RT-Mayer MultipleThe Mayer Multiple is a simple metric used to gauge whether Bitcoin is overvalued, undervalued, or fairly priced relative to its long term trend. It compares Bitcoin’s current price to its 200 day moving average and expresses that relationship as a single number.
Introduction
The Mayer Multiple was popularized by investor Trace Mayer as a way to track how far Bitcoin has stretched above or below its 200 day moving average (200DMA). The basic idea is:
Mayer Multiple = Current Bitcoin Price / 200 Day Moving Average of Bitcoin
When this ratio is low, price is trading close to or below its long term trend. When it is very high, price is extended well above trend and risk of mean reversion grows.
This script takes that concept and turns it into a set of colored bands around price. Instead of just plotting a single Mayer Multiple line, it maps different ranges of the multiple into visual “zones” so traders can quickly see whether Bitcoin is in a typical range, an accumulation zone, or a historically stretched area.
Behind The Math
In this implementation, the current Mayer Multiple value is computed for each bar and then mapped into band levels that typically span from roughly 0.4 up to the 8.0+ region. Each band represents a different multiple of the 200DMA.
Conceptually:
Values near 1.0 mean price is trading near its 200 day moving average.
Values well below 1.0 highlight periods where price is trading at a discount to long term trend.
Values far above 1.0 highlight periods where price is trading at a large premium to long term trend.
By converting these ranges into layered color zones, the script lets traders see where current price sits in the broader historical distribution of Mayer Multiple values, instead of focusing on a single number. In the chart below, the formula is overlaid in the center of the screen so you can see how the multiple is defined while looking at the bands.
Points Of Interest
Two regions on the Mayer structure tend to attract the most attention: lower “accumulation” areas and higher “distribution” areas.
Accumulation
Historically, many of the best long term accumulation opportunities have occurred when the Mayer Multiple spent time below roughly 0.9. In those zones, price is trading below its 200DMA and the band colors indicate that Bitcoin is at a relative discount compared to its long term trend. In the example chart below, the white arrows highlight past periods where price spent time in the lower bands while the Mayer Multiple was below roughly 0.9.
Distribution
On the other side, readings above roughly 2.0 have often lined up with distribution or profit taking areas, where price is extended well above the 200DMA. These zones have frequently preceded larger drawdowns or multi month cooling periods. In the example chart below, the white arrows highlight periods where price pushed into the upper bands above 2.0, areas that have often preceded larger cooling phases.
The 2.4 Rule
During the original exploration of the Mayer Multiple, backtests suggested that buying when the multiple was already above about 2.4 tended to produce weaker risk adjusted returns. In simple terms, history showed that:
A Mayer Multiple above 2.4 means Bitcoin is trading at more than 240 percent of its 200 day moving average.
Many of the most extreme speculative peaks occurred when the multiple was in or above this zone.
After such peaks, price often reverted back toward the 200DMA with drawdowns in the 30 percent to 80 percent range.
In this script, the 2.4 level is highlighted as a caution band. It does not mean price must reverse immediately, but it marks an area where the balance between upside potential and downside risk has historically shifted. In the chart below, the white arrow marks the 2.4 band that this script highlights as a caution zone.
Why Traders Watch This Zone
There are a few reasons traders and investors watch the upper Mayer bands, especially the 2.4 area:
Historical patterns – Many of Bitcoin’s more extreme tops, such as late 2013, late 2017, and early 2021, occurred when the Mayer Multiple was well above 2.0 and frequently near or above 2.4.
Overheated zone – When price is this far above its long term average, markets are often driven by FOMO and speculative flows rather than steady accumulation.
Mean reversion risk – Over time, price has repeatedly reverted back toward or below the 200DMA after visiting these upper bands.
Risk / reward balance – Above 2.4, the probability of large additional gains tends to shrink relative to the risk of a sharp correction, which is why many longer term participants treat it as a caution area rather than a fresh entry zone.
How Traders Use The Bands
Traders can use the Mayer Multiple bands in different ways depending on their style:
Long term investors may look for accumulation when the multiple is below 1.0 and be more cautious when it moves into higher bands.
Swing traders may use the bands as context when combining this script with structure, volume, or other timing tools.
Cycle focused traders may use the multiple to help frame where Bitcoin could be within a broader four year cycle.
