Donchian Channels %I enjoy Donchian Channels for identifying trends. However, I hate having them on my chart. They are next to impossible to interpret at a glance. This script converts DCs to a % making a useful oscillator. The horizontal lines on the chart correspond to the Fib retracements below 50%. There are many ways to trade using this script and it works on any time frame. Moving average crosses are worth your attention, particularly, the 34 period MA (purple line). Enjoy and happy trading.
Cari dalam skrip untuk "oscillator"
Voluminati: Uncovering Market SecretsVoluminati: Uncovering Market Secrets
Overview:
The Voluminati indicator dives deep into the secrets of trading volume, providing traders with unique insights into the market's strength and direction. This advanced tool visualizes the Relative Strength Index (RSI) of trading volume alongside the traditional RSI of price, presenting an enriched perspective on market dynamics.
Features:
Volume RSI: A unique twist on the traditional RSI, the Volume RSI measures the momentum of trading volume. This can help identify periods of increasing buying or selling pressure.
Traditional RSI: The renowned momentum oscillator that measures the speed and change of price movements. Useful for identifying overbought or oversold conditions.
Moving Averages: Both the Volume RSI and traditional RSI come with optional moving averages. These can be toggled on or off and are customizable in type (SMA or EMA) and length.
Overbought & Oversold Fills: Visual aids that highlight regions where the Volume RSI is in overbought (above 70) or oversold (below 30) territories. These fills help traders quickly identify potential reversal zones.
How to Use:
Look for divergence between the Volume RSI and price, which can indicate potential reversals.
When the Volume RSI moves above 70, it might indicate overbought conditions, and when it moves below 30, it might indicate oversold conditions.
The optional moving averages can be used to identify potential crossover signals or to smooth out the oscillators for a clearer trend view.
Customizations:
Toggle the display of the traditional RSI and its moving average.
Choose the type (SMA/EMA) and length for both the Volume RSI and traditional RSI moving averages.
Note: Like all indicators, the Voluminati is best used in conjunction with other tools and analysis techniques. Always use proper risk management.
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
MACD Normalized [ChartPrime]Overview of MACD Normalized Indicator
The MACD Normalized indicator, serves as an asset for traders seeking to harness the power of the moving average convergence divergence (MACD) combined with the advantages of the stochastic oscillator. This novel indicator introduces a normalized MACD, offering a potentially enhanced flexibility and adaptability to numerous market conditions and trading techniques.
This indicator stands out by normalizing the MACD to its average high and average low, also factoring in the deviation of the high-low position from the mean. This approach incorporates the high and low in the calculations, providing the benefits of stochastic without its common drawbacks, such as clipping problems. As a result, the indicator becomes exceptionally versatile and suitable for various trading strategies, including both faster and slower settings.
The MACD Normalized Indicator boasts a variety of options and settings. The features include:
Enable Ribbon: Toggle the display of the ribbon accompanying the MACD Normalized, as desired.
Fast Length: Determine the movement speed of the fast line to receive advance notice of potential market opportunities.
Slow Length: Control the movement pace of the slow line for smoother signals and a comprehensive outlook on market trends.
Average Length: Specify the length used to calculate the high and low averages, providing greater control over the indicator's granularity.
Upper Deviation: Establish the extent to which the high and low values deviate from the mean, ensuring adaptability to diverse market situations.
Inner Band (Middle Deviation): Adjust the balance between the high and low deviations to create an inner band signal, giving traders a secondary level of market analysis and decision-making support.
Enable Candle Color: Enable the coloring of candles based on the MACD Normalized value for effortless visualization of trading potential.
Use Cases for the MACD Normalized Indicator
In addition to analyzing market trends and identifying potential trading opportunities, ChartPrime's MACD Normalized Indicator offers a range of applications for traders. These use cases encompass distinct trading scenarios and strategies:
Overbought and Oversold Regions
One of the key applications of the MACD Normalized Indicator is identifying overbought and oversold regions. Overbought refers to a situation where an asset's price has risen significantly and is expected to face a downturn, while oversold indicates a price drop that may subsequently lead to a reversal.
