Multi-Timeframe Trend Detector [Alifer]Here is an easy-to-use and customizable multi-timeframe visual trend indicator.
The indicator combines Exponential Moving Averages (EMA), Moving Average Convergence Divergence (MACD), and Relative Strength Index (RSI) to determine the trend direction on various timeframes: 15 minutes (15M), 30 minutes (30M), 1 hour (1H), 4 hours (4H), 1 day (1D), and 1 week (1W).
EMA Trend : The script calculates two EMAs for each timeframe: a fast EMA and a slow EMA. If the fast EMA is greater than the slow EMA, the trend is considered Bullish; if the fast EMA is less than the slow EMA, the trend is considered Bearish.
MACD Trend : The script calculates the MACD line and the signal line for each timeframe. If the MACD line is above the signal line, the trend is considered Bullish; if the MACD line is below the signal line, the trend is considered Bearish.
RSI Trend : The script calculates the RSI for each timeframe. If the RSI value is above a specified Bullish level, the trend is considered Bullish; if the RSI value is below a specified Bearish level, the trend is considered Bearish. If the RSI value is between the Bullish and Bearish levels, the trend is Neutral, and no arrow is displayed.
Dashboard Display :
The indicator prints arrows on the dashboard to represent Bullish (▲ Green) or Bearish (▼ Red) trends for each timeframe.
You can easily adapt the Dashboard colors (Inputs > Theme) for visibility depending on whether you're using a Light or Dark theme for TradingView.
Usage :
You can adjust the indicator's settings such as theme (Dark or Light), EMA periods, MACD parameters, RSI period, and Bullish/Bearish levels to adapt it to your specific trading strategies and preferences.
Disclaimer :
This indicator is designed to quickly help you identify the trend direction on multiple timeframes and potentially make more informed trading decisions.
You should consider it as an extra tool to complement your strategy, but you should not solely rely on it for making trading decisions.
Always perform your own analysis and risk management before executing trades.
The indicator will only show a Dashboard. The EMAs, RSI and MACD you see on the chart image have been added just to demonstrate how the script works.
DETAILED SCRIPT EXPLANATION
INPUTS:
theme : Allows selecting the color theme (options: "Dark" or "Light").
emaFastPeriod : The period for the fast EMA.
emaSlowPeriod : The period for the slow EMA.
macdFastLength : The fast length for MACD calculation.
macdSlowLength : The slow length for MACD calculation.
macdSignalLength : The signal length for MACD calculation.
rsiPeriod : The period for RSI calculation.
rsiBullishLevel : The level used to determine Bullish RSI condition, when RSI is above this value. It should always be higher than rsiBearishLevel.
rsiBearishLevel : The level used to determine Bearish RSI condition, when RSI is below this value. It should always be lower than rsiBullishLevel.
CALCULATIONS:
The script calculates EMAs on multiple timeframes (15-minute, 30-minute, 1-hour, 4-hour, daily, and weekly) using the request.security() function.
Similarly, the script calculates MACD values ( macdLine , signalLine ) on the same multiple timeframes using the request.security() function along with the ta.macd() function.
RSI values are also calculated for each timeframe using the request.security() function along with the ta.rsi() function.
The script then determines the EMA trends for each timeframe by comparing the fast and slow EMAs using simple boolean expressions.
Similarly, it determines the MACD trends for each timeframe by comparing the MACD line with the signal line.
Lastly, it determines the RSI trends for each timeframe by comparing the RSI values with the Bullish and Bearish RSI levels.
PLOTTING AND DASHBOARD:
Color codes are defined based on the EMA, MACD, and RSI trends for each timeframe. Green for Bullish, Red for Bearish.
A dashboard is created using the table.new() function, displaying the trend information for each timeframe with arrows representing Bullish or Bearish conditions.
The dashboard will appear in the top-right corner of the chart, showing the Bullish and Bearish trends for each timeframe (15M, 30M, 1H, 4H, 1D, and 1W) based on EMA, MACD, and RSI analysis. Green arrows represent Bullish trends, red arrows represent Bearish trends, and no arrows indicate Neutral conditions.
INFO ON USED INDICATORS:
1 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
2 — MOVING AVERAGE CONVERGENCE DIVERGENCE (MACD)
The Moving Average Convergence Divergence (MACD) is a popular trend-following momentum indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a financial instrument's price.