This script is not a timing system by itself. It is intended as a context layer that helps answer “where are we relative to long term trend?” in a visual way.
What Makes This Tool Different
Many resources plot the Mayer Multiple as a single ratio line. This script focuses on turning that ratio into a banded structure around price so traders can see cycle zones on the chart itself:
It computes the Mayer Multiple on each bar and maps the value into multiple color coded bands instead of a single line.
It highlights historically important regions such as deep discounts, mid range trend zones, and high risk extension zones including the 2.4 band.
It is designed specifically for Bitcoin’s long term behavior, but the visual framework can be useful for studying other assets that have strong trend cycles.
Important Note
This indicator is intended to provide additional context around where price sits relative to its long term trend. It is not a standalone signal generator and should always be used together with your own analysis, testing, and risk management. Historical Mayer Multiple behavior does not guarantee future results, and past cycle extremes may not repeat in the same way.
🐋 Tight lines and happy trading!
在腳本中搜尋"Cycle"
Elliptic bands
Why Elliptic?
Unlike traditional indicators (e.g., Bollinger Bands with constant standard deviation multiples), the elliptic model introduces a cyclical, non-linear variation in band width. This reflects the idea that price movements often follow rhythmic patterns, widening and narrowing in a predictable yet dynamic way, akin to natural market cycles.
Buy: When the price enters from below (green triangle).
Sell: When the price enters from above (red triangle).
Inputs
MA Length: 50 (This is the period for the central Simple Moving Average (SMA).)
Cycle Period: 50 (This is the elliptic cycle length.)
Volatility Multiplier: 2.0 (This value scales the band width.)
Mathematical Foundation
The indicator is based on the ellipse equation. The basic formula is:
Ellipse Equation:
(x^2) / (a^2) + (y^2) / (b^2) = 1
Solving for y:
y = b * sqrt(1 - (x^2) / (a^2))
Parameters Explained:
a: Set to 1 (normalized).
x: Varies from -1 to 1 over the period.
b: Calculated as:
ta.stdev(close, MA Length) * Volatility Multiplier
(This represents the standard deviation of the close prices over the MA period, scaled by the volatility multiplier.)
y (offset): Represents the band distance from the moving average, forming the elliptic cycle.
Behavior
Bands:
The bands are narrow at the cycle edges (when the offset is 0) and become widest at the midpoint (when the offset equals b).
Trend:
The central moving average (MA) shows the overall trend direction, while the bands adjust according to the volatility.
Signals:
Standard buy and sell signals are generated when the price interacts with the bands.
Practical Use
Trend Identification:
If the price is above the MA, it indicates an uptrend; if below, a downtrend.
Support and Resistance:
The elliptic bands act as dynamic support and resistance levels.
Narrowing bands may signal potential trend reversals.
Breakouts:
RS Cycles [QuantVue]The RS Cycles indicator is a technical analysis tool that expands upon traditional relative strength (RS) by incorporating Beta-based adjustments to provide deeper insights into a stock's performance relative to a benchmark index. It identifies and visualizes positive and negative performance cycles, helping traders analyze trends and make informed decisions.
Key Concepts:
Traditional Relative Strength (RS):
Definition: A popular method to compare the performance of a stock against a benchmark index (e.g., S&P 500).
Calculation: The traditional RS line is derived as the ratio of the stock's closing price to the benchmark's closing price.
RS=Stock Price/Benchmark Price
Usage: This straightforward comparison helps traders spot periods of outperformance or underperformance relative to the market or a specific sector.
Beta-Adjusted Relative Strength (Beta RS):
Concept: Traditional RS assumes equal volatility between the stock and benchmark, but Beta RS accounts for the stock's sensitivity to market movements.
Calculation:
Beta measures the stock's return relative to the benchmark's return, adjusted by their respective volatilities.
Alpha is then computed to reflect the stock's performance above or below what Beta predicts:
Alpha=Stock Return−(Benchmark Return×β)
Significance: Beta RS highlights whether a stock outperforms the benchmark beyond what its Beta would suggest, providing a more nuanced view of relative strength.
RS Cycles:
The indicator identifies positive cycles when conditions suggest sustained outperformance:
Short-term EMA (3) > Mid-term EMA (10) > Long-term EMA (50).
The EMAs are rising, indicating positive momentum.
RS line shows upward movement over a 3-period window.
EMA(21) > 0 confirms a broader uptrend.
