10/20 MA Cross-Over with Heikin-Ashi Signals by SchobbejakThe 10/20 MA Heikin-Ashi Strategy is the best I know. It's easy, it's elegant, it's effective.
It's particularly effective in markets that trend on the daily. You may lose some money when markets are choppy, but your loss will be more than compensated when you're aboard during the big moves at the beginning of a trend or after retraces. There's that, and you nearly eliminate the risk of losing your profit in the long run.
The results are good throughout most assets, and at their best when an asset is making new all-time highs.
It uses two simple moving averages: the 10 MA (blue), and the 20 MA (red), together with heikin-ashi candles. Now here's the great thing. This script does not change your regular candles into heikin-ashi ones, which would have been annoying; instead, it subtly prints either a blue dot or a red square around your normal candles, indicating a heikin-ashi change from red to green, or from green to red, respectively. This way, you get both regular and heikin ashi "candles" on your chart.
Here's how to use it.
Go LONG in case of ALL of the below:
1) A blue dot appeared under the last daily candle (meaning the heikin-ashi is now "green").
2) The blue MA-line is above the red MA-line.
3) Price has recently breached the blue MA-line upwards, and is now above.
COVER when one or more of the above is no longer the case. This is very important. You want to keep your profit.
Go SHORT in case of ALL of the below:
1) A red square appeared above the last daily candle (meaning the heikin-ashi is now "red").
2) The red MA-line is above the blue MA-line.
3) Price has recently breached the blue MA-line downwards, and is now below.
Again, COVER when one or more of the above is no longer the case. This is what gives you your edge.
It's that easy.
Now, why did I make the signal blue, and not green? Because blue looks much better with red than green does. It's my firm believe one does not become rich using ugly charts.
Good luck trading.
--You may tip me using bitcoin: bc1q9pc95v4kxh6rdxl737jg0j02dcxu23n5z78hq9 . Much appreciated!--
Buscar en scripts para "one一季度财报"
ABK Multi EMA I really like to work with EMAs, but each time you use the "buit-in" one, you use one more slot in your indicators allowed.
So I built this simple one, 4 EMA in one indicator, and easy to use as following;
-displays 4 EMAs
-choose your EMA lenghts.
-choose your color and other options as needed.
5 MAs w. alerts [LucF]Is this gazillionth MA indicator worth an addition to the already crowded field of contenders? I say yes! This one shows up to 5 MAs and 6 different marker conditions that can be used to create alerts, among many other goodies.
Features
MAs can be darkened when they are falling.
MAs from another time frame can be displayed, with the option of smoothing them.
Markers can be filtered to Longs or Shorts only.
EMAs can be selected for either all or the two shortest MAs.
The background can be colored using any of the marker states except no. 3.
Markers are:
1. On crosses between any two user-defined MAs,
2. When price is above or below an MA,
3. On Quick Flips (a specific setup involving a cross, multiple MA states and increasing volume, when available),
4. When the difference between two MAs is within a % of its high/low historic values,
5. When an MA has been rising/falling for n bars,
6. When the difference between two MAs is greater than a multiple of ATR.
Some markers use similar visual cues, so distinguishing them will be a challenge if they are used concurrently.
Alerts
Alerts can be created on any combination of alerts. Only non-consecutive instances of markers 5 and 6 will trigger the alert condition. Make sure you are on the interval you want the alert to run at. Using the “Once Per Bar Close” trigger condition is usually the best option.
When an alert is created in TradingView, a snapshot of the indicator’s settings is saved with the alert, which then takes on a life of its own. That is why even though there is only one alert to choose from when you bring up the alert creation dialog box and choose “5 MAs”, that alert can be triggered from any number of conditions. You select those conditions by activating the markers you want the alert to trigger on before creating the alert. If you have selected multiple conditions, then it can be a good idea to record a reminder in the alert’s message field. When the alert triggers, you will need the indicator on the chart to figure out which one of your conditions triggered the alert, as there is currently no way to dynamically change the alert’s message field from within the script.
Background settings will not trigger alerts; only marker configurations.
Notes
MAs are just… averages. Trader lure would have them act as support and resistance levels. I’m not sure about that, and not the only one thinking along these lines. Adam Grimes has studied moving averages in quite a bit of detail. His numbers point to no evidence indicating they act as support/resistance, and to specific MA lengths not being more meaningful than others. His point of view is debated by some—not by me. Mean reversion does not entail that price stops when it reaches its MA; rather, it makes sense to me that price would often more or less oscillate around its MA, which entails the MA does not act as support/resistance. Aren’t the best mean reversion opportunities when price is furthest away from its MA? If so, it should be more profitable to identify these areas, which some of this indicator’s markers try to do.
I think MAs can be much more powerful when thought of as instruments we can use to situate price events in contexts of various resolutions, from the instantaneous to the big picture. Accordingly, I use the relative positions and slopes of MAs in both discretionary and automated trading; but never their purported ability to support/resist.
Regardless of how you use MAs, I hope you will find this indicator useful.
Biased References
The Art and Science of Technical Analysis: Market Structure, Price Action, and Trading Strategies, Adam Grimes, 2012.
Does the 200 day moving average “work”?
Moving averages: digging deeper
[CS] NWMA Moving Average 3.0PineScript Implementation of Moving Average 3.0 first referenced by Manfred G. Dürschner as New wma or Nwma.
See amazing original paper Moving Averages 3.0 at page 27:
ifta.org
As shown in the picture Nwma is performing better than DEMA, TEMA, EMA, and other common used moving averages such as Hull MA that is prone to overshooting. With NWMA lag is extremely reduced.
As already implemented in NinjaTrader C# Nwma plugin by sumana.m:
ninjatrader.com
(from the original paper)
Nyquist Criterion
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA1) and the sampling signal is the MA as well (referred to as MA2). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion . With the cycle period as parameter, the usual one in Technical Analysis, the Nyquist Criterion reads as follows: n1 = λ*n2 , with λ ≥ 2. n1 is the cycle period of the sampled signal to which a sampling signal with cycle period n2 is applied. n1 must at least be twice as large as n2. In Mulloy´s and Ehlers´ approaches (referred to as Moving Averages 2.0) both cycle periods are equal. Moving Averages 3.0 Using the Nyquist Criterion there is a relation by which the application of a MA to itself can be described more precisely. In figure 2 a price series C (black line), one MA (MA1, red line) with lag L1 to the price series and another MA with lag L2 to MA1 (MA2, blue line) are illustrated. Based on the approximation and the relations described in figure 2 the following equation holds: (1) D1/D2 = (C – MA1)/(MA1 – MA2) = L1/L2 According to the lag formulas in the introduction L1/L2 can be written as follows:
α := L1/L2 = (n1 – 1)/(n2 – 1).
