Cyclical IndicatorThis tool is an oscillator that detects cycles.
It is built on the basis of our centered moving averages.
It is fully configurable in design moreover it is possible to set the centering through the offset !
Offset 2, half cycle centering.
Offset 4, 1/4 cycle centering.
Recommended setting :
Offset 4
Cyclical ratio 2
Cari dalam skrip untuk "Cycle"
WD Gann: Vertical Lines for Predefined Days/Bars AgoThis Pine Script draws vertical lines on the chart at specific time intervals, inspired by WD Gann’s theories of time cycles . WD Gann, a famous trader, believed that market movements were influenced by predictable time cycles. This script enables traders to visualize these key time cycles on the chart by placing vertical lines at predefined intervals (in bars ago), helping to identify potential turning points in the market.
The time intervals used in this script are inspired by Gann’s work, as well as astrological and numerological principles , which many traders believe influence market behavior . You can customize which time intervals (such as 3, 7, 9, 21, etc.) you want to track by enabling or disabling specific vertical lines on the chart.
Key Features:
Time Cycles Based on Gann’s Theory: Draws vertical lines at significant time intervals such as 3, 7, 9, 21, 27 bars ago, which are commonly used by Gann traders.
Astrological & Numerological Significance: The predefined intervals also align with key numerological and astrological values, allowing for a broader perspective on market cycles.
Customizable Intervals: You can choose which time intervals to display by enabling or disabling checkboxes for each cycle, allowing flexibility in chart analysis.
Visual Labels: Each vertical line is labeled with its corresponding "bars ago" value, providing clear reference points for the selected time cycles.
What Users Can Do:
Track and analyze market movements based on time cycles that are significant to Gann’s theory, as well as numerological and astrological influences.
Enable or disable vertical lines for specific cycles, like the 3-bar cycle, 9-bar cycle, or 365-bar cycle, depending on the intervals that align with your trading strategy.
Combine with other technical analysis tools and Gann techniques (e.g., Gann Angles, Gann Fans, or Square of Nine) for a more comprehensive trading approach.
This tool is designed for traders who believe in the power of time cycles to influence market behavior, and is especially useful for predicting turning points or key price movements based on these cycles.
Financial Astrology Jupiter LongitudeJupiter energy influence the expansion, enthusiasm, joviality, optimism, devotion, administration and judgement. Is associated with people of nobility and good social position: ministers, bishops, religious leaders, judges, bankers, lawyers, merchants, influencers and so forth. This cycle is relevant for the industries of consumer goods, travel, publishing, higher education, banking, gambling and legal.
For most of the crypto-currencies is hard to analyse the impact of the Jupiter transit across different zodiac signs due to the emergent nature of this disrupting financial industry, many coins was launched in 2017 and have not experienced the complete Jupiter cycle. However, in BTCUSD we almost have a complete orbit and through the buy/sell frequency analysis we have observed the following patters: the bullish zodiac signs was Virgo, Libra, Capricorn and Aquarius, the bearish was Leo, and Scorpio. We was not able to obtain price data for the period when Jupiter transited Aries to Cancer so we are pending to analyze the trend direction during those zodiac positions.
This indicator provides Jupiter longitude since 2010 so will be limited to the analysis of 1 cycle, however we noted that the periods of retrogradation and stationary could give interesting trading signals. We encourage you to analyse this zodiac sign / speed phases cycles in different markets and share with us your observations, leave us a comment with your research outcomes. Happy research!
Note: The Jupiter 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.
RSI cyclic smoothed v2Cyclic Smoothed Relative Strength Indicator
The cyclic smoothed RSI indicator is an enhancement of the classic RSI , adding
additional smoothing according to the market vibration,
adaptive upper and lower bands according to the cyclic memory and
using the current dominant cycle length as input for the indicator.
The cRSI is used like a standard indicator. The chart highlights trading signals where the signal line crosses above or below the adaptive lower/upper bands. It is much more responsive to market moves than the basic RSI.
You can also review this short idea where BTC went down from 4300 USD (3 Sept 17) to 3700 USD (15 Sept 17) after the idea was posted and showed the clear short exit with the next low:
The indicator uses the dominant cycle as input to optimize signal, smoothing and cyclic memory. To get more in-depth information on the cyclic-smoothed RSI indicator, please read Chapter 4 "Fine tuning technical indicators" of the book "Decoding the Hidden Market Rhythm, Part 1" available at your favorite book store.
This is the open-source code version of the requested script already published as protected indicator back in 2017 "RSI cyclic smoothed". Now made public as v2. Would love to receive feedback and see your ideas.
Financial Astrology Sun LongitudeFinancial astrology is a branch of mundane astrology that research the correlations of planet cycles with market prices, this indicator developed by the Financial Astrology Research Group provides the visualization of the Sun Tropical Zodiac Longitude to support that astrology traders can study multiple markets within the powerful Trading View UI to detect potential cyclical patterns in price action that are connected with the cosmic rhythm of the Sun.
The Sun have been very relevant cycle among all ancient civilizations such as Maya, Aztec, Inca, this cyclical move is the fundamental frequency of our life's due to the fact that our calendar year is a model from this cycle. Chinese astrologers and W.D. Gann was aware of the powerful predictive power of the solar terms which is a representation of the most relevant weather transitions within the Sun longitude path.
With this indicator we try to ease the research work of the amazing community of astro-traders that prior to this indicators needed to create hundreds of manual annotations on the markets price charts to visualize the Sun zodiac position within a long period of time in order to research potential cycles. That manual work is over. Let's move faster in our cycles research!
We encourage all traders using astrology to continue their research, please share your ideas of astro cycles trading strategies and contribute your experiments at our Github exploration projects: github.com
Note: The Sun longitude 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.
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.
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:
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 .
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!
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
(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.
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.
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.
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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.