By adjusting the indicator's parameters, such as the upper and inner deviation levels, traders can set precise boundaries to determine overbought and oversold areas. When the MACD moves into the upper region, it may signal that the asset is overbought and due for a price correction. Conversely, if the MACD enters the lower region, it possibly indicates an oversold condition with the potential for a price rebound.
Signal Line Crossovers
The MACD Normalized Indicator displays two lines: the fast line and the slow line (inner band). A common trading strategy involves observing the intersection of these two lines, known as a crossover. When the fast line crosses above the slow line, it may signify a bullish trend or a potential buying opportunity. Conversely, a crossover with the fast line moving below the slow line typically indicates a bearish trend or a selling opportunity.
Divergence and Convergence
Divergence occurs when the price movement of an asset does not align with the corresponding MACD values. If the price establishes a new high while the MACD fails to do the same, a bearish divergence emerges, suggesting a potential downtrend. Similarly, a bullish divergence takes place when the price forms a new low but the MACD does not follow suit, hinting at an upcoming uptrend.
Convergence, on the other hand, is represented by the MACD lines moving closer together. This movement signifies a potential change in the trend, providing traders with a timely opportunity to enter or exit the market.
TOTAL:(RSI+TSI)TOTAL:(RSI+TSI)
This indicator collects instant data of RSI and TSI oscillators. RSI moves between (0) and (100) values as a moving line, while TSI moves between (-100) and (+100) values as two moving lines.
The top value of the sum of these values is graphically;
It takes the total value (+300) from RSI (+100), TSI (+100) and (+100).
The lowest value of the sum of these values is graphically;
It takes the value (-200) from the RSI (0), (-100) and (-100) from the TSI.
In case this indicator approaches (+300) graphically; It can be seen that price candlesticks mostly move upwards. This may not always give accurate results. Past incompatibilities can affect this situation.
In case this indicator approaches (-200) graphically; It can be seen that price candlesticks mostly move downwards. This may not always give accurate results. Past incompatibilities can affect this situation.
The graphical movements and numerical values created by this indicator do not give precise results for price candles.
Unified Composite Index [UCI] [KuraiBlu] [LazyBear]The purpose of this indicator is to combine the four basic types of indicators (Trend, Volatility, Momentum and Volume) to create a singular, composite index in order to provide a more holistic means of observing potential changes within the market, known as the Unified Composite Index . The indicators used in this index are as follows:
Trend - Trend Composite Index
Volatility - Bollinger Bands %b
Momentum - Relative Strength Index
Volume - Money Flow Index
The average price source can’t be altered as I’ve made it an average between ((open + close) / 2) and ((high + low) / 2).
The best way to use this is by observing several of the indicators at once in conjunction with the average, rather than simply using the average produced to determine the right moment to enter, or exit a trade by itself. I've found when one indicator goes way out of bounds relative to the other three (and subsequently, the average array), then it presents a good buying, or selling opportunity.
Some adjustments were made to several of the indicators in order to standardize them on a scale of 1-100 so that they could better accommodate the average array that was finally produced. Thanks to LazyBear for letting me strip down the WaveTrend Oscillator.
T3 Slope Variation [Loxx]T3 Slope Variation is an indicator that uses T3 moving average to calculate a slope that is then weighted to derive a signal.
The center line
The center line changes color depending on the value of the:
Slope
Signal line
Threshold
If the value is above a signal line (it is not visible on the chart) and the threshold is greater than the required, then the main trend becomes up. And reversed for the trend down.
Colors and style of the histogram
The colors and style of the histogram will be drawn if the value is at the right side, if the above described trend "agrees" with the value (above is green or below zero is red) and if the High is higher than the previous High or Low is lower than the previous low, then the according type of histogram is drawn.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or 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 price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Alets
Signals
Bar coloring
Loxx's Expanded Source Types
Multi T3 Slopes [Loxx]Multi T3 Slopes is an indicator that checks slopes of 5 (different period) T3 Moving Averages and adds them up to show overall trend. To us this, check for color changes from red to green where there is no red if green is larger than red and there is no red when red is larger than green. When red and green both show up, its a sign of chop.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or 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 price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Signals: long, short, continuation long, continuation short.
