52-Week High Drawdown (Events, Freq & Current)52-Week High Drawdown - Events, Freq & Current
OVERVIEW
Track and analyze drawdowns from 52-week highs with comprehensive statistics on drawdown events, frequency, and current market positioning. Perfect for risk management, historical analysis, and understanding volatility patterns.
KEY FEATURES
📊 Real-Time Drawdown Tracking
Visual area chart showing current intraday maximum drawdown from rolling high
Automatically plots depth below zero line for easy interpretation
Color-coded reference lines at -10% and -20% levels
📈 Event-Based Historical Analysis
Automatically categorizes drawdown cycles across four severity zones:
5-10% Drawdowns - Minor corrections
10-15% Drawdowns - Moderate pullbacks
15-20% Drawdowns - Significant corrections
20%+ Drawdowns - Major corrections/bear markets
⏱️ Frequency Metrics
Calculates average time between events for each category, displayed as "Every X months" to understand typical correction patterns.
🎯 Current Cycle Tracking
Real-time display of maximum drawdown depth in the current cycle, helping you gauge present market position.
📅 Smart Timeframe Adaptation
Auto-Adjust Mode: Automatically selects optimal lookback (Daily=252, Weekly=52, Monthly=12)
Manual Mode: Set custom lookback period for specialized analysis
HOW IT WORKS
The indicator identifies drawdown cycles - periods from one high to the next. When price touches a new rolling high, the previous cycle ends and is categorized by its maximum depth.
Cycle Logic:
Tracks deepest point reached since last high
When price touches/exceeds rolling high, cycle completes
Cycle categorized into appropriate drawdown zone
New cycle begins
This provides accurate event counting without double-counting fluctuations within larger drawdowns.
PRACTICAL APPLICATIONS
Risk Management
Understand typical drawdown patterns for position sizing
Set realistic stop-loss levels based on historical norms
Anticipate potential correction depths during bull markets
Market Context
Identify when current drawdowns are extreme vs. typical
Compare across different assets and timeframes
Historical perspective during volatile periods
Strategic Planning
Time entries during typical correction zones
Recognize when drawdowns exceed historical norms
Build resilience strategies based on frequency data
SETTINGS GUIDE
Auto-Adjust Lookback by Timeframe
Checked: Automatically uses appropriate period for chart timeframe
Unchecked: Uses manual lookback value
Manual Lookback Length
Default: 252 (trading days in a year)
Customize for specific analysis periods
Higher values = longer historical perspective
Table Position
Choose from Top Right, Bottom Right, Top Left, or Bottom Left based on your chart layout.
INTERPRETATION TIPS
Frequency data becomes more reliable with longer history (5+ years ideal)
"Never" frequency indicates zero events in available data range
Current Cycle Max shows 0.00% at new highs, otherwise displays deepest point
Compare frequencies across assets to understand relative volatility profiles
BEST USED FOR
Stocks, ETFs, and Indices with sufficient historical data
Long-term investing and swing trading strategies
Portfolio risk assessment and stress testing
Educational purposes - understanding market behavior
Multi-timeframe analysis (daily, weekly, monthly)
TECHNICAL NOTES
Uses ta.highest() for efficient rolling high calculation
Event detection logic prevents double-counting
Frequency calculated from actual data start time to present
All calculations update in real-time with each new bar
💡 Tip: Run this indicator on major indices like SPY or QQQ with maximum available history to build a comprehensive baseline for equity market corrections.
Created to provide institutional-grade drawdown analysis in an accessible format. Free to use and modify.
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Dynamic Equalizer [DW]This is an experimental study inspired by techniques primarily utilized in the visual and audio processing worlds.
This study is designed to serve as a pre or post processing filter designer that allows you to shape the frequency spectrum of your data on a more "in-depth" level.
First the data is fed through my Band-Shelf Equalizer function.
The EQ in this script works by dividing the input signal into 6 bands and 2 shelves using a series of roofing filters.
The bands are then gain adjusted recursively (in %) to match source as closely as possible at unity gain.
The recursive adjustment size can be changed using the "Gain Adjustment Increment" input, which will affect how tightly the resulting filter approximates source at unity.
The frequency range of each band is adjustable via the period inputs. In default settings, these are the ranges:
-> Low Shelf : 256+ Samples Per Cycle. This shelf is the largest trend component of the signal. Unlike the other bands and shelf, this shelf is not zero mean unless source data is.
-> Band 1 : 128 - 256 Samples Per Cycle. This band is a moderate trend and low cyclic component of the signal.
-> Band 2 : 64 - 128 Samples Per Cycle. This band is a mild trend and moderate cyclic component of the signal.
-> Band 3 : 32 - 64 Samples Per Cycle. This band is a high cyclic component of the signal.
-> Band 4 : 16 - 32 Samples Per Cycle. This band is a high cyclic component of the signal.
-> Band 5 : 8 - 16 Samples Per Cycle. This band is a moderate cyclic and mild to moderate noise component of the signal.
-> Band 6 : 4 - 8 Samples Per Cycle. This band is a high noise component of the signal.
-> High Shelf : 4- Samples Per Cycle. This shelf is primarily noise.
Each band and shelf can be manually gain adjusted via their respective inputs.
After EQ processing, each band and shelf is then optionally fed through my Peak Envelope Compressor function for dynamics control.
The compressor in this script works by reducing band power by a specified percentage when it exceeds a user defined percentage of the peak envelope.
The peak envelope measures maximum power of the band over its period range multiplied by a user defined integer.
There is an option included to apply Butterworth smoothing to the envelope as well, which will alter the shape of the compressor.
If you want an envelope that quickly responds to power peaks, use little to no smoothing. If you desire something more static, use a large smoothing period.
Attack and release are included in the algorithm to shape the sensitivity of the compressor.
Attack controls how many bars it takes from being triggered for attenuation to reach its target amount.
Release controls how many bars it takes from being un-triggered for attenuation to reach back to 0.
In addition, the compressor is equipped with parallel processing.
The "Parallel Mix" inputs control the amount of compressed vs non-compressed signal presence in the final output.
And of course, the compressor has a post-processing gain input (in %) to fine-tune the presence of the band.
For easy visual tuning, you can view each independent band's magnitude or power by selecting them in the display inputs.
This display setup can also be beneficial analytically if you wish to analyze specific frequency components of the source signal.
The default preset for this script is meant to show how versatile EQ filtering and compression can be for technical analysis.
The EQ preset detrends the data, moderately smooths the data, and emphasizes dominant cyclical ranges.
The compression preset provides fast, moderately heavy shaping to dial in dynamics and reduce transient effects.
The resulting curve is a great filter for responsively analyzing cyclical momentum.
The script is also fully equipped with outputs that can be used externally by other scripts.
You can integrate these external outputs with your own script by using a source input. Simply select the desired output from the dropdown tab on your script.
Multiband filtering and compression are concepts that are not conventionally used in the world of finance.
However, the versatile capabilities of these concepts make this a wonderful tool to have in the arsenal.
By surgically adjusting separate frequency components of a signal, you're able to design a wide variety of filters with unique responses for a vast array of applications.
