:
Calculates autocorrelation using minimum three-bar averaging
Applies discrete Fourier transform to extract cyclic information
Uses center-of-gravity algorithm to determine dominant cycle
ADVANTAGES
• Rapid response within half-cycle periods
• Accurate relative cyclic power estimation over time
• Correlation constraints between -1 and +1 eliminate amplitude compensation needs
• High resolution independent of windowing functions
HOW TO USE
Add the indicator to your chart
Adjust AvgLength input parameter:
• Default: 3 bars
• Higher values increase smoothing
• Lower values increase sensitivity
Interpret the results:
• Colored bars represent spectral power
• Red to yellow spectrum indicates cycle strength
• White line shows dominant cycle period
INTERPRETATION
• Strong colors indicate significant cyclic activity
• Sharp color transitions suggest potential cycle changes
• Dominant cycle line helps identify primary market rhythm
LIMITATIONS
• Requires sufficient historical data
• Performance may vary in non-cyclical markets
• Results depend on proper parameter settings
NOTES
• Uses highpass and super smoother filtering techniques
• Spectral estimates are normalized between 0 and 1
• Color intensity varies based on spectral power
THANKS
This implementation is based on Ehlers' original work and has been adapted for TradingView's Pine Script platform.
SW Gann DaysGann pressure days, named after the famous trader W.D. Gann, refer to specific days in a trading month that are believed to have significant market influence. These days are identified based on Gann's theories of astrology, geometry, and market cycles. Here’s a general outline of how they might be understood:
1. **Market Cycles**: Gann believed that markets move in cycles and that certain days can have heightened volatility or trend changes. Traders look for specific dates based on historical price movements.
2. **Timing Indicators**: Pressure days often align with key economic reports, earnings announcements, or geopolitical events that can cause price swings.
3. **Mathematical Patterns**: Gann used angles and geometric patterns to predict price movements, with pressure days potentially aligning with these calculations.
4. **Historical Patterns**: Traders analyze past data to identify dates that historically show strong price reactions, using this to predict future behavior.
5. **Astrological Influences**: Some practitioners incorporate astrological elements, believing that celestial events (like full moons or planetary alignments) can impact market psychology.
Traders might use these concepts to make decisions about entering or exiting positions, but it’s important to note that Gann's methods can be complex and are not universally accepted in trading communities.
Interval & Session Market StatisticsThe "Interval & Session Market Statistics" indicator is designed to uncover recurring patterns and market inefficiencies by analyzing market cycles. By breaking down price movements into defined intervals and sessions, this tool helps traders pinpoint periods of strength and weakness—identifying both bullish and bearish trends with clear percentage breakdowns. Its comprehensive visual tables make it easier to detect accumulation, distribution, and potential turning points, providing valuable insights that can be leveraged to optimize trading strategies.
Important: If the indicator does not reveal a strong bias toward either short or long positions and the statistics hover around 50%, consider reducing the analysis start date and adjusting the end time of the first interval in the settings. Over longer periods, the market tends to revert to a 50/50 balance, so significant deviations are often more visible in weekly or monthly intervals. Since this indicator focuses on intraday cycles, fine-tuning these parameters is crucial for capturing actionable trends.
Индикатор "Interval & Session Market Statistics" разработан для выявления закономерностей и неэффективностей на основе рыночных циклов. Разбивая ценовые движения на заданные интервалы и сессии, инструмент помогает трейдерам определить периоды силы и слабости, выявляя как бычьи, так и медвежьи тренды с наглядным процентным отображением. Подробные таблицы позволяют обнаруживать зоны накопления и распределения, а также потенциальные разворотные моменты, что даёт ценные данные для оптимизации торговых стратегий.
Важно: Если индикатор не выявляет ярко выраженного перекоса в сторону шортового или лонгового приоритета, и статистика колеблется в районе 50%, рекомендуется уменьшить дату начала анализа и поработать с окончанием первого интервала в настройках индикатора. На более длительных периодах рынок обычно стремится к балансу в 50%, поэтому существенные отклонения эффективнее искать в рамках недельных или месячных интервалов. Поскольку данный индикатор ориентирован на внутридневные циклы, корректировка этих параметров имеет решающее значение для выявления значимых трендов.
Retrograde Periods (Multi-Planet)**Retrograde Periods (Multi-Planet) Indicator**
This TradingView script overlays your chart with a dynamic visualization of planetary retrograde periods. Built in Pine Script v6, it computes and displays the retrograde status of eight planets—Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto—using hard-coded retrograde intervals from 2009 to 2026.
**Key Features:**
- Dynamic Background Coloring:
The indicator changes the chart’s background color based on the current retrograde status of the planets. The colors follow a priority order (Mercury > Venus > Mars > Jupiter > Saturn > Uranus > Neptune > Pluto) so that if multiple planets are retrograde simultaneously, the highest-priority planet’s color is displayed.
- Interactive Planet Selection:
User-friendly checkboxes allow you to choose which planets to list in the table’s “Selected” row. Note that while these checkboxes control the display of the planet names in the table, the retrograde calculations remain independent of these selections.
- Real-Time Retrograde Status Table:
A table in the top-right corner displays each planet’s retrograde status in real time. “Yes” is shown in red for a planet in retrograde and “No” in green when it isn’t. This offers an at-a-glance view of the cosmic conditions influencing your charts.
- Astrological & Astronomical Insights:
Whether you’re into sidereal astrology or simply fascinated by celestial mechanics, this script lets you visualize those retrograde cycles. In astrology, retrograde periods are often seen as times for reflection and re-evaluation, while in astronomy they reflect the natural orbital motions seen from our perspective on Earth.
Enhance your trading setup by integrating cosmic cycles into your technical analysis. Happy trading and cosmic exploring!
TOTAL3ES/ETH Mean ReversionTOTAL3ES/ETH Mean Reversion Indicator
Overview
The TOTAL3ES/ETH Mean Reversion indicator is a specialized tool designed exclusively for analyzing the ratio between TOTAL3 excluding stablecoins (TOTAL3ES) and Ethereum's market capitalization. This ratio provides crucial insights into the relative performance and valuation cycles between altcoins and ETH, making it an essential tool for cryptocurrency portfolio allocation and market timing decisions.