Alerts
Bar coloring
Loxx's expanded source types
wolfpack by multigrainContext
WolfPack was originally published by @darrellfischer1. The indicator was then made popular as a useful companion to the famous Market Cipher (and other similar) oscillators.
Improvements
Inspired by the Bjorgum TSI I have gone ahead and applied a Exponential Moving Average to the original WolfPack plot. The color changes assist in anticipating trend reversals and curls.
Credits
@bjorgum for the coloring and interpretation ideas
@darrellfischer1 for WolfPack
Fear and Greed IndexI couldn't find one based on the original, so I made my own, it's not quite identical, but it does the job.
Red = greed
Green = fear
I updated a lot of the subcomponents and fixed a bug. I've reduced the smoothing to 1, it was previously 5 if you prefer smoother signals. Also added a McClellan oscillator.
I've commented out the plotting of individual sub-components, just uncomment them to see what they do. Some look like pretty useful indicators on their own.
Enjoy!
Linear trendSimple way how to use Linear Regression for trading.
What we use:
• Linear Regression
• EMA 200 as a trend filter
Logic:
Firstly we make two different linear regression movings as oscillator. For this we need to subtract slow moving from fast moving, so we get the single moving around zero. This is the green/red line which appears on the chart.
The trade open when LR cross over the threshold. The trade close when LR cross under the threshold below. Crossing over the threshold is the same as faster moving cross over slower moving.
Also we use EMA as a filter. The trades would be only when the price is over than EMA 200.
Combo 4+ KDJ STO RSI EMA3 Visual Trend Pine V5@RL! English !
Combo 4+ KDJ STO RSI EMA3 Visual Trend Pine V5 @ RL
Combo 4+ KDJ STO RSI EMA3 Visual Trend Pine V5 @ RL is a visual trend following indicator that groups and combines four trend following indicators. It is compiled in PINE Script Version V5 language.
• STOCH: Stochastic oscillator.
• RSI Divergence: Relative Strength Index Divergence. RSI Divergence is a difference between a fast and a slow RSI.
• KDJ: KDJ Indicator. (trend following indicator).
• EMA Triple: 3 exponential moving averages (Default display).
This indicator is intended to help beginners (and also the more experienced ones) to trade in the right direction of the market trend. It allows you to avoid the mistakes of always trading against the trend.
The calculation codes of the different indicators used are standard public codes used in the usual TradingView coding for these indicators.
The STO indicator calculation script is taken from TradingView's standard STOCH calculation.
The RSI indicator calculation script is a replica of the one created by @Shizaru.
The KDJ indicator calculation script is a replica of the one created by @iamaltcoin.
The Triple EMA indicator calculation script is a replica of the one created by @jwilcharts.
This indicator can be configured to your liking. It can even be used several times on the same graph (multi-instance), with different configurations or display of another indicator among the four that compose it, according to your needs or your tastes.
A single plot, among the 4 indicators that make it up, can be displayed at a time, but either with its own trend or with the trend of the 4 (3 by default) combined indicators (sell=green or buy=red, background color).
Trend indications (potential sell or buy areas) are displayed as a background color (bullish: green or bearish: red) when at least three of the four indicators (3 by default and configurable from 1 to 4) assume that the market is moving in the same direction. These trend indications can be configured and displayed, either only for the signal of the selected indicator and displayed, or for the signals of the four indicators together and combined (logical AND).
You can tune the input, style and visibility settings of each indicator to match your own preferences or habits.
A 'buy stop' or 'sell stop' signal is displayed (layouts) in the form of a colored square (green for 'stop buy' and red for 'stop sell'. These 'stop' signals can be configured and displayed, either only for the indicator chosen, or for the four indicators together and combined (logical OR).
Note that the presence of a Stop Long signal cancels the background color of the Long trend (green).
Likewise, the presence of a Stop Short signal cancels out the background color of the Short trend (red).
It is also made up of 3 labels:
• Trend Label
• signal Stop Label (signals Stop buy or sell )
• Info Label (Names of Long / Short / Stop Long / Stop Short indicators, and / Open / Close / High / Low ).
Each label is configurable (visibility and position on the graph).