Play around with the settings and see what kinds of filters you can design!
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This is a premium script, and access is granted on an invite-only basis.
To gain access, get a copy of the script overview, or for additional inquiries, send me a direct message.
I look forward to hearing from you!
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General Disclaimer:
Trading stocks, futures, Forex, options, ETFs, cryptocurrencies or any other financial instrument has large potential rewards, but also large potential risk.
You must be aware of the risks and be willing to accept them in order to invest in stocks, futures, Forex, options, ETFs or cryptocurrencies.
Don’t trade with money you can’t afford to lose.
This is neither a solicitation nor an offer to Buy/Sell stocks, futures, Forex, options, ETFs, cryptocurrencies or any other financial instrument.
No representation is being made that any account will or is likely to achieve profits or losses of any kind.
The past performance of any trading system or methodology is not necessarily indicative of future results.
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NOTE: Unlike standard tools of this nature in other applications, I scaled the signals in % rather than dB, mainly since it's proven so far to be more user-friendly to keep things linear on here.
In addition, no transitions to frequency domain are done in this script. This EQ is an experimental variant that processes in the time domain and relies on a network of roofing filters.
When changing cutoff periods, make sure they are organized in descending order with low shelf as the highest period, and high shelf as the lowest period.
Using non-descending lengths may result in an undesired output.
Lastly, when changing cutoff periods, parts of the spectrum may leak slightly differently between bands, so the "Gain Match Adjustment Increment" may need to be changed as well if you want it to match as closely as possible at unity.
Despite these shortcomings, this tool functions surprisingly well, especially with the default periods, and it's quickly become one of my favorites. I hope you all enjoy it!
Bitcoin MVRV Ratio MomentumBitcoin MVRV Ratio with 365 Day SMA
The Market Value to Realized Value (MVRV) ratio is one of Bitcoin's most powerful on-chain metrics for identifying market cycle extremes and potential reversals. This indicator plots the MVRV ratio alongside its 365-day moving average to help identify market trends and sentiment shifts.
What is MVRV?
MVRV Ratio = Market Cap / Realized Cap
Market Cap: Current price × circulating supply (what the market values Bitcoin at today)
Realized Cap: Sum of all coins valued at the price they last moved on-chain (the aggregate cost basis of all holders)
The MVRV ratio essentially measures whether Bitcoin holders are, on average, in profit or loss, and by how much.
Key Components:
MVRV Ratio - Orange Line
Shows the current Market Value to Realized Value ratio
Values above 1.0 indicate holders are in profit on average
Values below 1.0 indicate holders are in loss on average
More volatile, responds quickly to price changes
365 Day SMA - White Dashed Line
Smooths out short-term volatility
Shows the trend direction of market sentiment
Acts as dynamic support/resistance
Fill Shading Between Lines
Green fill: MVRV is above its 365-day average (bullish momentum)
Red fill: MVRV is below its 365-day average (bearish momentum)
Helps quickly visualize trend strength and momentum shifts
Reference Levels:
1.0 (Gray Dashed): Market Cap = Realized Cap
Holders break even on average
Historically strong support during bear markets
Breaking below suggests capitulation territory
3.7 (Red Dotted): Historical Top Zone
Area where previous cycle tops occurred
Suggests market overheating
Not a precise sell signal, but indicates elevated risk
0.8 (Green Dotted): Historical Bottom Zone
Area where previous cycle bottoms formed
Suggests extreme undervaluation
Historically excellent long-term accumulation zone
Background Shading:
Light Red Background: MVRV > 3.5
Extreme overvaluation zone
Historically near cycle peaks
Consider taking profits or reducing exposure
Light Green Background: MVRV < 1.0
Undervaluation zone
Holders are underwater on average
Historically strong accumulation opportunities
How to Interpret:
Bullish Signals:
MVRV crosses above its 365-day SMA (green fill appears)
MVRV bounces from the 1.0 level
MVRV enters the <1.0 zone (long-term buying opportunity)
Rising 365-day SMA suggests improving market health
Bearish Signals:
MVRV crosses below its 365-day SMA (red fill appears)
MVRV reaches 3.5+ levels (overheated)
Declining 365-day SMA suggests deteriorating market health
MVRV peaks and begins declining from extreme levels
Trend Confirmation:
Extended green fill periods = bull market
Extended red fill periods = bear market
Multiple touches of the 365-day SMA = consolidation/ranging market
Historical Performance:
Looking at past cycles:
2013-2015: MVRV peaked near 6.0, bottomed around 0.8
2017-2018: MVRV peaked near 4.5, bottomed around 0.9
2021-2022: MVRV peaked near 3.7, bottomed around 1.0
Each cycle shows declining peak MVRV ratios (maturing market)
The 365-day SMA has consistently marked trend transitions
Best Practices:
For Long-Term Investors:
Accumulate when MVRV < 1.0 and in green background zone
Be cautious when MVRV > 3.5 with red background
Use 365-day SMA as a macro trend filter
Don't expect perfect timing; these are probabilistic zones
For Active Traders:
Trade crossovers of MVRV and its 365-day SMA
Use the fill color changes as momentum indicators
Combine with price action and other technical indicators
Consider reducing position size as MVRV approaches 3.5+
Risk Management:
MVRV is a lagging indicator; it confirms trends rather than predicts them
Extreme readings can persist longer than expected
Past cycle tops/bottoms are not guaranteed to repeat
Always use proper position sizing and stop losses
Why This Metric Matters:
Unlike pure price-based indicators, MVRV incorporates fundamental on-chain data about holder behavior. It answers the question: "How much profit/loss are Bitcoin holders sitting on?" This makes it particularly useful for:
Identifying when market euphoria reaches unsustainable levels
Spotting capitulation events when holders panic sell at losses
Understanding the psychology driving current price action
Filtering out noise to focus on macro trend shifts
The 365-day moving average addition helps smooth volatility and identify sustained trend changes, making the indicator more actionable for both investors and traders.
Technical Notes:
Uses real on-chain data from CoinMetrics (Realized Cap) and Glassnode (Supply)
Calculations performed on daily timeframe data
Works best on daily, weekly, and monthly chart timeframes
Data availability starts from early Bitcoin history (2010+)
Disclaimer: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own research and consider your risk tolerance before making investment decisions.
BTC Dynamic Trend Core - Indicator v46🚀 Dynamic Trend Core
The Dynamic Trend Core is a sophisticated, multi-layer trading engine designed to identify high-probability, trend-following opportunities. It offers both a quantitative backtesting engine and a rich, intuitive visual interface.
Its core philosophy is simple: confirmation. The system seeks to filter out market noise by requiring a confluence of conditions—trend, momentum, price action, and volume—to be in alignment before a signal is considered valid.
⚙️ Core Logic Components
Primary Trend Analysis (SAMA): The foundation is a Self-Adjusting Moving Average (SAMA) that determines the underlying market trend (Bullish, Bearish, or Consolidation).
Confirmation & Momentum: Signals are confirmed with a blend of the Natural Market Slope and a Cyclic RSI to ensure momentum aligns with the primary trend.
