Stop Loss With Average True Range (ATR)Stop Loss With Average True Range (ATR)
It simplifies the calculation of stop loss price for stop loss method using the average true range (ATR).
For example;
You want to stop loss below 3 ATR. Let's assume the price is 100, the average true range is 5. You will multiply the average true range by 3 and subtract from the price and enter a stop loss order at the 85 price you have reached. Instead of doing this calculation every time, you just need to use this script and set the multiplier to 3. A stop loss line will be drawn below the price candles.
You can set the method to be used when averaging the true range. Methods you can use to average: EMA (exponentially moving average), HMA (hull moving average), RMA (moving average used in RSI), SMA (simple moving average), SWMA (symmetrically weighted moving average), VWMA (volume-weighted moving average), WMA (weighted moving average).
You can set the length to be used when averaging the true range.
You can set the multiplier to be used when determining the stop loss price.
Turkish
Ortalama Gerçek Aralıkla (ATR) Zarar Durdurma
Gerçek aralığın ortalamasını kullanarak zarar durdurma yöntemi için zarar durdurma fiyatının hesaplanmasını kolaylaştırır.
Örneğin;
3 ATR kadar aşağıda zarar durdurmak istiyorsunuz. Fiyatın 100, ortalama gerçek aralığın 5 olduğunu varsayalım. Ortalama gerçek aralığı 3 ile çarparak fiyattan çıkaracaksınız ve ulaştığınız 85 fiyatına zarar durdurma emri gireceksiniz. Bu hesabı her seferinde yapmak yerine bu betiği kullanmanız ve çarpanı 3 olarak ayarlamanız yeterli. Bu sayede fiyat mumlarının altına zarar durdurma çizgisi çizilecektir.
Gerçek aralığın ortalaması alınırken kullanılacak yöntemi ayarlayabilirsiniz. Ortalama almak için seçebileceğiniz yöntemler: EMA (üstel hareketli ortalama), HMA (gövde hareketli ortalama), RMA (göreceli hareketli ortalama), SMA (basit hareketli ortalama), SWMA (simetrik ağırlıklı hareketli ortalama), VWMA (hacim ağırıklı hareketli ortalama), WMA (ağırlıklı hareketli ortalama).
Gerçek aralığın ortalaması alınırken kullanılacak periyot uzunluğunu ayarlayabilirsiniz.
Zarar durdurma fiyatını belirlerken kullanılacak çarpanı ayarlayabilirsiniz.
Cerca negli script per "Exponential Moving Average"
Combo 2/20 EMA & Bill Williams Averages. 3Lines This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
This indicator calculates 3 Moving Averages for default values of
13, 8 and 5 days, with displacement 8, 5 and 3 days: Median Price (High+Low/2).
The most popular method of interpreting a moving average is to compare
the relationship between a moving average of the security's price with
the security's price itself (or between several moving averages).
WARNING:
- For purpose educate only
- This script to change bars colors.
Grid Bot AutoThis script is an auto-adjusting grid bot simulator. This is an improved version of the original Grid Bot Simulator. The grid bot is best used for ranging/choppy markets. Prices are divided into grids, or trade zones, that will trigger signals each time a new zone is entered. During ranging markets, each transaction is followed by a “take profit.” As the market starts to trend, transactions are stacked (compare to DCA ), until the market consolidates. No signals are triggered above the Upper Limit or Below the Lower Limit. Unlike the previous version, the upper and lower limits are calculated automatically. Grid levels are determined by four factors: Smoothing, Laziness, Elasticity, and Grid Intervals.
Smoothing:
A moving average (or linear regression) is applied to each close price as a basis. Options for smoothing are Linear Regression, Simple Moving Average, Exponential Moving Average, Volume-Weighted Moving Average, Triple-Exponential Moving Average.
Laziness:
Laziness is the percentage change required to reach the next level. If laziness is 1.5, the price must move up or down by 1.5% before the grid will change. This concept is based on Alex Grover’s Efficient Trend Step. This allows the grids to be based on even price levels, as opposed to jagged moving averages.
Elasticity:
Elasticity is the degree of “stickiness” to the current price trend. If the smoothing line remains above (or below) the current grid center without reverting but still not enough to reach the next grid level, the grid line will start to curve toward the next grid level. Elasticity is added to (or subtracted from) the gridline by a factor of minimum system ticks for the current pair. Elasticity of zero will keep the gridlines horizontal. If elasticity is too high, the grid will distort.
Grid Intervals:
Grid intervals are the percentage of space between each grid.
Laziness = 4%, Elasticity = 0. Price must move at least 4% before reaching the next level. With zero elasticity, gridlines are straight.
Laziness = 5%, Elasticity = 100. For each bar at a new grid level, the grid will start “curve” toward the next price level (up if price is greater than the middle grid, down if less than middle grid). Elasticity is calculated by the user-inputted “Elasticity” multiplied by the minimum tick for the current pair (ELSTX = syminfo.mintick * iELSTX)
Try experimenting with different combinations of the Smoothing Length, Smoothing Type, Laziness, Elasticity, and Grid Intervals to find the optimum settings for each chart. Lower-priced pairs (e.g. XRP/ADA/DODGE) will require lower Elasticity. Also note that different exchanges may have different minimum tick values. For example, minimum tick for BITMEX:XBTUSD and BYBIT:BTCUSD is .5, but BINANCE:BTCUSDT and COINBASE:BTCUSD is .01.
s3.tradingview.com
DODGEUSDT, 5min. Laziness: 4%, Elasticity 2.5
Number of Grids: 2. Laziness: 3.75%. Elasticity: 150. Grid Interval 2%.
Settings Overview
Smoothing Length : Smoothing period
Smoothing Type : Linear Regression, Simple Moving Average, Exponential Moving Average, Volume-Weighted Moving Average, Triple-Exponential Moving Average
Laziness : Percentage required for price to move until it reaches the next level. If price does not reach the next level (up or down), the grid will remain the same as previous grid (because it’s lazy).
Elasticity : Amount of curvature toward the next grid, based on the current price trend. As elasticity increases, gridlines will curve up or down by a factor of the number of ticks since the last grid change.
Grid Interval : Percent between grid levels.
Number of Grids : Number of grids to show.
Cooldown : Number of bars to wait to prevent consecutive signals.
Grid Line Transparency : Lower transparencies brighten the gridlines; higher transparencies dim the gridlines. To hide the gridlines completely, enter 100.
Fill Transparency: Lower transparencies brighten the fill box; higher transparencies dim the fill box. To hide the fill box completely, enter 100.
Signal Size : Make signal triangles large or small.
Reset Buy/Sell Index When Grids Change : When a new grid is formed, resetting the index may prevent false signals (experimental)
Use Highs/Lows for Signals : If enabled, signals are triggered as soon as the price touches the next zone. If disabled, signals are triggered after bar closes. Enable this for “Once Per Bar alerts. Disable for “Once Per Bar Close” alerts.
Show Min Tick : If checked, syminfo.mintick is displayed in upper-righthand corner. Useful for estimating Laziness.
Reverse Fill Colors : Default fill for fill boxes is green after buy and red after sell. Check this box to reverse.
Note: The Grid Bot Simulator scripts are experimental and works in progress. Please feel free to comment or contact me if you have suggestions/complaints.
6 EMA SMA RMA + ForecastingDescription:
Hey hi, this Script is a bit simple. Let's start with some definitions.
Moving Average (MA)
In statistics, a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set. In finance, a moving average (MA) is a stock indicator that is commonly used in technical analysis . The reason for calculating the moving average of a stock is to help smooth out the price data by creating a constantly updated average price . This makes this tool one of the most important for technical analysis .
Forecasting
Forecasting is the process of making predictions based on past and present data and most commonly by analysis of trends . In the same way that the moving average (MA) the forecasting is something highly desirable, in this way we opted to develop an indicator that allows the use of up to 6 moving averages combined with the forecasting.
In addition to having the option of up to 6 moving averages, these can be of different types, being able to choose between up to 3 options (it is proposed to add more options later) which are listed below.