What This Indicator Measures
This indicator tracks the market cap ratio of all altcoins (excluding ETH and stablecoins) to Ethereum's market cap. When the ratio is:
Above 1.0 (Parity): Altcoins have a larger combined market cap than ETH
Below 1.0 (Parity): ETH's market cap exceeds the combined altcoin market cap
Key Features
Historical Context
Historical Range: 0.64 (July 2017 low) to 3.49 (all-time high)
Midpoint: 2.065 - the mathematical center of the historical range
Parity Line: 1.0 - the psychological level where altcoins = ETH market cap
Mean Reversion Zones
The indicator identifies extreme valuation zones based on historical data:
Upper Extreme Zone (~2.92 at 80% threshold): Suggests altcoins may be overvalued relative to ETH
Lower Extreme Zone (~1.21 at 80% threshold): Suggests altcoins may be undervalued relative to ETH
Visual Elements
Color-coded zones: Red shading for bearish reversion areas, green for bullish reversion areas
Multiple reference lines: Parity, midpoint, and historical extremes
Information table: Real-time metrics including current ratio, range position, and reversion pressure
Customizable display: Toggle zones, lines, and adjust transparency
How to Use This Indicator
Market Cycle Analysis
Extreme High Zone (Red): When ratio enters this zone, consider potential ETH outperformance
Extreme Low Zone (Green): When ratio enters this zone, consider potential altcoin season
Parity Crossovers: Monitor when ratio crosses above/below 1.0 for sentiment shifts
Portfolio Allocation Signals
High Ratio Values: May indicate overextended altcoin valuations relative to ETH
Low Ratio Values: May suggest undervalued altcoins relative to ETH
Midpoint Reversions: Historical tendency to revert toward the 2.065 midpoint
Alert Conditions
The indicator includes built-in alerts for:
Entering extreme high/low zones
Parity crossovers (above/below 1.0)
Mean reversion signals
Input Parameters
Display Settings
Show Reversion Zones: Toggle colored extreme zones on/off
Show Midpoint: Display the historical midpoint line
Show Parity Line: Show the 1.0 parity reference line
Zone Transparency: Adjust shaded area opacity (70-95%)
Calculation Settings
Reversion Strength Period: Moving average period for reversion calculations (10-50)
Extreme Threshold: Percentage of historical range defining extreme zones (0.5-1.0)
Information Table Metrics
The bottom-right table displays:
Current Ratio: Live TOTAL3ES/ETH value
Range Position: Current position within historical range (%)
From Parity: Distance from 1.0 parity level (%)
Reversion Pressure: Intensity of mean reversion forces (%)
Zone: Current market zone classification
Historical Range: Reference boundaries (0.64 - 3.49)
Midpoint: Historical center value
Important Notes
Chart Compatibility
Exclusively designed for CRYPTOCAP:TOTAL3ES/CRYPTOCAP:ETH
Built-in validation ensures proper chart usage
Will display error message if applied to incorrect charts
Trading Considerations
This is an analytical tool, not trading advice
Mean reversion is a tendency, not a guarantee
Consider multiple timeframes and confirmations
Factor in overall market conditions and trends
Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
Ideal Use Cases
Portfolio rebalancing between ETH and altcoins
Market cycle timing for position adjustments
Sentiment analysis of crypto market phases
Long-term allocation strategies based on historical patterns
Risk management through extreme zone identification
This indicator serves as a quantitative framework for understanding the cyclical relationship between Ethereum and the broader altcoin market, helping traders and investors make more informed allocation decisions based on historical valuation patterns.ons
- Factor in overall market conditions and trends
### Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
cycle144 dr ramy After Given Date📌 Description for Script Publishing
Cycle144 dr ramy After Given Date is a visual tool that highlights time-based cycles on the chart by marking specific candles that occur after a user-defined starting point.
🔹 How It Works:
You choose a specific date and time.
The script automatically identifies and labels the 18th, 36th, 54th, 72nd, 90th, 108th, 126th, and 144th candles after your selected date.
At each of those candles, the script:
Places a label (e.g., "18th Candle", "36th Candle", etc.).
Draws horizontal lines from the candle's high and low, extended to the right.
🔹 Purpose:
This indicator helps traders observe and analyze market behavior at regular cycle intervals after a significant date. It's useful for cycle-based strategies, time symmetry analysis, or just to visualize how price reacts at recurring time steps.
🛠️ No signals or strategies are included — this is a charting utility only.
Gann & Fibonacci Analysis for MSTRYes! Below is a step-by-step guide to performing Gann Analysis on MSTR in TradingView for the last year.
Step 1: Set Up the Chart
Open TradingView and search for MSTR (MicroStrategy).
Select the 1-day (D) timeframe to analyze the past year.
Set your chart to logarithmic scale (⚙ Settings → Scale → Log).
Enable grid lines for alignment (⚙ Settings → Appearance → Grid Lines).
Step 2: Identify Key Highs and Lows (Last Year)
Find the 52-week high and 52-week low for MSTR.
As of now:
52-Week High: ~$999 (March 2024).
52-Week Low: ~$280 (October 2023).
Step 3: Plot Gann Angles
Using TradingView's Gann Fan Tool:
Select "Gann Fan" (Press / and type “Gann Fan” to find it).
Start at the 52-week low (~$280, October 2023) and drag upwards.
Adjust the angles to match key levels:
1x1 (45°) → Main trendline
2x1 (26.5°) → Strong uptrend
4x1 (15°) → Weak trendline
1x2 (63.75°) → Strong resistance
Repeat the process from the 52-week high (~$999, March 2024) downward to see bearish angles.
Step 4: Apply Fibonacci & Gann Retracement Levels
Using Fibonacci Retracement:
Select "Fibonacci Retracement" tool.
Draw from 52-week high ($999) to 52-week low ($280).
Enable key Fibonacci levels:
23.6% ($816)
38.2% ($678)
50% ($640)
61.8% ($550)
78.6% ($430)
Watch for price reactions near these levels.
Using Gann Retracement Levels:
Select "Gann Box" in TradingView.
Draw from 52-week high ($999) to low ($280).
Enable key Gann retracement levels:
12.5% ($912)
25% ($850)
37.5% ($768)
50% ($640)
62.5% ($550)
75% ($480)
87.5% ($350)
Identify confluences with Gann angles and Fibonacci levels.
Step 5: Identify Significant Dates & Time Cycles
Use "Date Range" Tool in TradingView.