Advanced Filtering Layers: A suite of optional filters allows for robust customization:
Volume & ADX: Ensure sufficient market participation and trend strength.
Market Regime: Uses the total crypto market cap to gauge broad market health.
Multi-Timeframe (MTF): Aligns signals with the dominant weekly trend.
BTC Cycle Analysis: Uses Halving or Mayer Multiple models to position trades within historical macro cycles.
Delta Zones: An additional filter to confirm signals with recent buy or sell pressure detected in candle wicks.
📊 The On-Chart Command Center
The strategy's real power comes from its on-chart visual feedback system, which provides full transparency into the engine's decision-making process.
Note: For the dashboard to update in real-time, you must enable "Recalculate on every tick" in the script's settings.
Power Core Gauge: Located at the bottom-center, this gauge is the heart of the system. It displays the number of active filter conditions met (e.g., 6/7) and "powers up" by glowing brightly as a signal becomes fully confirmed.
Live Conditions Panel: In the bottom-right corner, this panel acts as a detailed pre-flight checklist. It shows the real-time status of every single filter, helping you understand exactly why a trade is (or is not) being triggered.
Energized Trendline: The main SAMA trendline changes color and brightness based on the strength and direction of the trend, providing immediate visual context.
Halving Cycle Visualization: An optional visual guide to the phases of the Bitcoin halving cycle.
Delta Zone Pressure Boxes: A visual guide that draws boxes around candles exhibiting significant buying or selling pressure.
🛠️ How to Use
Indicator version of BTC DTC Strategy: "Alerts-Only Mode" for generating live signals.
Configure Strategy: Start with the default filters. If a potential trade setup is missed, check the Live Conditions Panel to see exactly which filter blocked the signal. Adjust the filters to suit your specific asset and timeframe.
Manage Risk: Adjust the Risk & Exit settings to match your personal risk tolerance.
CryptoSignalScanner - Pi Cycle - Golden Ratio MultiplierDESCRIPTION:
All credits are going to Philip Swift who has written an article on Medium about the PI Cycle Top and The Golden Ratio Multiplier .
Based on the article this indicator has been created to display and indicate the Bitcoin PI Cycle Top which has historically been effective in picking out the market cycle highs within 3 days. It also displays the Golden Ratio Multiplier which explores Bitcoin's adoption curve and market cycles.
• The PI Cycle Top is based on the 350DMA (Daily Moving Average) multiplied by 2 and the 111DMA (Daily Moving Average)
• The Golden Ratio Multiplier is based on the 350DMA (Daily Moving Average) the The Golden Ratio which is defines as 350DMA * 1.61803398875 and the Fibonacci Sequence which is defined as 350DMA * 2, 350DMA * 3, 350DMA * 5, 350DMA * 8, 350DMA * 13 and 350DMA * 21
HOW TO USE:
• The PI Cycle Top is picking the market cycle tops within 3 days.
When the 350DMA x2 crosses below the 111DMA Bitcoin price peaks in its market cycle. This indicates that the market is overbought and it is time to take profit.
• The Golden Ratio Multiplier pics the top on every market cycle in Bitcoin’s history and forecasts when Bitcoin will top in the coming market cycle.
In 2011 the top was at 350DMA * 21
In 2013 the top was at 350DMA * 13
In 2014 the top was at 350DMA * 8
In 2018 the top was at 350DMA * 5
If we look at the results above the forecast for next top should be at 350DMA * 3
FEATURES:
• You can change the Long Moving Average which is by default 350
• You can change the Short Moving Average which is by default 111
• You can show/hide the Pi Cycle Top labels
• You can show/hide the Pi Cycle Bottom labels
• You can show/hide the Pi Cycle Moving Averages
• You can show/hide the Golden Ratio
• You can show/hide the Fibonacci Sequence
• You can set an alert when the Pi Cycle Top is reached
REMARKS:
• This advice is NOT financial advice.
• We do not provide personal investment advice and we are not a qualified licensed investment advisor.
• All information found here, including any ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, expressed or implied herein, are for informational, entertainment or educational purposes only and should not be construed as personal investment advice.
• We will not and cannot be held liable for any actions you take as a result of anything you read here.
• We only provide this information to help you make a better decision.
• While the information provided is believed to be accurate, it may include errors or inaccuracies.
HOW TO GET ACCESS TO THE SCRIPT:
• Access to this script is free of charge
• You can drop me a message to get access to the script
Good Luck,
SEOCO
🗓️ FTD Cycle Lite Tracker🗓️ FTD Cycle Lite Tracker (Open Source)This is the simplified, open-source companion to the premium FTD SPIKE PREDICTOR - ML Model.This Lite version focuses purely on time-based cyclic analysis, highlighting the periods when the market is approaching the most well-known FTD-related time windows, based on historical, cyclic patterns.It's the perfect tool for traders who want clean, visual confirmation of anticipated cyclic dates without the complexity or predictive power of a multi-factor model.Key Features of the Lite Version:T+35 Cycle Tracking: Highlights the approximate 49-day calendar cycle (representing 35 trading days) often associated with mandatory Failures-to-Deliver clearing.147-Day Major Cycle: Highlights the long-term institutional cycle commonly observed in assets with complex contract deadlines, anchored from the January 28, 2021 date.Custom Anchor Points: Both cycles allow you to adjust the anchor date to suit different ticker-specific patterns.Visual Windows: Provides clear background shading and shape markers to indicate when the critical 5-day cycle windows are active.👑 Upgrade to the Full Prediction Engine!The open-source Lite version only gives you the calendar dates. The full, proprietary indicator goes far beyond simple calendar counting by telling you how probable a spike is on those dates, and which other factors are confirming the risk.Why Upgrade?FeatureFTD Cycle Lite (Free)FTD SPIKE PREDICTOR (Premium)OutputCalendar Dates0-100% Probability ScoreLogic2 Time Cycles Only7 Weighted Features (ML Model)ConfirmationNoneVolume, Price, Volatility, OPEX, Swap RollConfidenceNone95% Confidence IntervalsSignalsDate MarkersCritical Alerts & Feature BreakdownUnlock the Full PowerYou can get the FTD SPIKE PREDICTOR - ML Model for a one-time fee of $50.00.Since TradingView's invite-only feature is not available, you can contact me directly to gain access:TradingView: Timmy741X.com (Twitter): TimmyCrypto78
BTC Dual Cycle: Stats DashboardOverview
"Price takes the elevator down, but takes the stairs up."
This indicator is a macro-analysis tool designed to visualize the true duration of Bitcoin’s market cycles. Unlike standard oscillators that focus on short-term price action, the Macro Cycle Tracker filters out the noise to answer two fundamental questions:
Are we in a phase of Expansion (Price Discovery)?
Are we in a phase of Recovery (Repairing the damage of a crash)?
It visually separates the market into two distinct regimes based on a configurable drawdown threshold (default: -50%) and provides real-time statistics on how long these phases historically last.