Exponential Moving Average ( EMA )
Simple Moving Average ( SMA )
Running Moving Average (RMA)
In addition to the above, 2 prediction methods were added, which are listed and detailed below.
Repetition. Makes forecast repeating the last candle M times.
Linear Regression ( LR ). Linear Regression does N period LR forecast averaged with length-N Moving Average
Anticipated Simple Moving Average Crossover IndicatorIntroducing the Anticipated Simple Moving Average Crossover Indicator
This is my Pinescript implementation of the Anticipated Simple Moving Average Crossover Indicator
Much respect to the original creator of this idea Dimitris Tsokakis
This indicator removes one bar of lag from simple moving average crossover signals with a high degree of accuracy to give a slight but very real edge.
Moving Averages
A moving average simplifies price data by smoothing it out by averaging closing prices and creating one flowing line which makes seeing the trend easier.
Moving averages can work well in strong trending conditions, but poorly in choppy or ranging conditions.
Adjusting the time frame can remedy this problem temporarily, although at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
While Exponential moving averages react quicker to price changes than simple moving averages. In some cases, this may be good, and in others, it may cause false signals.
Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look back period (200 days).
Trading Strategies — Moving Average Crossovers
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance.
The first type is a price crossover, which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up. This is known as a "golden cross."
Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down. This is known as a "dead/death cross."
MA and MA Cross Strategy Disadvantages
Moving averages are calculated based on historical data, and while this may appear predictive nothing about the calculation is predictive in nature.
Moving averages are always based on historical data and simply show the average price over a certain time period.
Therefore, results using moving averages can be quite random.
At times, the market seems to respect MA support/resistance and trade signals, and at other times, it shows these indicators no respect.
One major problem is that, if the price action becomes choppy, the price may swing back and forth, generating multiple trend reversal or trade signals.
When this occurs, it's best to step aside or utilize another indicator to help clarify the trend.
The same thing can occur with MA crossovers when the MAs get "tangled up" for a period of time during periods of consolidation, triggering multiple losing trades.
Ensure you use a robust risk management system to avoid getting "Chopped Up" or "Whip Sawed" during these periods.
Profit Maximizer StrategyFirst I would like to thank to @KivancOzbilgic for developing this indicator.
All the credit goes to him.
I just created a strategy, in order to try to find the perfect parameters, timeframe and currency for it.
I will provide below the same description like he has in the publish of profit maximizer
Profit Maximizer - PMax combines the powerful sides of MOST (Moving Average Trend Changer) and SuperTrend (ATR price detection) in one indicator.
Backtest and optimization results of PMax are far better when compared to its ancestors MOST and SuperTrend. It reduces the number of false signals in sideways and give more reliable trade signals.
PMax is easy to determine the trend and can be used in any type of markets and instruments. It does not repaint.
The first parameter in the PMax indicator set by the three parameters is the period/length of ATR.
The second Parameter is the Multiplier of ATR which would be useful to set the value of distance from the built in Moving Average.
I personally think the most important parameter is the Moving Average Length and type.
PMax will be much sensitive to trend movements if Moving Average Length is smaller. And vice versa, will be less sensitive when it is longer.
As the period increases it will become less sensitive to little trends and price actions.
In this way, your choice of period, will be closely related to which of the sort of trends you are interested in.
We are under the effect of the uptrend in cases where the Moving Average is above PMax;
conversely under the influence of a downward trend, when the Moving Average is below PMax.
Built in Moving Average type defaultly set as EMA but users can choose from 8 different Moving Average types like:
SMA : Simple Moving Average
EMA : Exponential Movin Average
WMA : Weighted Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average aka VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
Tip: In sideways VAR would be a good choice
You can use PMax default alarms and Buy Sell signals like:
1-
BUY when Moving Average crosses above PMax
SELL when Moving Average crosses under PMax
2-
BUY when prices jumps over PMax line.
SELL when prices go under PMax line.
[LunaOwl] 11 kinds of Adaptive MA Model作品: 11種自適應性平滑模型
It integrates eleven kinds of adaptive moving average method. At first, I just wanted to make a ATR. Later, the price series ±N*ATR mult, to form two series. Then use the concept of support/resistance breakthrough to design it, and then two adaptive series formation channels were formed. Take the average of the two series as the signal. When the price crosses the signal, it's judged to be long or short.
整合了十一種能夠自適應性的移動平均模型。起初只是想要做一個基本款ATR指標，後來將價格加減N個ATR倍數，形成兩條序列形成通道，再使用支撐阻力突破的概念去設計它，再形成兩條自適應性的序列形成通道，再取中間值當成信號。當價格與信號交叉，則判斷作多或者作空。
--------------------------*
Parameter 設置參數
Resolution: The default is "the same as the variety". Is a named constant for resolution input type of input function.
商品分辨率：預設與品種相同。是input函數的時間周期輸入類型的命名常量。
Smoothing: The default is Recursive Moving Average(RMA). It can choose other methods, the table is as follows.
平滑類型：預設是「遞回平均」，可以選擇其它方法，列表如下。
列表 / The table of moving averages is as follows:
//****中英對照表*****##______________________________________
1. 遞回平均 || Recursive Moving Average
2. 簡單平均 || Simple Moving Average
3. 指數平均 || Exponential Moving Average
4. 加權平均 || Weighted Moving Average
5. 船體平均 || Hull Moving Average
6. 成交量加權 || Volume Weighted Moving Average
7. 對稱加權 || Symmetric Weighted Moving Average
8. 雙重指數 || Double Exponential Moving Average
9. 三重指數 || Triple Exponential Moving Average
10. 高斯分佈 || Arnaud Legoux Moving Average
11. 提爾森T3 || Tillson T3 Moving Average
//##_________________________________________________________
Candle Mode: There are three versions, original, two-color and four-color.
燭台模式：預設模式只區分趨勢，可以改成原版蠟燭或四種顏色版本。
Length: The default is 14, usually no need to adjust.
平滑期數：預設值是14，基本上不用理它。
Occurrence: The default is 1. The range is 0~10. The larger the value, the more delayed. If zero will become too sensitive and noise.
滯後性：預設值是1。調整範圍是0~10，數值愈大信號愈延遲，如果值為0，會變得過於敏捷，那將會失去平滑的意義。
N multiple: The default is 0.618, can be set to 1. The range is 0.382~3.000.
倍數N：預設值是0.618，也可以設定1，最低是0.382，最大是3。
--------------------------*
1. Candle Mode can set the original candle, cancel candle trend color changes. However, the background will still be filled.
可以設定顯示原版的蠟燭線，背景與線並不會消失。
2. Four-color version of candles. It shows changes in trends and prices.
四色版本的蠟燭線，可以顯示趨勢與每日收盤價的變化。
6 Moving Averages with MTF v1.0This indicator is a collection of 6 different period Moving Averages. It has support for different time-frame resolution for all of them individually.
Also, it has 11 different type of Moving Average calculation functions:
1. Simple Moving Average (SMA)
2. Exponential Moving Average (EMA)
3. Weighted Moving Average (WMA)
4. Volume Weighted Moving Average (VWMA)
5. Smoothed Moving Average (SMMA)
6. Double Exponential Moving Average (DEMA)
7. Triple Exponential Moving Average (TEMA)
8. Hull WMA Moving Average (HullMA)
9. Triangular Moving Average (TMA)
10. Super Smoother Moving Average (SSMA)
11. Zero Lag Exponential Moving Average (ZEMA)
Note: The Moving Average calculation function is adapted from @JustUncleL
Happy trading 😉
Thank you.
Coding ema in pinescriptWhat is EMA ?
Ema is known as exponential moving average, it comes from the class of weighted moving average. It gives more weightage to the recent price changes, thus making it much more relevant to the current market analysis. Also it provides a dynamic way of calculating support and resistances in a trend following setup.
The most common way to mint profit out from the market is to use trend following setups which can be easily achieved by using a group of EMA’s
So how’s this EMA calculated ?