• Trend label: indicates the number of indicators suggesting the same trend (Long or Short) as well as a strength index (PWR) of this trend: For example: 3 indicators in Short trend, 1 indicator in Long trend and 1 indicator in neutral trend will give: PWR SHORT = 2/4. (3 Short indicators - 1 Long indicator = 2 Pwr Short). And if PWR = 0 then the display is "Wait and See". It also indicates which current indicator is displayed and the display mode used (combined 1 to 4 indicators or not combined ).
• Signal Stop Label: Indicates a possible stop of the current trend.
• Label Info (Simple or Full) gives trend info for each of the 4 indicators and OHLC info for the chart (in “Full” mode).
It is possible to display this indicator several times on a chart (up to 3 indicators max with the Basic TradingView Plan and more with the paid plans), with different configurations: For example:
• 1-Stochastic - 2/4 Combined Signals - no Label displayed
• 1-RSI - Combined Signals 3/4 - Stop Label only displayed
• 1-KDJ - Combined Signals 4/4 - the 3 Labels displayed
• 1-EMA'3 - Non-combined signals (EMA only) - Trend Label displayed
Some indicators have filters / thresholds that can be configured according to your convenience and experience!
The choice of indicator colors is suitable for a graph with a "dark" theme, which you will probably need to modify for visual comfort, if you are using a "Light" mode or a custom mode.
This script is an indicator that you can run on standard chart types. It also works on non-standard chart types but the results will be skewed and different.
Non-standard charts are:
• Heikin Ashi (HA)
• Renko
• Kagi
• Point & Figure
• Range
As a reminder: No indicator is capable of providing accurate signals 100% of the time. Every now and then, even the best will fail, leaving you with a losing deal. Whichever indicator you base yourself on, remember to follow the basic rules of risk management and capital allocation.
BINANCE:BTCUSDT
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! Français !
Combo 4+ KDJ STO RSI EMA3 Visual Trend Pine V5@RL
Combo 4+ KDJ STO RSI EMA3 Visual Trend Pine V5@RL est un indicateur visuel de suivi de tendance qui regroupe et combine quatre indicateurs de suivi de tendance. Il est compilé en langage PINE Script Version V5.
• STOCH : Stochastique.
• RSI Divergence : Relative Strength Index Divergence. La Divergence RSI est une différence entre un RSI rapide et un RSI lent.
• KDJ : KDJ Indicateur. (indicateur de suivi de tendance).
• EMA Triple : 3 moyennes mobiles exponentielles (Affichage par défaut).
Cet indicateur est destiné à aider les débutants (et aussi les plus confirmé) à trader à dans le bon sens de la tendance du marché. Il permet d'éviter les erreurs qui consistent à toujours trader à contre tendance.
Les codes de calcul des différents indicateurs utilisés sont des codes publics standards utilisés dans le codage habituel de TradingView pour ces indicateurs !
Le script de calcul de l’indicateur STO est issu du calcul standard du STOCH de TradingView.
Le script de calcul de l’indicateur RSI Div est une réplique de celui créé par @Shizaru.
Le script de calcul de l’indicateur KDJ est une réplique de celui créé par @iamaltcoin.
Le script de calcul de l’indicateur Triple EMA est une réplique de celui créé par @jwilcharts
Cet indicateur peut être configuré à votre convenance. Il peut même être utilisé plusieurs fois sur le même graphique (multi-instance), avec des configurations différentes ou affichage d’un autre indicateur parmi les quatre qui le composent, selon vos besoins ou vos goûts.
Un seul tracé, parmi les 4 indicateurs qui le composent, peut être affiché à la fois mais, soit avec sa propre tendance soit avec la tendance des 4 (3 par défaut) indicateurs combinés (couleur de fond vente=vert ou achat=rouge).
Les indications de tendance (zones de vente ou d’achat potentielles) sont affichés sous la forme de couleur de fond (Haussier : vert ou baissier : rouge) lorsque au moins trois des quatre indicateurs (3 par défaut et configurable de 1 à 4) supposent que le marché évolue dans la même direction. Ces indications de tendance peuvent être configuré et affichés, soit uniquement pour le signal de l’indicateur choisi et affiché, soit pour les signaux des quatre indicateurs ensemble et combinés (ET logique).
