wbburgin_utilsLibrary "wbburgin_utils"
trendUp(source)
Parameters:
source
smoothrng(source, sampling_period, range_mult)
Parameters:
source
sampling_period
range_mult
rngfilt(source, smoothrng)
Parameters:
source
smoothrng
fusion(overallLength, rsiLength, mfiLength, macdLength, cciLength, tsiLength, rviLength, atrLength, adxLength)
Parameters:
overallLength
rsiLength
mfiLength
macdLength
cciLength
tsiLength
rviLength
atrLength
adxLength
zonestrength(amplitude, wavelength)
Parameters:
amplitude
wavelength
atr_anysource(source, atr_length)
Parameters:
source
atr_length
supertrend_anysource(source, factor, atr_length)
Parameters:
source
factor
atr_length
Cari dalam skrip untuk "wave"
Hurst Spectral Analysis Oscillator"It is a true fact that any given time history of any event (including the price history of a stock) can always be considered as reproducible to any desired degree of accuracy by the process of algebraically summing a particular series of sine waves. This is intuitively evident if you start with a number of sine waves of differing frequencies, amplitudes, and phases, and then sum them up to get a new and more complex waveform." (Spectral Analysis chapter of J M Hurst's book, Profit Magic )
Background: A band-pass filter or bandpass filter is a device that passes frequencies within a certain range and rejects (attenuates) frequencies outside that range. Bandpass filters are widely used in wireless transmitters and receivers. Well-designed bandpass filters (having the optimum bandwidth) maximize the number of signal transmitters that can exist in a system while minimizing the interference or competition among signals. Outside of electronics and signal processing, other examples of the use of bandpass filters include atmospheric sciences, neuroscience, astronomy, economics, and finance.
About the indicator: This indicator will accept float/decimal length inputs to display a spectrum of 11 bandpass filters. The trader can select a single bandpass for analysis that includes future high/low predictions. The trader can also select which bandpasses contribute to a composite model of expected price action.
10 Statements to describe the 5 elements of Hurst's price-motion model:
Random events account for only 2% of the price change of the overall market and of individual issues.
National and world historical events influence the market to a negligible degree.
Foreseeable fundamental events account for about 75% of all price motion. The effect is smooth and slow changing.
Unforeseeable fundamental events influence price motion. They occur relatively seldom, but the effect can be large and must be guarded against.
Approximately 23% of all price motion is cyclic in nature and semi-predictable (basis of the "cyclic model").
Cyclicality in price motion consists of the sum of a number of (non-ideal) periodic cyclic "waves" or "fluctuations" (summation principle).
Summed cyclicality is a common factor among all stocks (commonality principle).
Cyclic component magnitude and duration fluctuate slowly with the passage of time. In the course of such fluctuations, the greater the magnitude, the longer the duration and vice-versa (variation principle).
Principle of nominality: an element of commonality from which variation is expected.
The greater the nominal duration of a cyclic component, the larger the nominal magnitude (principle of proportionality).
Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help:
🏆 @TerryPascoe
🏅 DavidF at Sigma-L, and @HPotter
👏 @Saviolis, parisboy, and @upslidedown
MLExtensionsLibrary "MLExtensions"
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src : The input series (i.e., the first-order derivative for price).
quadraticMeanLength : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src : The input series
min : The minimum value of the unbounded range
max : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src : The input series
oldMin : The minimum value of the range to rescale from
oldMax : The maximum value of the range to rescale from
newMin : The minimum value of the range to rescale to
newMax : The maximum value of the range to rescale to
Returns: The rescaled series
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src : The input series (i.e., the hyperbolic tangent).
lookback : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src : The input series (i.e., the result of the tanh calculation).
smoothingFrequency
quadraticMeanLength
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src : The input series (i.e., the result of the RSI calculation).
n1 : The length of the RSI.
n2 : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src : The input series (i.e., the result of the CCI calculation).
n1 : The length of the CCI.
n2 : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src : The input series (i.e., the result of the WaveTrend Classic calculation).
n1
n2
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc : The input series for the high price.
lowSrc : The input series for the low price.
closeSrc : The input series for the close price.
n1 : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src
threshold
useRegimeFilter
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src : The source series.
length : The length of the ADX.
adxThreshold : The ADX threshold.
useAdxFilter : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, useVolatilityFilter)
filter_volatility
Parameters:
minLength : The minimum length of the ATR.
maxLength : The maximum length of the ATR.
useVolatilityFilter : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isStopLossHit, maxBarsBackIndex, thisBarIndex)
Performs a basic backtest using the specified parameters and conditions.
Parameters:
high : The input series for the high price.
low : The input series for the low price.
open : The input series for the open price.
startLongTrade : The series of conditions that indicate the start of a long trade.`
endLongTrade : The series of conditions that indicate the end of a long trade.
startShortTrade : The series of conditions that indicate the start of a short trade.
endShortTrade : The series of conditions that indicate the end of a short trade.
isStopLossHit : The stop loss hit indicator.
maxBarsBackIndex : The maximum number of bars to go back in the backtest.
thisBarIndex : The current bar index.
Returns: A tuple containing backtest values
init_table()
init_table()
Returns: tbl The backtest results.
update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, stopLosses)
update_table(tbl, tradeStats)
Parameters:
tbl : The backtest results table.
tradeStatsHeader : The trade stats header.
totalTrades : The total number of trades.
totalWins : The total number of wins.
totalLosses : The total number of losses.
winLossRatio : The win loss ratio.
winrate : The winrate.
stopLosses : The total number of stop losses.
Returns: Updated backtest results table.
TrendCalculusThis indicator makes visualising some of the core TrendCalculus algorithm's key information and features both fast and easy for casual analysis.
Interpretation:
a) The light blue channel is the lagged price channel calculated over the timeframe of your choosing for a period of N values. When the current price breaks out of this channel the previous price major high/low can be identified as a trend reversal. This helps in counting trend "waves" and is a rolling visual version of ideas I developed for counting Elliot Waves. For EW analysis, your mileage may vary depending on the asset inspected, but the chart allows you to clearly count waves on a particular scale of time (period) ignoring noise on other time scales.
b) The green/red channel is a support/resistance indicator region that shows the relationship of the current price to the key pivot points on this time scale (period) and these make for good visual indication that the current trend is up (green), or down (red). You may find them helpful for identifying breakouts and placing stops - but this was not their original intention. The pink line is the mid point of closing values in the lagged price channel, and the orange line the mid point of closing values in the current price channel.
About TrendCalculus (TC):
TC is implemented in several languages including Lua, Scala and Python. The Lua implementation is the reference and has the most advanced functionality and delivers a powerful data processing tool for both multi-scale trend reversal detection, reversal labelling, as well as trend feature production - all useful things helping it to produce training data for machine learning models that detect trend changes in real time.
This charting tool includes: (1) two consecutive lagged Donchian channels configured to a common period N, (2) the current price, and (3) the mid price of both Donchian channels. These calculations are all part of the TC codebase, and are brought to life in this charting tool.
