DSS of Advanced Kaufman AMA [Loxx]DSS of Advanced Kaufman AMA is a double smoothed stochastic oscillator using a Kaufman adaptive moving average with the option of using the Jurik Fractal Dimension Adaptive calculation. This helps smooth the stochastic oscillator thereby making it easier to identify reversals and trends.
What is the double smoothed stochastic?
The Double Smoothed Stochastic indicator was created by William Blau. It applies Exponential Moving Averages (EMAs) of two different periods to a standard Stochastic %K. The components that construct the Stochastic Oscillator are first smoothed with the two EMAs. Then, the smoothed components are plugged into the standard Stochastic formula to calculate the indicator.
What is KAMA?
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility . KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements.
What is the efficiency ratio?
In statistical terms, the Efficiency Ratio tells us the fractal efficiency of price changes. ER fluctuates between 1 and 0, but these extremes are the exception, not the norm. ER would be 1 if prices moved up 10 consecutive periods or down 10 consecutive periods. ER would be zero if price is unchanged over the 10 periods.
What is Jurik Fractal Dimension?
There is a weak and a strong way to measure the random quality of a time series.
The weak way is to use the random walk index ( RWI ). You can download it from the Omega web site. It makes the assumption that the market is moving randomly with an average distance D per move and proposes an amount the market should have changed over N bars of time. If the market has traveled less, then the action is considered random, otherwise it's considered trending.
The problem with this method is that taking the average distance is valid for a Normal (Gaussian) distribution of price activity. However, price action is rarely Normal, with large price jumps occuring much more frequently than a Normal distribution would expect. Consequently, big jumps throw the RWI way off, producing invalid results.
The strong way is to not make any assumption regarding the distribution of price changes and, instead, measure the fractal dimension of the time series. Fractal Dimension requires a lot of data to be accurate. If you are trading 30 minute bars, use a multi-chart where this indicator is running on 5 minute bars and you are trading on 30 minute bars.
Included
-Toggle bar colors on/offf
Cari dalam skrip untuk "Exponential Moving Average"
3EMA + Boullinger + PIVOTTRES EMAS + BANDAS DE BOLLINGER + PIVOTE
INDICADOR 1: TRES EMAS (MEDIA MOVIL EXPONENCIAL)
Con este indicador puede visualizar el promedio de precios con mayor peso a los datos mas recientes.
Se calculan y dibujan tres medias móviles exponenciales: 8, 20 y 200 últimas velas.
-Rápida EMA1 = 8
-Media EMA2 = 20
-Lenta EMA 3 = 200
INDICADOR 2: BANDAS DE BOLLINGER
Con este indicador podrá ver la fuerza y la tendencia del mercado, es decir la mide la volatilidad del precio del activo.
Si el precio sobrepasa la banda superior, el activo está sobrecomprado.
Si el precio sobrepasa la banda inferior, el activo está sobrevendido.
Longitud tendencia - BASE = 20, paso = 1
Desviación Estándar - Multiplicador = 2, paso = 0.2
INDICADOR 3: PIVOTE
Este indicador etiqueta los puntos donde el precio es mínimo y máximo, en un rango de velas determinado en el parámetro "Distancia para el Pivote".
Estos 3 indicadores sirven para todo tipo de activos: FOREX, CRIPTO, CFD´s, ETC.
------------------------------------------------------------------------------------------------------------------
THREE EMAS + BOLLINGER BANDS + PIVOT
INDICATOR 1: THREE EMAS ( EXPONENTIAL MOVING AVERAGE )
With this indicator you can visualize the average of prices with greater weight to the most recent data.
Three exponential moving averages are calculated and drawn: 4, 20 and 200 last candles.
-Fast EMA1 = 8
-Average EMA2 = 20
-Slow EMA 3 = 200
INDICATOR 2: BOLLINGER BANDS
With this indicator you can see the strength and trend of the market, that is, it is measured by the volatility of the asset price.
If the price goes above the upper band, the asset is overbought.
If the price goes above the lower band, the asset is oversold.
Trend length - BASE = 20, step = 1
Standard Deviation - Multiplier = 2, step = 0.2
INDICATOR 3: PIVOT
This indicator labels the points where the price is minimum and maximum, in a range of candles determined in the parameter "Distance to Pivot".
These 3 indicators are used for all types of assets: FOREX, CRYPT, CFD's, ETC.
Combo 2/20 EMA & Adaptive Price Zone 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
The adaptive price zone (APZ) is a volatility-based technical indicator that helps investors
identify possible market turning points, which can be especially useful in a sideways-moving
market. It was created by technical analyst Lee Leibfarth in the article “Identify the
Turning Point: Trading With An Adaptive Price Zone,” which appeared in the September 2006 issue
of the journal Technical Analysis of Stocks and Commodities.
This indicator attempts to signal significant price movements by using a set of bands based on
short-term, double-smoothed exponential moving averages that lag only slightly behind price changes.
It can help short-term investors and day traders profit in volatile markets by signaling price
reversal points, which can indicate potentially lucrative times to buy or sell. The APZ can be
implemented as part of an automated trading system and can be applied to the charts of all tradeable assets.
WARNING:
- For purpose educate only
- This script to change bars colors.
pandas_taLibrary "pandas_ta"
Level: 3
Background
Today is the first day of 2022 and happy new year every tradingviewers! May health and wealth go along with you all the time. I use this chance to publish my 1st PINE v5 lib : pandas_ta
This is not a piece of cake like thing, which cost me a lot of time and efforts to build this lib. Beyond 300 versions of this script was iterated in draft.
Function
Library "pandas_ta"
PINE v5 Counterpart of Pandas TA - A Technical Analysis Library in Python 3 at github.com
The Original Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns.
I realized most of indicators except Candlestick Patterns because tradingview built-in Candlestick Patterns are even more powerful!
I use this to verify pandas_ta python version indicators for myself, but I realize that maybe many may need similar lib for pine v5 as well.