Before understanding the calculation of EMA let’s look into a much wider topic:
“The Law of Averages”
It states : If you do something often enough a ratio will appear, simply put, any time series data, tend to deviate from its average.
EMA provides a way to statistically calculate the exponential moving average for a provided time series data giving much more emphasis on the most recent data in the series.
So in the 17th century, when the people were playing with numbers in their free time, they came up with a statistical strategy to envelop any time series data to detect the direction of the data flow , they called it exponential moving average.
Later in 1940’s with the increase in signal processing requirements in the field of electronic devices scientists started using Exponential moving average onto the electronic signal followers, just to classify the signals as above or below a moving/dynamic threshold.
So EMA is a smoothed time-series data.
The simplest form of EMA Smoothing can be given by the formula:
S(t) = alpha * X(t) + (1 - alpha) * X(t - 1).
The value of alpha must lie between 0 and 1
Where
alpha , is the smoothing factor
X(t) , is the current observation data point
X(t - 1), is the past observational data point.
t , is the current time
Generally,
In current day trading setups for EMA the alpha is calculated by
alpha = 2 / (time period window + 1)
Things to note here is that the alpha calculated above is the most generally used factor calculation method for EMA ,
You can tweak the alpha function above until it gives value between 0 and 1 for example alpha can also be written as
alpha = ln ( current price / past price )
Note it’s just a weighing scheme,
But for Our Case of EMA
We will be using
alpha = 2 / (time period window + 1)
Please refer to the script code below
CM_Ultimate_MA_MTF_v7 IndicatorUpgraded CM_Ultimate_MA_MTF_V2 - Added Tilson T3
Defaults to Current Timeframe on Chart.
Ability to Plot 2nd Moving Average.
Ability to set Moving Averages to Custom Chart TimeFrame. Example Daily Ma on 60 Minute chart. Many Different Options from Weekly to 1 Minute.
Ability to Plot Cross where Moving Averages Cross (If using 2nd Moving Average).
Ability to Plot Highlight Bars when Price Crosses 1st Moving Average, or 2nd MA.
Moving Averages Supported in Inputs Tab
SMA - Simple Moving Average
EMA - Exponential Moving Average
WMA - Weighted Moving Average
HullMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
RMA - Moving Average used in RSI - Similar to EMA
TEMA - Triple Exponential Moving Average
Tilson T3 - Tilson T3 Moving Average
CM_Ultimate_MA_MTF_V2 strategyUpgraded CM_Ultimate_MA_MTF_V2 - Added Tilson T3
Defaults to Current Timeframe on Chart.
Ability to Plot 2nd Moving Average.
Ability to set Moving Averages to Custom Chart TimeFrame. Example Daily Ma on 60 Minute chart. Many Different Options from Weekly to 1 Minute.
Ability to Plot Cross where Moving Averages Cross (If using 2nd Moving Average).
Ability to Plot Highlight Bars when Price Crosses 1st Moving Average, or 2nd MA.
Moving Averages Supported in Inputs Tab
SMA - Simple Moving Average
EMA - Exponential Moving Average
WMA - Weighted Moving Average
HullMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
RMA - Moving Average used in RSI - Similar to EMA
TEMA - Triple Exponential Moving Average
Tilson T3 - Tilson T3 Moving Average
Relative Strength Index of Moving AveragePine script version 3
Author CryptoJoncis
RSIOMA is the abbreviation for Relative Strength index (RSI) of moving averages (MA). This custom built indicator is based on calculating the relative strength of two moving averages and the smoothes out the RSI using a moving average. Combined, the RSIOMA oscillator depicts trend changes in prices relative to the time frame. The RSIOMA can be used as a signal generator by itself. (www.ProfitF.com)
There are some minor things which you can use to modify this version of RSIOMA:
Choose 2 levels of Over Sold and Over Bought for RSI
Set the middle level to easier visualize the trend
Set x% wider MA line to avoid too many fake signals and gain higher precision
You can choose which MA would you like to use from the following list:
Tillson Moving Average (T3)
Double Exponential Moving Average ( DEMA )
Arnaud Legoux Moving Average ( ALMA )
Least Squares Moving Average ( LSMA )
Simple Moving Average ( SMA )
Exponential Moving Average ( EMA )
Weighted Moving Average ( WMA )
Smoothed Moving Average ( SMMA )
Triple Exponential Moving Average ( TEMA )
Hull Moving Average ( HMA )
Adaptive moving average (AMA)
Fractal Adaptive Moving Average (FAMA)
Variable Index Dynamic Average ( VIDYA )
Triangular Moving Average (TRIMA)
Any questions/suggestions/errors or spelling mistakes? Please leave a comment and let me know.
You can use,publish,modify this code in any way as you wish, but only if you reference me after.
You are not allowed to sell it as it is.
If this code is useful to you, then consider to buy me a coffee 2.17% (or better a pint of beer) by donating Bitcoin 0.64% or Etherium to:
BTC: 3FiBnveHo3YW6DSiPEmoCFCyCnsrWS3JBR
ETH: 0xac290B4A721f5ef75b0971F1102e01E1942A4578
References:
www.profitf.com
CM_Ultimate_MA_MTF_V2CM_Ultimate_MA_MTF_V2 - Added Tilson T3
Defaults to Current Timeframe on Chart.
Ability to Plot 2nd Moving Average.
Ability to set Moving Averages to Custom Chart TimeFrame. Example Daily Ma on 60 Minute chart. Many Different Options from Weekly to 1 Minute.
Ability to Plot Cross where Moving Averages Cross (If using 2nd Moving Average).
Ability to Plot Highlight Bars when Price Crosses 1st Moving Average, or 2nd MA.
Moving Averages Supported in Inputs Tab
SMA - Simple Moving Average
EMA - Exponential Moving Average
WMA - Weighted Moving Average
HullMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
RMA - Moving Average used in RSI - Similar to EMA
TEMA - Triple Exponential Moving Average
Tilson T3 - Tilson T3 Moving Average
Twiggs Go Money Flow Enhanced [KingThies]█ OVERVIEW
The Twiggs Money Flow (TMF) is a volume-weighted momentum oscillator that
measures buying and sellistng pressure by analyzing where price closes within
each bar's true range. It's an enhanced version of Chaikin Money Flow that
uses Wilder's smoothing method, providing better trend persistence and
smoother signals.
The indicator oscillates around a zero listne:
Values above zero indicate accumulation (buying pressure)
Values below zero indicate distribution (sellistng pressure)
TMF was developed by Colistn Twiggs as an improvement over traditional money
flow indicators by incorporating true range calculations and Wilder's
exponential moving average.
█ CONCEPTS
True Range Boundaries
TMF calculates a modified true range for each bar by comparing the current
bar's high and low with the previous close:
True Range High = maximum of (previous close, current high)
True Range Low = minimum of (previous close, current low)
This accounts for overnight gaps and ensures price continuity between bars.
Average Daily Value (ADV)
The ADV represents the portion of volume attributable to buying versus sellistng:
ADV = Volume × ((Close - TR Low) - (TR High - Close)) / True Range
When price closes near the high of the true range, ADV is positive and large.
When price closes near the low, ADV is negative and large.
A close in the middle produces values near zero.
Wilder's Moving Average
Unlistke simple moving averages, Wilder's smoothing method gives more weight
to recent values while maintaining memory of historical data:
WMA = (Previous WMA × (Period - 1) + Current Value) / Period
This creates smoother trends that are less prone to whipsaws than standard
moving averages.
Final Calculation
TMF = Wilder's MA(ADV, Period) / Wilder's MA(Volume, Period)
By dividing smoothed ADV by smoothed volume, TMF normalistzes the reading and
makes it comparable across different securities and timeframes.
█ HOW TO USE
Zero listne Crossovers
The most straightforward trading signals:
A cross above zero suggests buyers are gaining control.
Consider this a bullistsh signal, especially when confirmed by price action.
A cross below zero suggests sellers are gaining control.
Consider this a bearish signal.
The longer TMF remains above or below zero, the stronger the trend.