Mark major turning points:
High → Low: ~180 days (Half-year cycle).
Low → High: ~90 days (Quarter cycle).
Use Square-Outs (Time = Price method):
Example: If MSTR hit $500, check 500 days from key events.
Mark key anniversaries of past highs/lows for possible reversals.
Step 6: Analyze and Trade Execution
✅ If MSTR is at a Gann angle + Fibonacci level + key date → Expect a reaction.
✅ Use RSI, MACD, and Volume for extra confirmation.
✅ Set Stop-Loss at nearest Gann support/resistance.
Dominant Direction (DD)The Dominant Direction indicator is a custom technical analysis tool that uses the Dominant Cycle Estimators library to identify the dominant trend direction in the market. The indicator utilizes the MAMA Cycle function, which is a part of the library, to calculate the period of the data. The resulting period is then used to plot lines on the chart that represent the dominant trend direction.
The indicator takes two inputs, the source of data, and the high and low values of the source. The MAMA Cycle function is used to calculate the period of the data, with the lower bound and upper bound of the dynamic length defined by the user. The indicator then plots lines on the chart to represent the dominant trend direction. The lines are plotted from the current bar to the bar that is a certain number of periods away, as defined by the MAMA Cycle function, in the direction of the trend.
The indicator also has a feature of removing the lines when the trend is no longer confirmed. If the bar state is confirmed, the line is deleted and this helps the user to have a clearer view of the chart.
In summary, the Dominant Direction indicator is a powerful tool for identifying the dominant trend direction in the market. It uses the MAMA Cycle function to calculate the period of the data and plots lines on the chart to represent the dominant trend direction. This can help traders identify potential entry and exit points, and make more informed trading decisions.
True Open CalculationsIndicator Description: True Open Calculations
This custom Pine Script indicator calculates and plots key "True Open" levels based on specific time intervals and trading sessions. The True Open levels represent significant price points on the chart, helping traders identify key reference points tied to various market opening times. These levels are important for understanding price action in relation to market sessions and trading cycles. The indicator is designed to plot lines corresponding to different "True Opens" on the chart and display labels with the associated information.
Key Features:
True Year Open:
This represents the opening price on the first Monday of April each year. It serves as a reference point for the yearly price level.
Plot Color: Green.
True Month Open:
This represents the opening price on the second Monday of each month. It helps in identifying monthly trends and provides a key reference for monthly price movements.
Plot Color: Blue.
True Week Open:
This represents the opening price every Monday at 6:00 PM. It gives traders a level to track weekly opening movements and can be useful for weekly trend analysis.
Plot Color: Orange.
True Day Open:
This represents the opening price at 12:00 AM (midnight) each day. It serves as a daily benchmark for price action at the start of the trading day.
Plot Color: Red.
True New York Session Open:
This represents the opening price at 7:30 AM (New York session start time). This level is crucial for traders focused on the New York trading session.
Plot Color: Purple.
Additional Features:
Labels: The indicator displays labels to the right of each plotted line to describe which "True Open" it represents (e.g., "True Year Open," "True Month Open," etc.).
Dynamic Plotting: The lines are only plotted on the current candle, and the lines are dynamically updated for each time period based on the corresponding "True Open."
Visual Cues: The colors of the plotted lines (green, blue, orange, red, purple) help quickly distinguish between different "True Open" levels, making it easy for traders to track price action and make informed decisions.
Use Cases:
Yearly, Monthly, Weekly, Daily, and Session Benchmarking: This indicator provides traders with important price levels to use as benchmarks for the current year, month, week, and day, helping to identify trends and potential reversals.
Session Awareness: It is particularly useful for traders who want to track key market sessions, such as the New York session, and their impact on price movement.
Long-term Analysis: By including the yearly open, this indicator helps traders gain a broader perspective on market trends and provides context for analyzing shorter-term price movements.
Benefits:
Helps identify important reference points for longer-term trends (yearly, monthly) as well as shorter-term moves (daily, weekly, and session).
Visually intuitive with color-coded lines and labels, allowing quick and easy identification of key market open levels.
Dynamic and real-time: The indicator plots and updates the True Open levels dynamically as the market progresses.
Trading Sessions Highs/Lows | InvrsROBINHOODTrading Sessions Highs/Lows | InvrsROBINHOOD
🚀 A powerful indicator for tracking key trading sessions and the highs and lows of each session!
📌 Description
The Trading Sessions Highs/Lows indicator visually marks the most critical trading sessions—Asia, London, and New York—using small colored dots at the bottom of the candle. It also tracks and plots the highs and lows of each session, along with the Daily Open and Weekly Open levels.
This tool is designed to help traders identify session-based liquidity zones, price reactions, and potential trade setups with minimal chart clutter.
Key Features:
✅ Session markers (Asia, London, NY AM, NY Lunch, NY PM) plotted as small dots
✅ Plots session highs and lows for market structure insights
✅ Daily Open line for intraday reference
✅ Weekly Open line for higher timeframe bias
✅ Alerts for session high/low breaks to capture momentum shifts
✅ User-defined UTC offset for global traders
✅ Customizable session colors for personal preference
📖 How to Use the Indicator
1️⃣ Understanding the Sessions
Asia Session (Yellow Dot) → Marks liquidity buildup & pre-London moves
London Session (Blue Dot) → Strong volatility, breakout opportunities
New York AM Session (Green Dot) → Major trends & institutional participation
New York Lunch (Red Dot) → Low volume, ranging market
New York PM Session (Dark Green Dot) → End-of-day movements & reversals
2️⃣ Session Highs & Lows for Market Structure
Session Highs can act as resistance or breakout points.
Session Lows can act as support or stop-hunt zones.
Break of a session high/low with volume may indicate continuation or reversal.
3️⃣ Using the Daily & Weekly Open
The Daily Open (Black Line) helps gauge the intraday trend.
Above Daily Open → Bearish Bias
Below Daily Open → Bullish Bias
The Weekly Open (Red Line) sets the higher timeframe directional bias.
4️⃣ Alerts for Breakouts
The indicator will trigger alerts when price breaks session highs or lows.
Useful for setting stop-losses, breakout trades, and risk management.
💡 Why This Indicator is Important for Beginners
1️⃣ Avoids Overtrading:
Many beginners trade in low-volume periods (NY Lunch, Asia session) and get stuck in choppy price action.