How It Works
The script tracks the All-Time High (ATH) and divides market history into two colored zones:
🟢 The Green Zone (Expansion / Price Discovery)
Trigger: Starts immediately when Bitcoin breaks the previous ATH.
Meaning: The market is healthy, profitable, and exploring new valuation levels.
End: The zone ends when price drops by 50% (configurable) from the cycle top.
🔴 The Red Zone (Recovery / Capitulation)
Trigger: Starts when price drops below the 50% threshold from the peak.
Meaning: The asset is "underwater." This zone remains active persistently—even during relief rallies—until the previous ATH is fully reclaimed.
Philosophy: A cycle is not over until the damage is repaired.
Key Features
Cycle Timer: Displays the exact number of days passed for every historical cycle directly on the chart.
Live Counter: Shows the current duration of the active phase (e.g., "ZONE GREEN: 450 Days...").
Statistical Dashboard: A table in the bottom-right corner automatically calculates the Mean and Median duration (in days) for both Green and Red phases. This allows you to compare the current cycle against historical averages.
How to Use
For Investors (HODLers): Use the Red Zone to understand the "Time Cost" of a bear market. It helps visualize that recovery takes patience and that price action below the old ATH is merely accumulation.
For Analysts: Use the Dashboard statistics to project potential cycle turning points based on historical median durations.
Settings
Drop Percent (%): Default is 50%. This defines the "Crash" threshold. You can adjust this to 20% or 30% for more sensitive cycle detection.
Text Size: Adjust the size of the dashboard text to fit your screen resolution.
Disclaimer: This tool is for educational purposes only and does not constitute financial advice. Past performance is not indicative of future results.
Fast Fourier Transform (FFT) FilterDear friends!
I'm happy to present an implementation of the Fast Fourier Transform (FFT) algorithm. The script uses the FFT procedure to decompose the input time series into its cyclical constituents, in other words, its frequency components , and convert it back to the time domain with modified frequency content, that is, to filter it.
Input Description and Usage
Source and Length :
Indicates where the data comes from and the size of the lookback window used to build the dataset.
Standardize Input Dataset :
If enabled, the dataset is preprocessed by subtracting its mean and normalizing the result by the standard deviation, which is sometimes useful when analyzing seasonalities. This procedure is not recommended when using the FFT filter for smoothing (see below), as it will not preserve the average of the dataset.
Show Frequency-Domain Power Spectrum :
When enabled, the results of Fourier analysis (for the last price bar!) are plotted as a frequency-domain power spectrum , where “power” is a measure of the significance of the component in the dataset. In the spectrum, lower frequencies (longer cycles) are on the right, higher frequencies are on the left. The graph does not display the 0th component, which contains only information about the mean value. Frequency components that are allowed to pass through the filter (see below) are highlighted in magenta .
Dominant Cycles, Rows :
If this option is activated, the periods and relative powers of several dominant cyclical components that is, those that have a higher power, are listed in the table. The number of the component in the power spectrum (N) is shown in the first column. The number of rows in the table is defined by the user.
Show Inverse Fourier Transform (Filtered) :
When enabled, the reconstructed and filtered time-domain dataset (for the last price bar!) is displayed.
Apply FFT Filter in a Moving Window :
When enabled, the FFT filter with the same parameters is applied to each bar. The last data point of the reconstructed and filtered dataset is used to build a new time series. For example, by getting rid of high-frequency noise, the FFT filter can make the data smoother. By removing slowly evolving low-frequency components (including non-periodic constituents), one can reveal and analyze shorter cycles. Since filtering is done in real-time in a moving window (similar to the moving average), the modified data can potentially be used as part of a strategy and be subjected to other technical indicators.
Lowest Allowed N :
Indicates the number of the lowest frequency component used in the reconstructed time series.
Highest Allowed N :
Indicates the number of the highest frequency component used in the reconstructed time series.
Filtering Time Range block:
Specifies the time range over which real-time FFT filtering is applied. The reason for the presence of this block is that the FFT procedure is relatively computationally intensive. Therefore, the script execution may encounter the time limit imposed by TradingView when all historical bars are processed.
As always, I look forward to your feedback!
Also, leave a comment if you'd be interested in the tutorial on how to use this tool and/or in seeing the FFT filter in a strategy.
(1) Genie Cycles VS-200The Genie Cycles indicator contains two primary components. The first generates the primary turning-point Entry/Exit signals based on a hybrid algorithms that utilize multiple moving filters and oscillators, all working in concert. The second is our version of Hurst Cycles allowing the trader to view the harmonic convergence of short and long cycles.
The turning-point signals are generated by two Center of Gravity Oscillators (COG) originally developed by John Ehlers and published in Technical Analysis of Stocks and Commodities in its May 2002 issue.
COG produces a moving filter that heavily weights the most extreme and most current values in the stream of data within the window of the indicator. COG excels at determining and indicating where, within a parabolic path, tipping or turning points have occurred. Two COG indicators, each one set to a different length and different inputs are incorporated. The output of these two COG filters are them put through another Ehler’s filter, the Pass Band; July 2016 issue of TAOSAC. A pass band filter has the unique ability of removing the higher and lower frequencies from the signal, leaving behind only the core signal. Here we are taking a longer COG period of (10) days, utilizing the candles body size as it’s input and then subtracting a short period of (7) days utilizing only the close of the day. The result is an emphasis on the extreme values, i.e., the maximum apex and the minimum vertex of each parabolic swing. Finally, the Arnaud Legoux Moving Average (ALMA) is utilized as smoothing a filter to slightly shift the weighting from the COG Pass band filter, in a selective and adjustable manor to more current bars, not the most current bar. This is desirable because COG dramatically emphasizes the most current candle or bar as well as large candles and strong deviations from within the moving average.
This provides the trader with excellent responsiveness within a very smooth output signal with very few artifacts or whipsaws, producing highly reliable trading signals that indicate optimal entry and exit points with a high level of accuracy and very little lag.
The primary principals of Hurst cycles are price moves in waves that exhibit cyclic attributes based on their time scales. Genie Cycles incorporates Hurst cycles theories, but utilizes only two nested Laguerre moving filters. Laguerre moving filters have significantly less lag than traditional moving averages. These moving filters take as there inputs the highest high and the lowest lows for the two adjustable periods. The point of the indicator is to determine when a short-term swing cycle harmonizes or aligns with a long-term cycle, i.e., determining when the tops and bottoms of these cycles align.
The resulting nested channels produce natural bounding boxes. This dramatically highlights likely support and resistance levels as they often occur at prior highs or lows that this indicator is drawing. Convergence of the different cycle lengths can indicate strong trends that make excellent trading opportunities. Decoupling of the cycles indicates the end of the trend.
CAT FLD SmoothWhat is an FLD?
The FLD stands for Future Line of Demarcation, introduced by J.M. Hurst in his Cyclic Analysis work.
It is constructed by shifting the price forward in time by half the length of a given cycle. For example, if you want to analyze a 40-bar cycle, you would plot price shifted forward by 20 bars. This creates a projected line that acts as a dynamic reference for where the cycle rhythm should align.