In this expression denominator 2 for the SMA and EMA as well as denominator 3 for the WMA are missing. α is therefore valid for all three MAs.
Using the Nyquist Criterion one gets for α the following result:
(2) α = λ* (n1 – 1)/(n1 – λ).
α put in (1) and C replaced by the approximation term NMA, the notation for the new MA, one gets:
NMA = (1 +α) MA1 – α MA2.
In detail, equation (2) reads as follows:
(3) NMA = (1 + α) MA1 – α
MA2 ,
(4) α = λ* (n1 – 1)/(n1 – λ), with λ ≥ 2.
(3) and (4) are equations for a group of MAs (notation: Moving Averages 3.0). They are independent of the choice of an MA. As the WMA shows the smallest lag (see introduction), it should generally be the first choice for the NMA. n1 = n2 results in the value 1 for α and λ, respectively. Then equation (3) passes into Ehlers´ formula. Thus Ehlers´ formula is included in the NMA formula as limiting value. It follows from a short calculation that the lag for NMA results in a theoretical value zero.
Please enjoy,
CryptoStatistical
General Filter Estimator-An Experiment on Estimating EverythingIntroduction
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA , who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something more flexible and less complex with the ability to approximate any filter output. Its possible, but the methods to do so are not something that pinescript can do, we have to use another base for our estimation using coefficients, so i inspired myself from the alpha-beta filter and i started writing the code.
Calculation and The Estimation Coefficients
Simplicity is the key word, its also my signature style, if i want something good it should be simple enough, so my code look like that :
p = length/beta
a = close - nz(b ,close)
b = nz(b ,close) + a/p*gamma
3 line, 2 function, its a good start, we could put everything in one line of code but its easier to see it this way. length control the smoothing amount of the filter, for any filter f(Period) Period should be equal to length and f(Period) = p , it would be inconvenient to have to use a different length period than the one used in the filter we want to estimate (imagine our estimation with length = 50 estimating an ema with period = 100) , this is where the first coefficients beta will be useful, it will allow us to leave length as it is. In general beta will be greater than 1, the greater it will be the less lag the filter will have, this coefficient will be useful to estimate low lagging filters, gamma however is the coefficient who will estimate lagging filters, in general it will range around .
We can get loose easily with those coefficients estimation but i will leave a coefficients table in the code for estimating popular filters, and some comparison below.
Estimating a Simple Moving Average
Of course, the boxcar filter, the running mean, the simple moving average, its an easy filter to use and calculate.
For an SMA use the following coefficients :
beta = 2
gamma = 0.5
Our filter is in red and the moving average in white with both length at 50 (This goes for every comparison we will do)
Its a bit imprecise but its a simple moving average, not the most interesting thing to estimate.
Estimating an Exponential Moving Average
The ema is a great filter because its length times more computing efficient than a simple moving average. For the EMA use the following coefficients :
beta = 3
gamma = 0.4
N.B : The EMA is rougher than the SMA, so it filter less, this is why its faster and closer to the price
Estimating The Hull Moving Average
Its a good filter for technical analysis with tons of use, lets try to estimate it ! For the HMA use the following coefficients :
beta = 4
gamma = 0.85
Looks ok, of course if you find better coefficients i will test them and actualize the coefficient table, i will also put a thank message.
Estimating a LSMA
Of course i was gonna estimate it, but this time this estimation does not have anything a lsma have, no moving average, no standard deviation, no correlation coefficient, lets do it.
For the LSMA use the following coefficients :
beta = 3.5
gamma = 0.9
Its far from being the best estimation, but its more efficient than any other i previously made.
Estimating the Quadratic Least Square Moving Average
I doubted about this one but it can be approximated as well. For the QLSMA use the following coefficients :
beta = 5.25
gamma = 1
Another ok estimate, the estimate filter a bit more than needed but its ok.
Jurik Moving Average
Its far from being a filter that i like and its a bit old. For the comparison i will use the JMA provided by @everget described in this article : c.mql5.com
For the JMA use the following coefficients :
for phase = 0
beta = pow*2 (pow is a parameter in the Jma)
gamma = 0.5
Here length = 50, phase = 0, pow = 5 so beta = 10
Looks pretty good considering the fact that the Jma use an adaptive architecture.
Discussion
I let you the task to judge if the estimation is good or not, my motivation was to estimate such filters using the less amount of calculations as possible, in itself i think that the code is quite elegant like all the codes of IIR filters (IIR Filters = Infinite Impulse Response : Filters using recursion) .
It could be possible to have a better estimate of the coefficients using optimization methods like the gradient descent. This is not feasible in pinescript but i could think about it using python or R.
Coefficients should be dependant of length but this would lead to a massive work, the variation of the estimation using fixed coefficients when using different length periods is just ok if we can allow some errors of precision.
I dont think it should be possible to estimate adaptive filter relying a lot on their adaptive parameter/smoothing constant except by making our coefficients adaptive (gamma could be)
So at the end ? What make a filter truly unique ? From my point of sight the architecture of a filter and the problem he is trying to solve is what make him unique rather than its output result. If you become a signal, hide yourself into noise, then look at the filters trying to find you, what a challenging game, this is why we need filters.
Conclusion
I wanted to give a simple filter estimator relying on two coefficients in order to estimate both lagging and low-lagging filters. I will try to give more precise estimate and update the indicator with new coefficients.
Thanks for reading !
BTC Volume Lines [v2018-11-17] @ LekkerCryptisch.nlCombine the volume of 8 BTCUSD exchanges in one graph.
