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Moving RegressionMoving Regression is a generalization of moving average and polynomial regression. The procedure approximates a specified number of prior data points with a polynomial function of a user-defined degree. Then, polynomial interpolation of the last data point is used to construct a Moving Regression time series. Application: Moving Regression allows one to smooth noise on the analyzed chart, assess momentum, confirm trends, and establish areas of support and resistance. In addition, it can be used as a simple stand-alone forecasting method to identify trend direction and trend​ reversal points. When the local polynomial is predicted to move up in the next time step, the color of the Moving Regression curve will be green. Otherwise, the color of the curve is red. This function is (de)activated using the Predict Trend Direction flag. Selecting the ​model parameters: The effects of the moving window Length and the Local Polynomial Degree are confounded. This allows for​ finding the optimal trade-off between noise (variance) and lag (bias). Higher Length and lower Polynomial Degree (such as 1, i.e. linear), will result in "smoother" time series but at the cost of greater lag. Increasing the Polynomial​ Degree to, for example, 2 (squared) while maintaining the Length will diminish the lag and thus compromise the noise-lag tradeoff. Relation to other methods: When the degree of the local polynomial is set to 0 (i.e., fitting data to a constant level), the Moving Regression time series exactly matches the Simple Moving Average of the same length.
Indicador Pine Script®
por tbtkg
16
ALL TIME HIGHHH BTC! Ola Amigos, Weekly indicator. This indicator, more commonly called "the Pi indicator", is based on the use of two moving averages: mm50 and mm16. By dividing a mm50 in order to try to get as close as possible to PI, we fall back on mm16. 50/16 = 3.13 When the white curve passes above the blue curve, we are on historic highs. It is very easy to test on the BLX, being the graph with the most history. We can say thank you to JDC for this nice discovery which remains very useful for the rest of the BTC run. Love! Ola Amigos, Weekly indicator. Cet indicateur, plus communément appelé "the Pi indicator" est basé sur l'utilisation de deux moyennes mobiles : mm50 et mm16. En divisant une mm50 afin de chercher a essayer de se rapprocher le plus pres de PI, on retombe sur la mm16. 50/16= 3.13 Lorsque la courbe blanche passe au dessus de la courbe bleue, on se trouve sur des plus hauts historiques. Il est très facile a tester sur le BLX , étant le graph avec le plus d'historique. On peut dire merci a JDC pour cette jolie découverte qui reste tres utile pour la suite du run BTC . Love!
Indicador Pine Script®
por Tetrashnos
1
EMA21 Speed & AccelThe script calculates an plots first and second derivatives of a EMA of "length" periods, with a default value of 21 periods. - Blue curve is the first derivative of the EMA, which can be interpreted as the "speed" , "slope", or percentage of gains (or loses) walking over the EMA, measured in % per period. If timeframe is Days, it will show a %/day on the scale @ the right of graphic. - Fuchsia curve is the second derivative of the EMA, and can be assumed to be the "acceleration" or driving force that could augment or diminish the EMA Speed. When Speed & Acceleration ar both >=0, EMA is in positive rally, and becoming stepper, so the bacground is colored green. First and second derivatoves are performed using "basis functions", as are applied in FEM implementation. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- El Script calcula y plotea la primera y segunga derivada de una EMA de "length" períodos, con un valor por defecto de 21. - La curva azul es la primera derivada de la EMA; que puede ser interpretada conmo su "velocidad", "pendiente" o % de ganancia o pérdida que se tendría sobre la EMA. Cuando la unidad de tiempo del gráfico es Días, permite visualizar en la escala de la derecha el % de ganancia o pérdida por día. - La curva Fucsia muestra la segunda derivada, o "Aceleración", que se puede interpretar como la fuerza que puede aumentar o dismu¿inuir la pendiente de la EMA. Cuando la Velocidad y Aceleración son mayores que cero, las ganancias aumentan cada período, y el findo de colorea de verde. Las derivadas primera y segunda se calculan usando técnicas de funciones de forma, como las aplicadas en el MEF.