Negative cycles are marked when the opposite conditions are met:
Short-term EMA (3) < Mid-term EMA (10) < Long-term EMA (50).
The EMAs are falling, indicating negative momentum.
RS line shows downward movement over a 3-period window.
EMA(21) < 0 confirms a broader downtrend.
This indicator combines the simplicity of traditional RS with the analytical depth of Beta RS, making highlighting true relative strength and weakness cycles.
Atlantean Bitcoin Weekly Market Condition - Top/Bottom BTC Overview:
The "Atlantean Bitcoin Weekly Market Condition Detector - Top/Bottom BTC" is a specialized TradingView indicator designed to identify significant turning points in the Bitcoin market on a weekly basis. By analyzing long-term and short-term moving averages across two distinct resolutions, this indicator provides traders with valuable insights into potential market bottoms and tops, as well as the initiation of bull markets.
Key Features:
Market Bottom Detection: The script uses a combination of a simple moving average (SMA) and an exponential moving average (EMA) calculated over long and short periods to identify potential market bottoms. When these conditions are met, the script signals a "Market Bottom" label on the chart, indicating a possible buying opportunity.
Bull Market Start Indicator: When the short-term EMA crosses above the long-term SMA, it signals the beginning of a bull market. This is marked by a "Bull Market Start" label on the chart, helping traders to prepare for potential market upswings.
Market Top Detection: The script identifies potential market tops by analyzing the crossunder of long and short-term moving averages. A "Market Top" label is plotted, suggesting a potential selling point.
Customizable Moving Averages Display: Users can choose to display the moving averages used for detecting market tops and bottoms, providing additional insights into market conditions.
How It Works: The indicator operates by monitoring the interactions between the specified moving averages:
Market Bottom: Detected when the long-term SMA (adjusted by a factor of 0.745) crosses over the short-term EMA.
Bull Market Start: Detected when the short-term EMA crosses above the long-term SMA.
Market Top: Detected when the long-term SMA (adjusted by a factor of 2) crosses under the short-term SMA.
These conditions are highlighted on the chart, allowing traders to visualize significant market events and make informed decisions.
Intended Use: This indicator is best used on weekly Bitcoin charts. It’s designed to provide long-term market insights rather than short-term trading signals. Traders can use this tool to identify strategic entry and exit points during major market cycles. The optional display of moving averages can further enhance understanding of market dynamics.
Originality and Utility: Unlike many other indicators, this script not only highlights traditional market tops and bottoms but also identifies the aggressive start of bull markets, offering a comprehensive view of market conditions. The unique combination of adjusted moving averages makes this script a valuable tool for long-term Bitcoin traders.
Disclaimer: The signals provided by this indicator are based on historical data and mathematical calculations. They do not guarantee future market performance. Traders should use this tool as part of a broader trading strategy and consider other factors before making trading decisions. Not financial advice.
Happy Trading!
By Atlantean
Physics CandlesPhysics Candles embed volume and motion physics directly onto price candles or market internals according to the cyclic pattern of financial securities. The indicator works on both real-time “ticks” and historical data using statistical modeling to highlight when these values, like volume or momentum, is unusual or relatively high for some periodic window in time. Each candle is made out of one or more sub-candles that each contain their own information of motion, which converts to the color and transparency, or brightness, of that particular candle segment. The segments extend throughout the entire candle, both body and wicks, and Thick Wicks can be implemented to see the color coding better. This candle segmentation allows you to see if all the volume or energy is evenly distributed throughout the candle or highly contained in one small portion of it, and how intense these values are compared to similar time periods without going to lower time frames. Candle segmentation can also change a trader’s perspective on how valuable the information is. A “low” volume candle, for instance, could signify high value short-term stopping volume if the volume is all concentrated in one segment.
The Candles are flexible. The physics information embedded on the candles need not be from the same price security or market internal as the chart when using the Physics Source option, and multiple Candles can be overlayed together. You could embed stock price Candles with market volume, market price Candles with stock momentum, market structure with internal acceleration, stock price with stock force, etc. My particular use case is scalping the SPX futures market (ES), whose price action is also dictated by the volume action in the associated cash market, or SPY, as well as a host of other securities. Physics allows you to embed the ES volume on the SPY price action, or the SPY volume on the ES price action, or you can combine them both by overlaying two Candle streams and increasing the Number of Overlays option to two. That option decreases the transparency levels of your coloring scheme so that overlaying multiple Candles converges toward the same visual color intensity as if you had one. The Candle and Physics Sources allows for both Symbols and Spreads to visualize Candle physics from a single ticker or some mathematical transformation of tickers.