This indicator highlights when volatility is high so traders focus on better opportunities.
2️⃣ Session-Based Liquidity Traps:
Market makers often run stops at session highs/lows before reversing.
Watching session breaks prevents traders from falling into liquidity grabs.
3️⃣ Reduces Emotional Trading:
If price is above the Daily Open, a beginner shouldn’t look for shorts.
If price is below a key session low, it may signal a fake breakout.
4️⃣ Aligns with Institutional Trading:
Smart money traders use session highs/lows to set stop hunts & reversals.
Beginners can use this indicator to spot these zones before entering trades.
🛡️ How to Mitigate Risk with This Indicator
✅ Wait for Confirmations – Don’t trade blindly at session highs/lows. Look for wicks, rejections, or break/retests.
✅ Use Stop-Loss Above/Below Session Levels – If you’re going long, set SL below a session low. If short, set SL above a session high.
✅ Watch Volume & News Events – Breakouts without strong volume or news may be fake moves.
✅ Combine with Other Strategies – Use price action, trendlines, or EMAs with this indicator for higher probability trades.
✅ Use the Weekly Open for Trend Bias – If price stays below the Weekly Open, avoid bullish setups unless key support holds.
🎯 Who is This Indicator For?
📌 Beginners who need clear session-based trading levels.
📌 Day traders & scalpers looking to refine their intraday setups.
📌 Smart money traders using liquidity concepts.
📌 Swing traders tracking higher timeframe momentum shifts.
🚀 Final Thoughts
This indicator is an essential tool for traders who want to understand market structure, liquidity, and volatility cycles. Whether you’re trading forex, stocks, or crypto, it helps you stay on the right side of the market and avoid unnecessary risks.
🔹 Set it up, customize your colors, define your UTC offset, and start trading smarter today! 🏆📈
Yearly Profit BackgroundDescription:
The Yearly Profit Background indicator is a powerful tool designed to help traders quickly visualize the profitability of each calendar year on their charts. By analyzing the annual performance of an asset, this indicator colors the background of each completed year green if the year was profitable (close > open) or red if it resulted in a loss (close < open). This visual representation allows traders to identify long-term trends and historical performance at a glance.
Key Features:
Annual Profit Calculation: Automatically calculates the yearly performance based on the opening price of January 1st and the closing price of December 31st.
Visual Background Coloring: Highlights each completed year with a green (profit) or red (loss) background, making it easy to spot trends.
Customizable Transparency: The background colors are set at 90% transparency, ensuring they don’t obstruct your chart analysis.
Optional Price Plots: Displays the annual opening (blue line) and closing (orange line) prices for additional context.
How to Use:
Add the indicator to your chart.
Observe the background colors for each completed year:
Green: The year was profitable.
Red: The year resulted in a loss.
Use the optional price plots to analyze annual opening and closing levels.
Ideal For:
Long-term investors analyzing historical performance.
Traders looking to identify multi-year trends.
Anyone interested in visualizing annual market cycles.
Why Use This Indicator?
Understanding the annual performance of an asset is crucial for making informed trading decisions. The Yearly Profit Background indicator simplifies this process by providing a clear, visual representation of yearly profitability, helping you spot patterns and trends that might otherwise go unnoticed.
Smart Money Concepts //@deepak
//@version=5
indicator(title='Custom Also Builder - v1', shorttitle="Custom Also Builder - v1", overlay=true, max_bars_back=500)
ma(_source, _length, _type) =>
switch _type
"SMA" => ta.sma (_source, _length)
"EMA" => ta.ema (_source, _length)
"RMA" => ta.rma (_source, _length)
"WMA" => ta.wma (_source, _length)
"VWMA" => ta.vwma(_source, _length)
alarm(_osc, _message) =>
alert(syminfo.ticker + ' ' + _osc + ' : ' + _message + ', price (' + str.tostring(close, format.mintick) + ')')
//Conditional Sampling EMA Function
Cond_EMA(x, cond, n) =>
var val = array.new_float(0)
var ema_val = array.new_float(1)
if cond
array.push(val, x)
if array.size(val) > 1
array.remove(val, 0)
if na(array.get(ema_val, 0))
array.fill(ema_val, array.get(val, 0))
array.set(ema_val, 0, (array.get(val, 0) - array.get(ema_val, 0)) * (2 / (n + 1)) + array.get(ema_val, 0))
EMA = array.get(ema_val, 0)
EMA
//Conditional Sampling SMA Function
Cond_SMA(x, cond, n) =>
var vals = array.new_float(0)
if cond
array.push(vals, x)
if array.size(vals) > n
array.remove(vals, 0)
SMA = array.avg(vals)
SMA
//Standard Deviation Function
Stdev(x, n) =>
math.sqrt(Cond_SMA(math.pow(x, 2), 1, n) - math.pow(Cond_SMA(x, 1, n), 2))
//Range Size Function
rng_size(x, scale, qty, n) =>
ATR = Cond_EMA(ta.tr(true), 1, n)
AC = Cond_EMA(math.abs(x - x ), 1, n)
SD = Stdev(x, n)
rng_size = scale == 'Pips' ? qty * 0.0001 : scale == 'Points' ? qty * syminfo.pointvalue : scale == '% of Price' ? close * qty / 100 : scale == 'ATR' ? qty * ATR : scale == 'Average Change' ? qty * AC : scale == 'Standard Deviation' ? qty * SD : scale == 'Ticks' ? qty * syminfo.mintick : qty
rng_size
//Two Type Range Filter Function
rng_filt(h, l, rng_, n, type, smooth, sn, av_rf, av_n) =>
rng_smooth = Cond_EMA(rng_, 1, sn)
r = smooth ? rng_smooth : rng_
var rfilt = array.new_float(2, (h + l) / 2)
array.set(rfilt, 1, array.get(rfilt, 0))
if type == 'Type 1'
if h - r > array.get(rfilt, 1)
array.set(rfilt, 0, h - r)
if l + r < array.get(rfilt, 1)
array.set(rfilt, 0, l + r)
if type == 'Type 2'
if h >= array.get(rfilt, 1) + r
array.set(rfilt, 0, array.get(rfilt, 1) + math.floor(math.abs(h - array.get(rfilt, 1)) / r) * r)
if l <= array.get(rfilt, 1) - r
array.set(rfilt, 0, array.get(rfilt, 1) - math.floor(math.abs(l - array.get(rfilt, 1)) / r) * r)
rng_filt1 = array.get(rfilt, 0)
hi_band1 = rng_filt1 + r
lo_band1 = rng_filt1 - r
rng_filt2 = Cond_EMA(rng_filt1, rng_filt1 != rng_filt1 , av_n)
hi_band2 = Cond_EMA(hi_band1, rng_filt1 != rng_filt1 , av_n)
lo_band2 = Cond_EMA(lo_band1, rng_filt1 != rng_filt1 , av_n)
rng_filt = av_rf ? rng_filt2 : rng_filt1
hi_band = av_rf ? hi_band2 : hi_band1
lo_band = av_rf ? lo_band2 : lo_band1
ma_function(source, length, type) =>
if type == 'RMA'
ta.rma(source, length)
else if type == 'SMA'
ta.sma(source, length)
else if type == 'EMA'
ta.ema(source, length)
else if type == 'WMA'
ta.wma(source, length)
else if type == 'HMA'
if(length<2)
ta.hma(source,2)
else
ta.hma(source, length)
else
ta.vwma(source, length)
// Get Table Size
table_size(s) =>
switch s
"Auto" => size.auto
"Huge" => size.huge
"Large" => size.large
"Normal" => size.normal
"Small" => size.small
=> size.tiny
setup_group= "████████ Indicator Setup ████████"
signalexpiry = input.int(defval=3, title='Signal Expiry Candle Count',group=setup_group, inline='expiry',tooltip="Number of candles to wait for all indicators to confirm a signal. Default is 3 which means if leading indicator print the signal, it will wait for max 3 more candles for rest of the indicators to print signal, if not then this setup is invalided and will have to wait for another signal form the leading indicator.")