Extreme Values
Strong positive or negative readings indicate intense buying or sellistng pressure:
Sustained high positive values (above +0.4) suggest strong accumulation
but may also indicate overbought conditions.
Sustained low negative values (below -0.4) suggest strong distribution
but may also indicate oversold conditions.
These extremes work best when used in conjunction with price levels and
support/resistance zones.
Divergences
Divergences between price and TMF often signal potential reversals:
Bearish divergence: Price makes a higher high but TMF makes a
lower high — suggests buying pressure is weakening despite rising prices.
Bullistsh divergence: Price makes a lower low but TMF makes a
higher low — suggests sellistng pressure is weakening despite fallistng prices.
Trend Confirmation
Use TMF to confirm the strength of existing trends:
In an uptrend, TMF should remain mostly positive with occasional dips below zero.
In a downtrend, TMF should remain mostly negative with occasional rises above zero.
If TMF contradicts the price trend, consider the trend weak or potentially ending.
█ FEATURES
Period (default: 21)
The lookback length for Wilder's moving average calculation:
Shorter periods (10–15) make TMF more responsive to recent changes but
increase noise and false signals.
Longer periods (30–50) create smoother readings but lag price action more
significantly.
The default 21-period setting balances responsiveness with relistabilistty.
Consider adjusting the period based on your trading timeframe and the
volatilistty of the security you're analyzing.
█ LIMITATIONS
TMF is a lagging indicator due to its smoothing method. Signals may occur
after optimal entry or exit points.
In low-volume or illistquid markets, TMF can produce erratic readings that
may not reflect true buying or sellistng pressure.
Ranging or choppy markets often generate frequent zero-listne crosses that
can lead to whipsaws.
listke all volume-based indicators, TMF's relistabilistty depends on accurate
volume data.
For securities with unrelistable volume reporting, consider using
price-based momentum indicators instead.
█ NOTES
This indicator uses area-style plotting in the original version to visualistze
the magnitude of buying and sellistng pressure. The filled area makes it easy
to see at a glance whether the market is in accumulation or distribution mode.
TMF works on any timeframe but tends to be most relistable on daily charts
where volume data is most accurate and meaningful.
█ CREDITS
Original indicator developed by
LazyBear .
Based on the Twiggs Money Flow concept from Incredible Charts:
Incredible Charts – Twiggs Money Flow .
SFC Bollinger Band and Bandit概述 (Overview)
SFC 布林通道與海盜策略 (SFC Bollinger Band and Bandit Strategy) 是一個基於 Pine Script™ v6 的技術分析指標，結合布林通道 (Bollinger Bands)、移動平均線 (Moving Averages) 以及布林海盜 (Bollinger Bandit) 交易策略，旨在為交易者提供多時間框架的趨勢分析與進出場訊號。該腳本支援風險管理功能，並提供視覺化圖表與交易訊號提示，適用於多種金融市場。
This script, written in Pine Script™ v6, combines Bollinger Bands, Moving Averages, and the Bollinger Bandit strategy to provide traders with multi-timeframe trend analysis and entry/exit signals. It includes risk management features and visualizes data through charts and trading signals, suitable for various financial markets.
功能特點 (Key Features)
布林通道 (Bollinger Bands)
提供可調整的標準差參數 (σ1, σ2)，支援多層布林通道顯示。
進場訊號基於價格穿越布林通道上下軌，並結合連續K線確認機制。
Provides adjustable standard deviation parameters (σ1, σ2) for multi-layer Bollinger Bands display.
Entry signals are based on price crossing the upper/lower bands, combined with a consecutive bar confirmation mechanism.
移動平均線 (Moving Averages)
支援簡單移動平均線 (SMA) 或指數移動平均線 (EMA)，可自訂快、中、慢線週期。
Supports Simple Moving Average (SMA) or Exponential Moving Average (EMA) with customizable fast, medium, and slow line periods.
布林海盜策略 (Bollinger Bandit Strategy)
基於變動率 (ROC) 與布林通道動態止損，提供做多與做空訊號。
包含動態止損均線與平倉天數設定，增強交易靈活性。
Utilizes Rate of Change (ROC) and Bollinger Bands with dynamic stop-loss for long and short signals.
Includes dynamic stop-loss moving average and liquidation days for enhanced trading flexibility.
多時間框架分析 (Multi-Timeframe Analysis)
支援六個時間框架 (5分、15分、1小時、4小時、日線、週線) 的趨勢分析。
通過表格顯示各時間框架的連續上漲/下跌趨勢，輔助交易決策。
Supports trend analysis across six timeframes (5m, 15m, 1h, 4h, daily, weekly).
Displays consecutive up/down trends in a table to aid decision-making.
風險管理 (Risk Management)
提供基於 ATR 或布林通道的停利/停損設定。
自動計算交易手數，根據報價貨幣匯率調整風險敞口。
Offers take-profit/stop-loss settings based on ATR or Bollinger Bands.
Automatically calculates trading lots, adjusting risk exposure based on quote currency exchange rates.
視覺化與提示 (Visualization and Alerts)
繪製布林通道、移動平均線、海盜策略動態止損線及交易訊號。
提供多時間框架趨勢表格、交易手數標籤及浮水印。
支援交易訊號快訊，方便即時監控。
Plots Bollinger Bands, Moving Averages, Bandit strategy stop-loss lines, and trading signals.
Includes multi-timeframe trend tables, trading lot labels, and watermark.
Supports alert conditions for real-time trade monitoring.
使用說明 (Usage Instructions)
設置參數 (Parameter Setup)
布林通道 (Bollinger Bands): 可調整週期 (預設21)、標準差 (σ1=1, σ2=2) 及停利/停損依據 (ATR 或 BAND)。
移動平均線 (Moving Averages): 可選擇顯示快線 (10)、中線 (20)、慢線 (60)，並切換 SMA/EMA。
布林海盜 (Bollinger Bandit): 調整通道週期 (50)、平倉均線週期 (50) 及 ROC 週期 (30)。
時間框架 (Timeframes): 自訂六個時間框架，預設為 5分、15分、1小時、4小時、日線、週線。
Adjust Bollinger Band period (default 21), standard deviations (σ1=1, σ2=2), and take-profit/stop-loss basis (ATR or BAND).
Configure Moving Averages (fast=10, medium=20, slow=60) and toggle SMA/EMA.
Set Bollinger Bandit parameters: channel period (50), liquidation MA period (50), ROC period (30).
Customize six timeframes (default: 5m, 15m, 1h, 4h, daily, weekly).
交易訊號 (Trading Signals)
買入訊號 (Buy): 價格穿越下軌且滿足連續K線條件。
賣出訊號 (Sell): 價格穿越上軌且滿足連續K線條件。
海盜策略訊號: 基於 ROC 與布林通道穿越，結合動態止損。
Buy signal: Price crosses below lower band with consecutive bar confirmation.
Sell signal: Price crosses above upper band with consecutive bar confirmation.
Bandit strategy signals: Based on ROC and band crossings with dynamic stop-loss.
視覺化 (Visualization)
布林通道以不同顏色顯示上下軌與中軌。
移動平均線以快、中、慢線區分顏色。
趨勢表格顯示各時間框架的趨勢狀態 (🔴上漲, 🟢下跌, ⚪中性)。
海盜策略顯示動態止損線與交易狀態。
Bollinger Bands display upper, lower, and middle bands in distinct colors.
Moving Averages use different colors for fast, medium, and slow lines.
Trend table shows timeframe trends (🔴 up, 🟢 down, ⚪ neutral).
Bandit strategy displays dynamic stop-loss and trading status.
Turtle Strategy - Triple EMA Trend with ADX and ATRDescription
The Triple EMA Trend strategy is a directional momentum system built on the alignment of three exponential moving averages and a strong ADX confirmation filter. It is designed to capture established trends while maintaining disciplined risk management through ATR-based stops and targets.
Core Logic
The system activates only under high-trend conditions, defined by the Average Directional Index (ADX) exceeding a configurable threshold (default: 43).
A bullish setup occurs when the short-term EMA is above the mid-term EMA, which in turn is above the long-term EMA, and price trades above the fastest EMA.