In practice, each cycle has its own FLD (20, 40, 80 bars, etc.), and when price interacts with those FLDs, it often reveals the underlying rhythm of market waves.
How Traders Use the FLD
1. Cycle Detection
When price crosses its FLD, it is often the signal that a cycle trough or peak has recently formed. This allows the trader to recognize where one wave ends and the next begins.
Upward cross → suggests a new upward cycle has started.
Downward cross → suggests a downward cycle is unfolding.
2. Projection of Price Targets
One of Hurst’s key insights is that after crossing an FLD, price often travels a distance roughly equal to the recent cycle’s amplitude. This makes the FLD a tool not only for timing but also for projecting targets.
Example:
If price rises through the 40-bar FLD after a cycle trough, the expected move is often the same height as the move off the last trough to the point of a break through the FLD.
3. Support and Resistance
FLDs can act like invisible levels of support and resistance, but unlike static horizontal levels, they are dynamic and cycle-based. Price often hesitates, bounces, or accelerates when touching its FLD.
4. Multi-Cycle Confluence
Markets rarely move in just one cycle length. By plotting multiple FLDs (for example, 20-bar, 40-bar, and 80-bar), traders can see where several FLDs line up. These confluences are particularly powerful—they highlight high-probability turning points.
Why FLDs Matter?
They help separate noise from structure by focusing on repeating time rhythms.
They provide early signals of where cycles invert.
They give price targets that are not arbitrary, but cycle-derived.
They can be combined with other tools (trendlines, oscillators, volume) for confirmation.
👉 With this indicator, you can visualize Hurst’s FLDs directly on your TradingView charts, making it easier to detect cycles, project targets, and anticipate turning points before they become obvious to everyone else.
CastAway Trader LLC, the publisher of this indicator is not registered as an investment adviser nor a broker/dealer with either the U. S. Securities & Exchange Commission or any state securities regulatory authority.
CastAway Trader LLC reserves the right to un-publish this indicator or change it without any written notice.
Past results are not indicative of future profits.
MVRV Ratio [Alpha Extract]The MVRV Ratio Indicator provides valuable insights into Bitcoin market cycles by tracking the relationship between market value and realized value. This powerful on-chain metric helps traders identify potential market tops and bottoms, offering clear buy and sell signals based on historical patterns of Bitcoin valuation.
🔶 CALCULATION The indicator processes MVRV ratio data through several analytical methods:
Raw MVRV Data: Collects MVRV data directly from INTOTHEBLOCK for Bitcoin
Optional Smoothing: Applies simple moving average (SMA) to reduce noise
Status Classification: Categorizes market conditions into four distinct states
Signal Generation: Produces trading signals based on MVRV thresholds
Price Estimation: Calculates estimated realized price (Current price / MVRV ratio)
Historical Context: Compares current values to historical extremes
Formula:
MVRV Ratio = Market Value / Realized Value
Smoothed MVRV = SMA(MVRV Ratio, Smoothing Length)
Estimated Realized Price = Current Price / MVRV Ratio
Distance to Top = ((3.5 / MVRV Ratio) - 1) * 100
Distance to Bottom = ((MVRV Ratio / 0.8) - 1) * 100
🔶 DETAILS Visual Features:
MVRV Plot: Color-coded line showing current MVRV value (red for overvalued, orange for moderately overvalued, blue for fair value, teal for undervalued)
Reference Levels: Horizontal lines indicating key MVRV thresholds (3.5, 2.5, 1.0, 0.8)
Zone Highlighting: Background color changes to highlight extreme market conditions (red for potentially overvalued, blue for potentially undervalued)
Information Table: Comprehensive dashboard showing current MVRV value, market status, trading signal, price information, and historical context
Interpretation:
MVRV ≥ 3.5: Potential market top, strong sell signal
MVRV ≥ 2.5: Overvalued market, consider selling
MVRV 1.5-2.5: Neutral market conditions
MVRV 1.0-1.5: Fair value, consider buying
MVRV < 1.0: Potential market bottom, strong buy signal
🔶 EXAMPLES
Market Top Identification: When MVRV ratio exceeds 3.5, the indicator signals potential market tops, highlighting periods where Bitcoin may be significantly overvalued.
Example: During bull market peaks, MVRV exceeding 3.5 has historically preceded major corrections, helping traders time their exits.
Bottom Detection: MVRV values below 1.0, especially approaching 0.8, have historically marked excellent buying opportunities.
Example: During bear market bottoms, MVRV falling below 1.0 has identified the most profitable entry points for long-term Bitcoin accumulation.
Tracking Market Cycles: The indicator provides a clear visualization of Bitcoin's market cycles from undervalued to overvalued states.
Example: Following the progression of MVRV from below 1.0 through fair value and eventually to overvalued territory helps traders position themselves appropriately throughout Bitcoin's market cycle.
Realized Price Support: The estimated realized price often acts as a significant
support/resistance level during market transitions.
Example: During corrections, price often finds support near the realized price level calculated by the indicator, providing potential entry points.
🔶 SETTINGS
Customization Options:
Smoothing: Toggle smoothing option and adjust smoothing length (1-50)
Table Display: Show/hide the information table
Table Position: Choose between top right, top left, bottom right, or bottom left positions
Visual Elements: All plots, lines, and background highlights can be customized for color and style
The MVRV Ratio Indicator provides traders with a powerful on-chain metric to identify potential market tops and bottoms in Bitcoin. By tracking the relationship between market value and realized value, this indicator helps identify periods of overvaluation and undervaluation, offering clear buy and sell signals based on historical patterns. The comprehensive information table delivers valuable context about current market conditions, helping traders make more informed decisions about market positioning throughout Bitcoin's cyclical patterns.
QT/TD.Den Quarterly Theory QT//Quarterly Theory/OPTD
These Quarters represent:
A - Accumulation (required for a cycle to occur)
M - Manipulation
D - Distribution
X - Reversal/Continuation
The latter are going to always be in this specific sequence; however the cycle can be transposed to have its beginning in X, trivially followed by A, M, and finally D.
This feature is not automatic and at the subjective discretion of the Analyst.
Note: this theory has been developed on Futures, hence its validity and reliability may change depending on the market Time.
This tool does provide a dynamic and auto-adapting aspect to different market types and Times, however they must be seen as experimental.
> Quarterly Cycles
The Quarterly Cycles currently supported are: Yearly, Monthly, Weekly, Daily, 90 Minute, Micro Sessions.
– Yearly Cycle:
Analogously to financial quarters, the year is divided in four sections of three months each
Q1 - January, February, March
Q2 - April, May, June (True Open, April Open)
Q3 - July, August, September
Q4 - October, November, December
VIDYA with Dynamic Length Based on ICPThis script is a Pine Script-based indicator that combines two key concepts: the Instantaneous Cycle Period (ICP) from Dr. John Ehlers and the Variable Index Dynamic Average (VIDYA). Here's an overview of how the script works:
Components:
Instantaneous Cycle Period (ICP):
This part of the indicator uses Dr. John Ehlers' approach to detect the market cycle length dynamically. It calculates the phase of price movement by computing the in-phase and quadrature components of the price detrended over a specific period.
