Smoothing R-Squared ComparisonIntroduction
Heyo guys, here I made a comparison between my favorised smoothing algorithms.
I chose the R-Squared value as rating factor to accomplish the comparison.
The indicator is non-repainting.
Description
In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price.
One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model.
This PineScript code implements a smoothing R-squared comparison indicator.
It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them.
The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement.
The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data.
The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal.
The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data.
The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal.
The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data.
The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal.
The input parameters for the EMA and SMA techniques include the length of the window used for smoothing.
The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data.
Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data.
Usage
You can use it to find the best fitting smoothing method for the timeframe you usually use.
Just apply it on your preferred timeframe and look for the highlighted table cell.
Conclusion
It seems like the T3 works best on timeframes under 4H.
There's where I am active, so I will use this one more in the future.
Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙♂️
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Credits to:
▪@loxx – T3
▪@balipour – Super Smoother
▪ChatGPT – Wrote 80 % of this article and helped with the research
Moving_average
Historical AverageThis indicator calculates the sum of all past candles for each new candle.
For the second candle of the chart, the indicator shows the average of the first two candles. For the 10th candle, it's the average of the last ten candles.
Simple Moving Averages (SMAa) calculate the average of a specific timeframe (e.g. SMA200 for the last 200 candles). The historical moving average is an SMA 2 at the second candle, an SMA3 for the third candle, an SMA10 for the tenth, an SMA200 for the 200th candle etc.
Settings:
You can set the multiplier to move the Historical Moving Average along the price axis.
You can show two Historical Moving Averages with different multipliers.
You can add fibonacci multipliers to the Historical Moving Average.
This indicator works best on charts with a lot of historical data.
Recommended charts:
INDEX:BTCUSD
BLX
But you can use it e.g. on DJI or any other chart as well.
Colorful Moving Averageswhat is Colorful Moving Averages?
This indicator allows you to use your favorite moving averages in their advanced form.
what it does?
It gives you easy access to the following information with a single indicator: the direction and momentum of the price,
rate of change of momentum (acceleration),
time-dependent change in momentum,
and all the other information a moving average provides.
it paints the selected moving average type according to the momentum it has, and also shows the momentum and acceleration values in a table. colors are interpreted as follows: the color of the moving average is red, the momentum is negative; A green color means the momentum is positive, and a yellow color means the momentum is 0. As the momentum changes, the moving average takes on different shades of these 3 colors. how it actually works can be easily understood at a glance.
"Δ" sign indicates momentum compressed between 100 and -100.
"Γ" sign indicates the momentum of the momentum, that is the acceleration. its values are compressed between 100 and -100.
how it does it?
it uses this formulas:
how to use it?
First, select the moving average type you want to use. then set the length and source. Now, with a single indicator, you can observe both the distance of the price from the mean, its instantaneous momentum relative to the last candle by looking at the symbol "Δ", the current change of momentum by looking at the symbol "Γ", and the time-dependent change in its momentum by looking at the colors. you can also see the maximum and minimum points where the momentum is equal to 0.
Mason’s Line IndicatorThe Macon Strategy is an idea conceived by Didier Darcet , co-founder of Gavekal Intelligence Software. Inspired by the Water Level, an instrument used by masons to check the horizontality or verticality of a wall. This method aims to measure the psychology of financial markets and determine if the market is balanced or tilting towards an unfavorable side, focusing on the behavioral risk of markets rather than economic or political factors.
The strategy examines the satisfaction and frustration of investors based on the distance between the low and high points of the market over a period of one year. Investor satisfaction is influenced by the current price of the index and the path taken to reach that price. The distance to the low point provides satisfaction, while the distance to the high point generates frustration. The balance between the two dictates investors’ desire to hold or sell their positions.
To refine the strategy, it is important to consider the opinion of a group of investors rather than just one individual. The members of a hypothetical investor club invest successively throughout the past year. The overall satisfaction of the market on a given day is a democratic expression of all participants.
If the overall satisfaction is below 50%, investors are frustrated and sell their positions. If it is above, they are satisfied and hold their positions. The position of the group of investors relative to the high and low points represents the position of the air bubble in the water level. Market performance is measured day by day based on participant satisfaction or dissatisfaction.