Three use cases:
1) See the absolute volumes in one graph
2) See the relative volumes in one graph
3) See the deviation of the EMA the volumes in one graph
Tillson T3 Moving Average MTFMULTIPLE TIME FRAME version of Tillson T3 Moving Average Indicator
Developed by Tim Tillson, the T3 Moving Average is considered superior -1.60% to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
Inverse Fisher Transform on STOCHASTIC (modified graphics)Modified the graphic representation of the script from John Ehlers - From California, USA, he is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception). John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or sell. Hopefully, the signals are clear and unequivocal. However, more often than not your decision to pull the trigger is accompanied by crossing your fingers. Even if you have placed only a few trades you know the drill. In this article I will show you a way to make your oscillator-type indicators make clear black-or-white indication of the time to buy or sell. I will do this by using the Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of your indicators. In the past12 I have noted that the PDF of price and indicators do not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the familiar bell-shaped curve where the long “tails” mean that wide deviations from the mean occur with relatively low probability. The Fisher Transform can be applied to almost any normalized data set to make the resulting PDF nearly Gaussian, with the result that the turning points are sharply peaked and easy to identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is compressive. The Inverse Fisher Transform is found by solving equation 1 for x in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If the input falls between –0.5 and +0.5, the output is nearly the same as the input. For larger absolute values (say, larger than 2), the output is compressed to be no larger than unity. The result of using the Inverse Fisher Transform is that the output has a very high probability of being either +1 or –1. This bipolar probability distribution makes the Inverse Fisher Transform ideal for generating an indicator that provides clear buy and sell signals.
Tillson T3 Moving Average by KIVANÇ fr3762Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
Inverse Fisher Transform COMBO STO+RSI+CCIv2 by KIVANÇ fr3762A combined 3in1 version of pre shared INVERSE FISHER TRANSFORM indicators on RSI , on STOCHASTIC and on CCIv2 to provide space for 2 more indicators for users...
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function ( PDF ) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity . The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Creator: John EHLERS
Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index)
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity. The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Big Snapper Alerts R2.0 by JustUncleLThis is a diversified Binary Option or Scalping Alert indicator originally designed for lower Time Frame Trend or Swing trading. Although you will find it a useful tool for higher time frames as well.
The Alerts are generated by the changing direction of the ColouredMA (HullMA by default), you then have the choice of selecting the Directional filtering on these signals or a Bollinger swing reversal filter.
The filters include:
Type 1 - The three MAs (EMAs 21,55,89 by default) in various combinations or by themselves. When only one directional MA selected then direction filter is given by ColouredMA above(up)/below(down) selected MA. If more than one MA selected the direction is given by MAs being in correct order for trend direction.
Type 2 - The SuperTrend direction is used to filter ColouredMA signals.
Type 3 - Bollinger Band Outside In is used to filter ColouredMA for swing reversals.
Type 4 - No directional filtering, all signals from the ColouredMA are shown.
Notes:
Each Type can be combined with another type to form more complex filtration.
Alerts can also be disabled completely if you just want one indicator with one colouredMA and/or 3xMAs and/or Bollinger Bands and/or SuperTrend painted on the chart.
Warning:
Be aware that combining Bollinger OutsideIn swing filter and a directional filter can be counter productive as they are opposites. So careful consideration is needed when combining Bollinger OutsideIn with any of the directional filters.
Hints:
For Binary Options try ColouredMA = HullMA(13) or HullMA(8) with Type 2 or 3 Filter.
When using Trend filters SuperTrend and/or 3xMA Trend, you will find if price reverses and breaks back through the Big Fat Signal line, then this can be a good reversal trade.
Some explanation about the what Hull Moving average and ideas of how the generated in Big Snapper can be used:
tradingsim.com
forextradingstrategies4u.com
Inspiration from @vdubus
Big Snapper's Bollinger OutsideIn Swing filter in Action:
2-step Moving Average by HAH Financial- longer SMAs tend to sit too far from daily action
- shorter SMAs are too jittery
- the idea here is to create a smooth line, that is sits much closer to the daily price ranges
- this is achieved by mixing 2 MAs, a longer one and a shorter one
- the long one gives smoothness
- while averaging it with a shorter one, brings it (much in some cases) closer to the daily range
Price Action Doji Harami v0.2 by JustUncleLThis is an updated and final version of this indicator. This version distinguishes between the true Harami and the other Doji candlestick patterns as used with the Heikin Ashi candle charts. These candle patterns indicate a potential trend reversal or pullback.
The patterns identified are:
- Bearish Harami (Red Highlight above Bar):
One to three (default 3) large body Bull (green) candles followed by a small (red)
or no body candle (less than 0.5pip) with wicks top and bottom that are at least 60% of candle.
- Bullish Harami (Green Highlight below Bar):
One to three (default 3) large body Bear (red) candles followed by a small (green)
or no body candle (less than 0.5pip) with wicks top and bottom that are at least 60% of candle.
- Bearish Doji (Fuchsia Highlight above Bar):
One to three (default 3) large body Bull (green) candles followed by a small (green)
with wicks top and bottom that are at least 60% of candle.
- Bullish Doji (Aqua Highlight below Bar):
One to three (default 3) large body Bear (red) candles followed by a small (red)
with wicks top and bottom that are at least 60% of candle.
You can optionally specify how large the candles prior to Harami/Doji are in pips, default is 0 pip.
If you set this to zero then it will have no candle size consideration. You can also specify how many look back candles (1-3) are used in Harami/Doji calculations (default 3).
Included option to perform Calculations purely on Heikin Ashi candles, this helps when you want to see the HA Doji/Harami bars with the normal candle stick chart.
Also can optionally set an alert condition for when Harami/Doji found, this also displays a circle on the bottom of the screen when alert is triggered.
extended session - Regular Opening-Range- JayyOpening Range and some other scripts updated to plot correctly (see comments below.) There are three variations of the fibonacci expansion beyond the opening range and retracements within the opening range of the US Market session - I have not put in the script for the other markets yet.
The three scripts have different uses and strengths:
The extended session script (with the script here below) will plot the opening range whether you are using the extended session or the regular session. (that is to say whether "ext" in the lower right hand corner is highlighted or not.). While in the extended session the opening range has some plotting issues with periods like 13 minutes or any period that is not divisible into 330 mins with a round number outcome (eg 330/60 =5.5. Therefore an hour long opening range has problems in the extended session.