Indicador Pine Script®
por Saltapones
3
VAMA Volume Adjusted Moving AverageRichard Arms' Volume Adjusted Moving Average Settings: • Inp Avg Vol: Input - Purist method but not intended for live analysis, to retroactively alter MA curve enter Avg Vol from value shown on label into Use Avg Vol field. • Inp Avg Vol: Current - Live method using current volume , to retroactively alter past MA curve toggle any setting back and forth to force recalculation. • Inp Avg Vol: Subset - Similar to Current, but uses a subset rather than all bars for avg vol. • Use Avg Vol - Used for Inp Avg Vol: Input mode. Enter volume from Avg Vol label here after each new bar closes, label will turn green, else red. • Subset Data - Lookback length used for Inp Avg Vol: Subset mode. • VAMA Length - Specified number of volume ratio buckets to be reached. • Volume Incr - Size of volume ratio buckets. • VAMA Source - Price used for volume weighted calculations. • VAMA Strict - Must meet desired volume requirements, even if N bars has to exceed VAMA Length to do it. • Show Avg Vol Label - Displays label on chart of total chart volume. Notes: VAMA was created by Richard Arms. It utilizes a period length that is based on volume increments rather than time. It is an unusual indicator in that it cannot be used in some platforms in realtime mode as Arms had originally intended. VAMA requires that the average volume first be calculated for the entire chart duration, then that average volume is used to derive the variable adaptive length of the moving average. The consequence of this is that with each new bar, the new average volume alters the moving average period for the entire history. Since Pine scripts evaluate all historical bars only once upon initial script execution, there is no way to automatically shift the previous moving average values retroactively once a new bar has formed. Thus the historical plot of the moving average cannot be updated in realtime, but instead can only plot through previous bar that existed upon load or reinitialization through changing some setting. Setting Use Avg Vol to Input mode the average volume through previous bar shown in label can be entered (input) into the Inp Avg Vol setting after each new bar closes. Entering this total chart volume forces the script to reevaluate historical bars which in turn allows the historical moving average to update the plot. When using Input mode the color of the label is green when Inp Avg Vol value matches current label value, the label color red signifies Inp Avg Vol value has not been entered or is stale. Setting Use Avg Vol to Current mode allows the script to correctly calculate and plot the correct moving average upon initial load and the realtime moving average moving forward, but can not retroactively alter the plot of the past moving average unless some change is made in the script settings, such as toggling the Use Avg Vol from Current to some other choice and then back to Current . Setting Use Avg Vol to Subset mode uses a rolling window of volume data to calculate the average volume and can be used in realtime, but should be noted it is a deviation from Richard Arms' original specification. VAMA info: "Trading Without Fear" by Richard W Arms, Jr, www.fidelity.com NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
Indicador Pine Script®
por allanster
30
Shapeshifting Moving Average - Switching From Low-Lag To SmoothThe term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty well. In the case of moving averages based on convolution, their properties are fully described by the moving average kernel ( set of weights ), smooth moving averages tend to have a symmetrical bell shaped kernel, while low lag moving averages have negative weights. One of the few moving averages that would let the user alter the shape of its kernel is the Arnaud Legoux moving average, which convolve the input signal with a parametric gaussian function in which the center and width can be changed by the user, however this moving average is not a low-lagging one, as the weights don't include negative values. Other moving averages where the user can change the kernel from user settings where already presented, i posted a lot of them, but they only focused on letting the user decrease or increase the lag of the moving average, and didn't included specific parameters controlling its smoothness. This is why the shapeshifting moving average is proposed, this parametric moving average will let the user switch from a smooth moving average to a low-lagging one while controlling the amount of lag of the moving average. Settings/Kernel Interaction Note that it could be possible to design a specific kernel function in order to provide a more efficient approach to today goal, but the original indicator was a simple low-lag moving average based on a modification of the second derivative of the arc tangent function and because i judged the indicator a bit boring i decided to include this parametric particularity. As said the moving average "kernel", who refer to the set of weights used by the moving average, is based on a modification of the second derivative of the arc tangent function, the arc tangent function has a "S" shaped curve, "S" shaped functions are called sigmoid functions, the first derivative of a sigmoid function is bell shaped, which is extremely nice in order to design smooth moving averages, the second derivative of a sigmoid function produce a "sinusoid" like shape ( i don't have english words to describe such shape, let me know if you have an idea ) and is great to design bandpass filters. We modify this 2nd derivative in order to have a decreasing function with negative values near the end, and we end up with: The function is parametric, and the user can change it ( thus changing the properties of the moving average ) by using the settings, for example an higher power value would reduce the lag of the moving average while increasing overshoots. When power < 3 the moving average can act as a slow moving average in a moving average crossover system, as weights would not include negative values. Here power = 0 and length = 50. The shapeshifting moving average can approximate a simple moving average with very low power values, as this would make the kernel approximate a rectangular function, however this is only a curiosity and not something you should do. As A Smooth Moving Average “So smooth, and so tranquil. It doesn't get any quieter than this” A smooth moving average kernel should be : symmetrical, not to width and not to sharp, bell shaped curve are often appropriates, the proposed moving average kernel can be symmetrical and can return extremely smooth results. I will use the Blackman filter as comparison. The smooth version of the moving average can be used when the "smooth" setting is selected. Here power can only be an even number, if power is odd, power will be equal to the nearest lowest even number. When power = 0, the kernel is simply a parabola: More smoothness can be achieved by using power = 2 In red the shapeshifting moving average, in green a Blackman filter of both length = 100. Higher values of power will create lower negative values near the border of the kernel shape, this often allow to retain information about the peaks and valleys in the input signal. Power = 6 approximate the Blackman filter pretty well. Conclusion A moving average using a modification of the 2nd derivative of the arc tangent function as kernel has been presented, the kernel is parametric and allow the user to switch from a low-lag moving average where the lag can be increased/decreased to a really smooth moving average. As you can see once you get familiar with a function shape, you can know what would be the characteristics of a moving average using it as kernel, this is where you start getting intimate with moving averages. On a side note, have you noticed that the views counter in posted ideas/indicators has been removed ? This is truly a marvelous idea don't you think ? Thanks for reading !