A bearish setup is the mirror condition.
Execution Rules
Entry:
• Long when ADX confirms trend strength and EMA alignment is bullish.
• Short when ADX confirms trend strength and EMA alignment is bearish.
Exit:
• Stop Loss: 1.8 × ATR below (for longs) or above (for shorts) the entry price.
• Take Profit: 3.3 × ATR in the direction of the trade.
Both parameters are configurable.
Additional Features
• Start/end date inputs for controlled backtesting.
• Selective activation of long or short trades.
• Built-in commission and position sizing (percent of equity).
• Full visual representation of EMAs, ADX, stop-loss, and target levels.
This strategy emphasizes clean trend participation, strict entry qualification, and consistent reward-to-risk structure. Ideal for swing or medium-term testing across trending assets.
T3 ATR [DCAUT]█ T3 ATR
📊 ORIGINALITY & INNOVATION
The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output.
This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation.
The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations.
📐 MATHEMATICAL FOUNDATION
The T3 ATR calculation process involves two distinct stages:
Stage 1: True Range Calculation
The True Range (TR) is calculated using the standard formula:
TR = max(high - low, |high - close |, |low - close |)
This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves.
Stage 2: T3 Smoothing Application
The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession:
First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period)
Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period)
Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period)
Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter:
a = VF / 2
c1 = -a³
c2 = 3a² + 3a³
c3 = -6a² - 3a - 3a³
c4 = 1 + 3a + a³ + 3a²
The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness:
Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise
Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag
📊 COMPREHENSIVE SIGNAL ANALYSIS
Volatility Level Interpretation:
High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events
Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods
Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk
Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies
Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies
Volume Factor Impact on Signals:
Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations
Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading
High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis
🎯 STRATEGIC APPLICATIONS
Position Sizing Strategy:
Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience)
Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values)
Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR
Calculate position size: Position Size = (Account × Risk %) / Stop Distance
Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point
Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses)
Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading
Dynamic Stop-Loss Placement:
Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR)
For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value)
For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value)
Trail stop-losses by recalculating based on current T3 ATR as the trade progresses
Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops
Market Regime Identification:
Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA)
High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets
Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure
Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion
Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early
Risk Management Implementation:
Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital)
For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR)
When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position)
When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position)
This approach maintains constant dollar risk per trade regardless of market volatility changes
Use consistent volume factor settings across all positions to ensure uniform risk measurement
📋 DETAILED PARAMETER CONFIGURATION
ATR Length Parameter:
Default Setting: 14 periods
This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes
Selection Principles:
Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings
Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes
The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument
Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods
Practical Approach:
Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions
If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes
If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response
Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range
Test different periods using historical data for your specific instrument and strategy before committing to live trading
T3 Volume Factor Parameter:
Default Setting: 0.7
This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles
Understanding the Volume Factor:
Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering
Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly
The trade-off is between immediacy and stability - there is no universally optimal setting
Selection Principles:
Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF
Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response
Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay
Practical Adjustment Guidelines:
Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions
If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing
If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response
Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice
Test adjustments in simulation or paper trading before applying to live positions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments.
Signal Stability:
Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations.
Comparison with Standard ATR:
Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement
Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments
Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy
Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications
Suitable Use Cases:
T3 ATR is well-suited for the following scenarios:
Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions
Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading)
Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions
Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments
Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection
Known Limitations:
Like all technical indicators, T3 ATR has limitations that users should understand:
Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty
Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions
Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed
Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds
Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis
Performance Expectations:
T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied:
It can help reduce position risk during volatile periods through appropriate position sizing
It can help identify optimal times for more aggressive position sizing during stable periods
It can improve stop-loss placement by adapting to current market conditions
It can assist in strategy selection by identifying volatility regimes
However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology.
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms.
Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
MAMA [DCAUT]█ MAMA (MESA Adaptive Moving Average)
📊 OVERVIEW
The MESA Adaptive Moving Average (MAMA) represents an advanced implementation of John F. Ehlers' adaptive moving average system using the Hilbert Transform Discriminator. This indicator automatically adjusts to market cycles, providing superior responsiveness compared to traditional fixed-period moving averages while maintaining smoothness.
MAMA dynamically calculates two lines: the fast-adapting MAMA line and the following FAMA (Following Adaptive Moving Average) line. The system's core strength lies in its ability to automatically detect and adapt to the dominant market cycle, reducing lag during trending periods while providing stability during consolidation phases.
🎯 CORE CONCEPTS
Signal Interpretation:
• MAMA above FAMA: Indicates bullish trend momentum with the fast line leading upward movement
• MAMA below FAMA: Suggests bearish trend momentum with the fast line leading downward movement
• Golden Cross: MAMA crossing above FAMA signals potential upward momentum shift
• Death Cross: MAMA crossing below FAMA indicates potential downward momentum shift
• Line Convergence: MAMA and FAMA approaching each other suggests trend consolidation or potential reversal
Primary Applications:
• Trend Following: Enhanced responsiveness to trend changes compared to traditional moving averages
• Crossover Signals: MAMA/FAMA crossovers for identifying potential entry and exit points
• Cycle Analysis: Automatic adaptation to market's dominant cycle characteristics
• Reduced Lag: Minimized delay in trend detection while maintaining signal smoothness
📐 MATHEMATICAL FOUNDATION
Hilbert Transform Discriminator Technology:
The MAMA system employs John F. Ehlers' Hilbert Transform Discriminator, a sophisticated signal processing technique borrowed from telecommunications engineering. The Hilbert Transform creates a complex representation of the price series by generating a 90-degree phase-shifted version of the original signal, enabling precise cycle measurement.
The discriminator analyzes the instantaneous phase relationships between the original price series and its Hilbert Transform counterpart. This mathematical relationship reveals the dominant cycle period present in the market data at each point in time, forming the foundation for adaptive smoothing.
Instantaneous Period Calculation:
The algorithm computes the instantaneous period using the arctangent of the ratio between the Hilbert Transform and the original price series. This calculation produces a real-time measurement of the market's dominant cycle, typically ranging from short-term noise cycles to longer-term trend cycles.
The instantaneous period measurement undergoes additional smoothing to prevent erratic behavior from single-bar anomalies. This smoothed period value becomes the basis for calculating the adaptive alpha coefficient that controls the moving average's responsiveness.
Dynamic Alpha Coefficient System:
The adaptive alpha calculation represents the core mathematical innovation of MAMA. The alpha coefficient is derived from the instantaneous period measurement and constrained within the user-defined fast and slow limits.
The mathematical relationship converts the measured cycle period into an appropriate smoothing factor: shorter detected cycles result in higher alpha values (increased responsiveness), while longer cycles produce lower alpha values (increased stability). This creates an automatic adaptation mechanism that responds to changing market conditions.
MAMA/FAMA Calculation Process:
The MAMA line applies the dynamically calculated alpha coefficient to an exponential moving average formula: MAMA = alpha × Price + (1 - alpha) × MAMA . The FAMA line then applies a secondary smoothing operation to the MAMA line, creating a following average that provides confirmation signals.
This dual-line approach ensures that the fast-adapting MAMA line captures trend changes quickly, while the FAMA line offers a smoother confirmation signal, reducing the likelihood of acting on temporary price fluctuations.
Cycle Detection Mechanism:
The underlying cycle detection employs quadrature components derived from the Hilbert Transform to measure both amplitude and phase characteristics of price movements. This allows the system to distinguish between genuine trend changes and temporary price noise, automatically adjusting the smoothing intensity accordingly.
The mathematical framework ensures that during strong trending periods with clear directional movement, the algorithm reduces smoothing to minimize lag. Conversely, during consolidation phases with mixed signals, increased smoothing helps filter out false breakouts and whipsaws.