The MACD is calculated by subtracting a longer-term Exponential Moving Average (EMA) from a shorter-term EMA. The most commonly used time periods for the MACD are 26 periods for the longer EMA and 12 periods for the shorter EMA. The difference between the two EMAs creates the main MACD line.
Additionally, a Signal Line (usually a 9-period EMA) is computed, representing a smoothed version of the MACD line. Traders watch for crossovers between the MACD line and the Signal Line, which can generate buy and sell signals. When the MACD line crosses above the Signal Line, it generates a bullish signal, indicating a potential uptrend. Conversely, when the MACD line crosses below the Signal Line, it generates a bearish signal, indicating a potential downtrend.
In addition to the MACD line and Signal Line crossovers, traders often look for divergences between the MACD and the price chart. Divergence occurs when the MACD is moving in the opposite direction of the price, which can suggest a potential trend reversal.
3 — RELATIVE STRENGHT INDEX (RSI):
The Relative Strength Index (RSI) is another popular momentum oscillator used by traders to assess the overbought or oversold conditions of a financial instrument. The RSI ranges from 0 to 100 and measures the speed and change of price movements.
The RSI is calculated based on the average gain and average loss over a specified period, commonly 14 periods. The formula involves several steps:
Calculate the average gain over the specified period.
Calculate the average loss over the specified period.
Calculate the relative strength (RS) by dividing the average gain by the average loss.
Calculate the RSI using the following formula: RSI = 100 - (100 / (1 + RS))
The RSI oscillates between 0 and 100, where readings above 70 are considered overbought, suggesting that the price may have risen too far and could be due for a correction. Readings below 30 are considered oversold, suggesting that the price may have dropped too much and could be due for a rebound.
Traders often use the RSI to identify potential trend reversals. For example, when the RSI crosses above 30 from below, it may indicate the start of an uptrend, and when it crosses below 70 from above, it may indicate the start of a downtrend. Additionally, traders may look for bullish or bearish divergences between the RSI and the price chart, similar to the MACD analysis, to spot potential trend changes.
Wyszukaj w skryptach "moving averages"
Volume Channel - [With Volume Filter]The indicator calculates two volume-weighted moving averages (VWMA) using different lengths, and filters them based on a moving average of volume. The filtered VWMA values are then plotted on the chart as lines, representing the fast and slow moving averages. In addition, upper and lower bands are calculated based on the slow VWMA and plotted as lines on the chart.
The fast and slow VWMA lines can be used to identify trends in the market. When the fast VWMA is above the slow VWMA, it is an indication of an uptrend, and when the fast VWMA is below the slow VWMA, it is an indication of a downtrend. The position of the VWMA lines relative to the upper and lower bands can also be used to identify potential trade signals.
When the price is near the upper band, it indicates that the market is overbought, and when the price is near the lower band, it indicates that the market is oversold. Traders can use these signals to enter or exit trades.
The indicator also includes a volume filter, which means that the VWMA values are only calculated when the volume is above a certain moving average of volume. This helps to filter out noise in the market and provide more accurate signals.
Explanation for each parameter
vwmaLength1: This is the length of the fast volume-weighted moving average (VWMA) used in the calculation. The default value is 10, and it can be adjusted by the user.
vwmaLength2: This is the length of the slow volume-weighted moving average (VWMA) used in the calculation. The default value is 25, and it can be adjusted by the user.
bandLength: This is the length of the moving average used to calculate the upper and lower bands. The default value is 34, and it is not adjustable by the user.
volumeFilterLength: This is the length of the moving average of volume used as a filter for the VWMA calculation. The default value is 5, and it can be adjusted by the user.
src: This is the input source for the VWMA calculation. The default value is close, which means the indicator is using the closing price of each bar. However, the user can select a different input source by changing this parameter.
filteredVwma1: This is the filtered VWMA calculated based on the volume filter and the fast VWMA length. It is plotted as a line on the chart and can be used to identify short-term trends.
filteredVwma2: This is the filtered VWMA calculated based on the volume filter and the slow VWMA length. It is plotted as a line on the chart and can be used to identify long-term trends.
ma: This is the moving average of the filtered slow VWMA values, which is used to calculate the upper and lower bands. It is plotted as a line on the chart.
offs: This is the offset used to calculate the upper and lower bands. It is based on the standard deviation of the filtered slow VWMA values and is multiplied by 1.6185 * 3. It is plotted as a line on the chart.
up: This is the upper band calculated as the moving average plus the offset. It is plotted as a line on the chart and can be used to identify overbought conditions.
dn: This is the lower band calculated as the moving average minus the offset. It is plotted as a line on the chart and can be used to identify oversold conditions.