Indicador Pine Script®
por alexgrover
7
Grand Trend Forecasting - A Simple And Original Approach Today we'll link time series forecasting with signal processing in order to provide an original and funny trend forecasting method, the post share lot of information, if you just want to see how to use the indicator then go to the section "Using The Indicator". Time series forecasting is an area dealing with the prediction of future values of a series by using a specific model, the model is the main tool that is used for forecasting, and is often an expression based on a set of predictor terms and parameters, for example the linear regression (model) is a 1st order polynomial (expression) using 2 parameters and a predictor variable ax + b . Today we won't be using the linear regression nor the LSMA. In time series analysis we can describe the time series with a model, in the case of the closing price a simple model could be as follows : Price = Trend + Cycles + Noise The variables of the model are the components, such model is additive since we add the component with each others, we should be familiar with each components of the model, the trend represent a simple long term variation of high amplitude, the cycles are periodic fluctuations centered around 0 of varying period and amplitude, the noise component represent shorter term irregular variations with mean 0. As a trader we are mostly interested by the cycles and the trend, altho the cycles are relatively more technical to trade and can constitute parasitic fluctuations (think about retracements in a trend affecting your trend indicator, causing potential false signals). If you are curious, in signal processing combining components has a specific name, "synthesis" , here we are dealing with additive synthesis, other type of synthesis are more specific to audio processing and are relatively more complex, but could be used in technical analysis. So what to do with our components ? If we want to trade the trend, we should estimate right ? Estimating the trend component involve removing the cycle and noise component from the price, if you have read stuff about filters you should know where i'am going, yep, we should use filters, in the case of keeping the trend we can use a simple moving average of relatively high period, and here we go. However the lag problem, which is recurrent, come back again, we end up with information easier to interpret (here the trend, which is a simple fluctuation such as a line or other smooth curve) at the cost of decision timing, that is unfortunate but as i said the information, here the moving average output, is relatively simple, and could be easily forecasted right ? If you plot a moving average of high period it would be easier for you to forecast its future values. And thats what we aim to do today, provide an estimate of the trend that should be easy to forecast, and should fit to the price relatively well in order to produce forecast that could determine the position of future closing prices observations. Estimating And Forecasting The Trend The parameter of the indicator dealing with the estimation of the trend is length , with higher values of length attenuating the cycle and noise component in the price, note however that high values of length can return a really long term trend unlike a simple moving average, so a small value of length, 14 for example can still produce relatively correct estimate of trend. here length = 14. The rough estimate of the trend is t in the code, and is an IIR filter, that is, it is based on recursion. Now i'll pass on the filter design explanation but in short, weights are constants, with higher weights allocated to the previous length values of the filter, you can see on the code that the first part of t is similar to an exponential moving average with : t(n) = 0.9t(n-length) + 0.1*Price However while the EMA only use the precedent value for the recursion, here we use the precedent length value, this would just output a noisy and really slow output, therefore in order to create a better fit we add : 0.9*(t(n-length) - t(n-2length)) , and this create the rough trend estimate that you can see in blue. On the parameters, 0.9 is used since it gives the best estimate in my opinion, higher values would create more periodic output and lower values would just create a rougher output. The blue line still contain a residual of the cycle/noise component, this is why it is smoothed with a simple moving average of period length. If you are curious, a filter estimating the trend but still containing noisy fluctuations is called "Notch" filter, such filter would depending on the cutoff remove/attenuate mid term cyclic fluctuations while preserving the trend and the noise, its the opposite of a bandpass filter. In order to forecast values, we simply sum our trend estimate with the trend estimate change with period equal to the forecasting horizon period, this is a really really simple forecasting method, but it can produce decent results, it can also allows the forecast to start from the last point of the trend estimate. Using The Indicator We explained the length parameter in the precedent section, src is the input series which the trend is estimated, forecast determine the forecasting horizon, recommend values for forecast should be equal to length, length/2 or length*2, altho i strongly recommend length. here length and forecast are both equal to 14 . The corrective parameter affect the trend estimate, it reduce the overshoot and can led to a curve that might fit better to the price. The indicator with the non corrective version above, and the corrective one below. The source parameter determine the source of the forecast, when "Noisy" is selected the source is the blue line, and produce a noisy forecast, when "Smooth" is selected the source is the moving average of t , this create a smoother forecast. The width interval control...the width of the intervals, they can be seen above and under the forecast plot, they are constructed by adding/subtracting the forecast with the forecast moving average absolute error with respect to the price. Prediction intervals are often associated with a probability (determining the probability of future values being between the interval) here we can't determine such probability with accuracy, this require (i think) an analysis of the forecasting distribution as well as assumptions on the distribution of the forecasting error. Finally it is possible to see historical forecasts, that is, forecasts previously generated by checking the "Show Historical Forecasts" option. Examples Good forecasts mostly occur when the price is close to the trend estimate, this include the following highlighted periods on AMD 15TF with default settings : We can see the same thing at the end of EURUSD : However we can't always obtain suitable fits, here it is isn't sufficient on BTCUSD : We can see wide intervals, we could change length or use the corrective option to get better results, another option is to use a log scale. We will end the examples with the log SPX, who posses a linear trend, so for example a linear model such as a linear regression would be really adapted, lets see how the indicator perform : Not a great fit, we could try to use an higher length value and use "Smooth" : Most recent fits are quite decent. Conclusions A forecasting indicator has been presented in this post. The indicator use an original approach toward estimating the trend component in the closing price. Of course i should have given statistics related to the forecasting error, however such analysis is worth doing with better methods and in more advanced environment allowing for optimization. But we have learned some stuff related to signal processing as well as time series analysis, seeing a time series as the sum of various components is really helpful when it comes to make sense of chaotic and noisy series and is a basic topic in time series analysis. You can see that in this new year i work harder on the visual of my indicators without trying to fall in the label addict trap, something that i wasn't really doing before, let me know what do you think of it. Thanks for reading !