Motivation:
By creating a TC charting tool - the machine learning model is swapped for *your eyes* and *your brain*. Using the same inputs as the machine, you can use this chart to learn to detect trend changes, and understand how time frame (long periods, short periods) affect your view of trend change. If you choose to use it to trade, or make investment decisions, do so at your own risk. This indicator does not deliver financial advice.
TrendCalculus is the invention of Andrew Morgan, author of Mastering Spark for Data Science (2017).
The original core TrendCalculus (TC) algorithm itself is published as open-source code on github under a GPL licence, and free to use and develop.
CoRA Ribbon - Multiple Compound Ratio Weighted Moving AveragesWhat distinguishes this indicator?
A Compound Ratio Weighted Moving Average ("CoRA") is a Moving Average that, regardless of its length, has very little lag and that can be relied on to accurately track price movements and fluctuations - compared to other types of Moving Averages.
By combining multiple Compound Ratio Weighted Moving Averages you can identify the trend better and more reliably . This is where "CoRA Ribbon" comes in.
The original study, which supported one CoRA Wave, comes from RedKTrader and was introduced as "RedK Compound Ratio Moving Average (CoRa_Wave)” . Thanks to him for the great work!
What was improved or added to this version of the indicator?
With this version of the indicator, up to 5 waves of Compound Ratio Moving Averages with different lengths can be combined and output to one "CoRA Ribbon".
Alerts were implemented. You can be notified e.g. in the event of
changes in direction of each single CoRA Wave
a trend change, which is determined on the basis of all 5 CoRA Waves
A CoRA Wave compared to other Moving Averages - CoRa Waves are less lagging behind
A suggestion for interpretation of “CoRA Ribbon”:
Since CoRA Ribbon can help you to identify the trend better and more reliably, this indicator provides a good baseline for your strategy, but should always be used in conjunction with other indicators or market analysis.
By adjusting the length of each individual wave, you can adapt "CoRA Ribbon" to your trading style - whether it is more aggressive or more cautious.
The following general rules can be formulated:
If the Ribbon changes its color to green, this can be interpreted as a buy signal.
If the Ribbon changes its color to red, this can be interpreted as a sell signal.
Good to know: The default settings have been selected for timeframe lower than 15 minutes. Adjust them and the indicator will do a great job on higher timeframes too. Please remember to test carefully after every change before the changes are applied to your live trading.
Background “Compound Ratio Weighted Average” - provided by "RedKTrader"
A Compound Ratio Weighted Average is a moving average where the weights increase in a "logarithmically linear" way - from the furthest point in the data to the current point.
The formula to calculate these weights work in a similar way to how "compound ratio" works: you start with an initial amount, then add a consistent "ratio of the cumulative prior sum" each period until you reach the end amount. The result is the "step ratio" between the weights is consistent - This is not the case with linear-weighted “Moving Average Weighted” (WMA) or “Exponential Moving Average” (EMA)
For example, if you consider a Weighted Moving Average ( WMA ) of length 5, the weights will be (from the furthest point towards the most current) 1, 2, 3, 4, 5 -- we can see that the ratio between these weights are inconsistent. in fact, the ratio between the 2 furthest points is 2:1, but the ratio between the most recent points is 5:4. the ratio is inconsistent, and in fact, more recent points are not getting the best weights they should get to counter-act the lag effect. Using the Compound Ratio approach addresses that point.
A key advantage here is that we can significantly reduce the "tail weight" - which is "relatively" large in other Moving Averages.
A Compound Ratio Weighted Moving Average is a moving average that has very little lag and that can be relied on to accurately track price movements and fluctuations.
Use or modify the code, invite us for a coffee, ... most importantly: have a lot of fun and success with this indicator
The code is commented - please don't hesitate to use it as needed or customize it further ... and if you are satisfied and even successful with this indicator, maybe buy us a coffee ;-)
The original developer ( RedKTrader ) and I ( consilus ) are curious to see how our indicators will develop through further ideas - so please keep us updated.
Time Wolna_2021_iun3[wozdux] Description of the Time_Wolna indicator
The indicator is designed to study the behavior of time. There are many indicators that study just the price, a little less indicators that study the volume of trading and vanishingly few indicators that study time.
This is not an oscillator, it does not have oversold or overbought levels. This indicator has an indefinite beginning and an indefinite end. Its value is not in the absolute values of the indicator, but in relative ones. This indicator calculates the time of price rise and the time of price decline. It clearly shows how long the price rises and how long the price falls.
The initial idea was to use my RSIVol indicator to study the time. Each bar is counted as a unit of time. If the price rises during the period of one bar, then one is added, if the price falls, then one is subtracted. By default, the blue line shows this time movement according to the RsiVol indicator.
The basic RsiVol indicator is shown at the bottom of the diagram. The bill goes along the blue line, which calculates the movement of the volume price. If the blue RSIVol line is above the yellow level, then the blue Time_Wolna time line is colored green. If the blue line in the base RsiVol indicator falls below the lower yellow level, then the blue time line of the Time_Wolna indicator turns red.
The result is a broken line that clearly shows the waves of rising and falling prices. In principle, the time indicator makes it easier to recognize waves.
It is known that time plays an important role in Elliott wave analysis, although in practice this is almost never done. The mention of Elliott is just a lyrical digression.
Time is very difficult to study. This indicator does not give clear buy or sell signals. This is just an analysis tool to help analysts.
In addition to the RsiVol indicator, simply the Rsi from the price and a simple moving average from the price are also used.
So, the settings of this indicator.
"switch Price == close <==> ( High+Low)/2" -- select the base price in all subsequent calculations
"Key EMA=> True=ema(Price); False=ema(Price*Volume)" --The key for switching the moving average from the price or from the volume price.
"T==> EMA(price, T)" --The period for calculating the moving average
" key red==> Yes/No Rsi")--the key turns on or off the RSI line red line
"key green==> Yes/No Orsi") --the key turns on or off the Volume RSI line green line
" key olive==> Yes/No RsiVol200 " -- the key enables or disables the Volumetric RSIVol200 olive line. This is RsiVol minus the 200-period moving average.
"keyVol blue==> Yes/No " - the key enables or disables the base blue line RSIVol
"keyVol blue==> V->tt(RsiVol) ->tt(ema(Price))"—The blue line selection will be calculated as the time from RSIVol or as the time from the moving average EMA.
"keyVol blue==> : 1=Time, 2=Time* price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*price*Volume")- selection for the blue baseline. By default, the time of the price rise or fall is calculated simply. Key=1. But you can investigate the joint influence of time and price and then the key is=2. If we study the combined effect of time and price changes per bar, then the key=3. If we study the joint influence of time and volume, then the key=4. If we study the joint influence of time, price and volume, then the key=5.
"key RsiO red + green==> : 1=Time, 2=Time*Price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*Price*Volume") - - - similar settings for the red green line. By default, the time of the price rise or fall is calculated simply. Key=1. But you can investigate the joint influence of time and price and then the key is=2. If we study the combined effect of time and price changes per bar, then the key=3. If we study the joint influence of time and volume, then the key=4. If we study the joint influence of time, price and volume, then the key=5.
"Key Color – - here you can disable changing the color of the blue line to green or red when the base indicator RsiVol exits above the upper and below the lower levels.