Bitcoin CycleThis script displays 4 different Moving Averages:
2 Year Moving Average (White)
1 Year Moving Average (Doubled in value, Red)
116 Day Moving Average (Transparent, Red)
232 Day Moving Average (Transparent, White)
For the last cycles: once the 2 year MA crossed the 232 Day MA, it marked the cycle bottom within a few days and once the 1 year MA (x2) crossed the 116 Day MA, it marked the cycle top within a few days.
It is interesting to note that both 365/116 and 730/232 equal 3.1465, which is very close to Pi (3.142). It is actually the closest we can get to Pi when dividing 365 by another whole number.
Reversal off EMA-XsEMA-Xs works mostly on Forex due to the small prices and price fluctuations. It does work on Gold, oddly enough, and some others like UKX 100...but mostly on forex. It doesn't work as well on JPY pairs but occasionally does; the JPY pairs give less signals, but when a JPY pair gives a signal, its a high probability setup. Another script EMA-XL works better on the higher priced instruments like S&P, DJI, OIL, BTC etc.
This script will show 3 moving averages: 13, 34, 200 and works on the 5m, 1hr, 4hr, daily charts. Signals "B" or "S" will be on the chart above or below the candles respectively.
When to open:
The script gives buy and sell signals based on a counter-trend move away from the MA's. When the price rises a specific percent above/below the EMA, it'll give a signal. It's best to take a trade when it gives a cluster of consecutive signals near the same price. If using on the 5m, definitely wait for consecutive signals. Also, use this in conjunction with support and resistance areas. Using with fibs for confirmation really makes this a good tool with high probability: IE, when price hits a fib and the script gives a signal, its a high probability setup.
When to close:
1. After a fast move up/down you may use this to counter trade a scalp 10+ pips, but you need to be quick; applies mostly to the 5m chart.
2. If you have the tenacity wait until you see an opposite signal. With this method you may be holding a loosing trade for a while. But what I've noticed is if it trends against you, price usually with come near to the first time it signaled. You may want to stack trades on each cluster of signals. IE first trade is 1000 units, next is 2000 units, etc... then close when prices comes near the first time it signaled. By this time, if you held, you should have profit. This strategy will really test your mental resilience.
3. Wait until it comes back to one of the trendlines; remember this is a counter trend signal so price is moving away from the MA and it always returns to touch one of the MA's...LOL eventually
4. Applying to scalping on the 5m, keep the stops tight because if the instrument trends hard and fast, you'll be upside-down quickly.
If you put a lot of time into using this signal generator, you can really make good profit. But with all tools, you need to master it. There are nuances to the simple logic of this script that can be both fun and frustrating. With all endeavors, if you put the time into it, you will reap the rewards.
Good luck and let me know if you have any questions/comments.
CCI 5 LEVELS BY MOADThe Commodity Channel Index ( CCI ) is a momentum oscillator used in technical analysis primarily to identify overbought and oversold levels by measuring an instrument's variations away from its statistical mean. Besides overbought/oversold levels, CCI is often used to find reversals as well as divergences. Originally, the indicator was designed to be used for identifying trends in commodities , however it is now used in a wide range of financial instruments.
There are several steps involved in calculating the CCI . The following example is for a typical 14 Period CCI:
CCI = (Typical Price - 14 Period SMA of TP) / (.015 x Mean Deviation)
Typical Price (TP) = (High + Low + Close)/3
Constant = .015
The Constant is set at .015 for scaling purposes. By including the constant, the majority of CCI values will fall within the 100 to -100 range.
Mean Deviation:
1) Subtract the most recent 14 Period Simple Moving from each typical price (TP) for the Period.
2) Sum these numbers strictly using absolute values.
3) Divide the value generated in step 2 by the total number of Periods (14 in this case).
Overbought and Oversold conditions can be used in their more traditional sense to identify future reversals. Remember true overbought/oversold thresholds values can and often do vary between instruments.
During a Bullish Trend, price crossing above the overbought threshold may indicate strong confidence in the move and price will continue to rise.