Due to certain TradingView programming restrictions, each Candle can only be made out of a maximum of 8 candle segments, or an “8-bit” resolution. Since limits are just an opportunity to go beyond, the user has the option to stack multiple Candle indicators together to further increase the candle resolution. If you don’t want to see the Candles for some particular period of the day, you can hide them, or use the hiding feature to have multiple Candles calibrated to show multiple parts of the trading day. Securities tend to have low volume after hours with sharp spikes at the open or close. Multiple Candles can be used for multiple parts of the trading day to accommodate these different cycles in volume.
The Candles do not need be associated with the nominal security listed on the TV chart. The Candle Source allows the user to look at AAPL Candles, for instance, while on a TSLA or SPY chart, each with their respective volume actions integrated into the candles, for instance, to allow the user to see multiple security price and volume correlation on a single chart.
The physics information currently embeddable on Candles are volume or time, velocity, momentum, acceleration, force, and kinetic energy. In order to apply equations of motion containing a mass variable to financial securities, some analogous value for mass must be assumed. Traders often regard volume or time as inextricable variables to a securities price that can indicate the direction and strength of a move. Since mass is the inextricable variable to calculating the momentum, force, or kinetic energy of motion, the user has the option to assume either time or volume is analogous to mass. Volume may be a better option for mass as it is not strictly dependent on the speed of a security, whereas time is.
Data transformations and outlier statistics are used to color code the intensity of the physics for each candle segment relative to past periodic behavior. A million shares during pre-market or a million shares during noontime may be more intense signals than a typical million shares traded at the open, and should have more intense color signals. To account for a specific cyclic behavior in the market, the user can specify the Window and Cycle Time Frames. The Window Time Frame splits up a Cycle into windows, samples and aggregates the statistics for each window, then compares the current physics values against past values in the same window. Intraday traders may benefit from using a Daily Cycle with a 30-minute Window Time Frame and 1-minute Sample Time Frame. These settings sample and compare the physics of 1-minute candles within the current 30-minute window to the same 30-minute window statistics for all past trading days, up until the data limit imposed by TradingView, or until the Data Collection Start Date specified in the settings. Longer-term traders may benefit from using a Monthly Cycle with a Weekly Time Frame, or a Yearly Cycle with a Quarterly Time Frame.
Multiple statistics and data transformation methods are available to convey relative intensity in different ways for different trading signals. Physics Candles allows for both Normal and Log-Normal assumptions in the physics distribution. The data can then be transformed by Linear, Logarithmic, Z-Score, or Power-Law scoring, where scoring simply assigns an intensity to the relative physics value of each candle segment based on some mathematical transformation. Z-scoring often renders adequate detection by scoring the segment value, such as volume or momentum, according to the mean and standard deviation of the data set in each window of the cycle. Logarithmic or power-law transformation with a gamma below 1 decreases the disparity between intensities so more less-important signals will show up, whereas the power-law transformation with gamma values above 1 increases the disparity between intensities, so less more-important signals will show up. These scores are then converted to color and transparency between the Min Score and the Max Score Cutoffs. The Auto-Normalization feature can automatically pick these cutoffs specific to each window based on the mean and standard deviation of the data set, or the user can manually set them. Physics was developed with novices in mind so that most users could calibrate their own settings by plotting the candle segment distributions directly on the chart and fiddling with the settings to see how different cutoffs capture different portions of the distribution and affect the relative color intensities differently. Security distributions are often skewed with fat-tails, known as kurtosis, where high-volume segments for example, have a higher-probabilities than expected for a normal distribution. These distribution are really log-normal, so that taking the logarithm leads to a standard bell-shaped distribution. Taking the Z-score of the Log-Normal distribution could make the most statistical sense, but color sensitivity is a discretionary preference.
Background Philosophy
This indicator was developed to study and trade the physics of motion in financial securities from a visually intuitive perspective. Newton’s laws of motion are loosely applied to financial motion:
“A body remains at rest, or in motion at a constant speed in a straight line, unless acted upon by a force”.