In conclusion, memory, emotions, and decision-making ability are closely linked, and their interaction influences investment decisions. The Macon Strategy highlights the importance of the behavioral dimension in understanding financial market dynamics. By studying investor behavior through this strategy, it is possible to better anticipate market trends and make more informed investment decisions.
Presentation of the Mason’s Line Indicator:
The main strategy of this indicator is to measure the average satisfaction of investors based on the position of an imaginary air bubble in a tube delimited by the market’s highs and lows over a given period. After calculating the satisfaction level, it is then normalized between 0 and 1, and a moving average can be used to visualize trends.
Key features:
Calculation of highs and lows over a user-defined period.
Determination of the position of the air bubble in the tube based on the closing price.
Calculation of the average satisfaction of investors over a selected period.
Normalization of the average satisfaction between 0 and 1.
Visualization of normalized or non-normalized average satisfaction levels, as well as their corresponding moving averages.
User parameters:
Period for min and max (days) : Sets the period over which highs and lows will be calculated (1 to 365 days).
Period for average satisfaction (days) : Determines the period over which the average satisfaction of investors will be calculated (1 to 365 days).
Period for SMA : Sets the period of the simple moving average used to smooth the data (1 to 1000 days).
Bubble_value : Adjustment of the air bubble value, ranging from 0 to 1, in increments of 0.025.
Normalized average satisfaction : Option to choose whether to display the normalized or non-normalized average satisfaction.
Please note that the Mason’s Line Indicator is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Rainbow Collection - VioletMoving averages come in all shapes and types. The most basic type is the simple moving average which is simply the sum divided by the quantity. Therefore, the simple moving average is the sum of the values divided by their number.
In technical analysis, you generally use moving averages to understand the underlying trend and to find trading signals. In the case of the Violet indicator, we are using a Hull moving average which is a special variation based on different weights to minimize lag.
The Violet indicator is therefore used as follows:
* A bullish signal is generated whenever the close price surpasses the 20-period Hull moving average while the previous close prices from periods were all below their respective Hull moving average of the period.
*A bearish signal is generated whenever the close price breaks the 20-period Hull moving average while the previous close prices from periods were all above their respective Hull moving average of the period.
The aim of the Violet indicator is to capture reversals as early as possible through a combination of lagged conditions based on the Fibonacci sequence.
f_maSelectLibrary "f_maSelect"
Easy to use drop-in facade function to lots of different moving average calculations, including some that are not natively available in PineScript v5 such as Zero-Lag EMA. Simply call f_maSelect(series float serie, simple string ma_type="sma", ma_length=14) instead of a ta.*ma() call and you get access to all MAs offered by PineScript and more.
zema(src, len)
Zero-lag EMA (ZLMA)
Parameters:
src : Input series
len : Lookback period
Returns: Series smoothed with ZLMA
approximate_sma(x, ma_length)
Approximate Standard Moving Average, which substracts the average instead of popping the oldest element, hence losing the base frequency and is why it is approximative. For some reason, this appears to give the same results as a standard RMA
Parameters:
x : Input series.
ma_length : Lookback period.
Returns: Approximate SMA series.
f_maSelect(serie, ma_type, ma_length)
Generalized moving average selector
Parameters:
serie : Input series
ma_type : String describing which moving average to use
ma_length : Lookback period
Returns: Serie smoothed with the selected moving average.
generalized_dev(src, length, avg, lmode)
Generalized deviation calculation: Whereas other Bollinger Bands often just change the basis but not the stdev calculation, the correct way to change the basis is to also change it inside the stdev calculation.