During a Bearish Trend, price crossing below the oversold threshold may indicate strong confidence in the move and price will continue to fall.
The first option is a modified CCI indicator that uses the "Arnaud Legoux Moving Average" instead of the SMA , and the source uses the VWAP instead of the HLC3. Added to this version an option to calculate CCI with different types of moving averages:
Green dots mean they are overbought
Orange dots mean they are oversold
Added a "SuperTrend Background" based on the modified CCI indicator:
Bull event = CCI crossing over the 0 line
Bear event = CCI crossing below the 0 line
Added a signal as EMA (modified CCI , signal length)
The second option is a standard CCI indicator that shows a coloured histogram of important levels, giving a good visual of the CCI levels. Added to this version is an extra coloured level +/-200 and an option to use Traditional CCI calculations according to user @JustUncleL
LEVELS:
Aqua: Greater than 200.
Lavender: Greater than 100 and less than 200.
Dark Lavender: Greater than 0 and less than 100.
Dark Coral: Less than 0 and greater than -100.
Coral: Less than -100 and greater than -200.
Light Red: Less than -200.
Double CCIThe Commodity Channel Index (CCI) is a momentum oscillator used in technical analysis primarily to identify overbought and oversold levels by measuring an instrument's variations away from its statistical mean. Besides overbought/oversold levels, CCI is often used to find reversals as well as divergences. Originally, the indicator was designed to be used for identifying trends in commodities, however it is now used in a wide range of financial instruments.
There are several steps involved in calculating the CCI. The following example is for a typical 14 Period CCI:
CCI = (Typical Price - 14 Period SMA of TP) / (.015 x Mean Deviation)
Typical Price (TP) = (High + Low + Close)/3
Constant = .015
The Constant is set at .015 for scaling purposes. By including the constant, the majority of CCI values will fall within the 100 to -100 range.
Mean Deviation:
1) Subtract the most recent 14 Period Simple Moving from each typical price (TP) for the Period.
2) Sum these numbers strictly using absolute values.
3) Divide the value generated in step 2 by the total number of Periods (14 in this case).
Overbought and Oversold conditions can be used in their more traditional sense to identify future reversals . Remember true overbought/oversold thresholds values can and often do vary between instruments.
During a Bullish Trend , price crossing above the overbought threshold may indicate strong confidence in the move and price will continue to rise.
During a Bearish Trend , price crossing below the oversold threshold may indicate strong confidence in the move and price will continue to fall.
The first option is a modified CCI indicator that uses the "Arnaud Legoux Moving Average" instead of the SMA, and the source uses the VWAP instead of the HLC3. Added to this version an option to calculate CCI with different types of moving averages:
Green dots mean they are overbought
Orange dots mean they are oversold
Added a "SuperTrend Background" based on the modified CCI indicator:
Bull event = CCI crossing over the 0 line
Bear event = CCI crossing below the 0 line
Added a signal as EMA (modified CCI, signal length)
The second option is a standard CCI indicator that shows a coloured histogram of important levels, giving a good visual of the CCI levels. Added to this version is an extra coloured level +/-200 and an option to use Traditional CCI calculations according to user @JustUncleL
LEVELS:
Aqua: Greater than 200.
Lavender: Greater than 100 and less than 200.
Dark Lavender: Greater than 0 and less than 100.
Dark Coral: Less than 0 and greater than -100.
Coral: Less than -100 and greater than -200.
Light Red: Less than -200.
Zigzag CloudThis is Bollinger Band built on top of Zigzags instead of regular price + something more.
Indicator presents 7 lines and cloud around it. This can be used to visualize how low or high price is with respect to its past movement.
Middle line is moving average of last N zigzag pivots
Lines adjacent to moving average are also moving averages. But, they are made of only pivot highs and pivot lows. Means, line above moving average is pivot high moving average and line below moving average is pivot low moving average.
Lines after pivot high/low moving averages are upper and lower bolllinger bands based on Moving Average Line with 2 standard deviation difference.
Outermost lines are bollinger band top of Moving average pivot high and bollinger band bottom of moving average pivot low.
Ultimate Moving Average [CC+RedK]The Ultimate Moving Average was created by myself and @RedKTrader and I can proudly say that this is the holy grail of moving averages. Not only does this moving average react to the current price trends like a normal moving average but we have also included the ability to react to volume, momentum, and volatility. The only thing this moving average can't do is wash your car.