📋 PARAMETER CONFIGURATION
Source Selection Strategy:
• HL2 (High+Low)/2 (Default): Recommended for cycle analysis as it represents the midpoint of each period's trading range, reducing impact of opening gaps and closing spikes
• Close Price: Traditional choice reflecting final market sentiment, suitable for end-of-day analysis
• HLC3 (High+Low+Close)/3: Balanced approach incorporating range information with closing emphasis
• OHLC4 (Open+High+Low+Close)/4: Most comprehensive price representation for complete market view
Fast Limit Configuration (Default 0.5):
Controls the maximum responsiveness of the adaptive system. Higher values increase sensitivity to recent price changes but may introduce more noise. This parameter sets the upper bound for the dynamic alpha calculation.
Slow Limit Configuration (Default 0.05):
Determines the minimum responsiveness, providing stability during uncertain market conditions. Lower values increase smoothing but may cause delayed signals. This parameter sets the lower bound for the dynamic alpha calculation.
Parameter Relationship Considerations:
The fast and slow limits work together to define the adaptive range. The wider the range between these limits, the more dramatic the adaptation between trending and consolidating market conditions. Different market characteristics may benefit from different parameter configurations, requiring individual testing and validation.
📊 COLOR CODING SYSTEM
Line Visualization:
• Green Line (MAMA): The fast-adapting moving average that responds quickly to price changes
• Red Line (FAMA): The following adaptive moving average that provides confirmation signals
The fixed color scheme provides consistent visual identification of each line, enabling clear differentiation between the fast-adapting MAMA and the following FAMA throughout all market conditions.
💡 CORE VALUE PROPOSITION
Advantages Over Traditional Moving Averages:
• Cycle Adaptation: Automatically adjusts to market's dominant cycle rather than using fixed periods
• Reduced Lag: Faster response to genuine trend changes while filtering market noise
• Mathematical Foundation: Based on advanced signal processing techniques from telecommunications engineering
• Dual-Line System: Provides both fast adaptation (MAMA) and confirmation (FAMA) in one indicator
Comparative Performance Characteristics:
Unlike fixed-period moving averages that apply the same smoothing regardless of market conditions, MAMA adapts its behavior based on current market cycle characteristics. This may help reduce whipsaws during consolidation periods while maintaining responsiveness during trending phases.
Usage Considerations:
This indicator is designed for technical analysis purposes. The adaptive nature means that parameter optimization should consider the specific characteristics of the asset and timeframe being analyzed. Like all technical indicators, MAMA should be used as part of a comprehensive analysis approach rather than as a standalone signal generator.
Alert Functionality:
The indicator includes alert conditions for MAMA/FAMA crossovers, enabling automated notification of potential momentum shifts. These alerts can assist in timing analysis but should be combined with other forms of market analysis for decision-making purposes.
Signal Hunter Pro - GKDXLSignal Hunter Pro - GKDXL combines four powerful technical indicators with trend strength filtering and volume confirmation to generate reliable BUY/SELL signals. This indicator is perfect for traders who want a systematic approach to market analysis without the noise of conflicting signals.
🔧 Core Features
📈 Multi-Indicator Signal System
Moving Averages: EMA 20, EMA 50, and SMA 200 for trend analysis
Bollinger Bands: Dynamic support/resistance with price momentum detection
RSI: Enhanced RSI logic with smoothing and multi-zone analysis
MACD: Traditional MACD with signal line crossovers and zero-line analysis
🎛️ Advanced Filtering System
ADX Trend Strength Filter: Only signals when trend strength exceeds threshold
Volume Confirmation: Ensures signals occur with adequate volume participation
Multi-Timeframe Logic: Works on any timeframe from 1m to 1D and beyond
🚨 Intelligent Signal Generation
Requires 3 out of 4 indicators to align for signal confirmation
Separate bullish and bearish signal conditions
Real-time signal strength scoring (1/4 to 4/4)
Built-in alert system for automated notifications
⚙️ Customizable Parameters
📊 Technical Settings
Moving Averages: Adjustable EMA and SMA periods
Bollinger Bands: Configurable length and multiplier
RSI: Customizable length, smoothing, and overbought/oversold levels
MACD: Flexible fast, slow, and signal line settings
🎯 Risk Management
Risk Percentage: Set your risk per trade (0.1% to 10%)
Reward Ratio: Configure risk-to-reward ratios (1:1 to 1:5)
ADX Threshold: Control minimum trend strength requirements
🖥️ Display Options
Indicator Visibility: Toggle individual indicators on/off
Information Table: Optional detailed status table (off by default)
Volume Analysis: Real-time volume vs. average comparison
🎨 Visual Elements
📈 Chart Indicators
EMA Lines: Blue (20) and Orange (50) exponential moving averages
SMA 200: Gray long-term trend line
Bollinger Bands: Upper/lower bands with semi-transparent fill
Clean Interface: Minimal visual clutter for clear analysis
📋 Information Table (Optional)
Real-time indicator status with ✓/✗/— symbols
Current signal strength and direction
ADX trend strength measurement
Volume confirmation status
No-signal reasons when conditions aren't met
🔔 Alert System
📢 Three Alert Types
BUY Signal: Triggered when 3+ indicators align bullishly
SELL Signal: Triggered when 3+ indicators align bearishly
General Alert: Any signal detection for broader monitoring
📱 Alert Messages
Clear, actionable alert text
Includes indicator name for easy identification
Compatible with webhook integrations
🎯 How It Works
📊 Signal Logic
Indicator Assessment: Each of the 4 indicators is evaluated as Bullish/Bearish/Neutral
Consensus Building: Counts aligned indicators (minimum 3 required)
Filter Application: Applies trend strength and volume filters
Signal Generation: Generates BUY/SELL when all conditions are met
🔍 Indicator States
Moving Averages: Price position, EMA alignment, and crossovers
Bollinger Bands: Price relative to bands and momentum shifts
RSI: Multi-zone analysis with momentum and crossover detection
MACD: Signal line crossovers and zero-line positioning
🎉 Why Choose Signal Hunter Pro?
✅ Multi-Indicator Confirmation reduces false signals
✅ Trend Strength Filtering improves win rate
✅ Volume Confirmation ensures market participation
✅ Customizable Parameters adapt to any trading style
✅ Clean Visual Design doesn't clutter your charts
✅ Professional Alert System for automated trading
✅ No Repainting - reliable historical signals
✅ Works on All Timeframes from scalping to investing
RSI-GringoRSI-Gringo — Stochastic RSI with Advanced Smoothing Averages
Overview:
RSI-Gringo is an advanced technical indicator that combines the concept of the Stochastic RSI with multiple smoothing options using various moving averages. It is designed for traders seeking greater precision in momentum analysis, while offering the flexibility to select the type of moving average that best suits their trading style.
Disclaimer: This script is not investment advice. Its use is entirely at your own risk. My responsibility is to provide a fully functional indicator, but it is not my role to guide how to trade, adjust, or use this tool in any specific strategy.
The JMA (Jurik Moving Average) version used in this script is a custom implementation based on publicly shared code by TradingView users, and it is not the original licensed version from Jurik Research.
What This Indicator Does
RSI-Gringo applies the Stochastic Oscillator logic to the RSI itself (rather than price), helping to identify overbought and oversold conditions within the RSI. This often leads to more responsive and accurate momentum signals.
This indicator displays:
%K: the main Stochastic RSI line
%D: smoothed signal line of %K
Upper/Lower horizontal reference lines at 80 and 20
Features and Settings
Available smoothing methods (selectable from dropdown):
SMA — Simple Moving Average
SMMA — Smoothed Moving Average (equivalent to RMA)
EMA — Exponential Moving Average
WMA — Weighted Moving Average
HMA — Hull Moving Average (manually implemented)
JMA — Jurik Moving Average (custom approximation)
KAMA — Kaufman Adaptive Moving Average
T3 — Triple Smoothed Moving Average with adjustable hot factor
How to Adjust Advanced Averages
T3 – Triple Smoothed MA
Parameter: T3 Hot Factor
Valid range: 0.1 to 2.0
Tuning:
Lower values (e.g., 0.1) make it faster but noisier
Higher values (e.g., 2.0) make it smoother but slower
Balanced range: 0.7 to 1.0 (recommended)
JMA – Jurik Moving Average (Custom)
Parameters:
Phase: adjusts responsiveness and smoothness (-100 to 100)
Power: controls smoothing intensity (default: 1)
Tuning:
Phase = 0: neutral behavior
Phase > 0: more reactive
Phase < 0: smoother, more delayed
Power = 1: recommended default for most uses
Note: The JMA used here is not the proprietary version by Jurik Research, but an educational approximation available in the public domain on TradingView.