Function Brief Descriptions (Pls find details in script comments)
bton --> Binary to number
wcp --> Weighted Closing Price (WCP)
counter --> Condition counter
xbt --> Between
ebsw --> Even Better SineWave (EBSW)
ao --> Awesome Oscillator (AO)
apo --> Absolute Price Oscillator (APO)
xrf --> Dynamic shifted values
bias --> Bias (BIAS)
bop --> Balance of Power (BOP)
brar --> BRAR (BRAR)
cci --> Commodity Channel Index (CCI)
cfo --> Chande Forcast Oscillator (CFO)
cg --> Center of Gravity (CG)
cmo --> Chande Momentum Oscillator (CMO)
coppock --> Coppock Curve (COPC)
cti --> Correlation Trend Indicator (CTI)
dmi --> Directional Movement Index(DMI)
er --> Efficiency Ratio (ER)
eri --> Elder Ray Index (ERI)
fisher --> Fisher Transform (FISHT)
inertia --> Inertia (INERTIA)
kdj --> KDJ (KDJ)
kst --> 'Know Sure Thing' (KST)
macd --> Moving Average Convergence Divergence (MACD)
mom --> Momentum (MOM)
pgo --> Pretty Good Oscillator (PGO)
ppo --> Percentage Price Oscillator (PPO)
psl --> Psychological Line (PSL)
pvo --> Percentage Volume Oscillator (PVO)
qqe --> Quantitative Qualitative Estimation (QQE)
roc --> Rate of Change (ROC)
rsi --> Relative Strength Index (RSI)
rsx --> Relative Strength Xtra (rsx)
rvgi --> Relative Vigor Index (RVGI)
slope --> Slope
smi --> SMI Ergodic Indicator (SMI)
sqz* --> Squeeze (SQZ) * NOTE: code sufferred from very strange error, code was commented.
sqz_pro --> Squeeze PRO(SQZPRO)
xfl --> Condition filter
stc --> Schaff Trend Cycle (STC)
stoch --> Stochastic (STOCH)
stochrsi --> Stochastic RSI (STOCH RSI)
trix --> Trix (TRIX)
tsi --> True Strength Index (TSI)
uo --> Ultimate Oscillator (UO)
willr --> William's Percent R (WILLR)
alma --> Arnaud Legoux Moving Average (ALMA)
xll --> Dynamic rolling lowest values
dema --> Double Exponential Moving Average (DEMA)
ema --> Exponential Moving Average (EMA)
fwma --> Fibonacci's Weighted Moving Average (FWMA)
hilo --> Gann HiLo Activator(HiLo)
hma --> Hull Moving Average (HMA)
hwma --> HWMA (Holt-Winter Moving Average)
ichimoku --> Ichimoku Kinkō Hyō (ichimoku)
jma --> Jurik Moving Average Average (JMA)
kama --> Kaufman's Adaptive Moving Average (KAMA)
linreg --> Linear Regression Moving Average (linreg)
mgcd --> McGinley Dynamic Indicator
rma --> wildeR's Moving Average (RMA)
sinwma --> Sine Weighted Moving Average (SWMA)
ssf --> Ehler's Super Smoother Filter (SSF) © 2013
supertrend --> Supertrend (supertrend)
xsa --> X simple moving average
swma --> Symmetric Weighted Moving Average (SWMA)
t3 --> Tim Tillson's T3 Moving Average (T3)
tema --> Triple Exponential Moving Average (TEMA)
trima --> Triangular Moving Average (TRIMA)
vidya --> Variable Index Dynamic Average (VIDYA)
vwap --> Volume Weighted Average Price (VWAP)
vwma --> Volume Weighted Moving Average (VWMA)
wma --> Weighted Moving Average (WMA)
zlma --> Zero Lag Moving Average (ZLMA)
entropy --> Entropy (ENTP)
kurtosis --> Rolling Kurtosis
skew --> Rolling Skew
xev --> Condition all
zscore --> Rolling Z Score
adx --> Average Directional Movement (ADX)
aroon --> Aroon & Aroon Oscillator (AROON)
chop --> Choppiness Index (CHOP)
xex --> Condition any
cksp --> Chande Kroll Stop (CKSP)
dpo --> Detrend Price Oscillator (DPO)
long_run --> Long Run
psar --> Parabolic Stop and Reverse (psar)
short_run --> Short Run
vhf --> Vertical Horizontal Filter (VHF)
vortex --> Vortex
accbands --> Acceleration Bands (ACCBANDS)
atr --> Average True Range (ATR)
bbands --> Bollinger Bands (BBANDS)
donchian --> Donchian Channels (DC)
kc --> Keltner Channels (KC)
massi --> Mass Index (MASSI)
natr --> Normalized Average True Range (NATR)
pdist --> Price Distance (PDIST)
rvi --> Relative Volatility Index (RVI)
thermo --> Elders Thermometer (THERMO)
ui --> Ulcer Index (UI)
ad --> Accumulation/Distribution (AD)
cmf --> Chaikin Money Flow (CMF)
efi --> Elder's Force Index (EFI)
ecm --> Ease of Movement (EOM)
kvo --> Klinger Volume Oscillator (KVO)
mfi --> Money Flow Index (MFI)
nvi --> Negative Volume Index (NVI)
obv --> On Balance Volume (OBV)
pvi --> Positive Volume Index (PVI)
dvdi --> Dual Volume Divergence Index (DVDI)
xhh --> Dynamic rolling highest values
pvt --> Price-Volume Trend (PVT)
Remarks
I also incorporated func descriptions and func test script in commented mode, you can test the functino with the embedded test script and modify them as you wish.
This is a Level 3 free and open source indicator library.
Feedbacks are appreciated.
This is not the end of pandas_ta lib publication, but it is start point with pine v5 lib function and I will add more and more funcs into this lib for my own indicators.
Function Name List:
bton()
wcp()
count()
xbt()
ebsw()
ao()
apo()
xrf()
bias()
bop()
brar()
cci()
cfo()
cg()
cmo()
coppock()
cti()
dmi()
er()
eri()
fisher()
inertia()
kdj()
kst()
macd()
mom()
pgo()
ppo()
psl()
pvo()
qqe()
roc()
rsi()
rsx()
rvgi()
slope()
smi()
sqz_pro()
xfl()
stc()
stoch()
stochrsi()
trix()
tsi()
uo()
willr()
alma()
wcx()
xll()
dema()
ema()
fwma()
hilo()
hma()
hwma()
ichimoku()
jma()
kama()
linreg()
mgcd()
rma()
sinwma()
ssf()
supertrend()
xsa()
swma()
t3()
tema()
trima()
vidya()
vwap()
vwma()
wma()
zlma()
entropy()
kurtosis()
skew()
xev()
zscore()
adx()
aroon()
chop()
xex()
cksp()
dpo()
long_run()
psar()
short_run()
vhf()
vortex()
accbands()
atr()
bbands()
donchian()
kc()
massi()
natr()
pdist()
rvi()
thermo()
ui()
ad()
cmf()
efi()
ecm()
kvo()
mfi()
nvi()
obv()
pvi()
dvdi()
xhh()
pvt()
Swing Trades Validator - The One TraderThis swing trading strategy validator is built on the original strategy taught in my bootcamp for swing traders.