Financial securities remain at rest, or in motion at constant speed up or down, unless acted upon by the force of traders exchanging securities.
“When a body is acted upon by a force, the time rate of change of its momentum equals the force”.
Momentum is the product of mass and velocity, and force is the product of mass and acceleration. Traders render force on the security through the mass of their trading activity and the acceleration of price movement.
“If two bodies exert forces on each other, these forces have the same magnitude but opposite directions.”
Force arises from the interaction of traders, buyers and sellers. One body of motion, traders’ capitalization, exerts an equal and opposite force on another body of motion, the financial security. A securities movement arises at the expense of a buyer or seller’s capitalization.
Volume
The premise of this indicator assumes that volume, v, is an analogous means of measuring physical mass, m. This premise allows the application of the equations of motion to the movement of financial securities. We know from E=mc^2 that mass has energy. Energy can be used to create motion as kinetic energy. Taking a simple hypothetical example, the interaction of one short seller looking to cover lower and one buyer looking to sell higher exchange shares in a security at an agreed upon price to create volume or mass, and therefore, potential energy. Eventually the short seller will actively cover and buy the security from the previous buyer, moving the security higher, or the buyer will actively sell to the short seller, moving the security lower. The potential energy inherent in the initial consolidation or trading activity between buy and seller is now converted to kinetic energy on the subsequent trading activity that moves the securities price. The more potential energy that is created in the consolidation, the more kinetic energy there is to move price. This is why point and figure traders are said to give price targets based on the level of volatility or size of a consolidation range, or why Gann traders square price and time, as time is roughly proportional to mass and trading activity. The build-up of potential energy between short sellers and buyers in GME or TSLA led to their explosive moves beyond their standard fundamental valuations.
Position
Position, p, is simply the price or value of a financial security or market internal.
Time
Time, t, is another means of measuring mass to discover price behavior beyond the time snapshots that simple candle charts provide. We know from E=mc^2 that time is related to rest mass and energy given the speed of light, c, where time ≈ distance * sqrt(mass/E). This relation can also be derived from F=ma. The more mass there is, the longer it takes to compute the physics of a system. The more energy there is, the shorter it takes to compute the physics of a system. Similarly, more time is required to build a “resting” low-volatility trading consolidation with more mass. More energy added to that trading consolidation by competing buyers and sellers decreases the time it takes to build that same mass. Time is also related to price through velocity.
Velocity = (p(t1) – p(t0)) / p(t0)
Velocity, v, is the relative percent change of a securities price, p, over a period of time, t0 to t1. The period of time is between subsequent candles, and since time is constant between candles within the same timeframe, it is not used to calculate velocity or acceleration. Price moves faster with higher velocity, and slower with slower velocity, over the same fixed period of time. The product of velocity and mass gives momentum.
Momentum = mv
This indicator uses physics definition of momentum, not finance’s. In finance, momentum is defined as the amount of change in a securities price, either relative or absolute. This is definition is unfortunate, pun intended, since a one dollar move in a security from a thousand shares traded between a few traders has the exact same “momentum” as a one dollar move from millions of shares traded between hundreds of traders with everything else equal. If momentum is related to the energy of the move, momentum should consider both the level of activity in a price move, and the amount of that price move. If we equate mass to volume to account for the level of trading activity and use physics definition of momentum as the product of mass and velocity, this revised definition now gives a thousand-times more momentum to a one-dollar price move that has a thousand-times more volume behind it. If you want to use finance’s volume-less definition of momentum, use velocity in this indicator.
Acceleration = v(t1) – v(t0)
Acceleration, a, is the difference between velocities over some period of time, t0 to t1. Positive acceleration is necessary to increase a securities speed in the positive direction, while negative acceleration is necessary to decrease it. Acceleration is related to force by mass.
Force = ma
Force is required to change the speed of a securities valuation. Price movements with considerable force have considerably more impact on future direction. A change in direction requires force.
Kinetic Energy = 0.5mv^2
Kinetic energy is the energy that a financial security gains from the change in its velocity by force. The built-up of potential energy in trading consolidations can be converted to kinetic energy on a breakout from the consolidation.