Indicador Pine Script®
por alexgrover
25
Grover Llorens Activator [alexgrover & Lucía Llorens] Trailing stops play a key role in technical analysis and are extremely popular trend following indicators. Their main strength lie in their ability to minimize whipsaws while conserving a decent reactivity, the most popular ones include the Supertrend, Parabolic SAR and Gann Hilo activator. However, and like many indicators, most trailing stops assume an infinitely long trend, which penalize their ability to provide early exit points, this isn't the case of the parabolic SAR who take this into account and thus converge toward the price at an increasing speed the longer a trend last. Today a similar indicator is proposed. From an original idea of alexgrover & Lucía Llorens who wanted to revisit the classic parabolic SAR indicator, the Llorens activator aim to converge toward the price the longer a trend persist, thus allowing for potential early and accurate exit points. The code make use of the idea behind the price curve channel that you can find here : I tried to make the code as concise as possible. The Indicator The indicator posses 2 user settings, length and mult , length control the rate of convergence of the indicator, with higher values of length making the indicator output converge more slowly toward the price. Mult is also related with the rate of convergence, basically once the price cross the trailing stop its value will become equal to the previous trailing stop value plus/minus mult*atr depending on the previous trailing stop value, therefore higher values of mult will require more time for the trailing stop to reach the closing price, use higher values of mult if you want to avoid potential whipsaws. Above the indicator with slow convergence time (high length) and low mult. Points with early exit points are highlighted. Usage For Oscillators The difference between the closing price and an overlay indicator can provide an oscillator with characteristics depending on the indicators used for differencing, Lucía Llorens stated that we should find indicators for differencing that highlight the cycles in the price, in other terms : Price - Signal , where we want to find Signal such that we maximize the visibility of the cycles, it can be demonstrated that in the case where the closing price is an additive model : Trend + Cycles + Noise , the zero lag estimation of the Trend component can allow for the conservation of the cycle and noise component, that is : Price - Estimate(Trend) , for example the difference between the price and moving average isn't optimal because of the moving average lag, instead the use of zero lag moving averages is more suitable, however the proposed indicator allow for a surprisingly good representation of the cycles when using differencing. The normalization of this oscillator (via the RSI) allow to make the peak amplitude of the cycles more constant. Note however that such method can return an output with a sign inverse to the one of the original cycle component. Conclusion We proposed an indicator which share the logic of the SAR indicator, that is using convergence toward the price in order to provide early exit points detection. We have seen that this indicator can be used to highlight cycles when used for differencing and i don't exclude publishing more indicators based on this method. Lucía Llorens has been a great person to work with, and provided enormous feedback and support while i was coding the indicator, this is why i include her in the indicator name as well as copyright notice. I hope we can make more indicators togethers in the future. (altho i was against using buy/sells labels xD !) Thanks for reading !
Indicador Pine Script®
por alexgrover
44
Yope BTC PL channelThis is a new version of the old "Yope BTC tops channel", but modified to reflect a power-law curve fitted, similar to the model proposed by Harold Christopher Burger in his medium article "Bitcoin’s natural long-term power-law corridor of growth". My original tops channel fitting is still there for comparison. In fact, it looks like the old tops channel was a bit too pessimistic. Note that these channels are still pure naive curve-fitting, and do not represent an underlying model that explains it, like is the case for PlanB's "Modeling Bitcoin's Value with Scarcity" which uses Stock-to-Flow. The motivation for this exercise is to observe how long this empirical extrapolation is valid. Will the price of bitcoin stay in either of both channels? Note on usage: This script _only_ works with the BLX "BraveNewCoin Liquid Index for Bitcoin" in the 1D, 3D and 1W time-frames! It may be necessary to zoom in and out a few times to overcome drawing glitches caused by the extreme time-shifting of plots in order to draw the extrapolated part.