The pre session script is only for the premarket. You can select any opening range period you like. I have set the opening range to be the full premarket session. If you select a different session you will have to unselect "pre open to 9:30 EST for Opening Range?" in the format section. The script defaults to 15 minutes in the "period Of Pre Opening Range?". To go back to the 4 am to 9:30 pre opening range select "pre open to 9:30 EST for Opening Range?" there is no automatic 330 minute selection.
The past days offset script only works in 5 min or 15 minute period. It will show the opening range from up to 20 days past over the current days price action. Use this for the regular session only. 0 shows the current day's opening range. Use the positive integers for number of days back ie 1, 2, 3 etc not -1, -2, -3 etc. The script is preprogrammed to use the current day (0).
Scripts updated to plot correctly: One thing they all have in common is a way of they deal with a somewhat random problem that shifts the plots 4 hours in one direction or the other ie the plot started at 9:30 EST or 1:30PM EST. This issue started to occur approximately June 22, 2015 and impacts any script that tried to use "session" times to manage a plot in my scripts. The issue now seems to have been resolved during this past week.
Just in case the problem reoccurs I have added a "Switch session plot?" to each script. If the plot looks funny check or uncheck the "Switch session plot?" and see the difference. Of course if a new issue crops up it will likely require a different fix.
I have updated all of the scripts shown on this chart. If you are using a script of mine that suffers from the compiler issue then you will find an update on this chart. You can get any and all of the scripts by clicking on the small sideways wishbone on the left middle of the chart. You will see a dialogue box. Then click "make it mine". This will import all of the scripts to your computer and you can play around with them all to decide what you want and what you don't want. This is the easiest way to get all of the scripts in one fell swoop. It is also the easiest way for me to make all of the scripts available. I do not have all of the plots visible since it is too messy and one of the scripts (pre OR) is only for the regular session. To view the scripts click on the blue eye to the right of the script title to show it on this script. If you can only use the regular session. The scripts will all (with the exception of the pre OR) work fine.
If for any reason this script seems flakey refresh the page r try a slightly different period. I have noticed that sometimes randomly the script loves to return to the 5 min OR. This is a very new issue transient issue. As always if you see an issue please let me know.
Cheers Jayy
Camarilla - formula updated for 5 and 6 levelsSince levels 5 and 6 formulas are kind of surrounded in mystery it's difficult to find a widely agreed one.
While for the level 5 there is some consensus the 6th one is hard to find. I updated level 5 with the most common use of lvl 5 formula , some links like this one or from books (Secrets of a Pivot Boss) . Level 6 is a tough one, so please use this one experimentally . If you have other formulas for level 6, let me know. The 5 and 6 lvls are useful in volatile days.
forums.babypips.com
Session Markers - JDK AnalysisSession Markers is a tool designed to study how markets behave during specific, recurring time windows. Many traders know that price behaves differently depending on the day of the week, the time of the day, or particular market sessions such as the weekly open, the London session, or the New York open. This indicator makes those recurring windows visible on the chart and then analyzes what price typically does inside them. The result is a clear statistical understanding of how a chosen session behaves, both in direction and in strength.
The script works by allowing the trader to define any time window using a start day and time and an end day and time. Every time this window occurs on the chart, the indicator highlights it with a full-height vertical band. These visual markers reveal patterns that are otherwise difficult to detect manually, such as whether certain sessions tend to trend, reverse, consolidate, or create large imbalances. They also help the trader quickly scan through historical price action to see how the market has behaved under similar conditions.
For every completed session window, the indicator measures how much price changed from the moment the window began to the moment it ended. Instead of using raw price differences, it converts these changes into percentage moves. This makes the measurement consistent across different price ranges and market regimes. A one-percent move always has the same meaning, whether the asset is trading at 100 or 50,000. These percentage moves are collected for a user-selected number of past sessions, creating a dataset of how the market has behaved in the chosen time window.
Based on this dataset, the indicator generates several statistics. It counts how many past sessions closed higher and how many closed lower, producing a directional tendency. It also computes the probability of an upward session by dividing the number of positive sessions by the total. More importantly, it calculates the average percentage movement for all sessions in the lookback period. This average move reflects not just the direction but also the magnitude of price changes. A session with frequent small upward moves but occasional large downward moves will show a negative average movement, even if more sessions ended positive. This creates a more realistic representation of true market behavior.
Using this average movement, the script determines a “Bias” for the session. If the average percentage move is positive, the bias is considered bullish. If it is negative, the bias is bearish. If the values are very close to zero, the bias is neutral. This way, the indicator takes both frequency and impact into account, producing a magnitude-aware assessment instead of one that only counts wins and losses. A sequence such as +5%, –1% results in a bullish bias because the overall impact is strongly positive. On the other hand, a series of small gains followed by a large drop produces a bearish bias even if more sessions ended positive, because the large move dominates the average. This provides a far more truthful picture of what the market tends to do during the chosen window.
All relevant statistics are displayed neatly in a small panel in the top-right corner of the chart. The panel updates in real time as new sessions complete and older ones fall out of the lookback range. It shows how many sessions were analyzed, how many ended up or down, the probability of an upward move, the average percentage change, and the final bias. The background color of the panel instantly reflects that bias, making it easy to interpret at a glance.
To use the tool effectively, the trader simply needs to define a time window of interest. This could be something like the weekly opening window from Sunday to Monday, the London open each day, or even a unique custom window. After selecting how many past sessions to analyze, the indicator takes care of the rest. The vertical session markers reveal the structure visually. The statistics summarize the historical behavior objectively. The magnitude-weighted bias provides a realistic indication of whether the window tends to produce upward or downward movement on average.
Session Markers is helpful because it translates repeated market timing behavior into measurable data. It exposes hidden tendencies that are easy to feel intuitively but hard to quantify manually. By analyzing both direction and magnitude, it prevents misleading interpretations that can arise from looking only at win rates. It helps traders understand whether a session typically produces meaningful moves or just small noise, whether it tends to trend or reverse, and whether its behavior has recently changed. Whether used for bias building, session filtering, or deeper market research, it offers a structured framework for understanding the market through time-based patterns.
MTC – Multi-Timeframe Trend Confirmator V2MTC – Multi-Timeframe Trend Confirmator V2
A comprehensive trend analysis indicator that systematically combines six technical indicators across three customizable timeframes, using a weighted scoring system to identify high-probability trend conditions.