The ICP helps adjust the smoothing length dynamically, giving a real-time estimate of the dominant cycle in price action. The script uses a phase calculation, adjusts it for cycle dynamics, and smoothes it for more reliable readings.
VIDYA (Variable Index Dynamic Average):
VIDYA is a moving average that dynamically adjusts its smoothing length based on the market conditions, in this case, using the RSI (Relative Strength Index) as a weight.
The length of VIDYA is determined by the dynamically calculated ICP, allowing it to adapt to changing market cycles.
This indicator performs several recursive layers of VIDYA smoothing (applying VIDYA multiple times) to provide a more refined result.
Key Features:
Dynamic Length: The length for the VIDYA calculation is derived from the smoothed ICP value, meaning that the smoothing adapts to the detected cycle length in real-time, making the indicator more responsive to market conditions.
Multiple VIDYA Layers: The script applies multiple layers of VIDYA smoothing (up to 5 iterations), further refining the output to smooth out market noise while maintaining responsiveness.
Plotting: The final smoothed VIDYA value and the smoothed ICP length are plotted. Additionally, overbought (70) and oversold (30) horizontal lines are provided for visual reference.
Application:
This indicator helps identify trends, smooths out price data, and adapts dynamically to market cycles. It's useful for detecting shifts in momentum and trends, and traders can use it to identify overbought or oversold conditions based on dynamically calculated thresholds.
Intellect_city - World Cycle - Ath - Timeframe 1D and 1WIndicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA, not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. However, in this instance, it does so with a high degree of accuracy over Bitcoin's adoption phase of growth.
Bitcoin Price Prediction Using This Tool
The Pi Cycle Top Indicator forecasts the cycle top of Bitcoin’s market cycles. It attempts to predict the point where Bitcoin price will peak before pulling back. It does this on major high time frames and has picked the absolute tops of Bitcoin’s major price moves throughout most of its history.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter-term moving average, which is the 111-day moving average, has reached an x2 multiple of the 350-day moving average. Historically, it has proved advantageous to sell Bitcoin around this time in Bitcoin's price cycles.
It is also worth noting that this indicator has worked during Bitcoin's adoption growth phase, the first 15 years or so of Bitcoin's life. With the launch of Bitcoin ETF's and Bitcoin's increased integration into the global financial system, this indicator may cease to be relevant at some point in this new market structure.
Gherkinit Futures Cycle█ OVERVIEW
Presented here is code for the " NYSE:GME Futures cycle theory" originally conceived by Gherkinit (Pi-Fi) and his quantitative analysts which is still under peer review.
This theory was built upon the knowledge that many intelligent investors on Reddit accrued over the past year in regards to the Mother Of All Short Squeezes this stock has to offer.
Up until now, what happened in January 2021 was considered an anomaly brought on by FOMO and retail interest but it's starting to look like unfair market makers and similar went to cover and ran head on into retail FOMO which is why they cut off the buying at that time. In order to understand what happened and what's to come, visualizing the theory with ease is essential.
█ WHAT THE SETTINGS MEAN
- Enable Draw | Visual Clean up
(True/False) Quarterly dates : Enables or disables the quarterly dates that repeat every "cycle".
(True/False) Roll dates : Enables or disables the roll dates that repeat every "cycle".
(True/False) Expiration dates : Enables or disables the expiration dates that repeat every "cycle".
(True/False) Run dates : Enables or disables the run dates that repeat every "cycle".
- Date Colors | Making things look good
(Color) Quarterly : Color for the respective date.
(Color) Roll : Color for the respective date.
(Color) Expiration : Color for the respective date.
(Color) Run : Color for the respective date.
- Extended Cycle | Look into the future
(Integer) Extended line height multiplier : A multiplier value for the height of the lines representing the selected "future" cycle.
(Dollar Amount) Extended line height : The height value in dollars of the lines representing the selected "future" cycle.
(Integer) Extended line width : The width of the lines representing the selected "future" cycle.
(Integer) Extended cycle ID : The cycle you want to see "ahead" or in the "future". For example if you set the value to "0" you'll only see cycles from the past up until the present (already occurred). If you set the value to "1" you will see the estimated dates for the specific cycle in the future i.e. 1 cycle ahead of the last completed/visible cycle on the chart.
█ EXTRA INFO
This indicator was simply made by a bored CS student who didn't want to endlessly mark dates on a graph after learning more about the theory.
Hope this help whoever uses this. To the moon fellow apes!
- Winter ;)
P.s. Pickle 4 Life
Financial Astrology Saturn LongitudeSaturn energy strengthen the temperance, rectitude, constancy, greed, pessimism and precautionary. Under this influence the crowd will move with caution, slow and with strong and rigorous sense, analysing the environment in detail and deducting all the possible action outcomes based on the past experiences and utilising all the accesible wisdom. This cycle rules the land and real state, the state and institutions, officials, and regulations.
Due to the essential nature of this energy is expected that traders take more caution and reflexion in their investment decisions where Saturn transits through earth element (Taurus, Virgo, Capricorn) because the persons become more prudent and rigid. In water elements (Cancer, Scorpio and Pisces) traders will be reducing exposure to risky assets because the emotions are more unstable and the fear to loss results in risk aversion.
This cycle takes 29 years to complete so we don't have enough observations in the crypto-currencies sector to evaluate the potential effect of Saturn through all the zodiac signs but with the historical data available, there are some interesting patterns: the most bearish zodiac signs was Scorpio (water) and Capricorn (earth) and the most bullish was Sagittarius and Aquarius. This correlates well with other planet cycles where we have observed that air zodiac signs are usually bullish.
This indicator provides longitude since 2010 so will be limited in the zodiac signs that is possible to be analysed, however the periods of retrogradation and stationary speed phases could give interesting trading signals. We encourage you to analyse this cycles in different markets and share with us your observations, leave us a comment with your research outcomes. Happy research!
Note: The Saturn tropical longitude indicator is based on an ephemeris array that covers years 2010 to 2030, prior or after this years the longitude is not available, this daily ephemeris are based on UTC time so in order to align properly with the price bars times you should set UTC as your chart reference timezone.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
Ehlers Adaptive Center Of Gravity [CC]The Adaptive Center Of Gravity was created by John Ehlers and this is a regular center of gravity indicator combined to be use with the current cycle period. If you are not familiar with stock cycles then I would highly recommend his book on the subject: Cycle Analytics. Buy when the indicator turns green and sell when it turns red.
Let me know if there are any other indicators you want me to publish!
[blackcat] L2 Ehlers Dominant Cycle Tuned Bandpass FilterLevel: 2
Background
John F. Ehlers introuced his Dominant Cycle Tuned Bandpass Filter Strategy in Mar, 2008.
Function
In "Measuring Cycle Periods", author John Ehlers presents a very interesting technique of measuring dominant market cycle periods by means of multiple bandpass filtering. By utilizing an approach similar to audio equalizers, the signal (here, the price series) is fed into a set of simple second-order infinite impulse response bandpass filters. Filters are tuned to 8,9,10,...,50 periods. The filter with the highest output represents the dominant cycle. A full-featured formula that implements a high-pass filter and a six-tap low-pass Fir filter on input, then 42 parallel Iir band-pass filters.