The Ultimate Moving Average doesn't even use a set length so it is fully adaptable to any type of market whether it is choppy or trending. It tightens during volatile markets and loosens during choppy markets. I have included 3 of the main moving averages of a fixed length of 20 days to show you just how much better our moving average is.
The overall concept of this moving average was to fully adapt to any and all changes of the underlying stock. We used my Variable Power Weighted Moving Average as a base and changed the script to adapt to momentum instead. The idea behind this was when momentum reaches an extreme in either direction we tighten the moving average to be able to react accordingly. We then used the idea behind my Variable Length Moving Average to be able to react to volatility and make the length itself into a separate variable.
All of this work combined to create the most reactive moving average out there and I guarantee you will be using this in your daily trading! Let me know if there are any other scripts you would like to see me publish.
MACD ReLoaded STRATEGYSTRATEGY version of MACD ReLOADED Indicator:
A different approach to Gerald Appel's classical Moving Average Convergence Divergence.
Appel originaly set MACD with exponential moving averages.
In this version users can apply 11 different types of moving averages which they can benefit from their smoothness and vice versa sharpnesses...
Built in Moving Average type defaultly set as VAR but users can choose from 11 different Moving Average types like:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average a.k.a. VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
In shorter time frames backtest results shows us TILL, WWMA, VIDYA (VAR) could be used to overcome whipsaws because they have less numbers of signals.
In longer time frames like daily charts WMA, Volume Weighted MACD V2, and MACDAS and SMA are more accurate according to backtest results.
My interpretation of Buff Dormeier's Volume Weighted MACD V2:
Thomas Aspray's MACD: (MACDAS)
MACD ReLoadedA different approach to Gerald Appel's classical Moving Average Convergence Divergence.
Appel originaly set MACD with exponential moving averages.
In this version users can apply 11 different types of moving averages which they can benefit from their smoothness and vice versa sharpnesses...
Built in Moving Average type defaultly set as VAR but users can choose from 11 different Moving Average types like:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average a.k.a. VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
In shorter time frames backtest results shows us TILL, WWMA, VIDYA (VAR) could be used to overcome whipsaws because they have less numbers of signals.
In longer time frames like daily charts WMA, Volume Weighted MACD V2, and MACDAS and SMA are more accurate according to backtest results.
My interpretation of Buff Dormeier's Volume Weighted MACD V2:
Thomas Aspray's MACD: (MACDAS)
RexDog Average with ATRBam-- look what Rex did. A RexDog Average with ATR bands-- he's going insane. Simple but powerful.
This indicator includes the RexDog average but provides you with the ability to plot (and customize) both above and below ATR calculated bands.
With this indicator you can display all 3 or any combination of the bands: the RexDog Avg, Adding ATR Upper or the Subtracting ATR Below.
To remove a plot or customize color and line size go to the style options.
Before we get detailed with this version you can customize the default average factor of the RexDog Avg (default is 6). More tips on this below.
How This Works
Just as with the RexDog Average we take the 6 ATR data points (200, 100, 50, 24, 9, 5). We then create an average by dividing by 6. But wait there's more...
With this indicator you can customize independently the above and below bands via a float value for precision. 6 is the default (you can customize by increments at 0.25 or input value you like 1-20).
Now this works opposite how you might think but you'll get it once you start changing the numbers. For instance, editing the above band lowering the ATR factor will raise the band.
RexDog Avg Factor
With this release you are able to change the default average factor (6) to anything you want. You'll find though going too high or low from the default won't get the best results. The default increment change is 0.1 but you can enter any float value you like between 1-20.
The Original RexDog Average Overview
Yes, simple—the RexDog Average is a bias moving average indicator. The purpose is to provide the overall momentum bias you should have when trading an instrument. It works across all markets and all timeframes.
Usage:
Price above the RexDog AVG = long momentum bias
Price below the RexDog AVG = short momentum bias
With the ATR addition most likely your usage will be similar to Bollinger Bands. While not the same as in deviations much of the same principles might apply, especially with customization.
*Note: we have banned the word “trend” in the RexDog Trading Method.
Additional Usage Advice:
If price rips through the average your momentum bias should probably change. 80% of the time when price moves through the RexDog Average it will come back and test the area around average within 1-2 bars. 20% of the time it does not. The momentum is so strong in that direction so look for a 50-70% tests of the bar that impulse through the RexDog Average.