Parameters:
src : Series to use (default: close)
length : Lookback period
avg : Average basis to use to calculate the standard deviation
lmode : L1 or L2 regularization? (ie, lmode=1 uses abs() to cutoff negative values hence it calculates the Mean Absolute Deviation as does the ta.dev(), lmode=2 uses sum of squares hence it calculates the true Standard Deviation as the ta.stdev() function does). See also the research works of everget:
Returns: stdev Standard deviation series
generalized_dev_discount(src, length, avg, lmode, temporal_discount)
Standard deviation calculation but with different probabilities assigned to each bar, with newer bars having more weights en.wikipedia.org
Parameters:
src : Series to use (default: close)
length : Lookback period
avg : Average basis to use to calculate the standard deviation
lmode : L1 or L2 regularization? (ie, lmode=1 uses abs() to cutoff negative values hence it calculates the Mean Absolute Deviation as does the ta.dev(), lmode=2 uses sum of squares hence it calculates the true Standard Deviation as the ta.stdev() function does). See also the research works of everget:
temporal_discount : Probabilistic gamma factor to discount old values in favor of new ones, higher value = more weight to newer bars
Returns: stdev Standard deviation series
median_absdev(src, length, median)
Median Absolute Deviation
Parameters:
src : Input series
length : Lookback period
median : Median already calculated on the input series
Returns: mad, the median absolute deviation value
Blocky's EMA RibbonA classic EMA ribbon setup.
The script uses eight EMAs, with default lengths ranging from 21 to 55 periods, with an additional EMA with a default length of 200 periods.
The lengths of the EMAs can be customized, when customizing, the shortest time frame should be first and the longest time frame last.
The ribbons gradient strength is calculated based on the EMA's sequence, and their separation.
The color and transparency are set based on the calculated strength. The bolder the color, the stronger the strength.
Use the opacity multiplier to increase/decrease the strength of the gradient. BITSTAMP:BTCUSD
Short Term Bubble RiskThis risk indicator uses the extension of the closing price to the 20W SMA and displays a color-coded risk oscillator. The higher the oscillator is, the greater the short-term risk and vice-versa. This indicator has historically worked well for estimating the short-term risk of Bitcoin and Ethereum on a weekly timeframe.
Rainbow Moving AverageA Rainbow Moving Average script. There are many like it, but this one is mine. It is designed to be easy to read without too much noise in the number of lines and shading, with the moving average to be some of the commonly used ones. Using commonly referenced moving average values help us to understand "the crowd" and what moving average or trend lines they might be looking at. The default values are derived from hourly charts, but work well on any time frame.
The moving average function is simple to change so you can use it for any moving average type that you like, including volume-weighted.
Inspired by my daughter's love of rainbows, she has approved the colors.
Rekt Edge Reversion BandRekt Edge Reversion band is a technical indicator that utilizes a combination of moving averages and standard deviations to determine optimal entry and exit points in the market. By comparing the current price to its moving average, the indicator identifies potential trends and determines how you can position around them by plotting buy/sell signals and two channels based on user input parameters. The user can choose between Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ) and select the moving average period, the unit of separation, the multiples of the unit, and other important parameters. The indicator's inputs can be adjusted to suit different trading styles, and it can be used on any time frame. The indicator can be used to identify potential trend reversals or breakouts (or breakdowns) when the price moves outside of the channels. The indicators potential use cases include identifying overbought or oversold conditions. With its ability to provide a clear signal on when to enter and exit a trade, this indicator is a popular tool among traders looking to make more informed and profitable trading decisions. This indicator can also be used in conjunction with other technical analysis tools to confirm or invalidate trading signals.
Customizable Moving Average RibbonThis indicator is a highly customizable moving average ribbon with some unique features.
This script can utilize multiple unique sources, including a non-repainting renko closing price. Renko charts focus solely on price movement and minimize the impacts of time and the extra noise time creates. Employing the renko close helps smooth out the MA ribbon. Insignificant price movements will not cause a change in the plotted lines of the indicator unless a new threshold is breached or a "brick" is created. This is highly useful for quickly identifying consolidation areas or overall flat price movement.
There are two methods for selecting the box size when utilizing the renko source. Box size is critical for the overall function and efficacy of the plots you will visually see with this indicator. Box size is set automatically using the Average True Range "ATR" or manually using the "Traditional" setting. The simplest way to determine a manual box size is to take the ATR of the given instrument and round it to the nearest decimal place. As an example, if the ATR for the asset is 0.18, you would round that number to 0.2 and utilize this as your traditional box size.