Indicador Pine Script®
por yope
The Vostro Indicator by KIVANÇ fr3762The VOSTRO indicator is a trend indicator that automatically provides buying and selling signals. The indicator marks in a window the potential turning points. The indicator is recommended for scalping. The Vostro indicator determines the overbought zones (value greater than +80) and the oversold zones (less than the -80 level) BUY signal: The Vostro curve moves below the -80 level and forms a trough – Turnaround of the upward trend SELL signal: The Vostro curve moves above the +80 level and forms a peak – Downward trend further info: www.prorealcode.com Here's the link to a complete list of all my indicators: t.co Yazar: KıvanÇ @fr3762 twitter Şimdiye kadar paylaştığım indikatörlerin tam listesi için: t.co
Indicador Pine Script®
por KivancOzbilgic
7
Advanced PSAR v1 [wm]A port off Dennis Meyers Advance PSAR outlined in Stocks and Commodities V13:4 The shape, slope and speed of the SAR is controlled by three parameters: the starting acceleration factor (AF), the increment that the AF can change when a new price high or low is made, and the maximum AF. Because of the way the SAR is calculated, the shape of the SAR curve resembles a parabola - hence its name. Most software packages only allow the user to vary the AF increment and the AF maximum, fixing the starting AF at 0.02. This restriction hampers the trend-following abilities of the parabolic. Frequently as the SAR hugs the price curve, it is penetrated by a price bar by a minuscule amount, causing the SAR to generate an opposite signal. The price then immediately turns around and resumes going in the direction it was going before this penetration occurred, causing a costly whipsaw loss. Many of the whipsaw losses are caused by noise or randomness in the price series. Thus, if the SAR is to represent the trend of a real price series, it must have the capability to ignore penetrations of noise level amounts. To this end, I have modified the parabolic SAR formula to include a variable that allows the SAR not to reverse unless penetrated by a defined amount. This new parameter is defined as ‘XO Increment’ for crossover increment This version is configured for pips. If using on other assets with much larger values should be used. Also note the starting values have not been optimised. Should users of this script find good values please comment and share with the community if you could
Indicador Pine Script®
por causecelebre
4
ALMA Trend DirectionHere is a very simple tool that uses the Arnaud Legoux Moving Average(ALMA). The ALMA is based on a normal distribution and is a reliable moving average due to its ability to reduce lag while still keeping a high degree of smoothness. Input Options: -Offset : Value in range {0,1} that adjusts the curve of the Gaussian Distribution. A higher value will result in higher responsiveness but lower smoothness. A lower value will mean higher smoothness but less responsiveness. -Length : The lookback window for the ALMA calculation. -Sigma : Defines the sharpe of the curve coefficients. I find that this indicator is best used with a longer length and a 4 Hour timeframe. Overall, its purpose is to help identify the direction of a trend and determine whether a security is in an uptrend or a downtrend. For this purpose, it is best to use a lower offset value since we are looking to identify long-term, significant price movement rather than small fluctuations. The Chart: The ALMA is plotted as the aqua and pink alternating line. It is aqua when bullish and pink when bearish. The low price for each candle is then compared to the ALMA. If the low is greater than the ALMA, then there is a bullish trend and the area between the candles and ALMA is filled green. The area between the ALMA and candles is filled red when the low price is less than the ALMA. The difference between the slow ALMA and candles can reveal a lot about the current market state. If there is a significant green gap between the two, then we know that there is a significant uptrend taking place. On the other hand, a large red gap would indicate a significant downtrend. Similarly, if the gap between the two is narrowing and the ALMA line switches from aqua to pink, then we know that a reversal could be coming shortly. ~Happy Trading~
Indicador Pine Script®
por ProfitProgrammers
3
Double ALMAIncludes fast and slow Arnaud Legoux Moving Averages (ALMA). ALMA is a moving average based on a Gaussian(normal) distribution that reduces lag while still retaining smoothness. Input Options: -Offset : Value in range {0,1} that adjusts the curve of the Gaussian Distribution. A higher value will result in higher responsiveness but lower smoothness. A lower value will mean higher smoothness but less responsiveness. -Lengths : The lookback for each ALMA calculation. -Sigma : Defines the sharpe of the curve coefficients. The slow ALMA is the thickest red and green alternating line that indicates bullish or bearish movement. When slow ALMA is bullish, the graph's background changes to green. When the slow ALMA is bearish, the background is red. The fast ALMA uses a smaller lookback and is more responsive than the slow ALMA as a result of the shorter length and higher default offset parameter. The two dotted lines represent (slowALMA +/- 1.25 * stdev(slowALMA, slowALMA period *2)). The indicator bases its buy and sell signals based on the trend identified by the slow ALMA and the fast ALMA's crossings of the standard deviation bands. Comes with pre-set buy and sell alerts.