"Level nul ==> * Down Level Rsi - screen configuration in order to raise or lower chart
"Level nul ==> * Down Level ORsi -- beauty setup in order to raise or lower chart
"Level nul ==> * DownLevel RsiVol200 -- beauty setup in order to raise or lower chart
"blue =volume * price" – period for calculation of volumetric rates
"blue => RSIVOL(Volume*price,len) and EMA" – the period for calculating RsiVol
"blue__o1=> ema ( RSIVOL, o1)" – additional smoothing RsiVol
"red=rsi (Price,14)" – the period for calculating Rsi
"red= ema ( RSI ,3)" -- additional smoothing Rsi
"fuchsia__ => RsiVol200 (vp,200)" - the period for calculating RsiVol200
"fuchsia__o2=> ema ( RSIVOL200 , o2)" -- additional smoothing RsiVol200
To study the time between two fixed dates. Setting the start point of the calculation and the end point of the calculation
"Data(0)=Year" – the year of the start date
"Data(0)= Month" – the month of the start date
"Data (0)=Day" the day of the start date
"Data(1)=Year" – the year of the end date.
"Data(1)=Year" – month of the end date.
"Data(1)=Day" -- the day of the end date.
--------русский вариант описания ------
Описание индикатора Time_Wolna
Индикатор призван изучать поведение времени. Есть много индикаторов изучающих просто цену, немного меньше индикаторов изучающих объем торгов и исчезающе мало индикаторов, изучающих время.
Это не осциллятор у него нет уровней перепроданности или перекупленности. Данный индикатор имеет неопределенное начало и неопределенный конец. Ценность его не в абсолютных значениях индикатора, а в относительных. Этот индикатор высчитывает время подъема цены и время снижения цены. Он наглядно показывает сколько времени цена поднимается и сколько времени цена опускается.
Первоначальная идея была использовать мой индикатор RSIVol для изучения времени. Каждый бар считается за единицу времени. Если цена поднимается за период одного бара, то прибавляется единица, если цена опускается, то вычитается единица. По умолчанию голубая линия показывает такое движения времени по индикатору RsiVol.
Внизу на диаграмме показан базовый индикатор RsiVol. Счёт идет по синей линии, которая вычисляет движение объемной цены. Если синяя линия RSIVol находится выше желтого уровня, то голубая линия времени Time_Wolna окрашивается в зеленый цвет. Если синяя линия в базовом индикаторе RsiVol опускается ниже нижнего желтого уровня, то голубая линия времени индикатора Time_Wolna окрашивается в красный цвет.
В результате получается ломанная линия, четко показывающая волны восхождения и снижения цены. В принципе индикатор времени позволяет легче распознавать волны.
Известно, что время играет важную роль в волновом анализе Эллиотта, хотя на практике это почти никогда не делается. Упоминание Эллиотта это просто лирическое отступление.
Время очень трудно изучать. Этот индикатор не дает четких сигналов на покупку или продажу. Это всего лишь инструмент анализа в помощь аналитикам.
Кроме индикатора RsiVol, используются и просто Rsi от цены и простая скользящая средняя от цены.
Итак, настройки данного индикатора.
"switch Price == close <==> ( High+Low)/2" -- выбираем базовую цену во всех последующих вычислениях
"Key EMA=> True=ema(Price); False=ema(Price*Volume)" --Ключ переключения скользящей средней от цены или от объемной цены.
" T==> EMA(price,T)"--Период вычисления скользящей средней
"key red==> Yes/No Rsi")--ключ включает или выключает линию RSI красная линия
"key green==> Yes/No Orsi") --ключ включает или выключает линию Объемной RSI зеленая линия
"key olive==> Yes/No RsiVol200" -- ключ включает или выключает линию Объемной RSIVol200 оливковая линия. Это RsiVol минус 200-периодная скользящая средняя.
"keyVol blue==> Yes/No " – ключ включает или выключает базовую голубую линию RSIVol
"keyVol blue==> V->tt(RsiVol) ->tt(ema(Price))"—выбор голубая линия будет вычисляться как время от RSIVol или как время от скользящей средней EMA.
"keyVol blue==> : 1=Time, 2=Time* price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*price*Volume")—выбор для голубой базовой линии. По умолчанию вычисляется просто время подъема или опускания цены. Ключ=1. Но можно исследовать совместное влияние времени и цены и тогда ключ=2. Если изучаем совместное влияние времени и изменения цены за один бар, то ключ=3. Если изучаем совместное влияние времени и объема, то ключ=4. Если изучаем совместное влияние времени, цены и объема, то ключ=5.
"key RsiO red + green==> : 1=Time, 2=Time*Price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*Price*Volume") ---аналогичные настройки для красной зеленой линии. По умолчанию вычисляется просто время подъема или опускания цены. Ключ=1. Но можно исследовать совместное влияние времени и цены и тогда ключ=2. Если изучаем совместное влияние времени и изменения цены за один бар, то ключ=3. Если изучаем совместное влияние времени и объема, то ключ=4. Если изучаем совместное влияние времени, цены и объема, то ключ=5.
"Key Color" – здесь можно отключить изменение цвета голубой линии на зеленый или красный в моменты выхода базового индикатора RsiVol выше верхнего и ниже нижнего уровней.
"Level nul ==> * Down Level Rsi - косметическая настройка для того, чтобы поднять или опустить график
"Level nul ==> * Down Level ORsi -- косметическая настройка для того, чтобы поднять или опустить график
"Level nul ==> * DownLevel RsiVol200 -- косметическая настройка для того, чтобы поднять или опустить график
" blue =>volume * price" – период для вычисления объемной цены
" blue => RSIVOL(Volume*price,len) and EMA" – период для вычисления RsiVol
"blue__o1=> ema ( RSIVOL, o1)" – дополнительное сглаживание RsiVol
" red=rsi (Price,14)" – период для вычисления Rsi
" red= ema ( RSI ,3)" -- дополнительное сглаживание Rsi
"fuchsia__ => RsiVol200 (vp,200)" -- период для вычисления RsiVol200
"fuchsia__o2=> ema ( RSIVOL200 , o2)" -- дополнительное сглаживание RsiVol200
Для исследования времени между двумя фиксированными датами. Задаем начальную точку вычисления и конечную точку вычисления
"Data(0)=Year" – год начальной даты
"Data(0)= Month" – месяц начальной даты
"Data(0)=Day" день начальной даты
"Data(1)=Year" – год конечной даты.
"Data(1)=Year" – месяц конечной даты.
"Data(1)=Day" -- день конечной даты.
Amazing Oscillator MTF MulticolorIngles
The amazing multitemporal oscillator, allows you to see in a single graph the Waves that move the market in different temporalities, that is, you will be able to see the market trend, the impulse movement, the forced movement, and the entry and exit points, as well as also how both collide with each other, to understand why the smaller waves succumb to the impulse of the larger waves.
Elliot already described them as such, in his legacy of the Elliot waves and their different sub-waves, just as Wycoff spoke of the theory of effort and result.