I've coded John Ehlers' filter bank to measure the dominant cycle (DC) and the sine and cosine filter components in pine v4 for TradingView, based on John Ehlers' article in this issue, "Measuring Cycle Periods." The CycleFilterDC function plots and returns the DC series and its components, so it's a trivial matter to make use of them in a trading strategy.
Based on John Ehlers' article, "Measuring Cycle Periods," he chose to implement the dominant cycle-tuned bandpass filter response to test Ehlers' suggestion to use the sine and cosine crossovers as buy and sell signals. If the sine closely follows the price pattern as suggested, and the cosine is an effective leading function of the sine, then it seems to make sense that a crossover implementation would work well (Personally, what I observed this is not so accurated as his claims).
What he discovered in his tests was that crossovers happened at frequent intervals, even when price has not moved significantly. This leads to a higher percentage of losing trades, particularly when spread, slippage, and commissions are accounted for. Nevertheless, the cosine crossover was quite effective at identifying reversals very early in many cases, so this indicator could prove quite effective when used alongside other indicators. In particular, the use of an indicator to confirm a certain level of recent volatility, as well as an indicator to confirm significant rate of change, could prove quite helpful.
Key Signal
CosineLine--> Ehlers Dominant Cycle Tuned Bandpass Filter Strategy fast line
SineLine--> Ehlers Dominant Cycle Tuned Bandpass Filter Strategy slow line
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 72th script for Blackcat1402 John F. Ehlers Week publication.
NOTE: Although Dr. Ehlers think high of Cosine and Sine wave indicator and trading strategy, my study and trading experience indicated it did not work that well as many other oscillator indicators. However, I would like to keep the original code of Dr. Ehlers for anyone who want to make a deep dive into this kind of indicator or strategy with Cosine and Sine wave.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Strength Analyzer [DW]This is an experimental hybrid between relative strength and spectrum analysis methods aimed to deliver useful insights about cyclical dominance and momentum.
This study utilizes a modified RSI formula and a modified Goertzel algorithm to determine relative strength and spectral dominance for periods 8 through 50.
These periods are theorized by many analysts to be the main cyclical components of market movement.
In this study, you are given the option to apply equalization (EQ) to the dataset before estimating strength.
This enables you to transform your data and observe how strength estimates changes as well.
Whether you want to give emphasis to some frequencies, isolate specific bands, or completely alter the shape of your waveform, EQ filtration makes for an interesting experience.
The default EQ preset in this script cuts low end presence, dampens high frequency oscillations, and cleanly passes main cyclic components.
There are many ways to use EQ to transform your dataset, so play around with the settings and find the presets that work best for your analysis setup.
After EQ processing, the data is then passed through the modified RSI algorithm to generate momentum information
The modified RSI in this script is rescaled to oscillate between -1 and 1, and has the option to pass through a 2 pole Butterworth low pass filter before and after processing for a smoother output.
The strength thresholds are determined by the threshold value, which quantifies distance above and below 0.
The threshold value can also be thought of as conventional RSI distance from 50 rescaled so that an increment of 0.1 is equivalent to an increment of 5 on a conventional RSI.
A threshold value of 0.4 is equivalent to thresholds of 70 and 30 on a conventional RSI, so this is the default. The maximum threshold value is 1, which is equivalent to thresholds of 100 and 0.
This script plots colored sections for each period value using a gradient color scheme based on their respective strength estimates.
The color scheme in this script is a multicolored gradient that shows green scaled colors for bullish strength and red scaled colors for bearish strength.
Darker, less vibrant colors indicate lower strength. Brighter, more vibrant colors indicate higher strength.
Strength values near 0 will show the darkest colors, and values near the positive or negative threshold value will show the brightest.
The data is fed parallel through the modified Goertzel algorithm to obtain cyclic power information and to estimate the dominant cycle.
Gerald Goertzel's algorithm is a unique Fourier related transform that identifies tonal properties by quantifying resonance in a set of second order IIR filters with direct-form structure.
It is computationally more efficient than typical DFT or FFT algorithms, and yields decent spectral resolution.
In this variation of the algorithm, data is first passed through a 2 pole high pass filter to attenuate spectral dilation, then passed through a Hamming Window to tidy up the frequency range.
The clean windowed data is then passed through a recursive resonance loop over the frequency block to calculate filter coefficients, which are then used to identify real and imaginary magnitude components.
From there, the magnitude components are used to calculate cyclic power.
The power outputs of each period are then compared for dominant cycle estimation, which is plotted over the gradient.
The dominant cycle can also be optionally smoothed or halved based on your preferences.
Bar colors are included in this script. The color scheme is a gradient based on dominant cycle momentum.
Signals and alert conditions are included in this script as well, and can be customized to your liking.
The two main signal types in this script are:
-> Dominant Cycle - Signals based on dominant cycle or half dominant cycle changes from positive to negative strength or vice versa.
-> Confluence - Signals based on confluence emergence. Based on the majority of measured cycles or all measured cycles showing positive or negative strength.
The signals in this are also externally accessible by other scripts.
The output format is 1 for long signals, and -1 for short signals.
To integrate these signals with your own system, use a source input in your script and assign it to this script's "Direction Signals" output variable from the dropdown tab.
In addition, I included two external output variables that show dominant cycle strength and average cycle strength.
They can be integrated into your own scripts by using a source input and selecting the proper output variable, just like the signals.
The Strength Analyzer is a versatile and powerful analytical tool to have in the arsenal for generating unique insights about momentum and cycle dominance.
By analyzing strength on a spectral basis, we can look at relative price movements on a deeper level and gain insights that aren't necessarily obvious from simply looking at a price chart.
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This is a premium script, and access is provided on an invite-only basis.
To gain access, get a copy of the script overview, or for any other inquiries, send me a direct message!
I look forward to hearing from you!
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General Disclaimer:
Trading stocks, futures, Forex, options, ETFs, cryptocurrencies or any other financial instrument has large potential rewards, but also large potential risk.
You must be aware of the risks and be willing to accept them in order to invest in stocks, futures, Forex, options, ETFs or cryptocurrencies.
Don’t trade with money you can’t afford to lose.
This is neither a solicitation nor an offer to Buy/Sell stocks, futures, Forex, options, ETFs, cryptocurrencies or any other financial instrument.
No representation is being made that any account will or is likely to achieve profits or losses of any kind.
The past performance of any trading system or methodology is not necessarily indicative of future results.
------------------------------------------------
Note:
Because TV's UI can't handle displaying style options for 43 fills with 42 colors, the color scheme of the analyzer is currently not editable.
However, no other sacrifices to functionality or quality were made in this project.
As the TV team performs updates on the platform, the ability to customize this color scheme will likely come as well.
Also, it's important to note that this script uses a heavy amount of calculations to generate this output.
At times (very infrequently), TV will throw an error message saying "Calculation Takes Too Long", likely due to a momentary lull in available server space.