Cycle Theory and Relativity
Just as the physics of motion is relative to a point of reference, so too should the physics of financial securities be relative to a point of reference. An object moving at a 100 mph towards another object moving in the same direction at 100 mph will not appear to be moving relative to each other, nor will they collide, but from an outsider observer, the objects are going 100 mph and will collide with significant impact if they run into a stationary object relative to the observer. Similarly, trading with a hundred thousand shares at the open when the average volume is a couple million may have a much smaller impact on the price compared to trading a hundred thousand shares pre-market when the average volume is ten thousand shares. The point of reference used in this indicator is the average statistics collected for a given Window Time Frame for every Cycle Time Frame. The physics values are normalized relative to these statistics.
Examples
The main chart of this publication shows the Force Candles for the SPY. An intense force candle is observed pre-market that implicates the directional overtone of the day. The assumption that direction should follow force arises from physical observation. If a large object is accelerating intensely in a particular direction, it may be fair to assume that the object continues its direction for the time being unless acted upon by another force.
The second example shows a similar Force Candle for the SPY that counters the assumption made in the first example and emphasizes the importance of both motion and context. While it’s fair to assume that a heavy highly accelerating object should continue its course, if that object runs into an obstacle, say a brick wall, it’s course may deviate. This example shows SPY running into the 50% retracement wall from the low of Mar 2020, a significant support level noted in literature. The example also conveys Gann’s idea of “lost motion”, where the SPY penetrated the 50% price but did not break through it. A brick wall is not one atom thick and price support is not one tick thick. An object can penetrate only one layer of a wall and not go through it.
The third example shows how Volume Candles can be used to identify scalping opportunities on the SPY and conveys why price behavior is as important as motion and context. It doesn’t take a brick wall to impede direction if you know that the person driving the car tends to forget to feed the cats before they leave. In the chart below, the SPY breaks down to a confluence of the 5-day SMA, 20-day SMA, and an important daily trendline (not shown) after the bullish bounce from the 50% retracement days earlier. High volume candles on the SMA signify stopping volume that reverse price direction. The character of the day changes. Bulls become more aggressive than bears with higher volume on upswings and resistance, whiles bears take on a defensive position with lower volume on downswings and support. High volume stopping candles are seen after rallies, and can tell you when to take profit, get out of a position, or go short. The character change can indicate that its relatively safe to re-enter bullish positions on many major supports, especially given the overarching bullish theme from the large reaction off the 50% retracement level.
The last example emphasizes the importance of relativity. The Volume Candles in the chart below are brightest pre-market even though the open has much higher volume since the pre-market activity is much higher compared to past pre-markets than the open is compared to past opens. Pre-market behavior is a good indicator for the character of the day. These bullish Volume Candles are some of the brightest seen since the bounce off the 50% retracement and indicates that bulls are making a relatively greater attempt to bring the SPY higher at the start of the day.
Infrequently Asked Questions
Where do I start?
The default settings are what I use to scalp the SPY throughout most of the extended trading day, on a one-minute chart using SPY volume. I also overlay another Candle set containing ES future volume on the SPY price structure by setting the Physics Source to ES1! and the Number of Overlays setting to 2 for each Candle stream in order to account for pre- and post-market trading activity better. Since the closing volume is exponential-like up until the end of the regular trading day, adding additional Candle streams with a tighter Window Time Frame (e.g., 2-5 minute) in the last 15 minutes of trading can be beneficial. The Hide feature can allow you to set certain intraday timeframes to hide one Candle set in order to show another Candle set during that time.
How crazy can you get with this indicator?
I hope you can answer this question better. One interesting use case is embedding the velocity of market volume onto an internal market structure. The PCTABOVEVWAP.US is a market statistic that indicates the percent of securities above their VWAP among US stocks and is helpful for determining short term trends in the US market. When securities are rising above their VWAP, the average long is up on the day and a rising PCTABOVEVWAP.US can be viewed as more bullish. When securities are falling below their VWAP, the average short is up on the day and a falling PCTABOVEVWAP.US can be viewed as more bearish. (UPVOL.US - DNVOL.US) / TVOL.US is a “spread” symbol, in TV parlance, that indicates the decimal percent difference between advancing volume and declining volume in the US market, showing the relative flow of volume between stocks that are up on the day, and stocks that are down on the day. Setting PCTABOVEVWAP.US in the Candle Source, (UPVOL.US - DNVOL.US) / TVOL.US in the Physics Source, and selecting the Physics to Velocity will embed the relative velocity of the spread symbol onto the PCTABOVEVWAP.US candles. This can be helpful in seeing short term trends in the US market that have an increasing amount of volume behind them compared to other trends. The chart below shows Volume Candles (top) and these Spread Candles (bottom). The first top at 9:30 and second top at 10:30, the high of the day, break down when the spread candles light up, showing a high velocity volume transfer from up stocks to down stocks.