How to Use
Crossover Signals
Buy signal: %K crosses above %D from below the 20 line
Sell signal: %K crosses below %D from above the 80 line
Momentum Strength
%K and %D above 80: strong bullish momentum
%K and %D below 20: strong bearish momentum
With Trend Filters
Combine this indicator with trend-following tools (like moving averages on price)
Fast smoothing types (like EMA or HMA) are better for scalping and day trading
Slower types (like T3 or KAMA) are better for swing and long-term trading
Final Tips
Tweak RSI and smoothing periods depending on the time frame you're trading.
Try different combinations of moving averages to find what works best for your strategy.
This indicator is intended as a supporting tool for technical analysis — not a standalone decision-making system.
Compare Symbol [LuxmiAI]This indicator allows users to plot candles or bars for a selected symbol and add a moving average of their choice as an underlay. Users can customize the moving average type and length, making it versatile for a wide range of trading strategies.
This script is designed to offer flexibility, letting traders select the symbol, timeframe, candle style, and moving average type directly from the input options. The moving averages include the Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), and Volume-Weighted Moving Average (VWMA).
Features of the Script
This indicator provides the following key features:
1. Symbol Selection: Users can input the ticker symbol for which they want to plot the data.
2. Timeframe Selection: The script allows users to choose a timeframe for the symbol data.
3. Candle Styles: Users can select from three styles - regular candles, bars, or Heikin-Ashi candles.
4. Moving Average Options: Users can choose between EMA, SMA, WMA, and VWMA for added trend analysis.
5. Customizable Moving Average Length: The length of the moving average can be adjusted to suit individual trading strategies.
How the Script Works
The script starts by taking user inputs for the symbol and timeframe. It then retrieves the open, high, low, and close prices of the selected symbol and timeframe using the request.security function. Users can select between three candle styles: standard candles, bars, and Heikin-Ashi candles. If Heikin-Ashi candles are selected, the script calculates the Heikin-Ashi open, high, low, and close values.
To add further analysis capabilities, the script includes a moving average. Traders can select the moving average type from EMA, SMA, WMA, or VWMA and specify the desired length. The selected moving average is then plotted on the chart to provide a clear visualization of the trend.
Step-by-Step Implementation
1. Input Options: The script starts by taking inputs for the symbol, timeframe, candle style, moving average type, and length.
2. Data Retrieval: The script fetches OHLC data for the selected symbol and timeframe using request.security.
3. Candle Style Logic: It determines which candle style to plot based on the user’s selection. If Heikin-Ashi is selected, the script calculates Heikin-Ashi values.
4. Moving Average Calculation: Depending on the user’s choice, the script calculates the selected moving average.
5. Visualization: The script plots the candles or bars and overlays the moving average on the chart.
Benefits of Using This Indicator
This custom indicator provides multiple benefits for traders. It allows for quick comparisons between symbols and timeframes, helping traders identify trends and patterns. The flexibility to choose different candle styles and moving averages enhances its adaptability to various trading strategies. Additionally, the ability to customize the moving average length makes it suitable for both short-term and long-term analysis.
simple swing indicator-KTRNSE:NIFTY
1. Pivot High/Low as Lines:
Purpose: Identifies local peaks (pivot highs) and troughs (pivot lows) in price and draws horizontal lines at these levels.
How it Works:
A pivot high occurs when the price is higher than the surrounding bars (based on the pivotLength parameter).
A pivot low occurs when the price is lower than the surrounding bars.
These pivots are drawn as horizontal lines at the price level of the pivot.
Visualization:
Pivot High: A red horizontal line is drawn at the price level of the pivot high.
Pivot Low: A green horizontal line is drawn at the price level of the pivot low.
Example:
Imagine the price is trending up, and at some point, it forms a peak. The script identifies this peak as a pivot high and draws a red line at the price of that peak. Similarly, if the price forms a trough, the script will draw a green line at the low point.
2. Moving Averages (20-day and 50-day):
Purpose: Plots the 20-day and 50-day simple moving averages (SMA) on the chart.
How it Works:
The 20-day SMA smooths the closing price over the last 20 days.
The 50-day SMA smooths the closing price over the last 50 days.
These lines provide an overview of short-term and long-term price trends.
Visualization:
20-day SMA: A blue line showing the 20-day moving average.
50-day SMA: An orange line showing the 50-day moving average.
Example:
When the price is above both moving averages, it indicates an uptrend. If the price crosses below these averages, it might signal a downtrend.
3. Supertrend:
Purpose: The Supertrend is an indicator based on the Average True Range (ATR) and is used to track the market trend.
How it Works:
When the market is in an uptrend, the Supertrend line will be green.
When the market is in a downtrend, the Supertrend line will be red.
Visualization:
Uptrend: The Supertrend line will be plotted in green.
Downtrend: The Supertrend line will be plotted in red.
Example:
If the price is above the Supertrend, the market is considered to be in an uptrend, and if the price is below the Supertrend, the market is in a downtrend.
4. Momentum (Rate of Change):
Purpose: Measures the rate at which the price changes over a set period, showing if the momentum is positive or negative.
How it Works:
The Rate of Change (ROC) measures how much the price has changed over a certain number of periods (e.g., 14).
Positive ROC indicates upward momentum, and negative ROC indicates downward momentum.
Visualization:
Positive ROC: A purple line is plotted above the zero line.
Negative ROC: A purple line is plotted below the zero line.
Example:
If the ROC line is above zero, it means the price is increasing, suggesting bullish momentum. If the ROC is below zero, it indicates bearish momentum.
5. Volume:
Purpose: Displays the volume of traded assets, giving insight into the strength of price movements.
How it Works:
The script will color the volume bars based on whether the price closed higher or lower than the previous bar.
Green bars indicate bullish volume (closing price higher than the previous bar), and red bars indicate bearish volume (closing price lower than the previous bar).
Visualization:
Bullish Volume: Green volume bars when the price closes higher.
Bearish Volume: Red volume bars when the price closes lower.
Example:
If you see a green volume bar, it suggests that the market is participating in an uptrend, and the price has closed higher than the previous period. Red bars indicate a downtrend or selling pressure.
6. MACD (Moving Average Convergence Divergence):
Purpose: The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of the price.
How it Works:
The MACD Line is the difference between the 12-period EMA (Exponential Moving Average) and the 26-period EMA.
The Signal Line is the 9-period EMA of the MACD Line.
The MACD Histogram shows the difference between the MACD line and the Signal line.
Visualization:
MACD Line: A blue line representing the difference between the 12-period and 26-period EMAs.
Signal Line: An orange line representing the 9-period EMA of the MACD line.
MACD Histogram: A red or green histogram that shows the difference between the MACD line and the Signal line.
Example:
When the MACD line crosses above the Signal line, it’s considered a bullish signal. When the MACD line crosses below the Signal line, it’s considered a bearish signal.
Full Chart Example:
Imagine you're looking at a price chart with all the indicators:
Pivot High/Low Lines are drawn as red and green horizontal lines.
20-day and 50-day SMAs are plotted as blue and orange lines, respectively.
Supertrend shows a green or red line indicating the trend.
Momentum (ROC) is shown as a purple line oscillating around zero.
Volume bars are green or red based on whether the close is higher or lower.
MACD appears as a blue line and orange line, with a red or green histogram showing the MACD vs. Signal line difference.
How the Indicators Work Together:
Trend Confirmation: If the price is above the Supertrend line and both SMAs are trending up, it indicates a strong bullish trend.
Momentum: If the ROC is positive and the MACD line is above the Signal line, it further confirms bullish momentum.
Volume: Increasing volume, especially with green bars, suggests that the trend is being supported by active participation.