Español:
El oscilador asombroso multitemporal, permite ver en una sola grafica las Ondas que mueven el mercado en diferentes temporalidades, es decir, podrás ver la tendencia del mercado, el movimiento de impulso, el movimiento de fuerza y los puntos de entrada y salida, así como también como ambos chocan entre si, para entender porque las ondas mas pequeñas sucumben al impulso de las ondas de mayor tamaño.
Ya Elliot las describía como tal, en su legado de las ondas de Elliot y sus diferentes sub-ondas, al igual que Wycoff hablaba de la teoría de esfuerzo y resultado.
Amazing Oscillator MTF plusIngles
The amazing multitemporal oscillator, allows you to see in a single graph the Waves that move the market in different temporalities, that is, you will be able to see the market trend, the impulse movement, the force movement and the entry and exit points, as well as also how both collide with each other, to understand why the smaller waves succumb to the impulse of the larger waves.
Elliot already described them as such, in his legacy of the Elliot waves and their different sub-waves, just as Wycoff spoke of the theory of effort and result.
Español:
El oscilador asombroso multitemporal, permite ver en una sola grafica las Ondas que mueven el mercado en diferentes temporalidades, es decir, podrás ver la tendencia del mercado, el movimiento de impulso, el movimiento de fuerza y los puntos de entrada y salida, así como también como ambos chocan entre si, para entender porque las ondas mas pequeñas sucumben al impulso de las ondas de mayor tamaño.
Ya Elliot las describía como tal, en su legado de las ondas de Elliot y sus diferentes sub-ondas, al igual que Wycoff hablaba de la teoría de esfuerzo y resultado.
Trend Volume Accumulations [LuxAlgo]Deeply inspired by the Weiss wave indicator, the following indicator aims to return the accumulations of rising and declining volume of a specific trend. Positive waves are constructed using rising volume while negative waves are using declining volume.
The trend is determined by the sign of the rise of a rolling linear regression.
Settings
Length : Period of the indicator.
Src : Source of the indicator.
Linearity : Allows the output of the indicator to look more linear.
Mult : the multiplicative factor of both the upper and lower levels
Gradient : Use a gradient as color for the waves, true by default.
Usages
The trend volume accumulations (TVA) indicator allows determining the current price trend while taking into account volume, with blue colors representing an uptrend and red colors representing a downtrend.
The first motivation behind this indicator was to see if movements mostly made of declining volume were different from ones made of rising volume.
Waves of low amplitude represent movements with low trading activity.
Using higher values of Linearity allows giving less importance to individual volumes values, thus returning more linear waves as a result.
The indicator includes two levels, the upper one is derived from the cumulative mean of the waves based on rising volume, while the lower one is based on the cumulative mean of the waves based on declining volume, when a wave reaches a level we can expect the current trend to reverse. You can use different values of mult to control the distance from 0 of each level.
Minimal Godmode 2.1// Acknowledgments:
// Original Godmode Authors:
// @Legion, @LazyBear, @Ni6HTH4wK, @xSilas
// Drop a line if you use or modify this code.
// Godmode 3.1.4: @SNOW_CITY
// Godmode 3.2: @sco77m4r7in and @oh92
// Godmode3.2+LSMA: @scilentor
// Godmode 4.0.0-4.0.1: @chrysopoetics
// Jurik Moving Average: @everget
// Constance Brown Composite Index RSI: @LazyBear
// Wavetrend Oscillator: @fskrypt
// TTM Squeeze: @Greeny
// True TSI/RSI: @cI8DH and @chrysopoetics
// Laguerre RSI (Self-Adjusting Alpha with Fractals Energy): @everget
// RSI Shaded: @mortdiggiddy
// Minimal Godmode v2.0:
// 6 BTC pairs/exchanges (instead of 11) to reduce loading time from the pinescript security() function
// Volume Composite for engine calculation
// TTM Squeeze on Wavetrend Signal
// Constance Brown Composite Index RSI (CBCI)
// TrueTSI (Godmode 4.0.0 implementation)
// Laguerre RSI (LRSI)
// Minimal Godmode v2.1:
// Removed TTM Squeeze and Volume Composite
// EMA for Wavetrend Signal
// Multi-exchange for BTC no longer the default
// mg engine toggle for CBCI, Laguerre RSI, and TTSI
// Wavetrend Histogram component toggle
Indicator: ElliotWave Oscillator [EWO]This oscillator has to be used in conjunction with other EW tools (certainly cannot be the main indicator).
EWO has:
- Higher values during third waves' up
- Lower but still Positive values during the first and fifth waves up
- Negative values during the biggest corrections or downtrend impulse waves.
Personally, I am still trying to figure out EW, so do not use this. Just wanted to publish this for the EW masters out there who can put this to good use.
Appreciate any comments/feedback.
RSI Confluence (14 + 7) – Daniel Pour éviter trop d'indicateur j'ai créer la combinaison des 2 RSI 7 & 14 pour le Timeframe H1,M15 & M5
1. Timeframe optimal
Le RSI (14) ou Volume-Weighted RSI doit être placé sur :
Timeframe Rôle du RSI
H1 Filtre directionnel : si RSI > 60 → biais haussier, si < 40 → biais baissier.
M15 Confirme le momentum moyen : attendre le rejet sur 40–60 dans le sens du H1.
M5 Sert à confirmer le timing d’entrée avec WT (WaveTrend). Entrée idéale quand RSI repart du bord 40/60 en même temps que WT repart dans la même direction.
💡 Sur M5, c’est le plus utile : il te permet d’éviter les divergences WT trop précoces (faux signaux avant que le marché ne parte vraiment).
H1 – Directional Filter (Main Trend)
Purpose: Identify the dominant bias (bullish or bearish).
Key reading:
RSI > 60 → Bullish bias → only look for buys on M15/M5.
RSI < 40 → Bearish bias → only look for sells on M15/M5.
Advanced tip: Draw a neutral zone (40–60) → if RSI stays inside it, the market is ranging (no clear trend).
Visual tip: Add a soft gray band between 40 and 60 for clarity.
⏱️ M15 – Momentum Confirmation
Purpose: Confirm that the medium-term momentum aligns with the H1 bias.
Key reading:
When RSI M15 rejects 40 (bullish rebound) in an H1 bullish bias, it’s a buy confirmation.
When RSI M15 rejects 60 (bearish rebound) in an H1 bearish bias, it’s a sell confirmation.
Timing: Avoid entries until M15 confirms the rejection.
Optional: Apply a smoothed RSI (EMA 9) to visualize momentum swings more clearly.
⏳ M5 – Entry Timing
Purpose: Synchronize entries with the WaveTrend (WT) indicator.
Key reading:
Ideal entry when RSI bounces off 40/60 in the same direction as WT.
Example: RSI M5 rebounds from 40 and WT crosses up → perfect buy entry.
Conversely, RSI M5 turns down from 60 and WT crosses down → perfect sell entry.
Advantage: Helps avoid early WT divergences (false signals before the move truly starts).
Advanced filter: Combine with ADX > 25 to confirm market strength.