Vous pouvez accorder les paramètres d’entrée, de style et de visibilité de chacun des indicateurs pour correspondre à vos propres préférences ou habitudes.
Un signal ‘stop achat’ ou ‘stop vente’ est affiché (layouts) sous la forme d’un carré de couleur (vert pour ‘stop achat’ et rouge pour ‘stop vente’. Ces signaux ‘stop’ peuvent être configuré et affichés, soit uniquement pour l’indicateur choisi, soit pour les quatre indicateurs ensemble et combinés (OU logique).
A noter que la présence d’un signal Stop Long annule la couleur de fond de la tendance Long (vert).
De même, la présence d’un signal Stop Short annule la couleur de fond de la tendance Short (rouge).
Il est aussi composé de 3 étiquettes (Labels) :
• Trend Label (infos de tendance)
• Signal Stop Label (signaux « Stop » achat ou vente)
• Infos Label (Noms des indicateurs Long/Short/Stop Long/Stop Short,
et /Open/Close/High/Low )
Chaque label est configurable (visibilité et position sur le graphique).
• Label Trend : indique le nombre d’indicateurs suggérant une même tendance (Long ou Short) ainsi qu’un indice de force (PWR) de cette tendance :
Par exemple : 3 indicateurs en tendance Short, 1 indicateur en tendance Long et 1 indicateur en tendance neutre donnera :
PWR SHORT = 2/4. (3 indicateurs Short – 1 indicateur Long=2 Pwr Short).
Et si PWR=0 alors l’affichage est « Wait and See » (Attendre et Observer).
Il indique aussi quel indicateur actuel est affiché et le mode d’affichage utilisé (combiné 1 à 4 indicateurs ou non combiné ).
• Signal Stop Label : Indique un possible arrêt de la tendance en cours.
• Infos Label (Simple ou complet) donne les infos de tendance de chacun des 4 indicateurs et les infos OHLC du graphique (en mode « Complet »).
Il est possible d’afficher ce même indicateur plusieurs fois sur un graphique (jusqu’à 3 indicateurs max avec le Plan Basic TradingView et plus avec les plans payants), avec des configurations différentes :
Par exemple :
• 1-Stochastique – Signaux Combinés 2/4 – aucun Label affiché
• 1-RSI – Signaux Combinés 3/4 – Label Stop uniquement affiché
• 1-KDJ – Signaux Combinés 4/4 – les 3 Labels affichés
• 1-EMA’3 - Signaux Non combinés (EMA seuls) – Trend Label affiché
Certains indicateurs ont des filtres/seuils (Thresholds) configurables selon votre convenance et votre expérience !
Le choix des couleurs de l’indicateur est adapté pour un graphique avec thème « sombre », qu’il vous faudra probablement modifier pour le confort visuel, si vous utilisez un mode « Clair » ou un mode personnalisé.
Ce script est un indicateur que vous pouvez exécuter sur des types de graphiques standard. Il fonctionne aussi sur des types de graphiques non-standard mais les résultats seront faussés et différents.
Les graphiques Non-standard sont :
• Heikin Ashi (HA)
• Renko
• Kagi
• Point & Figure
• Range
Pour rappel : Aucun indicateur n’est capable de fournir des signaux précis 100% du temps. De temps en temps, même les meilleurs échoueront, vous laissant avec une affaire perdante. Quel que soit l’indicateur sur lequel vous vous basez, n’oubliez pas de suivre les règles de base de gestion des risques et de répartition du capital.
BINANCE:BTCUSDT
Efficiency RatioThe efficiency ratio (ER) is described by Perry Kaufman in his book, Trading Systems and Methods.
It works by measuring the momentum of the market, that is, the absolute change from the current price to a past price, and divides it by the volatility, which is the sum of the absolute changes of each bar. That makes this a bounded indicator, going from 0 to 100, like an oscillator. Higher values mean less noise, while lower values mean more.
Eg.: if the market moves from 10.0 to 15.0 in a directional manner, with every bar up, the ER is going to be at 100. However, if it moves up and down, and goes all over the place until finally reaching 15.0, the ER is going to be at around 20. It is very difficult for the ER to be at zero, because that would require 0 volatility, which is almost impossible to occur.