Indicador Pine Script®
por ProfitProgrammers
1
Modified Gann HiLo ActivatorIntroduction The gann hilo activator is a trend indicator developed by Robert Krausz published into W. D. Gann Treasure Discovered: Simple Trading Plans for Stocks & Commodities . This indicator crate a trailing stop aiming to show the direction of the trend. This indicator is fairly easy to compute and dont require lot of skills to understand. First we calculate the simple moving average of both price high and price low, when the close price is higher than the moving average of the price high the indicator return the moving average of the price low, else the indicator return the moving average of the price high if the close price is lower than the moving average of the price low. My indicator add a different calculation method in order to avoid whipsaw trades as well as adding significance to the moving average length. A Median method has been added to provide more robustness. The Indicator The indicator is a simple trailing stop aiming to show the direction of the trend. The indicator use a different source instead of the price high/low for its calculation. The first method is the "SMA" method which like the classic hilo indicator use a simple moving average for the calculation of the indicator. Sma Method with length = 25 The "Median" use a moving median instead of a simple moving average, this provide more robustness. Median Method with length = 25 The shape is less curved and the indicator can sometimes avoid whipsaw with high's length periods. Mult Parameter The mult parameter is a parameter set to be lower or equal to 1 and greater or equal to 0. High values allow the indicator to be far from the price thus avoiding whipsaw trades, lower ones lower the distance from the price. A mult parameter of 0.1 approximate the original hilo indicator. In blue the indicator with mult = 0.1 and in radical red the original hilo activator. Conclusion The modifications allow more control over the indicator as well as adding more robustness while the original one is destined to fail when market price is more complex. Thanks for reading :) For any questions/suggestions feel free to pm me
Indicador Pine Script®
por alexgrover
20
Quadratic Regression Slope [DW]This is a study geared toward identifying price trends using Quadratic regression. Quadratic regression is the process of finding the equation of a parabola that best fits the set of data being analyzed. In this study, first a quadratic regression curve is calculated, then the slope of the curve is calculated and plotted. Custom bar colors are included. The color scheme is based on whether the slope is positive or negative, and whether it is increasing or decreasing.
Indicador Pine Script®
por DonovanWall
11
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy. Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade. My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength. My sell strategy is triggered by either one of these conditions: the EMA(6) of the close value is crossing under the trailing stop value (green) or the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength. The trailing stop value (green) is set to a multiple of the ATR(15) value. ATR(15) is the SMA(15) value of the difference between the high and low values. The scripts shows a lot of graphical information: The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade. the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end)) the EMA and SMA values for both buy and sell signals are shown as a line the buy and sell(close) signals are labeled in blue How to use this strategy? Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR). Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters) Then keep using these parameters for future buy/sell signals only for that particular stock. Do the same for other stocks. Important : optimizing these parameters is no guarantee for future winning trades! Here are the parameters: Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20) Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100) Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120) Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20) Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100) Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120) Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20) Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing): BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20 NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78% BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9 NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55% AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8 NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938% TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14 NetProfit: 129%, #Trade
Estratégia Pine Script®
por XPl0RR
8
Donchian Channel Trend Intensity [DW]This is an experimental study designed to analyze trend intensity using two Donchian Channels. The DCTI curve is calculated by comparing the differences between Donchian highs and lows over a major an minor period, and expressing them as a positive and negative percentage. The curve is then smoothed with an exponential moving average to provide a signal line. Custom bar colors included with two coloring methods to choose from.
Indicador Pine Script®
por DonovanWall
9
Stefan Krecher: Jeddingen DivergenceThe main idea is to identify a divergence between momentum and price movement. E.g. if the momentum is rising but price is going down - this is what we call a divergence. The divergence will be calculated by comparing the direction of the linear regression curve of the price with the linear regression curve of momentum. A bearish divergence can be identified by a thick red line, a bullish divergence by a green line. When there is a divergence, it is likeley that the current trend will change it's direction. Looking at the chart, there are three divergences that need to get interpreted: 1) bearish divergence, RSI is overbought but MACD does not clearly indicate a trend change. Right after the divergence, price and momentum are going up. No clear signal for a sell trade 2) bearish divergence, RSI still overbought, MACD histogram peaked, MACD crossed the signal line, price and momentum are going down. Very clear constellation for a sell trade. 3) two bullish diverences, RSI is oversold, MACD crossover near the end of the second divergence, price and momentum started rising. Good constellation for a buy trade. Could act as exit signal for the beforementioned sell trade. More information on the Jeddingen Divergence is available here: www.forexpython.com