The MA ribbon contains eleven adjustable moving average lines. Users can choose to turn off as many as they would like. Users can also adjust the length of the individual moving averages and the source for all moving averages. There are nine types of moving averages to choose from for the ribbon. The MA options are:
Exponential Moving Average = 'EMA'
Double Exponential Moving Average= 'DEMA'
Triple Exponential Moving Average = 'TEMA'
Simple Moving Average = 'SMA'
Relative Moving Average = 'RMA'
Volume Weighted Moving Average = 'VWMA'
Weighted Moving Average = 'WMA'
Smoothed Simple Moving Average = 'SSMA'
Hull Moving Average = 'HULL'
We believe that the ribbons features, including the line color change, help quickly identify trends and give users optimum customization. Users can select from five different color schemes including:
Green/Red
Purple/White
White/Blue
Silver / Orange
Teal/ Orange
MA Band Distance Monitor'MA Band Distance Monitor' indicator is a simple tool for traders who rely on moving averages to make trading decisions. This indicator plots two moving averages of your choice (you can select the type of the moving average), and fills the space between them, creating a "band".
The indicator also generates a table that displays the current price distance from both the fast and slow moving averages, as well as the average of the two. This allows you to quickly assess the strength of the trend and potential entry or exit points.
In addition, the table also shows the average price distance from one to another MA and also the current distance between them, allowing you to compare the current price action to the historical average. This information can help you identify potential trend reversals and assess the overall health of the market.
*** Slow length input must be greater than fast length input, otherwise indicator will produce faulty results
VHF Adaptive Linear Regression KAMAIntroduction
Heyo, in this indicator I decided to add VHF adaptivness, linear regression and smoothing to a KAMA in order to squeeze all out of it.
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.
VHF:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Linear Regression Curve:
A line that best fits the prices specified over a user-defined time period.
This is very good to eliminate bad crosses of KAMA and the pric.
Usage
You can use this indicator on every timeframe I think. I mostly tested it on 1 min, 5 min and 15 min.
Signals
Enter Long -> crossover(close, kama) and crossover(kama, kama )
Enter Short -> crossunder(close, kama) and crossunder(kama, kama )
Thanks for checking this out!
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Credits to
▪️@cheatcountry – Hann Window Smoohing
▪️@loxx – VHF and T3
▪️@LucF – Gradient
Setup Max e Min Larry WilliansLarry Williams used this system to win the trading championship
Hello friends, I bring a script with a trading strategy to be used in futures such as Index, Forex and Commodities. Developed by famous trader Larry Williams.
In them we use two 3-period Simple Moving Averages (Arithmetic) (one with the high price, the other with the low price), and a 21-period Moving Average (Arithmetic) to determine the trend. This will form an average channel with the prices of the maximums and minimums of the last three candles.
Best time charts use the strategy: from 5 minutes to 60 minutes.
This strategy is quite simple. The 21 Moving Average will color according to the trend (Green for bullish, Red for bearish and Gray for transitions). The Script will signal the entry according to the trend by the colors of the candles and also by the signal:
When green, the buy will be on the crossing of the lower Moving Average crossing the candlestick, and the exit will be on the crossing of the candlestick on the next Upper Moving Average.
When red, the sell will be at the crossing of the Upper Moving Average crossing the candlestick, and the exit will be at the crossing of the candlestick on the next Lower Moving Average.
When the Script signals the candle with a purple X, it means that the trend is changing and the entire open operation must be closed.
This system has no Stop, so be careful when using it.
Na linguagem do autor:
Larry Williams usou esse sistema ganhar campeonato de trade
Olá amigos, trago um script com uma estratégia de trade pra ser usada em futuros como Índice, Forex e Commodities. Desenvolvido pelo famoso trader Larry Willians.
Neles usamos duas Médias Móveis Simples (Aritmética) de 3 períodos (uma com o preço da máxima, outra com o preço da mínima), e uma Média Móvel (Aritmética) de 21 períodos para determinar a tendência. Nisso vai formar uma canal de médias com os preços das máximas e mínimas dos últimos três candles.
Melhores tempos gráficos usar a estratégia: de 5 minutos até 60 minutos.