alternatesignal = input.bool (true, "Alternate Signal", group=setup_group, inline='alternate')
showsignal = input.bool (true, "Show Long/Short Signal", group=setup_group,inline='showsignal',tooltip="Option to turn on/off the Long/Short signal shown on the chart. by default it will print Long/ Short signal on the chart.")
showdashboard = input.bool (true, "Show Dashboard", group=setup_group,inline='dashboard')
string i_tab1Ypos = input.string('bottom', 'Dashboard Position',group=setup_group, inline='dashboard2', options= )
string i_tab1Xpos = input.string('right', '', inline='dashboard2', group=setup_group,options= )
in_dashboardtab_size = input.string(title="Dashboard Size ", defval="Normal",
options= ,
group= setup_group , inline= "dashboard3")
///////////////////////////////////////////////
///// Signal filters
/////////////////////////////////////////////
leadingindicator = input.string(title="Leading Indicator", defval="Range Filter",
options= , group='████████ Main Indicator (signal) ████████', inline='li')
confirmation_group = "████████ Confirmation Indicators (filter) ████████ "
ema_tooltip = "EMA filter for confirmation.\n\n Validates Long signal if price is above the EMA FILTER level, and validates Short signal if price is below the EMA FILTER level. \n\nDefault is 200, you can change that to meet your requiremnt."
respectema = input.bool (false, "EMA Filter", group=confirmation_group, inline='respectema')
respectemaperiod = input.int(defval=200, minval=1, title='', group=confirmation_group, inline='respectema', tooltip=ema_tooltip)
ema2_tooltip = "Generates Long signal if Fast EMA cross above Slow EMA.\n\n Generates Short signal when Fast EMA cross below the Slow EMA.\n\n Default values are 50 and 200. you can change that to meet your requirement."
respect2ma = input.bool (false, "2 EMA Cross : ", group=confirmation_group, inline='2ma')
respect2maperiod_1 = input.int(defval=50, title='',group=confirmation_group, inline='2ma')
respect2maperiod_2 = input.int(defval=200, title='',group=confirmation_group, inline='2ma',tooltip=ema2_tooltip)
ema3_tooltip = "Generates Long signal if first EMA (Fastest) cross above 2nd and 3rd EMA and 2nd EMA cross above 3rd EMA.\n\n Generates Short signal if first EMA (Fastest) cross below 2nd and 3rd EMA and 2nd EMA cross below 3rd EMA .\n\n Default values are 9,21 and 55. you can change that to meet your requirement."
respect3ma = input.bool (false, "3 EMA Cross : ", group=confirmation_group, inline='3ma',tooltip=ema3_tooltip)
respect3maperiod_1 = input.int(defval=9, title='',group=confirmation_group, inline='3ma',tooltip=ema3_tooltip)
respect3maperiod_2 = input.int(defval=21, title='',group=confirmation_group, inline='3ma',tooltip=ema3_tooltip)
respect3maperiod_3 = input.int(defval=55, title='',group=confirmation_group, inline='3ma',tooltip=ema3_tooltip)
respectrf = input.bool (false, "Range Filter", group=confirmation_group, inline='rf')
rftype = input.string(title="", defval="Default", options= , group=confirmation_group, inline='rf')
respectrqk = input.bool (true, "Rational Quadratic Kernel (RQK)", group=confirmation_group, inline='rqk',tooltip="Nadaraya Watson: Rational Quadratic Kernel (RQK)")
respectst = input.bool (false, "SuperTrend", group=confirmation_group, inline='st')
respectht = input.bool (false, "Half Trend", group=confirmation_group, inline='ht')
respectdonchian = input.bool (false, "Donchian Trend Ribbon", group=confirmation_group, inline='donchian')
respectroc = input.bool (false, "Rate of Change (ROC)", group=confirmation_group, inline='roc')
respecttsi = input.bool (false, "True Strength Indicator (TSI)", group=confirmation_group, inline='tsi')
tsitooltip = "Signal Crossover:\n\n TSI crossover or greater than signal line for long, and TSI crossunder signal line for short.\n\n Zero Line Cross:\n\n TSI cross above zero line and signal line for long signal. Tsi Cross below zero and signal line for short signal."