The strategy is simple and follows a trend trading pattern on prices reacting to Exponential Moving Averages over a multiple time-frame analysis.
The details of the strategy are as follows:
- Holding Period : Upto a couple of months
- Time-frames to be analysed : Month - Week - Day
- Trade Execution : Daily Time-frame
Analysis Details:
Step 1 : On the Monthly time-frame, the candle needs to be bullish with the latest close being higher than the opening price of the month.
Step 2 : The price needs to be above the 8ema on the Monthly time-frame.
Step 3 : The 8ema must be above the 20ema on the Monthly time-frame.
The above steps indicate a bullish strength in the instrument on the Monthly time-frame.
Step 4 : On the Weekly time-frame, the candle needs to be bullish with the latest close being higher than the opening price of the week.
Step 5 : The price needs to be above the 8ema on the Weekly time-frame.
Step 6 : The 8ema must be above the 20ema on the Weekly time-frame.
The above steps indicate a bullish strength in the instrument on the Weekly time-frame.
Step 7 : On the Daily time-frame, the candle needs to be bullish with the latest close being higher than the opening price of the day.
Step 8 : The price needs to be above the 8ema on the Daily time-frame.
Step 9 : The 8ema must be above the 20ema on the Daily time-frame.
The above steps indicate a bullish strength in the instrument on the Daily time-frame.
Step 10 : While the 8ema is above the 20ema on the Daily time-frame, the price must be allowed to rise before a pullback is seen towards the moving averages, indicating a bearish move trying to change the trend.
Step 11 : These pullback candles need to form a pattern called the Ring Low with the second pullback candle having a lower high and lower low and the low of the last pullback candle being lesser than or equal to the fat ema on the Daily time-frame.
Step 12 : If the stock is still bullish and the trend is displaying a strength in the underlying bullish direction, then there will be a resumption candle that will have a closing price higher than the previous day's high price.
This trend continuation signal is a confirmation that the instrument will continue in the underlying trend direction and we will be able to enter if this condition is satisfied.
The profit and loss percentages are set at a default 10% as this can be a minimum risk : reward for swing trades on average, but the inputs have been made available to the users in order to adjust the risk : reward to find the most optimum breathing room for each individual stock or instrument. This will give the user a highly custom overview of the strategy on individual instruments based on their volatility and price movements.
The strategy tester will auto back-test this strategy historically and find all the trades that were taken based on this strategy and populate a performance summary.
The most important data in V1.0 of this script are as follows:
1. No. of Trades Taken : We want to see many trades being taken on this strategy in that particular instrument. This shows us a healthy report on the number of winning vs. losing trades.
2. Percentage Profitable : We want to see that this strategy has worked out in the past and is giving us a high probability of return. This in no way an indication that the strategy will definitely work out in the future as well, but gives us an idea of whether or not we should enter this trade.
3. No. of Winning Trades vs. Losing Trades : We would like to see a significantly higher number of winning trades.
4. Avg. # of bars in a trade : This gives us an idea of how long on average we might have to wait to see the results of this strategy either in favor of our reward or against our desired direction. Some trades can be completed in around 15-20 bars on average and some trades have shown to take upto 45 days to reach desired reward. This is in line with our planned holding period, but gives the trader a sense of time and increased level of patience.
The future updates will have more utility of the various elements of the strategy tester and the entire exit strategy will be integrated into the script.
This script is not to be used as a standalone method and must be studied well in order to execute trades. I have not hidden visibility on other time-frames, but since order execution is done on the Daily time-frame, the script must run on the Daily time-frame only.
There are many other factors to be taken into consideration before entering a trade and proper risk management and position sizing rules must be followed.
Our bootcamp participants will use this strategy tester in conjunction with the invite-only Trading Toolkit assigned to them.
The development of this script will be ongoing and all comments and feedback are welcome.
Swing Dream - PAINT BARS | MA | EMA | DMA | VWAP | TABLE | ADR %- Swing Dream -
Script created for breakout-swing traders, in the style of QullaMaggie * , Dan Zanger, Oliver Kell, and Stockbee.
The following indicators are used by most successful breakout-swing traders such as mentioned above.
(As published) it contains:
Painted Bars, also known as inside/outside candles. Used for candle analysis and to determine breakout pivots & levels. For instance; use it in different timeframes and seek formations (ex, 3-1-2). For further inspiration, study Rob Smith's The Strat .
MA, Simple Moving Averages (Basic levels = 10,20,50,200). Use this indicator to define resistance/support areas as well as the overall long/swing-term trend. In breakout strategies such as EP, Flags, etc this can be used for trailing stops; an example, post-breakout, let the price ride the 20ma before exiting your position.
EMA, Exponential Moving Averages with periods inspired by Qullamaggie (10,20,65). Use this on shorter timeframes (ex, 1h) and for the same principles as MAs.
VWAP, Volume-Weighted Average Price. As for the previous, utilize this as a level indicator to find areas of resistance/support. Good for swing-trading as it implies whenever holders are profitable or not.
DMA, Displaced Moving Average (Horizontal). Personally, I use this a lot. Works very well for trailing stops (post breakout) and "bounce" areas. Choose your own offset and period.
ADR%, Average Daily Range Percentage. Displayed in the table and used to define a symbol's volatility. A very good tool for Qullamaggie-style trading. Personally, I try to find setups with over 6% ADR. Basic definition; low ADR% = Increased chance of a symbol to move slower and in smaller ranges. A higher value equals the opposite.
Table. A table with basic symbol-related information. Could save you plenty of time whenever you scan or search for new swing setups. Looking to add more features here.
Why should you use this script? Well, instead of having tens of different indicators, use this script and combine everything together with EP, Flag, or breakout principles. Suited for every plan, and more efficient in my opinion.