Tunç ŞatıroğluTunç Şatıroğlu's Technical Analysis Suite
Description:
This comprehensive Pine Script indicator, inspired by the technical analysis teachings of Tunç Şatıroğlu, integrates six powerful TradingView indicators into a single, user-friendly suite for robust trend, momentum, and divergence analysis. Each component has been carefully selected and enhanced by beytun to improve functionality, performance, and visual clarity, aligning with Şatıroğlu's approach to technical analysis. The default configuration is meticulously set to match the exact settings of the individual indicators as used by Tunç Şatıroğlu in his training, ensuring authenticity and ease of use for followers of his methodology. Whether you're a beginner or an experienced trader, this suite provides a versatile toolkit for analyzing markets across multiple timeframes.
Included Indicators:
1. WaveTrend with Crosses (by LazyBear, modified): A momentum oscillator that identifies overbought/oversold conditions and trend reversals with clear buy/sell signals via crosses and bar color highlights.
2. Kaufman Adaptive Moving Average (KAMA) (by HPotter, modified): A dynamic moving average that adapts to market volatility, offering a smoother trend-following signal.
3. SuperTrend (by Alex Orekhov, modified): A trend-following indicator that plots dynamic support/resistance levels with buy/sell signals and optional wicks for enhanced accuracy.
4. Nadaraya-Watson Envelope (by LuxAlgo, modified): A non-linear envelope that highlights potential reversals with customizable repainting options for smoother outputs.
5. Divergence for Many Indicators v4 (by LonesomeTheBlue, modified): Detects regular and hidden divergences across multiple indicators (MACD, RSI, Stochastic, CCI, Momentum, OBV, VWMA, CMF, MFI, and more) for early reversal signals.
6. Ichimoku Cloud (TradingView built-in, modified): A multi-faceted indicator for trend direction, support/resistance, and momentum, with enhanced visuals for the Kumo Cloud.
Key Features:
- Authentic Default Settings : Pre-configured to mirror the exact parameters used by Tunç Şatıroğlu for each indicator, ensuring alignment with his proven technical analysis approach.
- Customizable Settings : Enable/disable individual indicators and fine-tune parameters to suit your trading style while retaining the option to revert to Şatıroğlu’s defaults.
- Enhanced User Experience : Modifications improve visual clarity, performance, and usability, with options like repainting smoothing for Nadaraya-Watson and adjustable Ichimoku projection periods.
- Multi-Timeframe Analysis : Combines trend-following, momentum, and divergence tools for a holistic view of market dynamics.
- Alert Conditions : Built-in alerts for SuperTrend direction changes, buy/sell signals, and divergence detections to keep you informed.
- Visual Clarity : Overlays (KAMA, SuperTrend, Nadaraya-Watson, Ichimoku) and pane-based indicators (WaveTrend, Divergences) are clearly distinguished, with customizable colors and styles.
Notes:
- The Nadaraya-Watson Envelope and Ichimoku Cloud may repaint in their default modes. Use the "Repainting Smoothing" option for Nadaraya-Watson or adjust Ichimoku settings to mitigate repainting if preferred.
- Published under the MIT License, with components licensed under GPL-3.0 (SuperTrend), CC BY-NC-SA 4.0 (Nadaraya-Watson), MPL 2.0 (Divergence), and TradingView's terms (Ichimoku Cloud).
Usage:
Add this indicator to your TradingView chart to leverage Tunç Şatıroğlu’s exact indicator configurations out of the box. Customize settings as needed to align with your strategy, and use the combined signals to identify trends, reversals, and divergences. Ideal for traders following Şatıroğlu’s methodologies or anyone seeking a powerful, all-in-one technical analysis tool.
Credits:
Original authors: LazyBear, HPotter, Alex Orekhov, LuxAlgo, LonesomeTheBlue, and TradingView.
Modifications and integration by beytun .
License:
Published under the MIT License, incorporating code under GPL-3.0, CC BY-NC-SA 4.0, MPL 2.0, and TradingView’s terms where applicable.
Information Flow Analysis[b🔄 Information Flow Analysis: Systematic Multi-Component Market Analysis Framework
SYSTEM OVERVIEW AND ANALYTICAL FOUNDATION
The Information Flow Kernel - Hybrid combines established technical analysis methods into a unified analytical framework. This indicator systematically processes three distinct data streams - directional price momentum, volume-weighted pressure dynamics, and intrabar development patterns - integrating them through weighted mathematical fusion to produce statistically normalized market flow measurements.
COMPREHENSIVE MATHEMATICAL FRAMEWORK
Component 1: Directional Flow Analysis
The directional component analyzes price momentum through three mathematical vectors:
Price Vector: p = C - O (intrabar directional bias)
Momentum Vector: m = C_t - C_{t-1} (bar-to-bar velocity)
Acceleration Vector: a = m_t - m_{t-1} (momentum rate of change)
Directional Signal Integration:
S_d = \text{sgn}(p) \cdot |p| + \text{sgn}(m) \cdot |m| \cdot 0.6 + \text{sgn}(a) \cdot |a| \cdot 0.3
The signum function preserves directional information while absolute values provide magnitude weighting. Coefficients create a hierarchy emphasizing intrabar movement (100%), momentum (60%), and acceleration (30%).
Final Directional Output: K_1 = S_d \cdot w_d where w_d is the directional weight parameter.
Component 2: Volume-Weighted Pressure Analysis
Volume Normalization: r_v = \frac{V_t}{\overline{V_n}} where \overline{V_n} represents the n-period simple moving average of volume.
Base Pressure Calculation: P_{base} = \Delta C \cdot r_v \cdot w_v where \Delta C = C_t - C_{t-1} and w_v is the velocity weighting factor.
Volume Confirmation Function:
f(r_v) = \begin{cases}
1.4 & \text{if } r_v > 1.2 \
0.7 & \text{if } r_v < 0.8 \
1.0 & \text{otherwise}
\end{cases}
Final Pressure Output: K_2 = P_{base} \cdot f(r_v)
Component 3: Intrabar Development Analysis
Bar Position Calculation: B = \frac{C - L}{H - L} when H - L > 0 , else B = 0.5
Development Signal Function:
S_{dev} = \begin{cases}
2(B - 0.5) & \text{if } B > 0.6 \text{ or } B < 0.4 \
0 & \text{if } 0.4 \leq B \leq 0.6
\end{cases}
Final Development Output: K_3 = S_{dev} \cdot 0.4
Master Integration and Statistical Normalization
Weighted Component Fusion: F_{raw} = 0.5K_1 + 0.35K_2 + 0.15K_3
Sensitivity Scaling: F_{master} = F_{raw} \cdot s where s is the sensitivity parameter.
Statistical Normalization Process:
Rolling Mean: \mu_F = \frac{1}{n}\sum_{i=0}^{n-1} F_{master,t-i}
Rolling Standard Deviation: \sigma_F = \sqrt{\frac{1}{n}\sum_{i=0}^{n-1} (F_{master,t-i} - \mu_F)^2}
Z-Score Computation: z = \frac{F_{master} - \mu_F}{\sigma_F}
Boundary Enforcement: z_{bounded} = \max(-3, \min(3, z))
Final Normalization: N = \frac{z_{bounded}}{3}
Flow Metrics Calculation:
Intensity: I = |z|
Strength Percentage: S = \min(100, I \times 33.33)
Extreme Detection: \text{Extreme} = I > 2.0
DETAILED INPUT PARAMETER SPECIFICATIONS
Sensitivity (0.1 - 3.0, Default: 1.0)
Global amplification multiplier applied to the master flow calculation. Functions as: F_{master} = F_{raw} \cdot s
Low Settings (0.1 - 0.5): Enhanced precision for subtle market movements. Optimal for low-volatility environments, scalping strategies, and early detection of minor directional shifts. Increases responsiveness but may amplify noise.