ORIGINALITY AND CONCEPT
This indicator is original in its approach to multi-timeframe trend confirmation. Rather than relying on a single indicator or timeframe, it creates a composite score by evaluating six different technical conditions simultaneously across three timeframes. The scoring system weighs certain indicators more heavily based on their reliability in trend identification. The visual gauge provides an at-a-glance view of trend alignment across timeframes, making it easier to identify when multiple timeframes agree - a condition that typically produces stronger, more reliable trends.
HOW IT WORKS - DETAILED SCORING METHODOLOGY
The indicator evaluates six technical conditions on each timeframe. Each condition contributes to a composite score:
EMA 200 (Weight: 1 point)
Bullish: Price closes above EMA 200 (+1)
Bearish: Price closes below EMA 200 (-1)
Rationale: Long-term trend direction
SMA 50/200 Crossover (Weight: 1 point)
Bullish: SMA 50 above SMA 200 (+1)
Bearish: SMA 50 below SMA 200 (-1)
Rationale: Golden/Death cross confirmation
RSI 14 (Weight: 1 point)
Bullish: RSI above 55 (+1)
Bearish: RSI below 45 (-1)
Neutral: RSI between 45-55 (0)
Rationale: Momentum filter with buffer zone to avoid chop
MACD (12,26,9) (Weight: 1 point)
Bullish: MACD line above signal line (+1)
Bearish: MACD line below signal line (-1)
Rationale: Trend momentum confirmation
ADX 14 (Weight: 2 points - DOUBLE WEIGHTED)
Requires ADX above 25 to activate
Bullish: DI+ above DI- and ADX > 25 (+2)
Bearish: DI- above DI+ and ADX > 25 (-2)
Neutral: ADX below 25 (0)
Rationale: Trend strength filter - only counts when a strong trend exists. Double weighted because ADX is specifically designed to measure trend strength, making it more reliable than oscillators.
Supertrend (Factor: 3.0, ATR Period: 10) (Weight: 2 points - DOUBLE WEIGHTED)
Bullish: Direction indicator = -1 (+2)
Bearish: Direction indicator = +1 (-2)
Rationale: Dynamic support/resistance that adapts to volatility. Double weighted because Supertrend provides clear, objective trend signals with built-in stop-loss levels.
COMPOSITE SCORE CALCULATION:
Total possible score range: -10 to +10 points
Score interpretation:
Score > 2: UPTREND (majority of indicators bullish, especially weighted ones)
Score < -2: DOWNTREND (majority of indicators bearish, especially weighted ones)
Score between -2 and +2: NEUTRAL/RANGING (mixed signals or weak trend)
The threshold of +/- 2 was chosen because it requires more than just basic agreement - it typically means at least 3-4 indicators align, or that the heavily-weighted indicators (ADX, Supertrend) confirm the direction.
MULTI-TIMEFRAME LOGIC:
The indicator calculates the composite score independently for three timeframes:
Higher Timeframe (default: 4H) - Major trend direction
Mid Timeframe (default: 1H) - Intermediate trend
Lower Timeframe (default: 15min) - Entry timing
Main Trend Confirmation Rule:
The indicator only signals a confirmed trend when BOTH the higher timeframe AND mid timeframe scores agree (both > 2 for uptrend, or both < -2 for downtrend). This dual-timeframe confirmation significantly reduces false signals during choppy or ranging markets.
HOW TO USE IT
Setup:
Add indicator to chart
Customize timeframes based on your trading style:
Scalpers: 15min, 5min, 1min
Day traders: 4H, 1H, 15min (default)
Swing traders: Daily, 4H, 1H
Toggle individual indicators on/off based on your preference
Adjust Supertrend parameters if needed for your instrument's volatility
Reading the Gauge (Top Right Corner):
Each row shows one timeframe
Left column: Timeframe label
Middle column: Visual strength bars (10 bars = maximum score)
Green bars = Bullish score
Red bars = Bearish score
Yellow bars = Neutral/ranging
More filled bars = stronger trend
Right column: Numerical score
Trading Signals:
Entry Signals:
Long Entry: Wait for upward triangle arrow (appears when higher + mid TF both bullish)
Confirm gauge shows green bars on higher and mid timeframes
Lower timeframe should ideally turn green for entry timing
Chart background tints light green
Short Entry: Wait for downward triangle arrow (appears when higher + mid TF both bearish)
Confirm gauge shows red bars on higher and mid timeframes
Lower timeframe should ideally turn red for entry timing
Chart background tints light red
Position Management:
Stay in position while higher and mid timeframes remain aligned
Consider reducing position size when mid timeframe score weakens
Exit when higher timeframe trend reverses (daily label changes)
Avoiding False Signals:
Ignore signals when gauge shows mixed colors across timeframes
Avoid trading when scores are close to threshold (+/- 2 to +/- 4 range)
Best trades occur when all three timeframes align (all green or all red in gauge)
Use the numerical scores: higher absolute values (7-10) indicate stronger, more reliable trends
Practical Examples:
Example 1 - Strong Uptrend Entry:
Higher TF: +8 (strong green bars)
Mid TF: +6 (strong green bars)
Lower TF: +4 (moderate green bars)
Action: Look for long entries on lower timeframe pullbacks
Background is tinted green, upward arrow appears
Example 2 - Ranging Market (Avoid):
Higher TF: +3 (weak green)
Mid TF: -1 (weak red)
Lower TF: +2 (neutral yellow)
Action: Stay out, wait for alignment
Example 3 - Trend Reversal Warning:
Higher TF: +7 (still green)
Mid TF: -3 (turned red)
Lower TF: -5 (strong red)
Action: Consider exiting longs, prepare for potential higher TF reversal
Customization Options:
Timeframes: Adjust all three to match your trading horizon
Indicator Toggles: Disable indicators that don't suit your instrument:
Disable RSI for highly volatile crypto markets
Disable SMA crossover for range-bound instruments
Keep ADX and Supertrend enabled for trending markets
Visual Preferences:
Arrow size: 5 options from Tiny to Huge
Gauge size: Small/Medium/Large for different screen sizes
Toggle arrows on/off if you only want the gauge
Alert Setup:
Right-click chart, "Add Alert"
Condition: MTC v6 - UPTREND or DOWNTREND
Get notified when multi-timeframe confirmation occurs
Best Practices:
Use with Price Action: The indicator works best when combined with support/resistance levels, chart patterns, and volume analysis
Risk Management: Even with multi-timeframe confirmation, always use stop losses
Market Context: Works best in trending markets; less reliable in strong consolidation
Backtesting: Test the default settings on your specific instrument and timeframe before live trading
Patience: Wait for full multi-timeframe alignment rather than taking premature signals
Technical Notes:
All calculations use Pine Script's security function to fetch data from multiple timeframes
Prevents repainting by using confirmed bar data
Gauge updates in real-time on the last bar
Daily labels mark at the open of each new daily candle
Works on all instruments and timeframes
This indicator is ideal for traders who want objective, systematic trend identification without the complexity of analyzing multiple indicators manually across different timeframes.