tsitype = input.string(title="", defval="Signal Cross", options= ,tooltip=tsitooltip, group=confirmation_group, inline='tsi')
respecttdfi = input.bool (false, "Trend Direction Force Index (TDFI)", group=confirmation_group, inline='tdfi')
respectmd = input.bool (false, "McGinley Dynamic", group=confirmation_group, inline='md')
respectdpo = input.bool (false, "Detrended Price Oscillator (DPO)", group=confirmation_group, inline='dpo')
respectichi = input.bool (false, "Ichimoku Cloud", group=confirmation_group, inline='ichi')
respectsuperichi = input.bool (false, "SuperIchi", group=confirmation_group, inline='ichi',tooltip="Ichimoku Cloud Conditions: \n \n 1. Candle above cloud \n \n 2. Converstion Line above base line \n \n 3. Leading 26 bar cloud is green \n \n 4. lagging span is above the cloud")
respecttrendline_breakout = input.bool (false, "Trendline Breakout", group=confirmation_group, inline='tb')
respectrd = input.bool (false, "Range Detector", group=confirmation_group, inline='rd',tooltip="Range Detector:\n\n if used as leading indicator, it will be based on range breakout. \n\n If used as confirmation indicator, it will be used to filter entries within the active range area.")
respecthacolt = input.bool (false, "Heiken-Ashi Candlestick Oscillator", group=confirmation_group, inline='hacolt',tooltip="Vervoort LongTerm Heiken-Ashi Candlestick Oscillator:\n\n If oscilliation is above 0 line, then long signal is issued and if below zero line, short signal is issued.")
respectbx = input.bool (false, "B-Xtrender", group=confirmation_group, inline='bx')
bxtype = input.string(title="", defval="Short and Long term trend", options= , group=confirmation_group, inline='bx', tooltip = "Short term trend:\n\n===================== \n\n For buy signal the short term trend line must turn green, and for the sell signal, the short term trend line must turn red. \n\n Short and Long term trend: \n\n===================== \n\n For buy signal, the short term trend must change from red to green and long term trend cross above zero line, for Sell signal the short term trend must turn red and long term trend line cross down the zero line..")
respectbbpt = input.bool (false, "Bull bear Power Trend", group=confirmation_group, inline='bbpt')
bbpttype = input.string(title="", defval="Follow Trend", options= , group=confirmation_group, inline='bbpt', tooltip = "Follow Trend:\n\n===================== \n\n Buy signal will be validated if the BBPT trend line is above 2, and Sell signal will be validated if BBPT trend line is below -2. \n\n Without Trend: \n\n===================== \n\n Ignore the BBPT trend line.")
respectvwap = input.bool (false, "VWAP", group=confirmation_group, inline='vwap')
respectbbosc = input.bool (false, "BB Oscillator", group=confirmation_group, inline='bbosc')
bbtype = input.string(title="", defval="Entering Lower/Upper Band", options= , group=confirmation_group, inline='bbosc')
respecttm = input.bool (false, "Trend Meter", group=confirmation_group, inline='tm')
tmtype = input.string(title="", defval="3 TM and 2 TB change to same color", options= , group=confirmation_group, inline='tm')
respectce = input.bool (false, "Chandelier Exit", group=confirmation_group, inline='ce')
respectcci = input.bool (false, "CCI", group=confirmation_group, inline='cci')
respectao = input.bool (false, "Awesome Oscillator", group=confirmation_group, inline='ao')
aotype = input.string(title="", defval="Zero Line Cross", options= , group=confirmation_group, inline='ao', tooltip = "Zero Line Cross:\n\n If AO value cross the zero line up, Buy signal will be generated, and if AO value cross down the zero line, sell signal will be generated.")
respectadx = input.bool (false, "DMI (ADx)", group=confirmation_group, inline='adx')
adxtype = input.string(title="", defval="Adx & +Di -Di", options= , group=confirmation_group, inline='adx', tooltip = "Adx Only:\n\n If Adx value is above the defined level. \n\n Adx & +Di -DI :\n\n When Adx value is above the defined level and croseeover between +di and -di. Di will determine the direction of the movement. \n\n Advance: ")
respectsar = input.bool (false, "Parabolic SAR (PSAR)", group=confirmation_group, inline='sar')
respectwae = input.bool (false, "Waddah Attar Explosion", group=confirmation_group, inline='wae')
vo_tooltip = "Volatility Oscillator: \n\n ======================= \n\n If the spike line is above the upper line, buy signal is generated (or validated). \n\n If the spike line is below the lower line, sell signal is generated (or validated)."
respectvo = input.bool (false, "Volatility Oscillator", group=confirmation_group, inline='vo', tooltip = vo_tooltip)
ci_tooltip = "Choppiness index: \n\n ======================= \n\n If the index is below the defined threshold (default 61.8) then asset is considered trending and signal will be validated, if index is above 61.8 then asset is considered having sideway movement."
respectci = input.bool (false, "Choppiness Index ", group=confirmation_group, inline='ci')
ci_limit = input.float(61.8,title=" ", inline='ci',group=confirmation_group, tooltip = ci_tooltip)
respectdv = input.bool (false, "Damiani Volatility (DV)", group=confirmation_group, inline='dv')
dvtype = input.string(title="", defval="Simple", options= , group=confirmation_group, inline='dv', tooltip = "Simple\n Volatility is green. \nThreshold\n Volatility green and >1.1")
stochtooltip="CrossOver:\n------------------\n\n CrossOver of K and D line at any level. \n\n CrossOver in OB & OS levels:\n\n Generate buy signal if crossover happens in oversold area and crossing up oversold level.\n\n Generate sell signal on crossover in overbought area and cross down upper level. \n------------------\n\n %K above/below %D\n------------------\n: Generate Buy signal or validate other signal if %K is above %D and opposite for Sell Signal."
respectstochastic = input.bool (false, "Stochastic", group=confirmation_group, inline='stoch')
stochtype = input.string(title="", defval="CrossOver", options= ,tooltip=stochtooltip, group=confirmation_group, inline='stoch')
rsi_tooltip = "RSI MA Cross:\n=============\n Generate buy signal when RSI cross up RSI MA line and sell signal when RSI cross down RSI MA line.\n\nRSI Exits OB/OS zones:\n==================\n Generate Buy signal when RSI crosses down the overbough zone and sell signal when RSI crosses up the oversold zone.\n\nRSI Level:\n==========\nGenerate buy signal if RSI cross above the specific level and sell signal when RSI crossdown the level.\n\n\n +++++\nYou can change the setting to define the OB/OS and MidLine Levels"
respectrsi = input.bool (false, "RSI", group=confirmation_group, inline='rsi')
rsitype = input.string(title="", defval="RSI MA Cross", options= , tooltip=rsi_tooltip, group=confirmation_group, inline='rsi')
rsima_tooltip = "RSI MA Direction:\n=============\n The buy and sell signal will respect the RSI MA direction. For buy signal, the RSI MA should be increasing or same compared to previous RSI MA. \n\n for SHORT, the RSI MA should be same or decreasing compared to last RSI MA"
respectrsima = input.bool (false, "RSI MA Direction", group=confirmation_group, inline='rsi2',tooltip=rsima_tooltip)
rsilimit_tooltip = "RSI Limit:\n=============\n This is to allow you to set limit for the RSI value for long and short. default value for long is 40, which means if the RSI is 40 or above, only then BUY signal will be validated. \n\nfor short if RSI is 60 or less, only then sell signal willbe validated."