How do I plot the indicator distribution and why should I even care?
The distribution is visually helpful in seeing how different normalization settings effect the distribution of candle segments. It is also helpful in seeing what physics intensities you want to ignore or show by segmenting part of the distribution within the Min and Max Cutoff values. The intensity of color is proportional to the physics value between the Min and Max Cutoff values, which correspond to the Min and Max Colors in your color scheme. Any physics value outside these Min and Max Cutoffs will be the same as the Min and Max Colors.
Select the Print Windows feature to show the window numbers according to the Cycle Time Frame and Window Time Frame settings. The window numbers are labeled at the start of each window and are candle width in size, so you may need to zoom into to see them. Selecting the Plot Window feature and input the window number of interest to shows the distribution of physics values for that particular window along with some statistics.
A log-normal volume distribution of segmented z-scores is shown below for 30-minute opening of the SPY. The Min and Max Cutoff at the top of the graph contain the part of the distribution whose intensities will be linearly color-coded between the Min and Max Colors of the color scheme. The part of the distribution below the Min Cutoff will be treated as lowest quality signals and set to the Min Color, while the few segments above the Max Cutoff will be treated as the highest quality signals and set to the Max Color.
What do I do if I don’t see anything?
Troubleshooting issues with this indicator can involve checking for error messages shown near the indicator name on the chart or using the Data Validation section to evaluate the statistics and normalization cutoffs. For example, if the Plot Window number is set to a window number that doesn’t exist, an error message will tell you and you won’t see any candles. You can use the Print Windows option to show windows that do exist for you current settings. The auto-normalization cutoff values may be inappropriate for your particular use case and literally cut the candles out of the chart. Try changing the chart time frame to see if they are appropriate for your cycle, sample and window time frames. If you get a “Timeframe passed to the request.security_lower_tf() function must be lower than the timeframe of the main chart” error, this means that the chart timeframe should be increased above the sample time frame. If you get a “Symbol resolve error”, ensure that you have correct symbol or spread in the Candle or Physics Source.
How do I see a relative physics values without cycles?
Set the Window Time Frame to be equal to the Cycle Time Frame. This will aggregate all the statistics into one bucket and show the physics values, such as volume, relative to all the past volumes that TV will allow.
How do I see candles without segmentation?
Segmentation can be very helpful in one context or annoying in another. Segmentation can be removed by setting the candle resolution value to 1.
Notes
I have yet to find a trading platform that consistently provides accurate real-time volume and pricing information, lacking adequate end-user data validation or quality control. I can provide plenty of examples of real-time volume counts or prices provided by TradingView and other platforms that were significantly off from what they should have been when comparing against the exchanges own data, and later retroactively corrected or not corrected at all. Since no indicator can work accurately with inaccurate data, please use at your own discretion.
The first version is a beta version. Debugging and validating code in Pine script is difficult without proper unit testing. Please report any bugs with enough information to reproduce them and indicate why they are important. I also encourage you to export the data from TradingView and verify the calculations for your particular use case.
The indicator works on real-time updates that occur at a higher frequency than the candle time frame, which TV incorrectly refers to as ticks. They use this terminology inaccurately as updates are really aggregated tick data that can take place at different prices and may not accurately reflect the real tick price action. Consequently, this inaccuracy also impacts the real-time segmentation accuracy to some degree. TV does not provide a means of retaining “tick” information, so the higher granularity of information seen real-time will be lost on a disconnect.
TV does not provide time and sales information. The volume and price information collected using the Sample Time Frame is intraday, which provides only part of the picture. Intraday volume is generally 50 to 80% of the end of day volume. Consequently, the daily+ OHLC prices are intraday, and may differ significantly from exchanged settled OHLC prices.
The Cycle and Window Time Frames refer to calendar days and time, not trading days or time. For example, the first window week of a monthly cycle is the first seven days of the month, not the first Monday through Friday of trading for the month.
Chart Time Frames that are higher than the Window Time Frames average the normalized physics for price action that occurred within a given Candle segment. It does not average price action that did not occur.