Essa estratégia é bem simples. A Média Móvel de 21 irá colorir de acordo com a tendência (Green pra alta, Red para baixa e Gray para transições). O Script irá sinalizar a entrada de acordo com a tendência pela cores dos candles e também pela sinalização:
Quando green, a compra será no cruzamento da Média Móvel inferior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Superior seguinte.
Quando red, a venda será no cruzamento da Média Móvel Superior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Inferior seguinte.
Quando o Script sinaliza o candle com X purple, significa que a tendência está em mudança e deve ser fechada toda a operação em aberto.
Este sistema não possui Stop, portando cuidado quanto a seu uso.
Fibonacci Step IndicatorThe Fibonacci Step Indicator assumes irregularity in calculating a moving average. It is measured as the mean of the previous lows and highs situated at Fibonacci past periods. For example, the mean of the lows from 2, 3, 5, 8, etc. periods ago form the Fibonacci step indicator.
The indicator uses the formula for the first twelve Fibonacci numbers on highs and lows so that it creates a moving support/resistance zone. Afterwards, the zone is stabilized by taking the highest highs of the upper indicator and the lowest lows of the lower indicator part.
The indicator is used as a trend following way. It can be compared to the Ichimoku Kinko Hyo cloud (without the future projection). The zone form a support and resistance area. During ranging periods, the market will fluctuate within the area which is a bad time to follow the trend (if any).
Extended from Moving AverageThis indicator helps avoid chasing extended stocks by showing every time a stock is too far extended from a selected moving average.
Features:
✔️ selectable moving average and source (high, low, close)
✔️ choose to plot or hide the moving average
✔️ selectable distance to be considered too extended
Power Indicator - EMAs + VWAP + Volume BarThe Power Indicator is intended to return some exponential moving average, vwap, volume bar, and others. With this compilation, you will be able to use them as one indicator in Trading View.
The components are:
- EMA9 - Exponential Moving Average of 9 days
- EMA21 - Exponential Moving Average of 21 days
- EMA50 - Exponential Moving Average of 50 days
- EMA200 - Exponential Moving Average of 200 days
- Volume Bar - This indicator provides the volume of the candle and its strength by showing different colors. It's a way to check expressive volume in one bar.
- Vwap line
- Indicator
If you have any questions, let me know!
Colored Moving Averages With Close Signals[Whvntr][TradeStation]Plots the first time the close price is above or below the colored portion of the chosen MA. The MA's formula is from TradeStation's indicator: "Colored Moving Averages Can Help You Spot Trends" . I modified that indicator with customizations that include: Buy and Sell signals. Each time the current bar closes above the MA, while it's red (bearish), there's a Sell label at the start of that MA trend. Likewise: each time the current bar closes below the MA, while it's white (bullish), there's a Buy label at the beginning of that MA trend. You can now, also, easily see which MA you are selecting by hovering your cursor over the tooltips icon. I've included a modified Hull MA as default because I've found this SMA combination with the WMA to be a very smooth oscillation. I've also added some different types of MA's. Colored moving averages are helpful to determine when a trend may be reversing.
MA's
1 · Modified Hull MA: (SMA of the WMAs Hull Formula)
2 · Hull MA
3 · Exponential Moving Average
4 · Weighted Moving Average
5 · RMA Moving Average used in RSI
6 · Volume Weighted MA
7 · Simple Moving Average
This indicator isn't endorsed as a guarantee of future, favorable, results.
Library_SmoothersLibrary "Library_Smoothers"
CorrectedMA(Src, Len)
CorrectedMA The strengths of the corrected Average (CA) is that the current value of the time series must exceed a the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals when the trend is in a weak phase.
Parameters:
Src
Len
Returns: The Corrected source.
EHMA(src, len)
EMA Exponential Moving Average.
Parameters:
src : Source to act upon
len
Returns: EMA of source
FRAMA(src, len, FC, SC)
FRAMA Fractal Adaptive Moving Average
Parameters:
src : Source to act upon
len : Length of moving average
FC : Fast moving average
SC : Slow moving average
Returns: FRAMA of source
Jurik(src, length, phase, power)
Jurik A low lag filter
Parameters:
src : Source
length : Length for smoothing
phase : Phase range is ±100
power : Mathematical power to use. Doesn't need to be whole numbers
Returns: Jurik of source
SMMA(src, len)
SMMA Smoothed moving average. Think of the SMMA as a hybrid of its better-known siblings — the simple moving average (SMA) and the exponential moving average (EMA).