If you receive this error, simply hide then unhide the indicator, and everything should function as expected.
Trend Catcher - Alpha v2 - by Crypto_Dan_CroIf you want to get this indicator, contact me on
X handle: @crypto_dan_cro
What is Trend Catcher v2?
This is the only indicator you need ;)
This indicator is a proprietary market analysis system designed to identify high-probability trading zones by synchronizing multiple layers of market structure, momentum behaviour and cyclical dynamics.
It dynamically adapts to changing market conditions by evaluating:
- macro trend alignment
- structural price positioning
- momentum acceleration & deceleration
- volatility-based reaction zones
- cycle maturity levels
The system filters out low-quality setups and highlights only areas where multiple hidden conditions align, providing:
- trend continuation signals
- structural shift detection
- cycle-based expansion targets
- adaptive support & resistance mapping
Rather than reacting to price alone, the indicator anticipates areas where market psychology historically shifts, allowing traders to position themselves ahead of major moves.
Core philosophy:
This tool does not attempt to predict the market — it tracks the underlying pressure points where probability favours expansion or exhaustion.
It functions as:
- a trend alignment engine
- a cycle decoder
- a volatility interpreter
- a structure validation system
What it gives the user:
- Clear visual guidance without overloading the chart
- Objective market context independent of emotion
- Early trend recognition
- Cycle-aware price targeting
- Decision zones instead of random entries
Ideal for:
- traders who trade structure, not noise
- investors who respect market cycles
- strategists focused on probability over prediction
- disciplined entries & exits
In short:
It is a market interpretation framework built for traders who think two steps ahead.
Contains:
1. Higher Timeframe mode (Monthly / Weekly) on all timeframes
2. Current Chart Timeframe mode
3. Global Trend via BTC MACD
4. SMA
5. EMA
6. BO (Break Out), BD (Break Down) signals
7. TOP & BOTTOM Detection
8. Support & Resistance Zones
9. RSI confirmation
10. Smart Info Panel (Global trend, MACD, SMA, EMA, RSI statuses - Bull, Bear, Neutral)
11. Monthly timeframe (Fibbonaci Retracement levels)
12. Monthly timeframe (all Cycle tops, and Cycle bottoms)
Crypto markets are volatile, if you choose to use this indicator for trading, you are doing it on your own. Crypto_dan_cro is not responsible for any profits or losses created by using this Indicator.
Torus Trend Bands — Windowed HammingTorus Trend Bands — Windowed Hamming
This TradingView indicator creates dynamic support and resistance bands on your chart. It uses the mathematical model of a torus (a donut shape) to generate cyclical and responsive channel boundaries. The bands are further refined with an advanced smoothing method called a Hamming window to reduce noise and provide a clearer signal.
How It Works
The Torus Model: The indicator maps price action onto a geometric torus shape. This is defined by two key parameters:
Major Radius (a): The distance from the center of the torus to the center of the tube. This controls the overall size and primary cycle.
Minor Radius (b): The radius of the tube itself. This controls the secondary, faster "breathing" motion of the bands.
Dual-Phase Engine: The behavior of the bands is driven by two different cyclical inputs, or "phases":
Major Rotation (φ): A slow, time-based cycle (φ period) that governs the long-term oscillation of the bands.
Minor Rotation (q): A fast, momentum-based cycle derived from the Relative Strength Index (RSI). This makes the bands react quickly to price momentum, expanding and contracting as the market becomes overbought or oversold.
Standard Technical Core : The torus model is anchored to the price chart using standard indicators:
Midline : A central moving average that acts as the baseline for the channel. You can choose from EMA, SMA, HMA, or VWAP.
Width Source: A volatility measure that determines the fundamental width of the bands. You can choose between the Average True Range (ATR) or Standard Deviation.
Hamming Window Smoothing: This is a sophisticated weighted averaging technique (a Finite Impulse Response filter) used in digital signal processing. It provides exceptionally smooth results with less lag than traditional moving averages. You can apply this smoothing to the RSI, the midline, and the width source independently to filter out market noise.
How to Interpret and Use the Indicator
Dynamic Support & Resistance: The primary use is to identify potential reversal or continuation points. The upper band acts as dynamic resistance, and the lower band acts as dynamic support.
Trend Identification: The color of the bands helps you quickly see the current trend. Teal bands indicate an uptrend (the midline is rising), while red bands indicate a downtrend (the midline is falling).
Volatility Gauge: When the bands widen, it signals an increase in market volatility. When they contract, it suggests volatility is decreasing.
Alerts: The indicator includes built-in alerts that can notify you when the price touches or breaks through the upper or lower bands, helping you stay on top of key price action.
Key Settings
Torus Parameters : Adjust Major radius a and Minor radius b to change the shape and cyclical behavior of the bands.
Phase Controls:
φ period: Controls the length of the main, slow cycle in bars.
RSI length → q: Sets the lookback for the RSI that drives the momentum-based cycle.
Midline & Width: Choose the type and length for the central moving average and the volatility source (ATR/StDev) that best fits your trading style.
Width & Bias Shaping:
Min/Max width ×: Control how much the bands expand and contract.
Bias ×: Shifts the entire channel up or down based on RSI momentum, helping the bands better capture strong trends.
Hamming Controls: Enable or disable the advanced smoothing on different parts of the indicator and set the Hamming length (a longer length results in more smoothing).
This indicator provides a unique and highly customizable way to visualize market cycles, volatility, and trend, combining geometry with proven technical analysis tools.
Market GloryV1 -Introducing the new Market Glory indicator! In this indicator you will find:
- Dynamic Trends: a beta feature that takes into account both the maximum high and lowest low values anywhere between 5 to 200 bars back to determine the respective resistance and support levels at all times, with a trailing guidance middle bar that can serve as a meter for direction and takes into account only the close values of the defined 5-200 lookback bars! ( ***Strictly based on the 1 minute timeframe. )
- Engulfing bars: a beta feature that allows you to seek out potential reversal bars, based on the dema tema clouds and the respective bar's open and close!!
- Cycle bars: a Market Sniper classic feature, enabling you to catch momentum, consolidation, and continuation via hollow candles! This is achieved by detecting whether the open and close values stem from within the dema tema cloud's boundaries!
- Levels: also a Market Sniper classic, which lets you see support and resistance levels based on previous daily, weekly, and monthly opening and closing values! Also takes into account current closing price action, which will update the levels after being broken!! Furthermore, takes into account fibonacci steps (0.236, 0.382, and 0.5) per timeframe to determine where the nearest level will draw out. **The Calibration feature enables you to look ahead for potential upcoming resistances, with maximum precision.
- EMA crossings: A legacy feature in almost any popular indicator, as a means to correspond with the dema tema cycles for better entries and exits!!
- Multi-timeframe popup labels: By hovering (or long pressing in mobile) over the support and resistance level labels, you can see each dedicated timeframe's current cycle and crossing, to assess whether the stock is following a particular direction! (based solely on real-time close value)
- Lastly...
--- Fully customizable options in coloring and values, including ready-to-go defaults with tooltips to guide you to the Glory you deserve!!!