By using these combined indicators, you can get a comprehensive view of the market's trend, momentum, and potential reversal points (via pivot highs and lows).
Larry Williams Valuation Index [tradeviZion]Larry Williams Valuation Index
Welcome to the Larry Williams Valuation Index by tradeviZion! This script is an interpretation of Larry Williams' famous WillVal (Valuation) Index, originally developed in 1990 to help traders determine whether a market or asset is overvalued or undervalued. We've extended it to support multiple securities and offer alerts for different valuation levels, helping you make more informed trading decisions.
What is the Valuation Index?
The Valuation Index measures how a security's current price compares to its historical price action. It helps identify whether the security is overvalued (priced too high), undervalued (priced too low), or in a normal range.
This version supports multiple securities and uses valuation parameters to help you assess the relative valuation of three securities simultaneously. It can help you determine the best times to enter (buy) or exit (sell) the market.
Key Features
Multi-Security Analysis: Analyze up to three securities simultaneously to get a broader view of market conditions.
Valuation Levels: Automatically calculate overvaluation and undervaluation levels or set manual levels for consistent analysis.
Custom Alerts: Create custom alerts when securities move between overvalued, undervalued, or normal ranges.
Customizable Table Display: Display a table with valuation values and their status on the chart.
Getting Started
Step 1: Adding the Script to Your Chart
First, add the Larry Williams Valuation Index script to your chart on TradingView. The script is designed to work with any timeframe, but for best results, use weekly or daily timeframes for a longer-term perspective.
Step 2: Configuring Securities
The script allows you to analyze up to three different securities :
Security 1 (Default: DXY)
Security 2 (Default: GC1!)
Security 3 (Default: ZB1!)
You can enable or disable each security individually.
Custom Timeframe Option: You have the option to select a custom timeframe for analysis. This allows you to see whether the security is overvalued or undervalued in lower or higher timeframes. Note that this feature is experimental and has not been extensively tested. Larry Williams originally used the weekly timeframe to determine if a stock was overvalued or undervalued. By default, the indicator compares the current price with the security based on the selected timeframe, except if you choose to use a custom timeframe.
Pro Tip : New users can start with the default securities to understand the concept before using other assets.
Step 3: Valuation Index Settings
Short EMA Length : This is the short-term average used for calculations. A lower value makes it more responsive to recent price changes.
Long EMA Length : This is the long-term average, used to smooth the valuation over time.
Valuation Length (Default: 156) : Represents approximately three years of daily bars (as recommended by Larry Williams).
How is the Valuation Index Calculated?
The valuation calculation is done using a method called WVI (WillVal Index), which compares the current price of a security to the price of another correlated security. Here’s a step-by-step explanation:
1. Data Collection: The script takes the closing price of the security you are analyzing and the closing price of the correlated security.
2. Ratio Calculation : The ratio of the two prices is calculated:
Price Ratio = (Price of your security) / (Price of correlated security) * 100.
This ratio helps determine how expensive or cheap your security is compared to the correlated one.
3. Exponential Moving Averages (EMAs) : The price ratio is used to calculate short-term and long-term EMAs (Exponential Moving Averages). EMAs are used to create smooth lines that represent the average price of a security over a specific period of time, with more weight given to recent data. By calculating both short-term and long-term EMAs, we can identify the trend direction and how the security is performing compared to its historical averages.
4. Valuation Index Calculation:
The Valuation Index is calculated as the difference between the short-term EMA and the long-term EMA. This difference helps to determine if the security is currently overvalued or undervalued:
A positive value indicates that the price is above its longer-term trend, suggesting potential overvaluation.
A negative value indicates that the price is below its longer-term trend, suggesting potential undervaluation.
5. Normalization:
To make the valuation easier to interpret, the calculated valuation index is then normalized using the highest and lowest values over the selected valuation length (e.g., 156 bars).
This normalization process converts the index into a percentage between 0 and 100, where higher values indicate overvaluation and lower values indicate undervaluation.
Step 4: Understanding Valuation Levels
The valuation levels indicate whether a security is currently undervalued, overvalued, or in a normal range.
Manual Levels : You can manually set the overvaluation and undervaluation thresholds (default is 85 for overvalued and 15 for undervalued).
Auto Levels : The script can automatically calculate these levels based on recent price action, allowing you to adapt to changing market conditions.
Auto Levels Calculation Explained:
The Auto Levels are calculated by taking the average of the valuation indices for all three securities (e.g., index1, index2, and index3).
The script then looks at the highest and lowest values of this average over a selected number of recent bars (e.g., 50 bars).
The overvaluation level is determined by taking the highest value and multiplying it by a multiplier (e.g., 5). Similarly, the undervaluation level is calculated using the lowest value and the multiplier.
These dynamic levels adjust according to recent price action, providing an adaptive approach to identifying overvalued and undervalued conditions.
Step 5: How to Use the Script to Make Trading Decisions
For new users, here's a step-by-step trading strategy you can use with the Valuation Index:
1. Identify Undervalued Opportunities
When two or more securities are in the undervalued range (below 15 for manual or below automatically calculated undervalue levels), wait for at least two of these securities to turn from undervalued to normal .
This transition indicates a potential buy opportunity .
2. Buying Signal
When at least two securities transition from undervalued to normal, you can consider buying the asset.
This indicates that the market may be recovering from undervalued conditions and could be moving into a growth phase.
3. Selling Signal
Exit when the price high closes below the EMA 21 (21-day exponential moving average).
Alternatively, if the valuation index reaches overvalued levels (above 85 manually or auto-calculated), wait for it to drop back to normal . This can be another point to exit the trade .
You can also use any other sell condition based on your r isk management strategy .
Alerts for Valuation Levels
The script includes alerts to notify you of changing market conditions:
To activate these alerts, follow these steps, referring to the provided screenshot with detailed steps:
1. Enable Alerts : Click on the settings gear icon on the script title in your chart. In the settings menu, scroll to the section labeled Alerts Settings .
Enable Alerts by checking the Enable Alerts box.
Set the Required Securities for Alert (default is 2 securities).
Choose the Alert Frequency : Selecting Once Per Bar Close will trigger alerts only at the close of each bar, ensuring you receive confirmed signals rather than potentially noisy intermediate signals.
2. Select Alert Type : Choose the type of alert you want to activate, such as Alert on Overvalued, Alert on Undervalued, Alert on Over to Normal , or Alert on Under to Normal .
3. Save Settings : Click OK to save your alert settings.
4. Add Alert on Indicator : Click the "..." (More button) next to the indicator name on the chart and select " Add alert on tradeviZion - WillVal ".
5. Create Alert : In the Create Alert window:
Set Condition to tradeviZion - WillVal .
Ensure Any alert() function call is selected.
Set the Alert Name and select your Expiration preferences.
6. Set Notification Preferences : Go to the Notifications tab and select how you want to receive notifications, such as via app notification, toast notification, email , or sound alert . Adjust these preferences to best suit your needs.
7. Click Create : Finally, click Create to activate the alert.
These alerts will help you stay informed about key market conditions and take action accordingly, ensuring you do not miss critical trading opportunities.
Understanding the Table Display
The script includes an interactive table on the chart to show the valuation status of each security:
Security : The name of the security being analyzed.
Value : The current valuation index value.
Status : Indicates whether the security is overvalued, undervalued , or in a normal range.
Color: Displays a color code for easy identification of status:
Red for overvalued.
Green for undervalued.
Other colors represent normal valuation levels.
Empowering Messages : Motivational messages are displayed to encourage disciplined trading. These messages will change periodically, helping keep a positive trading mindset.
Acknowledgment
This tool builds upon the foundational work of Larry Williams, who developed the WillVal (Valuation) Index concept. It also incorporates enhancements to extend multi-security analysis, valuation normalization, and advanced alerting features, providing a more versatile and powerful indicator. The Larry Williams Valuation Index [ tradeviZion ] helps traders make informed decisions by assessing overvalued and undervalued conditions for multiple securities simultaneously.
Note : Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
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