respectrsilimit = input.bool (false, "RSI Limit : ", group=confirmation_group, inline='rsi3',tooltip=rsilimit_tooltip)
rsilimitup = input.int(40, title="Long",inline='rsi3', group=confirmation_group)
rsilimitdown = input.int(60, title="short",inline='rsi3', group=confirmation_group)
rsimalimit_tooltip = "RSI MA Limit:\n=============\n This is to allow you to set limit for the RSI MA value for long and short. default value for long is 40, which means if the RSI MA is 40 or above, only then BUY signal will be validated. \n\nfor short if RSI MA is 60 or less, only then sell signal willbe validated."
respectrsimalimit = input.bool (false, "RSI MA Limit : ", group=confirmation_group, inline='rsi4',tooltip=rsimalimit_tooltip)
rsimalimitup = input.int(40, title="Long",inline='rsi4', group=confirmation_group)
rsimalimitdown = input.int(60, title="short",inline='rsi4', group=confirmation_group)
macdtooltip="MACD Crossover:\n------------------\n\n CrossOver of MACD and the Signal line. Generates Long signal when MACD cross up Signal line and Short signal when MACD cross down Signal Line. . \n\n Zero line crossover:\n------------------\n\n Generate buy signal when MACD cross up the zero line and Sell signal when MACD cross down the zero line."
respectmacd = input.bool (false, "MACD", group=confirmation_group, inline='macd')
macdtype = input.string(title="", defval="MACD Crossover", options= ,tooltip=macdtooltip, group=confirmation_group, inline='macd')
respectssl = input.bool (false, "SSL Channel", group=confirmation_group, inline='ssl')
respectstc = input.bool (false, "Schaff Trend Cycle (STC)", group=confirmation_group, inline='stc')
respectchaikin = input.bool (false, "Chaikin Money Flow", group=confirmation_group, inline='chaikin')
respectvol = input.bool (false, "Volume", group=confirmation_group, inline='volume')
volumetype = input.string(title="", defval="volume above MA", options= , group=confirmation_group, inline='volume', tooltip = "Simple volume is comparing the up/down volme with previous candle. \nVolume delta will compare the delta or difference between up and down volume with previous candle.\nExample:\n up volume = 100 \n Down volume=-1100\n Delta = -1000\n Satisfy the bear flag condition if previous -ve delta is lower")
respectwolf = input.bool (false, "Wolfpack Id", group=confirmation_group, inline='wolf')
respectqqe = input.bool (false, "QQE Mod", group=confirmation_group, inline='qqe')
qqetype = input.string(title="", defval="Line", options= , group=confirmation_group, inline='qqe', tooltip = "Line: signal generated when QQE line is above or below 0. \nBar: when Blue bar is above 0 or Red bar below 0 \nLine & Bar: Both Bar and Line to be above(bullist) or below (beari
Smoothed ROC Z-Score with TableSmoothed ROC Z-Score with Table
This indicator calculates the Rate of Change (ROC) of a chosen price source and transforms it into a smoothed Z-Score oscillator, allowing you to identify market cycle tops and bottoms with reduced noise.
How it works:
The ROC is calculated over a user-defined length.
A moving average and standard deviation over a separate window are used to standardize the ROC into a Z-Score.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter noise and highlight clearer cycle signals.
The smoothed Z-Score oscillates around zero, with upper and lower bands defined by user inputs (default ±2 standard deviations).
When the Z-Score reaches or exceeds ±3 (customizable), the value shown in the table is clamped at ±2 for clearer interpretation.
The indicator plots the smoothed Z-Score line with zero and band lines, and displays a colored Z-Score table on the right for quick reference.
How to read it:
Values near zero indicate neutral momentum.
Rising Z-Scores towards the upper band suggest increasing positive momentum, possible market tops or strength.
Falling Z-Scores towards the lower band indicate negative momentum, potential bottoms or weakness.
The color-coded table gives an easy visual cue: red/orange for strong positive signals, green/teal for strong negative signals, and gray for neutral zones.
Use cases:
Identify turning points in trending markets.
Filter noisy ROC data for cleaner signals.
Combine with other indicators to time entries and exits more effectively.
Maancyclus Volatiliteitsindicator (2025)This Moon Cycle Volatility Indicator for TradingView is designed to help traders track and analyze market volatility around specific lunar phases, namely the Full Moon and New Moon. The indicator marks the dates of these moon phases on the chart and measures volatility using the Average True Range (ATR) indicator, which gauges market price fluctuations.
Key Features:
Moon Phase Markers: The indicator marks the Full Moon and New Moon on the chart using labels. Blue labels are placed below bars for Full Moons, while red labels are placed above bars for New Moons. These markers are based on a manually curated list of moon phase dates for the year 2025.
Volatility Calculation: The indicator calculates market volatility using the ATR (14), which provides a sense of market movement and potential risk. Volatility is plotted as histograms, with blue histograms representing volatility around Full Moons and red histograms around New Moons.
Comparative Analysis: By comparing the volatility around these moon phases to the average volatility, traders can spot potential patterns or heightened market movements. This can inform trading strategies, such as anticipating increased market activity around specific lunar events.
In essence, this tool helps traders identify potential high-volatility periods tied to lunar cycles, which could impact market sentiment and price action.
FX Rotation Dashboard – FX vs DXYFX Rotation Dashboard
This FX Rotation Dashboard indicator offers a clear, at-a-glance overview of the relative strength and momentum of major FX pairs when measured against the US Dollar Index (DXY). It helps identify which currency pairs are leading or lagging in performance and how their relative positioning is evolving over time.