View settings to turn on/off different indicators.
* If you're looking for an introduction and further explanation of how Qullamaggie uses mentioned indicators, I could recommend checking out his website, stream, or participation in "Chat With Traders".
At last, I want to credit: @jkcqld @neolao @TheScrutiniser
This Script will get updated and improved.
// TechFille006
[blackcat] L1 Tim Tillson IE/2Level: 1
Background
Before this script, I cannot find a IE/2 moving average script in tradingview. Although it is not so complex, it is meaningful to be the 1st Tim Tilson IE/2 script in tradingview community. IE/2 moving average was disclosed in "Smoothin Techniques For More Accurate Signals", Tim Tilson, S&C Magazine, Traders Tips, 01/1998.
Function
IE/2 is one of pre-studies created while T3 famous average was developing. It is calculated as (ILRS(n)+EPMA(n))/2. ILRS, is an integral of linear regression slope. In this moving average, the slope of a linear regression line is simply integrated as it is fitted in a moving window of length n across the data. The derivative of ILRS is the linear regression slope.EPMA is an end point moving average - it is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length.
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).
Inputs
Price --> price data to use
Period --> number of bars to use in calculation
Key Signal
Price --> Price Input.
IE/2 --> IE/2 Ouput.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
Bull vs Bear Power by DGTElder-Ray Bear and Bull Power
Dr. Alexander Elder cleverly named his first indicator Elder-Ray because of its function, which is designed to see through the market like an X-ray machine. Developed in 1989, the Elder-Ray indicator can be applied to the chart of any security and helps traders determine the strength of competing groups of bulls and bears by gazing under the surface of the markets for data that may not immediately be ascertainable from a superficial glance at prices
The Elder-Ray indicator is comprised by three elements – Bear Power, Bull Power and a 13-period Exponential Moving Average.
As the high price of any candle shows the maximum power of buyers and the low price of any candle shows the maximum power of sellers, Elder uses the 13-period EMA in order to present the average consensus of price value. Bull power shows whether buyers are capable of pushing prices above the average consensus of value. Bear power shows whether sellers are capable of pushing prices below the average consensus of value. Mathematically, Bull power is the result of subtracting the 13-period EMA from the high price of the day, and Bear power is the result of subtracting the 13-period EMA from the low price of the day.
What does this study implements
Attempts to customize interpretation of Alexander Elder's Elder-Ray Indicator (Bull and Bear Power) by
• adding additional insights to support/confirm Elder’s strategy with different indicators related with the Elder’s concept
• providing different options of visualization of the indicator
• providing smoothing capability
Other Indicators to support/confirm Elder-Ray Indicator:
Colored Directional Movement Index (CDMI) , a custom interpretation of J. Welles Wilder’s Directional Movement Index (DMI) , where :
DMI is a collection of three separate indicators ( ADX , +DI , -DI ) combined into one and measures the trend’s strength as well as its direction
CDMI is a custom interpretation of DMI which presents ( ADX , +DI , -DI ) with a color scale - representing the trend’s strength, color density - representing momentum/slope of the trend’s strength, and triangle up/down shapes - representing the trend’s direction. CDMI provides all the information in a single line with colored triangle shapes plotted on the top. DMI can provide quality information and even trading signals but it is not an easy indicator to master, whereus CDMI simplifies its usage.
Alexander Elder considers the slope of the EMA, which gives insight into the recent trend whether is up or down, and CDMI adds additional insight of verifying/confirming the trend as well as its strength
Note : educational content of how to read CDMI can be found in ideas section named as “Colored Directional Movement Index”
different usages of CDMI can be observed with studies “Candlestick Patterns in Context by DGT", “Ichimoku Colored SuperTrend + Colored DMI by DGT”, “Colored Directional Movement and Bollinger Band's Cloud by DGT”, and “Technical Analyst by DGT”
Price Convergence/Divergence , if we pay attention to mathematical formulations of bull power, bear power and price convergence/divergence (also can be expressed as price distance to its ma) we would clearly observe that price convergence/divergence is in fact the result of how the market performed based on the fact that we assume 13-period EMA is consensus of price value. Then, we may assume that the price convergence/divergence crosses of bull power, or bear power, or sum of bull and bear power could be considered as potential trading signals
Additionally, price convergence/divergence visualizes the belief that prices high above the moving average or low below it are likely to be remedied in the future by a reverse price movement
Alternatively, Least Squares Moving Average of Price Convergence/Divergence (also known as Linear Regression Curve) can be plotted instead of Price Convergence/Divergence which can be considered as a smoothed version of Price Convergence/Divergence
Note : different usages of Price Convergence/Divergence can be observed with studies “Trading Psychology - Fear & Greed Index by DGT”, “Price Distance to its MA by DGT”, “P-MACD by DGT”, where “Price Distance to its MA by DGT” can also be considered as educational content which includes an article of a research carried on the topic
Options of Visualization
Bull and Bear Power plotted as two separate
• histograms
• lines
• bands
Sum of Bull and Bear Power plotted as single
• histogram
• line
• band
Others
Price Convergence/Divergence displayed as Line
CDMI is displayed as single colored line of triangle shapes, where triangle shapes displays direction of the trend (triangle up represents bull and triangle down represent bear), colors of CDMI displays the strength of the trend (green – strong bullish, red – strong bearish, gray – no trend, yellow – week trend)
In general with this study, color densities also have a meaning and aims to displays if the value of the indicator is falling or growing, darker colors displays more intense move comparing to light one
Note : band's upper and lower levels are calculated by using standard deviation build-in function with multiply factor of 0.236 Fibonacci’s ratio (just a number for our case, no any meaning)
Smoothing
No smoothing is applied by default but the capability is added in case Price Convergence/Divergence Line is assumed to be used as a signal line it will be worth smoothing the bear, bull or sum of bear and bull power indicators
Interpreting Elder-Ray Indicator, according to Dr. Alexander Elder
Bull Power should remain positive in normal circumstances, while Bear Power should remain negative in normal circumstances. In case the Bull Power indicator enters into negative territory, this implies that sellers have overcome buyers and control the market. In case the Bear Power indicator enters into positive territory, this indicates that buyers have overcome sellers and control the market. A trader should not go long at times when the Bear Power indicator is positive and he/she should not go short at times when the Bull Power indicator is negative.