Moderate Settings (0.6 - 1.2): Balanced sensitivity for standard market conditions across multiple timeframes.
High Settings (1.3 - 3.0): Reduced sensitivity to minor fluctuations while emphasizing significant flow changes. Ideal for high-volatility assets, trending markets, and longer timeframes.
Directional Weighting (0.1 - 1.0, Default: 0.7)
Controls emphasis on price direction versus volume and positioning factors. Applied as: K_{1,weighted} = K_1 \times w_d
Lower Values (0.1 - 0.4): Reduces directional bias, favoring volume-confirmed moves. Optimal for ranging markets where momentum may generate false signals.
Higher Values (0.7 - 1.0): Amplifies directional signals from price vectors and acceleration. Ideal for trending conditions where directional momentum drives price action.
Velocity Weighting (0.1 - 1.0, Default: 0.6)
Scales volume-confirmed price change impact. Applied in: P_{base} = \Delta C \times r_v \times w_v
Lower Values (0.1 - 0.4): Dampens volume spike influence, focusing on sustained pressure patterns. Suitable for illiquid assets or news-sensitive markets.
Higher Values (0.8 - 1.0): Amplifies high-volume directional moves. Optimal for liquid markets where volume provides reliable confirmation.
Volume Length (3 - 20, Default: 5)
Defines lookback period for volume averaging: \overline{V_n} = \frac{1}{n}\sum_{i=0}^{n-1} V_{t-i}
Short Periods (3 - 7): Responsive to recent volume shifts, excellent for intraday analysis.
Long Periods (13 - 20): Smoother averaging, better for swing trading and higher timeframes.
DASHBOARD SYSTEM
Primary Flow Gauge
Bilaterally symmetric visualization displaying normalized flow direction and intensity:
Segment Calculation: n_{active} = \lfloor |N| \times 15 \rfloor
Left Fill: Bearish flow when N < -0.01
Right Fill: Bullish flow when N > 0.01
Neutral Display: Empty segments when |N| \leq 0.01
Visual Style Options:
Matrix: Digital blocks (▰/▱) for quantitative precision
Wave: Progressive patterns (▁▂▃▄▅▆▇█) showing flow buildup
Dots: LED-style indicators (●/○) with intensity scaling
Blocks: Modern squares (■/□) for professional appearance
Pulse: Progressive markers (⎯ to █) emphasizing intensity buildup
Flow Intensity Visualization
30-segment horizontal bar graph with mathematical fill logic:
Segment Fill: For i \in : filled if \frac{i}{29} \leq \frac{S}{100}
Color Coding System:
Orange (S > 66%): High intensity, strong directional conviction
Cyan (33% ≤ S ≤ 66%): Moderate intensity, developing bias
White (S < 33%): Low intensity, neutral conditions
Extreme Detection Indicators
Circular markers flanking the gauge with state-dependent illumination:
Activation: I > 2.0 \land |N| > 0.3
Bright Yellow: Active extreme conditions
Dim Yellow: Normal conditions
Metrics Display
Balance Value: Raw master flow output ( F_{master} ) showing absolute directional pressure
Z-Score Value: Statistical deviation ( z_{bounded} ) indicating historical context
Dynamic Narrative System
Context-sensitive interpretation based on mathematical thresholds:
Extreme Flow: I > 2.0 \land |N| > 0.6
Moderate Flow: 0.3 < |N| \leq 0.6
High Volatility: S > 50 \land |N| \leq 0.3
Neutral State: S \leq 50 \land |N| \leq 0.3
ALERT SYSTEM SPECIFICATIONS
Mathematical Trigger Conditions:
Extreme Bullish: I > 2.0 \land N > 0.6
Extreme Bearish: I > 2.0 \land N < -0.6
High Intensity: S > 80
Bullish Shift: N_t > 0.3 \land N_{t-1} \leq 0.3
Bearish Shift: N_t < -0.3 \land N_{t-1} \geq -0.3
TECHNICAL IMPLEMENTATION AND PERFORMANCE
Computational Architecture
The system employs efficient calculation methods minimizing processing overhead:
Single-pass mathematical operations for all components
Conditional visual rendering (executed only on final bar)
Optimized array operations using direct calculations
Real-Time Processing
The indicator updates continuously during bar formation, providing immediate feedback on changing market conditions. Statistical normalization ensures consistent interpretation across varying market regimes.
Market Applicability
Optimal performance in liquid markets with consistent volume patterns. May require parameter adjustment for:
Low-volume or after-hours sessions
News-driven market conditions
Highly volatile cryptocurrency markets
Ranging versus trending market environments
PRACTICAL APPLICATION FRAMEWORK
Market State Classification
This indicator functions as a comprehensive market condition assessment tool providing:
Trend Analysis: High intensity readings ( S > 66% ) with sustained directional bias indicate strong trending conditions suitable for momentum strategies.
Reversal Detection: Extreme readings ( I > 2.0 ) at key technical levels may signal potential trend exhaustion or reversal points.
Range Identification: Low intensity with neutral flow ( S < 33%, |N| < 0.3 ) suggests ranging market conditions suitable for mean reversion strategies.
Volatility Assessment: High intensity without clear directional bias indicates elevated volatility with conflicting pressures.
Integration with Trading Systems
The normalized output range facilitates integration with automated trading systems and position sizing algorithms. The statistical basis provides consistent interpretation across different market conditions and asset classes.
LIMITATIONS AND CONSIDERATIONS
This indicator combines established technical analysis methods and processes historical data without predicting future price movements. The system performs optimally in liquid markets with consistent volume patterns and may produce false signals in thin trading conditions or during news-driven market events. This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Users should combine this analysis with proper risk management, position sizing, and additional confirmation methods before making any trading decisions. Past performance does not guarantee future results.
Note: The term "kernel" in this context refers to modular calculation components rather than mathematical kernel functions in the formal computational sense.
As quantitative analyst Ralph Vince noted: "The essence of successful trading lies not in predicting market direction, but in the systematic processing of market information and the disciplined management of probability distributions."
— Dskyz, Trade with insight. Trade with anticipation.
HUll Dynamic BandEducational Hull Moving Average Wave Analysis Tool
**MARS** is an innovative educational indicator that combines multiple Hull Moving Average timeframes to create a comprehensive wave analysis system, similar in concept to Ichimoku Cloud but with enhanced smoothness and responsiveness.