-NATANTIA
Grok/Claude AI Regime Engine • Grok/Claude X SeriesGrok/Claude AI Regime Engine
This is a TradingView indicator designed to identify market regimes (bullish, bearish, or neutral) and generate buy/sell signals based on multiple technical factors working together.
Core Concept
At its heart, this indicator tries to answer a simple question: "What kind of market are we in right now, and when should I consider buying or selling?"
It does this by blending several well-known technical analysis tools into a unified system. Think of it as a dashboard that synthesizes multiple indicators into clear, actionable information.
How It Determines Market Regime
The indicator creates what it calls a "Money Line" by combining two exponential moving averages (EMAs) — a fast one (default 8 periods) and a slow one (default 24 periods). These are weighted together, with the fast EMA getting 60% influence by default. This blended line serves as the primary trend reference.
Bullish regime is declared when the short EMA crosses above the long EMA, provided the RSI isn't already in overbought territory. Bearish regime kicks in when the opposite happens — short EMA crosses below long, as long as RSI isn't oversold. Neutral regime occurs when the indicator detects sideways, choppy conditions.
The neutral detection is particularly interesting. It uses two optional methods: one looks at how flat the Money Line's slope is (compared to recent volatility via ATR), and the other checks how close together the two EMAs are as a percentage of price. When the market is grinding sideways, these methods help the indicator avoid falsely calling a trend.
Signal Generation Logic
Buy and sell signals are generated using Donchian Channel breakouts as the trigger mechanism. The Donchian Channel tracks the highest high and lowest low over a lookback period (default 20 bars), using the previous bar's values to avoid repainting issues.
A buy signal fires when price touches or breaks below the lower Donchian band, suggesting a potential reversal from oversold conditions. A sell signal fires when price reaches the upper band. However, these raw breakout signals pass through several filters before being displayed:
FilterPurposeADX thresholdOnly signals when the market has sufficient trend strength (default: ADX > 25)RSI filterBuy signals require RSI to be oversold; sell signals require overbought RSICooldown periodPrevents signal spam by requiring a minimum number of bars between signalsClose confirmationOptional setting to require a candle close beyond the band, not just a wick
Additional Metrics Displayed
The indicator calculates and displays several supplementary metrics in an information panel. ADX (Average Directional Index) measures trend strength — values below 15 suggest a weak, ranging market, while above 25 indicates a strong trend. The colored dots at the bottom of the chart reflect this: white for weak, orange for moderate, blue for strong.
BBWP (Bollinger Band Width Percentile) measures current volatility relative to historical volatility over roughly a year of data. High readings suggest volatility expansion; low readings suggest compression, which often precedes significant moves.
Alerts and Notifications
The indicator generates alerts in two scenarios: when the market regime changes (bullish to bearish, etc.) and when buy/sell signals trigger. Alert messages include the ticker symbol, timeframe, current price, RSI, ADX, and other relevant context so you can quickly assess the situation without opening the chart.
Visual Customization
Users can toggle various display elements on or off, including the EMA lines, Donchian bands, shaded regime zones between the bands, and price labels at signal points. The shading between the upper and lower bands changes color based on the current regime — green for bullish, magenta for bearish, and blue for neutral — providing an at-a-glance view of market conditions over time.
Summary
This is essentially a trend-following system with mean-reversion entry signals, filtered by momentum and trend strength indicators. It's designed to help traders identify favorable market conditions and time entries while avoiding signals during choppy, directionless periods. The multiple confirmation layers aim to reduce false signals, though like any technical system, it will still produce losing trades in certain market conditions.
Multi EMA and SMA with VWAP Indicator📊 Custom Multi-MA & VWAP Indicator
A comprehensive and fully customizable moving average indicator that combines 6 Exponential Moving Averages (EMAs), 3 Simple Moving Averages (SMAs), and VWAP in one clean, easy-to-use tool.
✨ Features:
6 Configurable EMAs:
• Default periods: 9, 21, 50, 100, 150, 200
• Fully adjustable lengths
• Individual color customization
• Show/hide toggles for each EMA
3 Configurable SMAs:
• Default periods: 20, 50, 100
• Fully adjustable lengths
• Individual color customization
• Show/hide toggles for each SMA
• Thicker lines for easy distinction from EMAs
VWAP (Volume Weighted Average Price):
• Toggle on/off
• Customizable color and line width
• Essential for intraday trading and institutional levels
🎯 Use Cases:
• Trend identification and confirmation
• Support and resistance levels
• Entry and exit signals
• Multi-timeframe analysis
• Day trading and swing trading strategies
• Institutional price levels (VWAP)
⚙️ Fully Customizable:
Every aspect of this indicator is configurable through the settings panel:
• Adjust any MA period to fit your trading strategy
• Choose your preferred colors for better chart visualization
• Enable/disable specific MAs to reduce chart clutter
• Customize VWAP line thickness
📈 Perfect For:
• Traders who use multiple moving averages in their strategy
• Those seeking an all-in-one MA solution
• Clean chart organization with one indicator instead of multiple
• Both beginners and experienced traders
💡 Tips:
• Use shorter EMAs (9, 21) for quick trend changes
• Longer EMAs (100, 150, 200) act as strong support/resistance
• VWAP is particularly useful for intraday trading
• Customize colors to match your chart theme
Version: Pine Script v6
Overlay: Yes (plots directly on price chart)
MTF EMA Hariss 369The strategy has been prepared in a simplistic manner and easy to understand the concept by any novice trader.
Indicators used:
Current Time frame 20 EMA- Gives clear look about current time frame dynamic support and resistance and trend as well.