13-period EMAs slope can be used in order to identify the direction of the major trend. According to Elder, the most reliable buy signals are generated, when there is a bullish divergence between the Bear Power indicator and the price (Bear Power forms higher lows, while the market forms lower lows). The most reliable sell signals are generated, when there is a bearish divergence between the Bull Power indicator and the price (Bull Power forms lower highs, while the market forms higher highs).
There are four basic conditions, required to go long or short, with the use of the Elder-Ray method alone.
In order to go long:
1. The market is in a bull trend, as indicated by the 13-period EMA
2. Bear Power is in negative territory, but increasing
3. The most recent Bull Power top is higher than its prior top
4. Bear Power is going up from a bullish divergence
The last two conditions are optional that fine-tune the buying decision
In order to go short:
1. The market is in a bear trend, as indicated by the 13-period EMA
2. Bull Power is in positive territory, but falling
3. The most recent Bear Power bottom is lower than its prior bottom
4. Bull Power is falling from a bearish divergence
The last two conditions are optional, they provide a stronger signal for shorting but they are not absolutely essential
If a trader is willing to add to his/her position, he/she needs to:
1. add to his/her long position, when the Bear Power falls below zero and then climbs back into positive territory
2. add to his/her short position, when the Bull Power increases above zero and then drops back into negative territory.
note : terminology of the definitions used herein are as per TV dictionary
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer : The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Market Adaptive Stop-LossI realized that the zone changes in the stoploss remained slow, so I couldn't make enough use of the characteristics of technical indicators when opening positions.
This pushed me to keep stop-loss under the influence of a dependent variable.
This script helped me a lot (everget) :
I've redesigned the stop-loss to be affected by intersections.
Therefore, this script is also suitable for adaptive moving averages, fractional periods.
Script features:
1.You can select calculation methods created by using various technical analysis methods from the scripts' settings:
-Moving Average Convergence Divergence ( Macd )
-Stochastic Oscillator ( Stoch )
-Stochastic Relative Strength Index (StochRSI)
-Stochastic Money Flow Index (StochMFI ) (More info : )
-Know Sure Thing ( KST )
-OBV ( On Balance Volume )
-SMA ( Simple Moving Average )
-EMA ( Exponential Moving Average )
-FISHERTRANSFORM ( Fisher Transform )
-AWESOMEOSCILLATOR( Awesome Oscillator )
-PSAR ( Parabolic Stop and Reverse - Parabolic SAR )
-HULLMA( Hull Moving Average )
-VWMA ( Volume Weighted Moving Average )
-RMA (Moving Average using in Relative Strength Index calculations.)
-COG (Center of Gravity )
-ACC-DIST ( Accumulation / Distribution Index )
2 - The region is determined according to the above calculation methods and if it is larger or smaller than the previous stop loss level.
And if the price in the negative zone is lower than the stoploss, it is the exact signal and is shown with more highlighted colors.
And, in the positive zone, where the price is greater than the stoploss, the trade zones are certain.
Shown with more highlighted colors.
If the zones are correct but stop-loss is not suitable for opening positions:
In other words, if the stop-loss is above/under the highest-lowest levels in the positive zone or if the stop loss is located in the lower zone in the negative zone, these zones are shown to be darker and dimmed so that they do not cause false movements.
*** SUMMARY : As a result, you can use this script with support and resistances,and trend lines to get good results.
I hope it helps in your analyzes. Best regards.
Triple Moving AverageSimple indicator combining up to three moving averages. Uses simple moving average (SMA) and exponential moving average (EMA).
Culter's RSIA variation called Cutler's RSI is based on a simple moving average of U and D, instead of the exponential average. Cutler had found that since Wilder used an exponential moving average to calculate RSI, the value of Wilder's RSI depended upon where in the data file his calculations started. Cutler termed this Data Length Dependency. Cutler's RSI is not data length dependent, and returns consistent results regardless of the length of, or the starting point within a data file.
Cutler's RSI generally comes out slightly different from the normal Wilder RSI, but the two are similar, since SMA and EMA are also similar.
Volume Weighted Average Divergence [DW]This is an experimental study inspired by the volume weighted moving average convergence divergence (VWMACD) concept.
In this formula, divergences between two volume weighted moving averages and two simple moving averages over their respective lookback periods are calculated.
The difference between the divergences is calculated, then the difference between the result and an exponential moving average of the result are calculated to provide a histogram.
Finally, the mean value between the two divergences is calculated to provide the VWAD line.
Custom bar colors are also included.
Predictive EMAFrom the MQL5 Indicator database, here is what the author said about the script,
"Goal of this indicator:
Given three EMA's of varying lengths, use their values
for a estimator of "where we are now" or will be in the near future.
This is a very simplistic method, better ones are probably found
in the signal processing and target tracking literature.
A Kalman filter has been known since the 1950's 1960's and there
is better still. Nevertheless this is easily programmable in the
typical environments of a retail trading application like Metatrader4.
Method:
An an exponential moving average (EMA) or a simple moving average (SMA), for that
matter, have a bandwidth parameter 'L', the effective length of the window. This
is in units of time or, really, inverse of frequency. Higher L means a lower
frequency effect.
With a parameter L, the weighted time index of the EMA and SMA is (L-1)/2. Example:
take an SMA of the previous 5 values: -5 -4 -3 -2 -1 now. The average "amount of time"
back in the past of the data which go in to the SMA is hence -3, or (L-1)/2. Same applies
for an EMA. The standard parameterization makes this correspondence between EMA
and SMA.
Therefore the idea here is to take two different EMA's, a longer, and
a shorter of lengths L1 and L2 (L2 <L1). Now take the pairs:
which defines a line.
Extrapolate to , solve for y and that is the predictive EMA estimate.
Application:
Traditional moving averages, as simple-minded linear filters, have significant group delay.
In engineering that isn't so important as nobody cares if your sound from your iPod is delayed
a few milliseconds after it is first processed. But in markets, you can't
trade on the smoothed price, only the actual noisy, market price now. Hence you
ought to estimate better.
This statistic (what math/science people call what technical analysts call an 'indicator')
may be useful as the "fast" moving average in a moving average crossover trading system.
It could also be useful for the slow moving average as well.