This indicator is useful when planning for trades. If you notice the ER being higher than average, you may choose to increase the position size, because that would mean that the market is directional and has less chance of a whipsaw.
TASC 2021.10 - MAD Moving Average DifferencePresented here is code for the "Moving Average Difference" indicator originally conceived by John Ehlers, also referred to as MAD. This is one of TradingView's first code releases published in the October 2021 issue of Trader's Tips by Technical Analysis of Stocks & Commodities (TASC) magazine.
This indicator has a companion indicator that is discussed in the article entitled Cycle/Trend Analytics And The MAD Indicator , authored by John Ehlers. He's providing an innovative double dose of indicator code for the month of October 2021.
John Ehlers generally describes it as a "thinking man's" MACD . MAD has similar, yet distinct, intended operation. For those of you familiar with the MACD indicator operation, you will find MACD adjustments having defaults of 12 and 26, while MAD has comparable adjustments with defaults of 8 and 23. These are intended for adjustment, same as any other oscillator.
The MAD indicator can be basically described as two simple moving averages applied within a "rate of change" (ROC) calculation.
Further Related Information
• SMA
• ROC
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Real Momentum Osc.An earlly oscillator. Sometimes It mat be dangerous. Be careful please. I just combined TSI, WMA, Stochastic.
[blackcat] L1 Vitali Apirine Rate Of Change With BandsLevel: 1
Background
Vitali Apirine introuced this RoC indicator of “Rate Of Change With Bands” on March 2021.
Function
In Vitali Apirine's article “Rate Of Change With Bands” , the author introduces a concept of identifying overbought and oversold levels based on calculating standard deviation bands of the rate of change (ROC) momentum oscillator. The rate of change bands widen and narrow as the ROC deviation increases and decreases. The author proposes using this indicator in conjunction with other technical analysis methods to determine if the instrument is overbought or oversold.
Key Signal
UpperBand --> overbought threshold
oMARoc --> Output RoC Moving Average
LowerBand --> oversold threshold
Labels
L --> Long
S --> Short
XL --> Close Long
XS --> Close Short
Pros and Cons
100% Vitali Apirine definition translation, even variable names are the same. This help readers who would like to use pine to read his article.
Remarks
The 1st script for Blackcat1402 Vitali Apirine series publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Strategy - DMI Indicator with DPO Indicator as a GuardThe Directional Movement Index Indicator is one of my favorite indicators in tradingview's built-in library. It is free to use for all
For more information on what the DMI is, please visit: www.tradingview.com
The only problem I've come across with the DMI is that when it hits a 'trade range zone' it triggers false new trends (this is the case with almost every indicator I've ever tested).
This script modifies the DMI by removing the need for the ADX logic. It only focuses on the +DI and the -DI.
In order to remove the 'noise' generated during a trade range zone I have added another powerful indicator called the Detrended Price Oscillator.
The DPO is also a 'built-in' indicator on tradingview. www.tradingview.com
The DPO is used in conjunction with the DMI to stop trade ranges from wrecking your profits.
This strategy logic simply checks for the DMI indicator to cross itself. If the +DI crosses over the -DI this is a bullish cross and visa versa, if the -DI crosses over the +DI then it could mean bearish sentiment is building.
But then strategy logic uses the DPO to check if the DPO is above 0 or below 0 value
If the +DI crosses over the -DI and the DPO is above 0 value, then it's a Long entry point.
However, if the +DI crosses over the -DI and the DPO is below 0 value, then the Long signal is void.
And visa versa, if the -DI crosses over the +DI and the DPO is below 0 value, then it's a Short entry point (unless the DPO is greater than 0)
With this DPO 'guard' in place, it helps us keep the total trades executed to a minimum.
This is vital to push through trade ranges that can wreck your profit potential.
I wish I could create a better plotting mechanism for this indicator so you can better see the visuals. But combining the DMI to scale with the DPO is not possible.
The best solution is to simply add another DMI indicator to your chart so you can compare the DMI to this script that is dominated by the DPO (yellow line).
Enjoy! Likes are much appreciated!
Stochastic TrendDear community,
I've made another simple trading bot for you to use. This bot is based on the Stochastic Oscillator. It only produces long trades currently.