Indicador Pine Script®
por TradingClue
14
Power Law Correlation Indicator 2.0 The Power Law Correlation Indicator is an attempt to chart when a stock/currency/futures contract goes parabolic forming a upward or downward curve that accelerates according to power laws. I've read about power laws from Sornette Diedler ( www.marketcalls.in ). And I think the theory is a good one. The idea behind this indicator is that it will rise to 1.0 as the curve resembles a parabolic up or down swing. When it is below zero, the stock will flatten out. There are many ways to use this indicator. One way I am testing it out is in trading Strangles or Straddle option trades. When this indicator goes below zero and starts to turn around, it means that it has flattened out. This is like a squeeze indicator. (see the TTM squeeze indicator). Since this indicator goes below zero and the squeeze plays tend to be mean-reverting; then its a great time to put on a straddle/strangle. Another way to use it is to think of it in terms of trend strength. Think of it as a kind of ADX, that measures the trend strength. When it is rising, the trend is strong; when it is dropping, the trend is weak. Lastly I think this indicator needs some work. I tried to put the power (x^n) function into it but my coding skill is limited. I am hoping that Lazy Bear or Ricardo Santos can do it some justice. Also I think that if we can figure out how to do other power law graphs, perhaps we can plot them together on one indicator. So far I really like this one for finding Strangle spots. So check it out. Peace SpreadEagle71
Indicador Pine Script®
por SpreadEagle71
2
RSI MA Cross + Divergence Signal (V2) Core Logic RSI + Moving Average The script calculates a standard RSI (default 14). It then overlays a moving average (SMA/EMA/WMA, default 9). When RSI crosses above its MA → bullish momentum. When RSI crosses below its MA → bearish momentum. Divergence Filter Signals are only valid if there’s confirmed divergence: Bullish divergence: Price makes a lower low, RSI makes a higher low. Bearish divergence: Price makes a higher high, RSI makes a lower high. Overbought / Oversold Filter Optional extra: Bullish signals only valid if RSI ≤ 30 (oversold). Bearish signals only valid if RSI ≥ 70 (overbought). This ensures signals happen in “stretched” conditions. Risk & Trade Management Entries taken only when all conditions align. Exits can be managed with ATR stops, partial take-profits, breakeven moves, and trailing stops (we coded these in the strategy version). Cooldown, session filters, and daily loss guard to keep risk tight. 🔹 Strengths ✅ High selectivity: Combining RSI cross + divergence + OB/OS means signals are rare but higher quality. ✅ Great at catching reversals: Divergence highlights where price may be running out of steam. ✅ Risk management baked in: ATR stops + partial exits smooth out equity curve. ✅ Works across markets: ES, FX, crypto — anywhere RSI divergences are respected. ✅ Flexible: You can loosen/tighten filters depending on aggressiveness. 🔹 Weaknesses ❌ Lag from pivots: Divergence only confirms after a few bars → you enter late sometimes. ❌ Choppy in ranges: In sideways markets, RSI divergences appear often and whipsaw. ❌ Filters reduce signals: With all filters ON (divergence + OB/OS + trend + session), signals can be very rare — may under-trade. ❌ Not standalone: Needs higher-timeframe context (trend, liquidity pools) to avoid counter-trend entries. 🔹 Best Ways to Trade It Use Higher Timeframe Bias Run the strategy on 15m/1H, but only trade in direction of higher timeframe trend (e.g., 4H EMA). Example: If daily is bullish → only take bullish divergences. Pair With Structure Look for signals at key zones: HTF support/resistance, VWAP, or FVGs. Divergence + RSI cross inside an FVG is a strong entry trigger. Adjust OB/OS for Volatility For crypto/FX: use 35/65 instead of 30/70 (markets trend harder). For ES/S&P: 30/70 works fine. Risk Management Is King Use partial exits: take profit at 1R, trail rest. Size by % of equity (we coded this into the strategy). Avoid News Spikes Divergences break down around CPI, NFP, Fed announcements — stay flat. 🔹 When It Shines Trending markets that make extended pushes → clean divergences. Reversal zones (oversold → bullish bounce, overbought → bearish fade). Swing trading (15m–4H) — less noise than 1m/5m scalping. 🔹 When to Avoid Low volatility chop → lots of false divergences. During high-impact news → RSI swings wildly. In strong one-way trends without pullbacks — divergence keeps calling tops/bottoms too early. ✅ Summary: This is a reversal-focused RSI divergence strategy with strict filters. It’s powerful when combined with higher-timeframe bias + structure confluence, but weak if traded blindly in choppy or news-driven conditions. Best to treat it as a precision entry trigger, not a full system — layer it on top of your FVG/ORB framework for maximum edge.
Indicador Pine Script®
por noxum
EMA vs TMA Regime FilterEMA vs TMA Regime Filter This indicator is built as a visual study tool to compare the behavior of the Exponential Moving Average (EMA) and the Triangular Moving Average (TMA). The EMA applies an exponential weighting to price data, giving stronger importance to the most recent values. This makes it a faster, more responsive line that reflects short-term momentum. The TMA, by contrast, applies a double-smoothing process (or in the “True TMA” option, a split SMA sequence), which produces a much slower curve. The TMA emphasizes balance over reactivity, often used for filtering noise and observing longer-term structure. When both are plotted on the same chart, their differences become clear. The shaded region between them highlights times when short-term price dynamics diverge from longer-term smoothing. This is where the idea of “regime” comes in — not as a trading signal, but as a descriptive way of seeing whether market action is currently dominated by speed or by stability. Users can customize: Line styles, widths, and colors. Cloud transparency for visual clarity. Whether to color bars based on relative position (optional, purely visual). The goal is not to create a system, but to help traders experiment, observe, and learn how different smoothing techniques can emphasize different aspects of price. By switching between the legacy and true TMA, or adjusting lengths, users can study how each approach interprets the same data differently.