Higher Time Frame 20 EMA: Gives macro level trend, support and resistance
Kama: Capture volatility and trend direction.
RVOL: Main factor of price movement.
Buy when price closes above current time frame 20 ema and current time frame 20 ema is above higher time frame 20 ema. Stop loss just below the low of last candle. One can use current time frame 20 ema, higher time frame 20 ema or kama as stop loss depending upon type of asset class and risk appetite. The ideal way is to keep 20 ema as trailing sl if one wants to trail with trend.
Sell when price closes below current time frame 20 ema and current time frame 20 ema is lower than higher time frame 20 ema. Stop loss just above high of last candle.
Ideal target is 1.5 or 2 times of stop loss.
Entry and exit time depends on trading style. Eg. if you want to enter and exit in 5 min time frame, then choose 15 min or 1h as higher time frame as trend filter. Buy and sell signals are also plotted based on this strategy. One should always go with the higher time frame trend. Opting higher time frame trend filter always filters out market noises.
CoreTFRSIMD CoreTFRSIMD library — Reusable TFRSI core for consistent momentum inputs across scripts
The library provides a reusable exported function such as calcTfrsi(src, len, signalLen) so you can compute TFRSI in your own indicators or strategies, e.g. tfrsi = CoreTFRSIMD.calcTfrsi(close, 6, 2)
Summary
CoreTFRSIMD is a Pine Script v6 library that implements a TFRSI-style oscillator core and exposes it as a reusable exported function. It is designed for authors who want the same TFRSI calculation across multiple indicators or strategies without duplicating logic. The library includes a simple demo plot and band styling so you can visually sanity-check the output. No higher-timeframe sampling is used, and there are no loops or arrays, so runtime cost is minimal for typical chart usage.
Motivation: Why this design?
When you reuse an oscillator across different tools, small implementation differences create inconsistent signals and hard-to-debug results. This library isolates the signal path into one exported function so that every dependent script consumes the exact same oscillator output. The design combines filtering, normalization, and a final smoothing pass to produce a stable, RSI-like readout intended for momentum and regime context.
What’s different vs. standard approaches?
Baseline: Traditional RSI computed directly from gains and losses with standard smoothing.
Architecture differences:
A high-pass stage to attenuate slower components before the main smoothing.
A multi-pole smoothing stage implemented with persistent state to reduce noise.
A running peak-tracker style normalization that adapts to changing signal amplitude.
A final signal smoothing layer using a simple moving average.
Practical effect:
The oscillator output tends to be less dominated by raw volatility spikes and more consistent across changing conditions.
The normalization step helps keep the output in an RSI-like reading space without relying on fixed scaling.
How it works (technical)
1. Input source: The exported function accepts a source series and two integer parameters controlling responsiveness and final smoothing.
2. High-pass stage: A recursive filter is applied to the source to emphasize shorter-term movement. This stage uses persistent storage so it can reference prior internal states across bars.
3. Smoothing stage: The filtered stream is passed through a SuperSmoother-like recursive smoother derived from the chosen length. This again uses persistent state and prior values for continuity.
4. Adaptive normalization: The absolute magnitude of the smoothed stream is compared to a slowly decaying reference level. If the current magnitude exceeds the reference, the reference is updated. This acts like a “peak hold with decay” so the oscillator scales relative to recent conditions.
5. Oscillator mapping: The normalized value is mapped into an RSI-like reading range.
6. Signal smoothing: A simple moving average is applied over the requested signal length to reduce bar-to-bar chatter.
7. Demo rendering: The library script plots the oscillator, draws horizontal guide levels, and applies background plus gradient fills for overbought and oversold regions.
Parameter Guide
Parameter — Effect — Default — Trade-offs/Tips
src — Input series used by the oscillator — close in demo — Use close for general momentum, or a derived series if you want to emphasize a specific behavior.
len — Controls the responsiveness of internal filtering and smoothing — six in demo — Smaller values react faster but can increase short-term noise; larger values smooth more but can lag turns.
signalLen — Controls the final smoothing of the mapped oscillator — two in demo — Smaller values preserve detail but can flicker; larger values reduce flicker but can delay transitions.
Reading & Interpretation
The plot is an oscillator intended to be read similarly to an RSI-style momentum gauge.
The demo includes three reference levels: upper at one hundred, mid at fifty, and lower at zero.
The fills visually emphasize zones above the midline and below the midline. Treat these as context, not as standalone entries.
If the oscillator appears unusually compressed or unusually jumpy, the normalization reference may be adapting to an abrupt change in amplitude. That is expected behavior for adaptive normalization.
Practical Workflows & Combinations
Trend following:
Use structure first, then confirm with oscillator behavior around the midline.
Prefer signals aligned with higher-high higher-low or lower-low lower-high context from price.
Exits/Stops:
Use oscillator loss of momentum as a caution flag rather than an automatic exit trigger.
In strong trends, consider keeping risk rules price-based and use the oscillator mainly to avoid adding into exhaustion.
Multi-asset/Multi-timeframe:
Start with the demo defaults when you want a responsive oscillator.
If an asset is noisier, increase the main length or the signal smoothing length to reduce false flips.
Behavior, Constraints & Performance
Repaint/confirmation: No higher-timeframe sampling is used. Output updates on the live bar like any normal series. There is no explicit closed-bar gating in the library.
security or HTF: Not used, so there is no HTF synchronization risk.
Resources: No loops, no arrays, no large history buffers. Persistent variables are used for filter state.
Known limits: Like any filtered oscillator, sharp gaps and extreme one-bar events can produce transient distortions. The adaptive normalization can also make early bars unstable until enough history has accumulated.
Sensible Defaults & Quick Tuning
Starting values: length six, signal smoothing two.
Too many flips: Increase signal smoothing length, or increase the main length.
Too sluggish: Reduce the main length, or reduce signal smoothing length.
Choppy around midline: Increase signal smoothing length slightly and rely more on price structure filters.
What this indicator is—and isn’t
This library is a reusable signal component and visualization aid. It is not a complete trading system, not predictive, and not a substitute for market structure, execution rules, and risk controls. Use it as a momentum and regime context layer, and validate behavior per asset and timeframe before relying on it.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
The Strat Lite [rdjxyz]◆ OVERVIEW
The Strat Lite is a stripped down version of the Strat Assistant indicator by rickyzcarroll—focusing on visual simplicity and script performance. If you're new to The Strat, you may prefer the Strat Assistant as a learning aid.