If you are using the RexDog Trading Method by default if the price is above the average and you are short you are in a fade trade. The momentum trade would be long. Of course reverse if price is below.
On multiple time frames. Of course, one timeframe can be long bias and a lower timeframe can be short bias. Which one do you use? Both—if your in a short trade using lower timeframe and with the bias of the average your in a momentum trade—but on the higher timeframe your aware you are essential fading the overall momentum.
Background:
Rex and I searched high and low for one simple thing. A moving average (or combination of some) that we could use to form our momentum bias that worked for all timeframes and all markets we trade.
We tried and tested them all. Even went down the path of ribbons and various other types of hybrid EMA /MA derivatives. Nothing had a high enough accuracy or mathematically was reliable that we could say with a high probability that it was on the right side of the momentum.
We almost stopped and landed on using the true and tested 200 MA—but we found through extensive tests that using the 200MA or EMA you’re often late to the party. Look you don’t need to be the first one in the trade but having a heads up sure helps.
To quote one of the best financial movies of the modern era—Margin Call:
“There are three ways to make a living in this business: be first, be smarter, or cheat… it sure is a hell of a lot easier to be first”. The RexDog Average used properly enables you to be first or damn near close.
Under the Hood:
This is so simple most reading this will discount it. You might even scoff and berate Rex for wasting your time. But you would be wrong. The RexDog Average has been tested across all markets—FOREX, Crypto, Equities, Futures (even tick charts), and even the Penguin population in Antarctica.
The RexDog Average is an average of 6 simple moving averages: 200, 100, 50, 24, 9, 5.
Yes, that’s it.
RexDog AverageYes, simple—the RexDog Average is a bias moving average indicator. The purpose is to provide the overall momentum bias you should have when trading an instrument. It works across all markets and all timeframes.
Usage:
Price above the RexDog AVG = long momentum bias
Price below the RexDog AVG = short momentum bias
*Note: we have banned the word “trend” in the RexDog Trading Method.
Additional Usage Advice:
If price rips through the average your momentum bias should probably change. 80% of the time when price moves through the RexDog Average it will come back and test the area around average within 1-2 bars. 20% of the time it does not. The momentum is so strong in that direction so look for a 50-70% tests of the bar that impulse through the RexDog Average.
If you are using the RexDog Trading Method by default if the price is above the average and you are short you are in a fade trade. The momentum trade would be long. Of course reverse if price is below.
On multiple time frames. Of course, one timeframe can be long bias and a lower timeframe can be short bias. Which one do you use? Both—if your in a short trade using lower timeframe and with the bias of the average your in a momentum trade—but on the higher timeframe your aware you are essential fading the overall momentum.
Background:
Rex and I searched high and low for one simple thing. A moving average (or combination of some) that we could use to form our momentum bias that worked for all timeframes and all markets we trade.
We tried and tested them all. Even went down the path of ribbons and various other types of hybrid EMA/MA derivatives. Nothing had a high enough accuracy or mathematically was reliable that we could say with a high probability that it was on the right side of the momentum.
We almost stopped and landed on using the true and tested 200 MA—but we found through extensive tests that using the 200MA or EMA you’re often late to the party. Look you don’t need to be the first one in the trade but having a heads up sure helps.
To quote one of the best financial movies of the modern era—Margin Call:
“There are three ways to make a living in this business: be first, be smarter, or cheat… it sure is a hell of a lot easier to be first”. The RexDog Average used properly enables you to be first or damn near close.
Under the Hood:
This is so simple most reading this will discount it. You might even scoff and berate Rex for wasting your time. But you would be wrong. The RexDog Average has been tested across all markets—FOREX, Crypto, Equities, Futures (even tick charts), and even the Penguin population in Antarctica.
The RexDog Average is an average of 6 simple moving averages: 200, 100, 50, 24, 9, 5.
Yes, that’s it.
The RexDog Average Plus will be released soon with additional parameters and most likely upper and lower bounds. In addition, we are working on a hybrid RexDog Exponential Average.