Indicador Pine Script®
por geneclash
Adaptive Valuation [BackQuant]Adaptive Valuation What this is A composite, zero-centered oscillator that standardizes several classic indicators and blends them into one “valuation” line. It computes RSI, CCI, Demarker, and the Price Zone Oscillator, converts each to a rolling z-score, then forms a weighted average. Optional smoothing, dynamic overbought and oversold bands, and an on-chart table make the inputs and the final score easy to inspect. How it works Components • RSI with its own lookback. • CCI with its own lookback. • DM (Demarker) with its own lookback. • PZO (Price Zone Oscillator) with its own lookback. Standardization via z-score Each component is transformed using a rolling z-score over lookback bars: z = (value − mean) ÷ stdev , where the mean is an EMA and the stdev is rolling. This puts all inputs on a comparable scale measured in standard deviations. Weighted blend The z-scores are combined with user weights w_rsi, w_cci, w_dm, w_pzo to produce a single valuation series. If desired, it is then smoothed with a selected moving average (SMA, EMA, WMA, HMA, RMA, DEMA, TEMA, LINREG, ALMA, T3). ALMA’s sigma input shapes its curve. Dynamic thresholds (optional) Two ways to set overbought and oversold: • Static : fixed levels at ob_thres and os_thres . • Dynamic : ±k·σ bands, where σ is the rolling standard deviation of the valuation over dynLen . Bands can be centered at zero or around the valuation’s rolling mean ( centerZero ). Visualization and UI • Zero line at 0 with gradient fill that darkens as the valuation moves away from 0. • Optional plotting of band lines and background highlights when OB or OS is active. • Optional candle and background coloring driven by the valuation. • Summary table showing each component’s current z-score, the final score, and a compact status. How it can be used • Bias filter : treat crosses above 0 as bullish bias and below 0 as bearish bias. • Mean-reversion context : look for exhaustion when the valuation enters the OB or OS region, then watch for exits from those regions or a return toward 0. • Signal confirmation : use the final score to confirm setups from structure or price action. • Adaptive banding : with dynamic thresholds, OB and OS adjust to prevailing variability rather than relying on fixed lines. • Component tuning : change weights to emphasize trend (raise DM, reduce RSI/CCI) or range behavior (raise RSI/CCI, reduce DM). PZO can help in swing environments. Why z-score blending helps Indicators often live on different scales. Z-scoring places them on a common, unitless axis, so a one-sigma move in RSI has comparable influence to a one-sigma move in CCI. This reduces scale bias and allows transparent weighting. It also facilitates regime-aware thresholds because the dynamic bands scale with recent dispersion. Inputs to know • Component lookbacks : rsilb, ccilb, dmlb, pzolb control each raw signal. • Standardization window : lookback sets the z-score memory. Longer smooths, shorter reacts. • Weights : w_rsi, w_cci, w_dm, w_pzo determine each component’s influence. • Smoothing : maType, smoothP, sig govern optional post-blend smoothing. • Dynamic bands : dyn_thres, dynLen, thres_k, centerZero configure the adaptive OB/OS logic. • UI : toggle the plot, table, candle coloring, and threshold lines. Reading the plot • Above 0 : composite pressure is positive. • Below 0 : composite pressure is negative. • OB region : valuation above the chosen OB line. Risk of mean reversion rises and momentum continuation needs evidence. • OS region : mirror logic on the downside. • Band exits : leaving OB or OS can serve as a normalization cue. Strengths • Normalizes heterogeneous signals into one interpretable series. • Adjustable component weights to match instrument behavior. • Dynamic thresholds adapt to changing volatility and drift. • Transparent diagnostics from the on-chart table. • Flexible smoothing choices, including ALMA and T3. Limitations and cautions • Z-scores assume a reasonably stationary window. Sharp regime shifts can make recent bands unrepresentative. • Highly correlated components can overweight the same effect. Consider adjusting weights to avoid double counting. • More smoothing adds lag. Less smoothing adds noise. • Dynamic bands recalibrate with dynLen ; if set too short, bands may swing excessively. If too long, bands can be slow to adapt. Practical tuning tips • Trending symbols: increase w_dm , use a modest smoother like EMA or T3, and use centerZero dynamic bands. • Choppy symbols: increase w_rsi and w_cci , consider ALMA with a higher sigma , and widen bands with a larger thres_k . • Multiday swing charts: lengthen lookback and dynLen to stabilize the scale. • Lower timeframes: shorten component lookbacks slightly and reduce smoothing to keep signals timely. Alerts • Enter and exit of Overbought and Oversold, based on the active band choice. • Bullish and bearish zero crosses. Use alerts as prompts to review context rather than as stand-alone trade commands. Final Remarks We created this to show people a different way of making indicators & trading. You can process normal indicators in multiple ways to enhance or change the signal, especially with this you can utilise machine learning to optimise the weights, then trade accordingly. All of the different components were selected to give some sort of signal, its made out of simple components yet is effective. As long as the user calibrates it to their Trading/ investing style you can find good results. Do not use anything standalone, ensure you are backtesting and creating a proper system.
Indicador Pine Script®
por BackQuant