---
🎯 Key Features
**Triple Wave System**
- **Peak Wave (34-period)**: Fast momentum signals, similar to Ichimoku's Conversion Line
- **Primary Wave (89-period)**: Main trend identification with retest detection
- **Swell Wave (178-period)**: Long-term trend context and major wave analysis
**Visual Wave Analysis**
- **Wave Power Fill**: Dynamic area between primary and swell waves showing trend strength
- **Peak Power Fill**: Short-term momentum visualization
- **Smooth Curves**: Hull MA-based calculations provide cleaner signals than traditional moving averages
**Intelligent Signal System**
- **Trend Shift Signals**: Clear visual markers when trend changes occur
- **Retest Detection**: Identifies potential retest opportunities with specific conditions
- **Correction Alerts**: Early warning signals for market corrections
---
📊 How It Works
The indicator uses **Hull Moving Averages** with **Fibonacci-based periods** (34, 89, 178) and a **Golden Ratio multiplier (1.64)** to create natural market rhythm analysis.
**Key Signal Types:**
- 🔵 **Circles**: Major trend shifts (primary wave crossovers)
- 💎 **Diamonds**: Retest opportunities with multi-wave confirmation
- ❌ **X-marks**: Correction signals and structural breaks
- 🌊 **Wave Fills**: Visual trend strength and direction
---
🎓 Educational Purpose
This indicator demonstrates:
- Advanced moving average techniques using Hull MA
- Multi-timeframe analysis in a single view
- Wave theory application in technical analysis
- Dynamic support/resistance concept visualization
**Similar to Ichimoku but Different:**
- Ichimoku uses price-based calculations → Angular cloud shapes
- MARS uses weighted averages → Smooth, flowing wave patterns
- Both identify trend direction, but MARS offers faster signals with cleaner visualization
---
⚙️ Customizable Settings
- **Wave Periods**: Adjust primary wave length (default: 89)
- **Multipliers**: Fine-tune wave sensitivity (default: 1.64 Golden Ratio)
- **Visual Style**: Customize line widths and signal displays
- **Peak Analysis**: Independent fast signal system (default: 34)
---
🔍 Usage Tips
1. **Trend Identification**: Watch wave fill colors and line positions
2. **Entry Timing**: Look for retest diamonds after trend shift circles
3. **Risk Management**: Use wave boundaries as dynamic support/resistance
4. **Confirmation**: Combine with price action and market structure analysis
---
⚠️ Important Notes
- **Educational Tool**: Designed for learning wave analysis concepts
- **Not Financial Advice**: Always use proper risk management
- **Backtesting Recommended**: Test on historical data before live trading
- **Combine with Analysis**: Works best with additional confirmation methods
---
🚀 Innovation
MARS represents a unique approach to wave analysis by:
- Combining Hull MA smoothness with Ichimoku-style visualization
- Providing multi-timeframe analysis without chart clutter
- Offering retest detection with specific wave conditions
- Creating an educational bridge between different analytical methods
---
*This indicator is shared for educational purposes to help traders understand advanced moving average techniques and wave analysis concepts. Always practice proper risk management and combine with your own analysis.*
Constance Brown Composite Index EnhancedWhat This Indicator Does
Implements Constance Brown's copyrighted Composite Index formula (1996) from her Master's thesis - a breakthrough oscillator that solves the critical problem where RSI fails to show divergences in long-horizon trends, providing early warning signals for major market reversals.
The Problem It Solves
Traditional RSI frequently fails to display divergence signals in Global Equity Indexes and long-term charts, leaving asset managers without warning of major price reversals. Brown's research showed RSI failed to provide divergence signals 42 times across major markets - failures that would have been "extremely costly for asset managers."
Key Components
Composite Line: RSI Momentum (9-period) + Smoothed RSI Average - the core breakthrough formula
Fast/Slow Moving Averages: Trend direction confirmation (13/33 periods default)
Bollinger Bands: Volatility envelope around the composite signal
Enhanced Divergence Detection: Significantly improved trend reversal timing vs standard RSI
Research-Proven Performance
Based on Brown's extensive study across 6 major markets (1919-2015):
42 divergence signals triggered where RSI showed none
33 signals passed with meaningful reversals (78% success rate)
Only 5 failures - exceptional performance in monthly/2-month timeframes
Tested on: German DAX, French CAC 40, Shanghai Composite, Dow Jones, US/Japanese Government Bonds
New Customization Features
Moving Average Types: Choose SMA or EMA for fast/slow lines
Optional Fills: Toggle composite and Bollinger band fills on/off
All Periods Adjustable: RSI length, momentum, smoothing periods
Visual Styling: Customize colors and line widths in Style tab
Default Settings (Original Formula)
RSI Length: 14
RSI Momentum: 9 periods
RSI MA Length: 3
SMA Length: 3
Fast SMA: 13, Slow SMA: 33
Bollinger STD: 2.0
Applications
Long-term investing: Monthly/2-month charts for major trend changes
Elliott Wave analysis: Maximum displacement at 3rd-of-3rd waves, divergence at 5th waves
Multi-timeframe: Pairs well with MACD, works across all timeframes
Global markets: Proven effective on equities, bonds, currencies, commodities
Perfect for serious traders and asset managers seeking the proven mathematical edge that traditional RSI cannot provide.
Fractal Circles#### FRACTAL CIRCLES ####
I combined 2 of my best indicators Fractal Waves (Simplified) and Circles.
Combining the Fractal and Gann levels makes for a very simple trading strategy.
Core Functionality
Gann Circle Levels: This indicator plots mathematical support and resistance levels based on Gann theory, including 360/2, 360/3, and doubly strong levels. The system automatically adjusts to any price range using an intelligent multiplier system, making it suitable for forex, stocks, crypto, or any market.
Fractal Wave Analysis: Integrates real-time trend analysis from both current and higher timeframes. Shows the current price range boundaries (high/low) and trend direction through dynamic lines and background fills, helping traders understand market structure.
Key Trading Benefits
Active Level Detection: The closest Gann level to current price is automatically highlighted in green with increased line thickness. This eliminates guesswork about which level is most likely to act as immediate support or resistance.
Real-Time Price Tracking: A customizable line follows current price with an offset to the right, projecting where price sits relative to upcoming levels. A gradient-filled box visualizes the exact distance between current price and the active Gann level.
Multi-Timeframe Context: View fractal waves from higher timeframes while maintaining current timeframe precision. This helps identify whether short-term moves align with or contradict longer-term structure.
Smart Alert System: Comprehensive alerts trigger when price crosses any Gann level, with options to monitor all levels or focus only on the active level. Reduces the need for constant chart monitoring while ensuring you never miss significant level breaks.
Practical Trading Applications
Entry Timing: Use active level highlighting to identify the most probable support/resistance for entries. The real-time distance box helps gauge risk/reward before entering positions.
Risk Management: Set stops based on Gann level breaks, particularly doubly strong levels which tend to be more significant. The gradient visualization makes it easy to see how much room price has before hitting key levels.
Trend Confirmation: Fractal waves provide immediate context about whether current price action aligns with broader market structure. Bullish/bearish background fills offer quick visual confirmation of trend direction.
Multi-Asset Analysis: The auto-scaling multiplier system works across all markets and timeframes, making it valuable for traders who monitor multiple instruments with vastly different price ranges.