I changed the oscillation period to a much longer one, which in turn creates opportunities to trade long term trends.
The bot goes long when the Entry lines is crossed from below and it will close its long position once the Exit line has been crossed from above.
Full strategy Psar+ adx + cmf + rsi This ia full strategy made with a combination of a trender, volume, volatility and oscillator.
In this case we only go long.
Indicators used:
Default PSAR
Default CMF
Modified RSI logic, not using OB/OS
ADX with EMA applied
The rules are : we check if we are in a uptrend on psar, together with a positive value in volume, rsi is above the middle line(50), using a big length, and lastly the ADx is superior to the ema ADx
For exit, we check the opposite, like downtrend psar, negative value volume, rsi < 50, and adx < ema adx
If you have any questions let me know.
Moving Average Periodical DivergenceUses the difference between two PMA (Moving Average Periodical) indicators to create an oscillator.
Useful for visualizing daily/weekly cycles, strength and potential momentum. The defaults are 2 days (fast) and 5 days (slow).
Accumulation and Distribution MomentumThis applies Chande Momentum to Accumulation and Distribution index as a means to changes.
Experimental oscillator.
Compare it to both Money Flows, Acc/Dis and Chande and you notice it has elements of all of them. Could potentially replace other volume based momentum indicators in your strategy.
It is a little more volatile, reaching from side to side, while having a tendency to lean towards the side that gets the most action over a longer period of time.
It also tends to reach and hang in oversold regions BEFORE a pump - something I noticed.
Could be used as an early warning sign as well as for overall trend analysis.
Comparison (Malaysia Index & Sector)This is just a simple tool for convenient to compare and showing a clear image of all sector and index in Malaysia. They are just in one indicator. From this indicator, you can predict momentum of each sector in Malaysia, which is currently in bull or bear trend.
STRUCTURE
In the setting, the first line with the option of the following index (Malaysia Index) :
1. FBMKLCI
2. FTSEMYX:FBMSCAP
3. FTSEMYX:FBMACE
4. FTSEMYX:FBM70
5. FTSEMYX:FBMT100
6. FTSEMYX:FBMFLG
7. FTSEMYX:FBMEMAS
8. FTSEMYX:FA40
9. FTSEMYX:FBMMSCS
10. FTSEMYX:FBMAPMYR
11. FTSEMYX:FBMMSCAP
The rest of lines is all of the following sector (Malaysia Sector):
1. Technology
2. Telecommunication
3. Health
4. Consumer Product
5. Industrial Product
6. Construction
7. Property
8. Plantation
9. Utilities
10. Transportation
11. Energy
12. REIT
13. Finance
The last line (Line 15) is provided for other stock/index which is not available in option to manually fill.
All sector and index price are smoothen by Moving Average (MA). The default moving average is Relative Moving Average (RMA) which is used in Relative Strength Index ( RSI ) Oscillator. But the range is different from RSI , it is from -100 to 100 instead of 0 to 100. In the end, result and interpretation are just the same as RSI . Green area indicates oversold area, while red area is overbought.
Other choice of Moving Averages are available to change.
The problem of putting all together is the script may take longer to process. It is just for convenient use.
Bottom-Up or Top-Down Invest?
Finnie's RSI with EMA + MFI + Stoch V2RSI seams to be one of the most used indicators by far, and that comes because of merit . With that in mind, the goal of this indicator is to expand upon the tradition RSI or Relative Strength Index we all know and love :) I started by adding an EMA crossover. Which gives you, the users, a general idea of when to buy and sell outside of just watching a line go down and up. To take thinks even further, I decided to add options for both Fast and Slow Stochastic oscillators. Adding STOCH brings in another variable when deciding on an entry, technically its a bit hard to explain but in practice it would go something like this: you notice RSI is down around the level 20 mark and RSI is crossing up above it's EMA , which is BULLISH signal, and you're thinking about going long. As a second confirmation you can look at the STOCH rsi , if it's also crossing above the previously spoken EMA that's another BULLISH signal. This process can be repeated once RSI has risen to find an exit.
V2 changes:
-added MFI
-added overbought(yellow)/oversold(red) visual indicator
-removed K stoch in order to clean the indicator up visually, I haven't regretted it since :)