Parameters:
src : Source
len
Returns: SMMA of source
SuperSmoother(src, len)
SuperSmoother
Parameters:
src : Source to smooth
len
Returns: SuperSmoother of the source
TMA(src, len)
TMA Triangular Moving Average
Parameters:
src : Source
len
Returns: TMA of source
TSF(src, len)
TSF Time Series Forecast. Uses linear regression.
Parameters:
src : Source
len
Returns: TSF of source
VIDYA(src, len)
VIDYA Chande's Variable Index Dynamic Average. See www.fxcorporate.com
Parameters:
src : Source
len
Returns: VIDYA of source
VAWMA(src, len, startingWeight, volumeDefault)
VAWMA = VWMA and WMA combined. Simply put, this attempts to determine the average price per share over time weighted heavier for recent values. Uses a triangular algorithm to taper off values in the past (same as WMA does).
Parameters:
src : Source
len : Length
startingWeight
volumeDefault : The default value to use when a chart has no volume.
Returns: The VAWMA of the source.
WWMA(src, len)
WWMA Welles Wilder Moving Average
Parameters:
src : Source
len
Returns: The WWMA of the source
ZLEMA(src, len)
ZLEMA Zero Lag Expotential Moving Average
Parameters:
src : Source
len
Returns: The ZLEMA of the source
SmootherType(mode, src, len, fastMA, slowMA, offset, phase, power, startingWeight, volumeDefault, Corrected)
Performs the specified moving average
Parameters:
mode : Name of moving average
src : the source to apply the MA type
len
fastMA : FRAMA fast moving average
slowMA : FRAMA slow moving average
offset : Linear regression offset
phase : Jurik phase
power : Jurik power
startingWeight : VAWMA starting weight
volumeDefault : VAWMA default volume
Corrected
Returns: The MA smoothed source
Strategija TrioThis is a Primo #4 with extra ADX condition to avoid range bound enviroments.
1. ADX must be above 20
2. Price above 50 SMA for long and below 50 SMA for short settings.
3. Short EMA above Middle EMA
4. Pullback and 80 % bounce from Middle EMA within 2 bars
Risk/reward ratio and fund management is eseential, I recomend at least 3/1 and no more than 3 %. Arrows depict the entry bars, Data window shows the Take profit and Stop loss prices
Feel free to adjust it or use it on your own. This is not a financial advice.
Mean Reversion DotsMarkets tend to mean revert. This indicator plots a moving average from a higher time frame (type of MA and length selectable by the user). It then calculates standard deviations in two dimensions:
- Standard deviation of move of price away from this moving average
- Standard deviations of number of bars spent in this extended range
The indicator plots a table in the upper right corner with the % of distance of price from the moving average. It then plots 'mean reversion dots' once price has been 1 or more standard deviations away from the moving average for one or more standard deviations number of bars. The dots change color, becoming more intense, the longer the move persists. Optionally, the user can display the standard deviations in movement away from the moving average as channels, and the user can also select which levels of moves they want to see. Opting to see only more extreme moves will result in fewer signals, but signals that are more likely to imminently result in mean reversion back to the moving average.
In my opinion, this indicator is more likely to be useful for indices, futures, commodities, and select larger cap names.
Combinations I have found that work well for SPX are plotting the 30min 21ema on a 5min chart and the daily 21ema on an hourly chart.
In many cases, once mean reversion dots for an extreme enough move (level 1.3 or 2.2 and above) begin to appear, a trade may be initiated from a support/resistance level. A safer way to use these signals is to consider them as a 'heads up' that the move is overextended, and then look for a buy/sell signal from another indicator to initiate a position.
Note: I borrowed the code for the higher timeframe MA from the below indicator. I added the ability to select type of MA.
RedK K-MACD : a MACD with some more musclesMoving Averages are probably the most commonly used analysis tools, and MACD is possibly the first charting indicator a trader gets to learn about.