Confluence Trading: Combine Gann levels with fractal wave boundaries to identify high-probability setups where multiple technical factors align.
This tool is particularly valuable for traders who appreciate mathematical precision in their technical analysis while maintaining the flexibility to adapt to real-time market conditions.
Aethix Cipher Pro2Aethix Cipher Pro: AI-Enhanced Crypto Signal Indicator grok Ai made signal created for aethix users.
Unlock the future of crypto trading with Aethix Cipher Pro—a powerhouse indicator inspired by Market Cipher A, turbocharged for Aethix.io users! Built on WaveTrend Oscillator, 8-EMA Ribbon, RSI+MFI, and custom enhancements like Grok AI confidence levels (70-100%), on-chain whale volume thresholds, and fun meme alerts ("To the moon! 🌕").
Key Features: no whale tabs
WaveTrend Signals: Spot overbought/oversold with levels at ±53/60/100—crosses trigger red diamonds, blood diamonds, yellow X's for high-prob buy/sell entries.
Neon Teal EMA Ribbon: Dynamic 5-34 EMA gradient (bullish teal/bearish red) for trend direction—crossovers plot green/red circles, blue triangles.
RSI+MFI Fusion: Overbought (70+)/oversold (30-) with long snippets for sentiment edges.
Aethix Cipher Pro2Aethix Cipher Pro: AI-Enhanced Crypto Signal Indicator grok Ai made signal created for aethix users.
Unlock the future of crypto trading with Aethix Cipher Pro—a powerhouse indicator inspired by Market Cipher A, turbocharged for Aethix.io users! Built on WaveTrend Oscillator, 8-EMA Ribbon, RSI+MFI, and custom enhancements like Grok AI confidence levels (70-100%), on-chain whale volume thresholds, and fun meme alerts ("To the moon! 🌕").
Key Features:
WaveTrend Signals: Spot overbought/oversold with levels at ±53/60/100—crosses trigger red diamonds, blood diamonds, yellow X's for high-prob buy/sell entries.
Neon Teal EMA Ribbon: Dynamic 5-34 EMA gradient (bullish teal/bearish red) for trend direction—crossovers plot green/red circles, blue triangles.
RSI+MFI Fusion: Overbought (70+)/oversold (30-) with long snippets for sentiment edges.
Aethix Cipher ProAethix Cipher Pro: AI-Enhanced Crypto Signal Indicator grok Ai made signal created for aethix users.
Unlock the future of crypto trading with Aethix Cipher Pro—a powerhouse indicator inspired by Market Cipher A, turbocharged for Aethix.io users! Built on WaveTrend Oscillator, 8-EMA Ribbon, RSI+MFI, and custom enhancements like Grok AI confidence levels (70-100%), on-chain whale volume thresholds, and fun meme alerts ("To the moon! 🌕").
Key Features:
WaveTrend Signals: Spot overbought/oversold with levels at ±53/60/100—crosses trigger red diamonds, blood diamonds, yellow X's for high-prob buy/sell entries.
Neon Teal EMA Ribbon: Dynamic 5-34 EMA gradient (bullish teal/bearish red) for trend direction—crossovers plot green/red circles, blue triangles.
RSI+MFI Fusion: Overbought (70+)/oversold (30-) with long snippets for sentiment edges.
Market Energy – Trend vs Retest (with Saturation %)Market Energy – Trend vs Retest Indicator
This indicator measures the bullish and bearish energy in the market based on volume-weighted price changes.
It calculates two smoothed energy waves — bullish energy and bearish energy — using exponential moving averages of volume-adjusted price movements.
The indicator detects trend changes and retests by comparing the relative strength of these waves.
A saturation percentage quantifies the intensity of the current dominant side (bulls or bears) relative to recent highs.
- High saturation (>70%) indicates strong momentum and dominance by bulls or bears.
- Low saturation (<30%) suggests weak momentum and possible market indecision or consolidation.
The background color highlights the current control: green for bulls, red for bears, with transparency indicating the saturation level.
A label shows which side is currently in control along with the saturation percentage for quick interpretation.
Use this tool to identify strong trends, possible retests, and momentum strength to support your trading decisions.
Golden Pocket Syndicate [GPS]Golden Pocket Syndicate is a multi-layered market analysis toolkit built for precision entries and sniper-style reversals in both trending and ranging conditions. The script fuses volume dynamics, golden pocket structures, market maker behavior, and liquidation cluster tracking into one high-confluence system.
Core Features:
• 📐 Golden Pocket Zones: Dynamic GP levels from daily, weekly, monthly, and yearly timeframes. These levels update in real-time and serve as confluence zones for entries and exits.
• 📊 WaveTrend Divergence Diamonds: Momentum shifts are detected using a custom filtered WaveTrend cross system to mark high-probability reversal conditions.
• 🧠 Market Maker Premium Divergence: Tracks price dislocation between CME and Binance to detect large player manipulation using a configurable premium threshold.
• 💎 MM Reversal Diamonds: Identifies potential market maker traps and large player pivots using historical candle behavior, EMA alignment, and price structure breaks.
• 📉 Stealth Liquidation Cluster Arrows: Volume-based liquidation pressure visualized as lightweight directional arrows based on calculated wick expansion and volume bursts. Highlights key zones where price is likely to bounce or reject.
• 🧭 Trend Validation: Uses volume-based trend conditions and short-term EMA positioning to further qualify signals and eliminate noise.
How to Use:
This indicator is designed to help traders visualize confluence between key institutional price levels, momentum shifts, and volume-based pressure points. Long/short opportunities can be explored at marked reversal diamonds or liquidation zones that align with key GP levels. Intended for use on higher timeframes (15m to 4H), though flexible across any pair or market.
Heikin RiderHeikin Rider
Smoothed Heikin Ashi Breakout Signals with Flow Confirmation
by Ben Deharde, 2025
Overview:
Heikin Rider is a trend-following indicator that detects clean breakout signals using a custom smoothed Heikin Ashi wave (the H-Wave) with optional confirmation from a flow-based filter. It's designed for traders who want precise, momentum-aligned entries.
What It Does:
Plots dynamic high/low bands from smoothed Heikin Ashi candles.
Triggers Buy/Sell signals on full candle breakouts above/below the wave.
Colors bars based on price position and momentum relative to a custom flow line.
Optionally filters signals based on flow direction.
How the H-Wave Works:
The H-Wave is a two-stage smoothed Heikin Ashi construction:
Pre-smoothing: Price is smoothed using a short-length MA (SMA, EMA, or HMA).
HA Calculation: Heikin Ashi values are calculated from the smoothed data.
Post-smoothing: A second, longer MA is applied to the HA values.
Wave Envelope: The high and low wicks of the final smoothed HA candles form the H-Wave envelope.
Signals are generated when price fully breaks this envelope, with optional confirmation from the flow color.
Inputs:
Trend timeframe
Pre/Post smoothing type and length
Flow MA type and length
Toggle for bar coloring and signal filtering
Notes:
Built with original logic, using the open-source TAExt library (credited).
No repainting — all signals are confirmed at close.
For use on standard candles only (not HA or Renko).
Alerts:
Long Signal (Buy)
Short Signal (Sell)