One of the main performance bottleneck in TradingView’s Pine Script is client-side drawing and plotting. The performance of this indicator can be increased by lowering the resolution (the number of sub-candles this indicator plots), getting a faster computer, or increasing the performance of your computer like plugging your laptop in and eliminating unnecessary processes.
The statistical integrity of this indicator relies on the number of samples collected per sample window in a given cycle. Higher sample counts can be obtained by increasing the chart time frame or upgrading the TradingView plan for a higher bar count. While increasing the chart time frame doesn’t increase the visual number of bars plotted on the chart, it does increase the number of bars that can be pulled at a lower time frame, up to 100,000.
Due to a limitation in Pine Scripts request_lower_tf() function, using a spread symbol will only work for regular trading hours, not extended trading hours.
Ideally, velocity or momentum should be calculated between candle closes. To eliminate the need to deal with price gaps that would lead to an incorrect statistical distributions, momentum is calculated between candle open and closes as a percent change of the price or value, which should not be an issue for most liquid securities.
Bitcoin Price Bottom IndicatorThis Indicator flashes up on bottoms of each Bitcoin market cycle. It’s suggesting, that the price of BTC finds strong support at the 200W SMA . Thats why it’s not flashing up in the first cycle, because there was not enough price data at that moment.
This Indicator uses price data from the weekly timeframe so for the best experience USE WEEKLY TIMEFRAME .
[iQ]PRO Market Sessions+🌐 PRO Market Sessions+: The Architecture of Market Time
Elevate your market analysis with the PRO v1 Time Cycles indicator—a sophisticated, proprietary framework engineered to meticulously map and visualize critical, high-probability time segments across global trading sessions. This tool transcends conventional session highlighting by providing a multi-layered, time-boxed view of market behavior, offering unparalleled clarity on structural shifts and key price levels.
This tool is optimized for professional traders, providing an edge by focusing on the fractal nature of market timing.
⏳ Precision Time Segmentation
The core functionality revolves around the hyper-precise segmentation of the trading day, anchored to the New York (EST) timezone to capture institutional flow.
Global Overlap Coverage: Integrates key Asia and London sessions with the comprehensive New York trading day, allowing for the analysis of transitional volatility and overlap strategies.
Structured Cycles: Deploys a unique system of 270-minute cycles, nested with 90-minute and 30-minute subdivisions. This hierarchical structure reveals how market structure evolves from macro-sessions down to critical, granular pivots.
New York Focus: Features distinct AM and PM 270-minute cycles, further broken down into 90-minute tranches (AM1, AM2, AM3 / PM1, PM2, PM3) and fine-tuned with 30-minute and even 10-minute boxes for exceptional high-resolution analysis.
London Depth: The London session is captured as a 270-minute block, with its own nested 90/30-minute structures, providing a complete view of the European market's structural integrity before the US open.
✨ Dynamic Structural Analysis
Beyond mere visualization, the indicator computes and projects critical structural levels within each time box, acting as dynamic reference points for price action.
Dynamic Price Anchors: Each time-cycle box is calculated to reveal key price metrics, including the Open Price and the Equilibrium (EQ) Level (Mid-Range). These lines serve as potent technical levels, often representing institutional reference points for deviation and reversion.
High/Low Capture: The extreme High and Low of each significant time segment are captured and marked, forming the boundaries of the structural range and identifying potential areas of liquidity draw.
Persistent Levels: Projects Previous Day, Week, and Month High/Low levels. These crucial historical benchmarks act as magnets or barriers to current price movement, providing essential macro-context to intra-day analysis.
🎨 Customizable & Non-Intrusive
The PRO v1 Time Cycles is designed for seamless integration into any chart setup, offering extensive customization without cluttering the price action.
Control over Granularity: Users maintain complete control over which time cycles (270, 90, 30, 10-minute) are displayed, ensuring the chart reflects the specific trading strategy and timeframe required.
Aesthetic Flexibility: Features highly detailed options for color, border styles, text alignment, and line thickness for every major session and nested cycle, allowing for a fully personalized and professional workspace.
This tool is a fundamental component of the iQ PRO suite, providing the essential temporal context required to execute sophisticated, time-based trading strategies. Its robust architecture is built to empower the discerning trader with a clearer, more structured view of the market's inner workings.
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.
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.