For instance, on a 5 minute chart:
try for the fast: (will be very wiggly, note)
LongPeriod 25.0
ShortPeriod 8.0
ExtraTimeForward 1.0
and for the slow:
LongPeriod 500.0
ShortPeriod 50.0 to 200.0
ExtraTimeForward 0.0
But often a regular MA for the slow can work as well or better, it appears from visual inspection.
Enjoy.
In chaos there is order, and in that order there is chaos and order inside again.
Then, surrounding everything, pointy haired bosses. "
I may have done it incorrectly, feel free to revise
Variable Moving Average [LazyBear]Variable Moving Average, often abbreviated as VMA, is an Exponential Moving Average developed by Tushar S. Chande. VMA automatically adjusts its smoothing constant on the basis of Market Volatility.
Use this like other Moving Averages. I have added the following options that can be enabled via options page:
- Trend Direction Indication: Green = Up trend, Blue = Potential congestion, Red = down trend.
- Color bars based on Trend
More info:
www.thewizardtrader.com
List of my other indicators:
- GDoc: docs.google.com
- Chart:
Mimas buy and sellBollinger Bands: Calculated using a simple moving average (basis) and standard deviation (dev).
EMAs: Two exponential moving averages (EMA 5 and EMA 20) are plotted to identify short-term and long-term trends.
Price Action Patterns: The script detects higher highs and higher lows for bullish conditions, and lower highs and lower lows for bearish conditions.
Trend Strength: An exponential moving average of the price change is used to gauge the strength of the trend.
Trade Signals: Buy and sell signals are plotted on the chart when specific conditions are met, combining price action patterns, trend strength, Bollinger Bands, and EMA crossovers.
Take-Profit Levels: Dynamic take-profit levels are calculated based on recent swing highs and lows, adjusted by a user-defined multiplier. These levels are displayed on the chart using plot to draw horizontal lines.
ADR & ATR Extension from EMAThis indicator helps identify how extended the current price is from a chosen Exponential Moving Average (EMA) in terms of both Average Daily Range (ADR) and Average True Range (ATR).
It calculates:
ADR Extension = (Price - EMA) / ADR
ATR Extension = (Price - EMA) / ATR
The results are shown in a floating table on the chart.
The ADR line turns red if the price is more than 4 ADRs above the selected EMA
Customization Options:
- Select EMA length
- Choose between close or high as price input
- Set ADR and ATR periods
- Customize the label’s position, color, and transparency
- Use the chart's timeframe or a fixed timeframe
SSRO Z-ScoreSSRO Z-Score Indicator — Description
What it does:
This indicator measures the Stablecoin Supply Ratio (SSR) relative to Bitcoin’s market cap and calculates a normalized Z-Score of this ratio to help identify potential market tops and bottoms in the crypto market.
How it works:
The Stablecoin Supply Ratio (SSR) is calculated by dividing Bitcoin’s market capitalization by the combined market capitalization of major stablecoins (USDT, USDC, TUSD, DAI, FRAX).
The SSR is then smoothed over a user-defined lookback period to reduce noise.
A Z-Score is computed by normalizing the SSR over a specified moving window, which shows how far the current SSR deviates from its historical average in terms of standard deviations.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter short-term volatility.
How to read the Z-Score:
Z-Score = 0: SSR is at its historical average.
Z-Score > 0: SSR is above average, indicating Bitcoin’s market cap is relatively high compared to stablecoin supply, potentially signaling bullish market conditions.
Z-Score < 0: SSR is below average, indicating stablecoin supply is high relative to Bitcoin’s market cap, possibly signaling bearish pressure or increased liquidity waiting to enter the market.
Upper and Lower Bands: These user-defined levels (e.g., +2 and -2) represent thresholds for extreme conditions. Values above the upper band may indicate overbought or overheated market conditions, while values below the lower band may indicate oversold or undervalued conditions.
Additional Features:
A dynamic table displays a linear scaled Z-Score alongside the main plot, clamped between -2 and +2 relative to the upper and lower bands for intuitive interpretation.
Usage Tips:
Combine the SSRO Z-Score with other technical indicators or volume analysis for more reliable signals.
Look for divergence between price and Z-Score extremes as potential reversal signals.
Context MTF [Th16rry]Context MTF
A multi-timeframe trend context indicator that overlays an Exponential Moving Average (EMA) and a Weighted Moving Average (WMA) whose look-back periods adapt automatically to your chart’s timeframe. Inspired by Mike Bellafore and Brian Shannon (Multi timeframe analysis)
🔍 Overview
Context MTF helps you quickly gauge the prevailing trend and its strength by plotting two complementary moving averages in a single view:
* EMA (solid line) for smooth, responsive trend direction
* WMA (dotted line) for emphasis on recent price action
By automatically selecting period lengths that reflect meaningful market cycles, Context MTF provides intuitive context at a glance:
| Timeframe | Period | Market Cycle Represented |
| :--------: | :----: | :----------------------: |
| Daily (D) | 63 | Quarterly trend |
| Weekly (W) | 52 | Yearly trend |
| 1H (60) | 126 | Monthly trend |
| 15m (15) | 130 | Weekly trend |
| 5m (5) | 78 | Last 24 hours |
⚙️ How It Works
1. Automatic Period Selection
The script detects your chart’s timeframe and applies the appropriate look-back for both EMA and WMA.
2. Solid vs. Dotted
* EMA is drawn as a continuous solid line.
* WMA is rendered as a dotted line of the same color, highlighting short-term momentum within the broader trend.
3. Visual Trend Context
* Widening Gap : Indicates strengthening trend momentum.
* Convergence/Overlap : Suggests a market in consolidation or range.
🎯 Benefits
* Multi-Timeframe Context in a single pane—no need to switch charts.
* Instant trend strength assessment by comparing EMA vs. WMA divergence.
* Clear identification of range conditions when averages align.
* Fully automated period adjustment —set and forget.
⚙️ Settings
* Color : Shared color for both lines (default blue).
* Line Width : Adjustable via script inputs (default 2).
* Dotted WMA : Simulated using built-in dotted line styling for precise rendering.
Use Context MTF to enhance trend-based strategies, confirm breakout momentum, or filter ranging markets. Ideal for swing traders, day traders, and anyone who values clear, time-aligned trend information on every timeframe.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
Gamma + Fibonacci EMA Bands# Gamma + Fibonacci EMA Bands
## Overview
The Gamma + Fibonacci EMA Bands indicator combines two powerful analytical approaches: Gamma-weighted Exponential Moving Averages and Fibonacci sequence-based standard EMAs. This dual system creates a comprehensive "band" structure that helps identify trend direction, strength, and potential reversal zones with greater precision than single moving average systems.