MAMA by EHLERSMESA Adaptive Moving Average aka: Mother of Adaptive Moving Averages:
The MESA Adaptive Moving Average ( MAMA ) adapts to price movement in an
entirely new and unique way. The adapation is based on the rate change of phase as
measured by the Hilbert Transform Discriminator I have previously described.1
The advantage of this method of adaptation is that it features a fast attack average and a
slow decay average so that composite average rapidly ratchets behind price changes
and holds the average value until the next ratchet occurs. The action of MAMA is
shown in Figure 1. Since the average fallback is slow I can build trading systems that
are virtually free of whipsaw trades.
For detailed information of MAMA: (creators' PDF document)
www.mesasoftware.com
Long condition: when MAMA Crosses over FAMA (Following Adaptive Moving Average )
Short condition: when FAMA Crosses over MAMA
(Personally modified LazyBear's version which was originally calculated in degrees instead of radian by applying explanations in the MESA pdf document.http://www.mesasoftware.com/papers/MAMA.pdf)
Creator: John EHLERS
MR.Z Strategy Reversal Signal Nadaraya SMA)Nadaraya-Watson Envelope (NW Envelope):
A smoothed, non-linear dynamic envelope that adapts to price structure. It visually identifies price extremes using kernel regression. The upper and lower bands move with the chart and provide reliable dynamic support and resistance.
EMA Levels:
Includes three key exponential moving averages:
EMA 50 (short-term trend)
EMA 100 (medium-term)
EMA 200 (long-term, institutional level)
Fully Scrollable and Responsive:
All lines and envelopes are plotted using plot() so they move with the chart and respond to zoom and pan actions naturally.
🧠 Ideal Use:
Identify reversal zones, dynamic support/resistance, and trend momentum exhaustion.
Combine WTB and NW Envelope for confluence-based entries.
Use EMA structure for trend confirmation or breakout anticipation.
Let me know if you'd like to add:
Divergence detection
Buy/Sell signals
Alerts or signal filtering options
I’ll be happy to extend the description or the script accordingly!
Moving Average Candles**Moving Average Candles — MA-Based Smoothed Candlestick Overlay**
This script replaces traditional price candles with smoothed versions calculated using various types of moving averages. Instead of plotting raw price data, each OHLC component (Open, High, Low, Close) is independently smoothed using your selected moving average method.
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### 📌 Features:
- Choose from 13 MA types: `SMA`, `EMA`, `RMA`, `WMA`, `VWMA`, `HMA`, `T3`, `DEMA`, `TEMA`, `KAMA`, `ZLEMA`, `McGinley`, `EPMA`
- Fully configurable moving average length (1–1000)
- Color-coded candles based on smoothed Open vs Close
- Works directly on price charts as an overlay
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### 🎯 Use Cases:
- Visualize smoothed market structure more clearly
- Reduce noise in price action for better trend analysis
- Combine with other indicators or strategies for confluence
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> ⚠️ **Note:** Since all OHLC values are based on moving averages, these candles do **not** represent actual market trades. Use them for trend and structure analysis, not trade entries based on precise levels.
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*Created to support traders seeking a cleaner visual representation of price dynamics.*
[blackcat] L2 FiboKAMA Adaptive TrendOVERVIEW
The L2 FiboKAMA Adaptive Trend indicator leverages advanced technical analysis techniques by integrating Fibonacci principles with the Kaufman Adaptive Moving Average (KAMA). This combination creates a dynamic and responsive tool designed to adapt seamlessly to changing market conditions. By providing clear buy and sell signals based on adaptive momentum, this indicator helps traders identify potential entry and exit points effectively. Its intuitive design and robust features make it a valuable addition to any trader’s arsenal 📊💹.
According to the principle of Kaufman's Adaptive Moving Average (KAMA), it is a type of moving average line specifically designed for markets with high volatility. Unlike traditional moving averages, KAMA can automatically adjust its period based on market conditions to improve accuracy and responsiveness. This makes it particularly useful for capturing market trends and reducing false signals in varying market environments.
The use of Fibonacci magic numbers (3, 8, 13) enhances the performance and accuracy of KAMA. These numbers have special mathematical properties that align well with the changing trends of KAMA moving averages. Combining them with KAMA can significantly boost its effectiveness, making it a popular choice among traders seeking reliable signals.
This fusion not only smoothens price fluctuations but also ensures quick responses to market changes, offering dependable entry and exit points. Thanks to the flexibility and precision of KAMA combined with Fibonacci magic numbers, traders can better manage risks and aim for higher returns.