🔎 Structure
Each row in the table represents a currency pair and provides the following data:
Symbol: The FX pair (e.g., EURJPY, GBPUSD, AUDNZD)
RS: The current relative strength ratio vs. DXY
MOM: The momentum of the RS – showing whether strength is accelerating or decelerating
Quadrant:
🔴 Lagging: Underperforming and losing momentum
🔵 Improving: Underperforming but gaining momentum
🟢 Leading: Outperforming with rising momentum
🟡 Weakening (not visible in current table): Outperforming but slowing down
Meaning: A descriptive label summarizing the quadrant status
🧭 Interpretation
Currency pairs in the Leading quadrant (e.g., EURJPY, GBPJPY, CHFJPY, CADJPY) are currently outperforming the USD with rising momentum – often indicating strength across both RS and MOM dimensions.
Pairs in the Improving quadrant (e.g., GBPUSD, EURUSD, AUDUSD) are showing positive momentum but still lagging in relative strength – potential early signs of rotation into leadership.
Pairs in the Lagging quadrant (e.g., USDCHF, USDJPY, AUDCHF) are underperforming and continue to weaken – often considered the least attractive at the current stage of the cycle.
🧠 Purpose
This FX Rotation visualization is particularly useful for:
Macro-level FX rotation analysis
Spotting emerging trends before they are fully priced in
Tracking performance of G10 and cross pairs against USD
It provides context for currency strength beyond individual price movements by placing them in a relative performance framework.
⚠️ Disclaimer: This indicator is for informational and analytical purposes only. It does not constitute investment advice or a recommendation to buy or sell any financial instrument. Always conduct your own research before making trading decisions.
GOLDEN SCALP DEXDescription:
This tool is designed for traders who want to capture momentum shifts that occur within larger timeframe structures. The strategy identifies unique breakout opportunities inside the HTF cycle and provides precise entry and exit signals without cluttering the chart.
The system focuses on:
Pinpointing immediate momentum breakouts
Clean chart visualization with intuitive buy/sell markers
Full backtesting capability through TradingView’s Strategy Tester
Customizable position sizing for futures, forex, and crypto traders
It is especially useful for traders who prefer fast, rule-based signals during high-impact intraday moves.
⚠️ Disclaimer: This is a trading tool, not financial advice. Results may vary depending on market conditions, and proper risk management is essential.
Intraday Time Cycle Levels (Labels + Alerts + Colors)Jag japp detta spelet fram och tbx.
Tack för ert förtoende.
XRP Breathe Strategy Zones +🫁 XRP Breathe Strategy Zones
A time-based trading overlay designed specifically for XRPUSD.
This tool highlights weekly "Inhale" and "Exhale" phases based on a 20-day cycle of price action. It visually guides traders through expected accumulation and distribution zones, helping align trades with market rhythm.
🔹 Key Features:
Color-coded Inhale and Exhale phases
Critical price levels marked for support and resistance
Built-in signal arrows for trend confirmation
Perfect for swing traders and intraday strategists looking to trade XRP with more structure, timing, and confidence.
SCPEM - Socionomic Crypto Peak Model (0-85 Scale)SCPEM Indicator Overview
The SCPEM (Socionomic Crypto Peak Evaluation Model) indicator is a TradingView tool designed to approximate cycle peaks in cryptocurrency markets using socionomic theory, which links market behavior to collective social mood. It generates a score from 0-85 (where 85 signals extreme euphoria and high reversal risk) and plots it as a blue line on the chart for visual backtesting and real-time analysis.
#### How It Works
The indicator uses technical proxies to estimate social mood factors, as Pine Script cannot fetch external data like sentiment indices or social media directly. It calculates a weighted composite score on each bar:
- Proxies derive from price, volume, and volatility data.
- The raw sum of factor scores (max ~28) is normalized to 0-85.
- The score updates historically for backtesting, showing mood progression over time.
- Alerts trigger if the score exceeds 60, indicating high peak probability.
Users can adjust inputs (e.g., lengths for RSI or pivots) to fine-tune for different assets or timeframes.
Metrics Used (Technical Proxies)
Crypto-Specific Sentiment
Approximated by RSI (overbought levels indicate greed).
Social Media Euphoria
Based on volume relative to its SMA (spikes suggest herding/FOMO).
Broader Social Mood Proxies
Derived from ATR volatility (high values signal uncertain/mixed mood).
Search and Cultural Interest Proxied by OBV trend (rising accumulation implies growing interest).
Socionomic Wildcard
Uses Bollinger Band width (expansion for positive mood, contraction for negative).
Elliott Wave Position
Counts recent price pivots (more swings indicate later wave stages and exhaustion).
Simplified STH-MVRV + Z-ScoreSimplified Short Term Holder MVRV (STH-MVRV) + Z-Score Indicator
Description:
This indicator visualizes the Short Term Holder Market Value to Realized Value ratio (STH-MVRV) and its normalized Z-Score, providing insight into Bitcoin’s market cycle phases and potential overbought or oversold conditions.
How it works:
The STH-MVRV ratio compares the market value of coins held by short-term holders to their realized value, helping to identify periods of profit-taking or accumulation by these holders.
The indicator calculates three versions:
STH-MVRV (MVRV): Ratio of current MVRV to its 155-day SMA.
STH-MVRV (Price): Ratio of BTC price to its 155-day SMA.
STH-MVRV (AVG): Average of the above two ratios.
You can select which ratio to display via the input dropdown.
Threshold Lines:
Adjustable upper and lower threshold lines mark significant levels where market sentiment might shift.
The indicator also plots a baseline at 1.0 as a reference.
Z-Score Explanation:
The Z-Score is a normalized value scaled between -3 and +3, calculated relative to the chosen threshold levels.
When the ratio hits the upper threshold, the Z-Score approaches +2, indicating potential overbought conditions.
Conversely, reaching the lower threshold corresponds to a Z-Score near -2, signaling potential oversold conditions.
This Z-Score is shown in a clear table in the top right corner of the chart for easy monitoring.
Data Sources:
MVRV data is fetched from the BTC_MVRV dataset.
Price data is sourced from the BTC/USD index.
Usage:
Use this indicator to assess short-term holder market behavior and to help identify buying or selling opportunities based on extremes indicated by the Z-Score.
Combining this tool with other analysis can improve timing decisions in Bitcoin trading.