## Features
- **Gamma-weighted EMAs**: Three customizable Gamma EMAs (fast-responding) with adjustable gamma parameters
- **Fibonacci Sequence EMAs**: Six standard EMAs based on the Fibonacci sequence (34, 55, 89, 144, 233, 377)
- **Visual Band Structure**: Color-coded for instant visual analysis
- **Trend Confirmation**: Multiple timeframe validation through varied moving average periods
- **Support/Resistance Identification**: Natural price reaction zones highlighted by EMA confluences
## How It Works
The indicator uses two complementary EMA systems:
1. **Gamma EMAs** (γ-EMAs) - These responsive moving averages use a direct gamma weighting factor (between 0-1) rather than a period length. Lower gamma values create smoother lines, while higher values create more responsive ones. These react quickly to price changes and serve as short-term trend indicators.
2. **Fibonacci EMAs** - These traditional EMAs use period lengths based on the Fibonacci sequence (34, 55, 89, 144, 233, 377). They provide longer-term trend context and naturally identify key support/resistance levels that align with market psychology.
## Interpretation
### Trend Direction
- When price is above all bands: Strong bullish trend
- When price is below all bands: Strong bearish trend
- When price is between bands: Consolidation or trend transition
### Support/Resistance
- Gamma EMAs (purple shades): Short-term dynamic support/resistance
- Fibonacci EMAs (orange/red shades): Stronger, longer-term support/resistance
### Trend Strength
- Wider band separation: Stronger trend momentum
- Compressed bands: Consolidation or trend weakness
### Reversal Signals
- Price breaking through multiple bands: Potential trend reversal
- Gamma EMAs crossing Fibonacci EMAs: Changing momentum
## Settings
- **Source**: Price data source (default: close)
- **Gamma 1**: Fast γ-EMA value (default: 0.2)
- **Gamma 2**: Medium γ-EMA value (default: 0.5)
- **Gamma 3**: Slow γ-EMA value (default: 0.8)
## Notes
This indicator works best on higher timeframes (1H+) and liquid markets. The Gamma-weighted EMAs provide faster signals while the Fibonacci sequence EMAs provide reliable support/resistance levels that often align with key market turning points.
For optimal use, watch for price interaction with these bands and how the bands interact with each other to confirm trend changes before they become obvious to the majority of market participants.
Multiple (12) Strong Buy/Sell Signals + Momentum
Indicator Manual: "Multiple (12) Strong Buy/Sell Signals + Momentum"
This indicator is designed to identify strong buy and sell signals based on 12 configurable conditions, which include a variety of technical analysis methods such as trend-following indicators, pattern recognition, volume analysis, and momentum oscillators. It allows for customizable alerts and visual cues on the chart. The indicator helps traders spot potential entry and exit points by displaying buy and sell signals based on the selected conditions.
Key Observations:
• The script integrates multiple indicators and pattern recognition methods to provide comprehensive buy/sell signals.
• Trend-based indicators like EMAs and MACD are combined with pattern recognition (flags, triangles) and momentum-based signals (RSI, ADX, and volume analysis).
• User customization is a core feature, allowing adjustments to the conditions and thresholds for more tailored signals.
• The script is designed to be responsive to market conditions, with multiple conditions filtering out noise to generate reliable signals.
________________________________________
Key Features:
1. 12 Combined Buy/Sell Signal Conditions: This indicator incorporates a diverse set of conditions based on trend analysis, momentum, and price patterns.
2. Minimum Conditions Input: You can adjust the threshold of conditions that need to be met for the buy/sell signals to appear.
3. Alert Customization: Set alert thresholds for both buy and sell signals.
4. Dynamic Visualization: Buy and sell signals are shown as triangles on the chart, with momentum signals highlighted as circles.
________________________________________
Detailed Description of the 12 Conditions:
1. Exponential Moving Averages (EMA):
o Conditions: The indicator uses EMAs with periods 3, 8, and 13 for quick trend-following signals.
o Bullish Signal: EMA3 > EMA8 > EMA13 (Bullish stack).
o Bearish Signal: EMA3 < EMA8 < EMA13 (Bearish stack).
o Reversal Signal: The crossing over or under of these EMAs can signify trend reversals.
2. MACD (Moving Average Convergence Divergence):
o Fast MACD (2, 7, 3) is used to confirm trends quickly.
o Bullish Signal: When the MACD line crosses above the signal line.
o Bearish Signal: When the MACD line crosses below the signal line.
3. Donchian Channel:
o Tracks the highest high and lowest low over a given period (default 20).
o Breakout Signal: Price breaking above the upper band is bullish; breaking below the lower band is bearish.
4. VWAP (Volume-Weighted Average Price):
o Above VWAP: Bullish condition (price above VWAP).
o Below VWAP: Bearish condition (price below VWAP).
5. EMA Stacking & Reversal:
o Tracks the order of EMAs (3, 8, 13) to confirm strong trends and reversals.
o Bullish Reversal: EMA3 < EMA8 < EMA13 followed by a crossing to bullish.
o Bearish Reversal: EMA3 > EMA8 > EMA13 followed by a crossing to bearish.
6. Bull/Bear Flags:
o Bull Flag: Characterized by a strong price movement (flagpole) followed by a pullback and breakout.
o Bear Flag: Similar to Bull Flag but in the opposite direction.
7. Triangle Patterns (Ascending and Descending):
o Detects ascending and descending triangles using pivot highs and lows.
o Ascending Triangle: Higher lows and flat resistance.
o Descending Triangle: Lower highs and flat support.
8. Volume Sensitivity:
o Identifies price moves with significant volume increases.
o High Volume: When current volume is significantly above the moving average volume (set to 1.2x of the average).
9. Momentum Indicators:
o RSI (Relative Strength Index): Confirms overbought and oversold levels with thresholds set at 65 (overbought) and 35 (oversold).
o ADX (Average Directional Index): Confirms strong trends when ADX > 28.
o Momentum Up: Momentum is upward with strong volume and bullish RSI/ADX conditions.
o Momentum Down: Momentum is downward with strong volume and bearish RSI/ADX conditions.