MACD Basic concept
----------------------------
Without repeating all the tons of documentation about what MACD does, let's quickly re-visit the MACD concept from a 10-mile altitude (note we're keen on simplifying here rather than being technically accurate - so please forgive the use of any "common lingos")
- MACD goal is to represent the distance between 2 Moving Averages (MAs) - one fast and one slow, relatively - as an unrestricted zero-based oscillator.
- The value of the main MACD line is the distance, or the displacement between the 2 MA's
- usually a signal line is used (which is another MA of that distance value) to enable better visualization of the change (and rate of change, since this is all depicted on a time axis) of that displacement - this represents price momentum (price movement in the recent period versus movements for a relatively longer period).
- the difference between the main MACD line and its signal is then represented as a histogram above and below the zero line. in this case, that histogram is really redundant, since it shows a value that is already represented visually by the main line and its signal line.
How K-MACD is different
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K-MACD takes that simple concept of the classic MACD and expands around it - the idea is to use the same simple approach to representing price momentum while bringing in more insight to price moves in the short, medium and long terms, ability to represent more than 2 MA's and to enable better identification of tradeable patterns (like Volatility Contraction and others) - while still keeping things simple and visually clean.
K-MACD is an indicator that allows us to view how price moves against 3 moving averages: a fast / slow pair, and a "market" Filter or Baseline (very long) that will be used as a flag for Bear/Bull market mode. Many traders and trading literature use the 200 day (40 week) SMA as that key filter
so in total, there are 4 MA lines in K-MACD (excluding the "orange" signal line):
* Price Proxy: Which is a very fast moving average that will represent the price itself - let's use a WMA(3) or something close to that here - there will be a signal line to enable better visualization of this similar to a classic MACD - that's the orange line
* Fast & Slow MA's : Use whatever represents the "medium term" momentum for your trading - Some traders use 20 and 50, others use 10 and 20 .. if on your price chart, you keep using a pair of MA's for this, use the same settings in K-MACD - these will be represented by the 3-color Momentum Bars that fluctuate above and below the baseline
* Filter/Baseline MA: Should be your long (Bullish/Bearish Mode) MA. so 100 or 200 or any other value you consider your market to be bearish below and bullish above. on K-MACD this is actually the blue zero line - everything else is "relative" to it
Review the sample chart which explains various elements and the "price chart" setup that K-MACD represents. With K-MACD you can clean up your chart from those various Moving Averages - or use a different set than the ones you already have K-MACD represent - or other indicators (like ATR channels..etc)
Other "muscles" in the K-MACD
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- Relative vs Classic Calculation Mode
A key issue with the classic MACD is that the displacement between the 2 moving averages is represented as "absolute or direct" values - as the price of the underlying increases with time, you can't really use these values to make useful comparison between the past and now (see below example) - also you can't use them to compare 2 different instruments.
- The "Relative" calculation option in K-MACD addresses that issue by relating all "distances" to the Baseline MA as percentage (above or below) - you can see this clear when you look at the above chart the far left versus the far right and compare K-MACD with the classic MACD - the Classic option is still available
- More MA "type" options for all MA lines: choose between SMA, EMA, WMA, and RSS_WMA (which i use a lot in my trading and is my default for the Price Proxy)
- More Alerts: a total or 9 alerts (in 3 groups) are available with K-MACD (Momentum above or below baseline, Price Proxy crossing signal line, and Price Proxy crossing baseline)
- New 52 week High / Low markers: These will show as Green/red circles on the zero line in K-MACD. this will only work for 1D timeframe and above, i'm just using a simple approach and would like to keep it that way.
- i know i added some more features not covered above :) -- if you have questions about any of the settings, feel free to ask below
Closing thoughts
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K-MACD is a combination of couple of indicators i published in the past (xMACD and Mo_Bars) - so you can go back and read about them if needed - I then added improvements to accommodate ideas from swing trading literature and common practices that i plan to focus on in future. So K-MACD is really part of my own trading setup.
I assume here that most traders are familiar with what a MACD is - so kept this post short - if you thing we should expand more about the concepts covered here let me know in the comments - i can make some separate posts with examples and more details.
I hope many fellow traders find this work useful - and feel free let me know in comments below if you do.
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