◇ FEATURES REMOVED FROM THE ORIGINAL SCRIPT
Candle Numbering & Up/Down Arrows
Previous Week High & Low Lines
Previous Day High & Low Lines
Action Wick Percentage
Actionable Signals Plot
Strat Combo Plots
Extensive Alerts
◇ FEATURES KEPT FROM THE ORIGINAL SCRIPT
Full Timeframe Continuity
Candle Coloring
◇ FEATURES ADDED TO THE ORIGINAL SCRIPT
Failed 2 Down Classification
Failed 2 Up Classification
◆ DETAILS
The Strat is a trading methodology developed by Rob Smith that offers an objective approach to trading by focusing on the 3 universal scenarios regarding candle behavior:
SCENARIO ONE
The 1 Bar - Inside Bar: A candle that doesn't take out the highs or the lows of the previous candle; aka consolidation.
These are shown as gray candles by default.
SCENARIO TWO
The 2 Bar - Directional Bar: A candle that takes out one side of the previous candle; aka trending (or at least attempting to trend).
SCENARIO THREE
The 3 Bar - Outside Bar: A candle that takes out both sides of the previous candle; aka broadening formation.
In addition to Rob's 3 universal scenarios, this indicator identifies two variations of 2 bars:
Failed 2 up: A candle that takes out the high of the previous candle but closes bearish.
Failed 2 down: A candle that takes out the low of the previous candle but closes bullish.
◆ SETTINGS
◇ INPUTS
FTC (FULL TIMEFRAME CONTINUITY)
Show/hide FTC plots
Offset FTC plots from current bar
◇ STYLE
STRAT COLORS
Color 0 (Failed 2 Up) - Default is fuchsia
Color 1 (Failed 2 Down) - Default is teal
Color 2 (Inside 1) - Default is gray
Color 3 (Outside 3) - Default is dark purple
Color 4 (2 up) - Default is aqua
Color 5 (2 down) - Default is white
◆ USAGE
It's recommended to use The Strat Lite with a top down analysis so you can find lower timeframe positions with higher timeframe context.
◇ TOP DOWN ANALYSIS
MONTHLY LEVELS
Starting on a monthly chart, the previous month's high and low are manually plotted.
WEEKLY LEVELS
Dropping down to a weekly chart, the previous week's high and low are manually plotted.
DAILY LEVELS
Dropping down to a daily chart, the previous day's high and low are manually plotted.
12H LEVELS
Dropping down to a 12h chart, the previous 12h's high and low are manually plotted.
ANALYSIS
The monthly low was broken, creating a lower low (aka a broadening formation), signalling potential exhaustion risk, which can be a catalyst for reversals. The daily candle that tested the monthly low closed as a Failed 2 Down—potentially an early sign of a reversal. With these 2 confluences, it's reasonable to expect the next daily candle to be a 2 Up. Now it's time to look for a lower timeframe entry.
◇ LOWER TIMEFRAME POSITION
HOURLY PRICE ACTION
Dropping down to an hourly chart, we're anticipating a 2 Up on the daily timeframe, so we're looking for a bullish pattern to enter a position long. I personally like the 6:00 AM UTC-5 hourly candle, as it's the midpoint of the day (for futures).
In this specific example, we see the opening gap was filled and there's a potential 2-1-2 bullish reversal set up.
At this point, price can either do one of 5 things:
Form another 1 (inside) candle
Form a 2 up (directional) candle
Form a 2 down (directional) candle
Form a 2 up, fail, and potentially flip to form a bearish 3 (outside) candle
Form a 2 down, fail, and potentially flip to form a bullish 3 (outside) candle
Knowing the finite potential outcomes helps us set up our positions, manage them accordingly, and flip bias if needed.
POSITION SETUP
Here we can set up a position long AND short. To go long, we set a buy stop at the 1h high and stop loss just below the 50% level of the inside candle; to go short, we set a sell stop at 1h low and stop loss just above the 50% level of the inside candle.
If the short gets triggered first, we can wait for price to move in our favor before cancelling the buy order. If the short becomes a failed 2 down, potentially reversing to become a bullish 3, we can either wait for the stop loss to trigger and for the long position to trigger OR we can move the buy stop to our short stop loss and move the long stop loss to the low of the 1h candle.
POSITION REFINEMENT
For an even tighter risk-to-reward, we can drop to a lower timeframe and look for setups that would be an early trigger of the 1h entry. Just know, the lower you go the more noise there is—increasing risk of getting stopped out before the 1h trigger.
Above are 30m refined entries.
In this example, the long buy stop was triggered. It closed bullish, so the sell stop order can be cancelled.
◇ TARGETS & POSITION MANAGEMENT
TARGETS
These depend on whether you intend to scalp, day trade, or swing trade, but targets are typically the highs of previous candles (when bullish) and lows of previous candles (when bearish). It's advised to be cautious of swing pivots as there's a risk of exhaustion and reversal at these levels.
In this example, the nearest target was the previous 12h high and the next target was the previous day high; if you're a swing trader, you could target previous week's high and previous month's high.
POSITION MANAGEMENT
This largely depends on your risk tolerance, but it's common to either:
Move stop loss slightly into profit
Trail stop loss behind higher highs (bullish) or lower lows (bearish)
Scale out of positions at potential pivot points, leaving a runner
Scale into positions on pullbacks on the way to target
◆ WRAP UP
As demonstrated, The Strat Lite offers a stripped down version of the Strat Assistant—making it visually simple for more experienced Strat traders. By following a top-down approach with The Strat methodology, you can find high probability setups and manage risk with relative ease.
◆ DISCLAIMER
This indicator is a tool for visual analysis and is intended to assist traders who follow The Strat methodology. As with any trading methodology, there's no guarantee of profits; trading involves a high degree of risk and you could lose all of your invested capital. The example shown is of past performance and is not indicative of future results and does not constitute and should not be construed as investment advice. All trading decisions and investments made by you are at your own discretion and risk. Under no circumstances shall the author be liable for any direct, indirect, or incidental damages. You should only risk capital you can afford to lose.