10. Bollinger & Keltner Squeeze:
o Squeeze Condition: A contraction in both Bollinger Bands and Keltner Channels indicates low volatility, signaling a potential breakout.
o Squeeze Breakout: Price breaking above or below the squeeze bands.
11. 3 Consecutive Candles Condition:
o Bullish: Price rises for three consecutive candles with higher highs and lows.
o Bearish: Price falls for three consecutive candles with lower highs and lows.
12. Williams %R and Stochastic RSI:
o Williams %R: A momentum oscillator with signals when the line crosses certain levels.
o Stochastic RSI: Provides overbought/oversold levels with smoother signals.
o Combined Signals: You can choose whether to require both WPR and StochRSI to signal a buy/sell.
________________________________________
User Inputs (Inputs Tab):
1. Minimum Conditions for Buy/Sell:
o min_conditions: Number of conditions required to trigger a buy/sell signal on the chart (1 to 12).
o Alert_min_conditions: User-defined alert threshold (how many conditions must be met before an alert is triggered).
2. Donchian Channel Settings:
o Show Donchian: Toggle visibility of the Donchian channel.
o Donchian Length: The length of the Donchian Channel (default 20).
3. Bull/Bear Flag Settings:
o Bull Flag Flagpole Strength: ATR multiplier to define the strength of the flagpole.
o Bull Flag Pullback Length: Length of pullback for the bull flag pattern.
o Bull Flag EMA Length: EMA length used to confirm trend during bull flag pattern.
Similar settings exist for Bear Flag patterns.
4. Momentum Indicators:
o RSI Length: Period for calculating the RSI (default 9).
o RSI Overbought: Overbought threshold for the RSI (default 65).
o RSI Oversold: Oversold threshold for the RSI (default 35).
5. Bollinger/Keltner Squeeze Settings:
o Squeeze Width Threshold: The maximum width of the Bollinger and Keltner Bands for squeeze conditions.
6. Stochastic RSI Settings:
o Stochastic RSI Length: The period for calculating the Stochastic RSI.
7. WPR Settings:
o WPR Length: Period for calculating Williams %R (default 14).
________________________________________
User Inputs (Style Tab):
1. Signal Plotting:
o Control the display and colors of the buy/sell signals, momentum indicators, and pattern signals on the chart.
o Buy/Sell Signals: Can be customized with different colors and shapes (triangle up for buys, triangle down for sells).
o Momentum Signals: Custom circle placement for momentum-up or momentum-down signals.
2. Donchian Channel:
o Show Donchian: Toggle visibility of the Donchian upper, lower, and middle bands.
o Band Colors: Choose the color for each band (upper, lower, middle).
________________________________________
How to Use the Indicator:
1. Adjust Minimum Conditions: Set the minimum number of conditions that must be met for a signal to appear. For example, set it to 5 if you want only stronger signals.
2. Set Alert Threshold: Define the number of conditions needed to trigger an alert. This can be different from the minimum conditions for visual signals.
3. Customize Appearance: Modify the colors and styles of the signals to match your preferences.
________________________________________
Conclusion:
This comprehensive trading indicator uses a combination of trend-following, pattern recognition, and momentum-based conditions to help you spot potential buy and sell opportunities. By adjusting the input settings, you can fine-tune it to match your specific trading strategy, making it a versatile tool for different market conditions.
Signal Reliability Based on Condition Count
The reliability of the buy/sell signals increases as more conditions are met. Here's a breakdown of the probabilities:
1. 1-3 Conditions Met: Lower Probability
o Signals that meet only 1-3 conditions tend to have lower reliability and are considered less probable. These signals may represent false positives or weaker market movements, and traders should approach them with caution.
2. 4 Conditions Met: More Reliable Signal
o When 4 conditions are met, the signal becomes more reliable. This indicates that multiple indicators or market patterns are aligning, increasing the likelihood of a valid buy/sell opportunity. While not foolproof, it's a stronger indication that the market may be moving in a particular direction.
3. 5-6 Conditions Met: Strong Signal
o A signal meeting 5-6 conditions is considered a strong signal. This indicates a well-confirmed move, with several technical indicators and market factors aligning to suggest a higher probability of success. These are the signals that traders often prioritize.
4. 7+ Conditions Met: Rare and High-Confidence Signal
o Signals that meet 7 or more conditions are rare and should be considered high-confidence signals. These represent a significant alignment of multiple factors, and while they are less frequent, they are highly reliable when they do occur. Traders can be more confident in acting on these signals, but they should still monitor market conditions for confirmation.
________________________________________
You can adjust the number of conditions as needed, but this breakdown should give a clear structure on how the signal strength correlates with the number of conditions met!
DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB
🛠️ Overview
DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core.
DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals.
🔍 How It Works
1️⃣ Double Exponential Moving Average (DEMA)
The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum.
2️⃣ Gaussian Filtering
A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure.
3️⃣ Recursive Moving Average (RMA) Core
The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic.
4️⃣ ATR-Scaled Breakout Zones
Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility.
• ✅ Long Signal when price closes above the upper envelope
• ❌ Short Signal when price closes below the lower envelope
• ➖ Neutral when inside the band (no signal noise)
✨ Key Features
🔹 Multi-Layer Trend Model
DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust.
🔹 Volatility-Aware Entry System
Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods.
🔹 Noise-Reducing Gaussian Kernel
Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag.
🔹 Clean Visual System
Candle coloring and band fills make trend state easy to read and act on at a glance.
⚙️ Custom Settings
• DEMA Source – Input source for trend core (default: close)
• DEMA Length – Length for initial smoothing (default: 30)
• Gaussian Filter Length – Determines smoothing depth (default: 4)
• Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0)
• RMA Length – Core baseline smoothing (default: 12)
• ATR Length – Volatility detection period (default: 40)
• ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7)
📌 How to Use
1️⃣ Trend-Following Mode
• Go Long when price closes above the upper ATR band
• Go Short when price closes below the lower ATR band
• Remain neutral otherwise
2️⃣ Breakout Confirmation Tool
DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges.
3️⃣ Volatility Monitoring
Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts.
📌 Conclusion
DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness.
Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable.
🔹 Summary
• ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core
• ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws
• ✅ Fully Customizable → Tailor to any asset or timeframe
• ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