FEATURES
Enhanced Kaufman Adaptive Moving Average (KAMA): Incorporates Fibonacci principles for improved adaptability:
Source Price: Allows customization of the price series used for calculation (default: HLCC4).
Fast Length: Determines the period for quicker adjustments to recent price changes.
Slow Length: Sets the period for smoother transitions over longer-term trends.
Dynamic Lines:
KAMA Line: A yellow line representing the primary adaptive moving average, which adapts quickly to new trends.
Trigger Line: A fuchsia line serving as a reference point for detecting crossovers and generating signals.
Visual Cues:
Buy Signals: Green 'B' labels indicating potential buying opportunities.
Sell Signals: Red 'S' labels signaling possible selling points.
Fill Areas: Colored regions between the KAMA and Trigger lines to visually represent trend directions and strength.
Alert Functionality: Generates real-time alerts for both buy and sell signals, ensuring timely notifications for actionable insights 🔔.
Customizable Parameters: Offers flexibility through adjustable inputs, allowing users to tailor the indicator to their specific trading strategies and preferences.
HOW TO USE
Adding the Indicator:
Open your TradingView chart and navigate to the indicators list.
Select L2 FiboKAMA Adaptive Trend and add it to your chart.
Configuring Parameters:
Adjust the Source Price to choose the desired price series (e.g., close, open, high, low).
Set the Fast Length to define how quickly the indicator responds to recent price movements.
Configure the Slow Length to determine the smoothness of long-term trend adaptations.
Interpreting Signals:
Monitor the chart for green 'B' labels indicating buy signals and red 'S' labels for sell signals.
Observe the colored fill areas between the KAMA and Trigger lines to gauge trend strength and direction.
Setting Up Alerts:
Enable alerts within the indicator settings to receive notifications whenever buy or sell signals are triggered.
Customize alert messages and frequencies according to your trading plan.
Combining with Other Tools:
Integrate this indicator with additional technical analysis tools and fundamental research for comprehensive decision-making.
Confirm signals using other indicators like RSI, MACD, or Bollinger Bands for increased reliability.
Optimizing Performance:
Backtest the indicator across various assets and timeframes to understand its behavior under different market conditions.
Fine-tune parameters based on historical performance and current market dynamics.
Integrating Magic Numbers:
Understand the basic principles of KAMA to find suitable entry points for Fibonacci magic numbers.
Utilize the efficiency ratio to measure market volatility and adjust moving average parameters accordingly.
Apply Fibonacci magic numbers (3, 8, 13) to enhance the responsiveness and accuracy of KAMA.
LIMITATIONS
Market Volatility: May produce false signals during periods of extreme volatility or sideways movement.
Parameter Sensitivity: Requires careful tuning of fast and slow lengths to balance responsiveness and stability.
Asset-Specific Behavior: Effectiveness can vary significantly across different financial instruments and time horizons.
Complementary Analysis: Should be used alongside other analytical methods to enhance accuracy and reduce risk.
NOTES
Historical Data: Ensure adequate historical data availability for precise calculations and backtesting.
Demo Testing: Thoroughly test the indicator on demo accounts before deploying it in live trading environments.
Continuous Learning: Stay updated with market trends and continuously refine your strategy incorporating feedback from the indicator's performance.
Risk Management: Always implement proper risk management practices regardless of the signals provided by the indicator.
ADVANCED USAGE TIPS
Multi-Timeframe Analysis: Apply the indicator across multiple timeframes to gain deeper insights into underlying trends.
Divergence Strategy: Look for divergences between price action and the KAMA line to spot potential reversals early.
Volume Integration: Combine volume analysis with the indicator to confirm the strength of identified trends.
Custom Scripting: Modify the script to include additional filters or conditions tailored to your unique trading approach.
IMPROVING KAMA PERFORMANCE
Increase Length: Extend the KAMA length to consider more historical data, reducing the impact of short-term price fluctuations.
Adjust Fast and Slow Lengths: Make KAMA smoother by increasing the fast length and decreasing the slow length.
Use Smoothing Factor: Apply a smoothing factor to control the level of smoothness; typical values range from 0 to 1.
Combine with Other Indicators: Pair KAMA with other smoothing indicators like EMA or SMA for more reliable signals.
Filter Noise: Use filters or other technical analysis tools to eliminate price noise, enhancing KAMA's effectiveness.