Adaptive Oscillator constructor [lastguru]Adaptive Oscillators use the same principle as Adaptive Moving Averages. This is an experiment to separate length generation from oscillators, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. Note that all Oscillators here are normalized to -1..1 range. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource , so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Oscillators.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers , but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power ( exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Oscillators section offer you a choice of Oscillator algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
CMO - Chande Momentum Oscillator
RSI - Relative Strength Index
Volume-scaled RSI - my own version of RSI. It scales price movements by the proportion of RMS of volume
Momentum RSI - RSI of price momentum
Rocket RSI - inspired by RocketRSI by John F. Ehlers (not an exact implementation)
MFI - Money Flow Index
LRSI - Laguerre RSI by John F. Ehlers
LRSI with Fractal Energy - a combo oscillator that uses Fractal Energy to tune LRSI gamma
Fractal Energy - Fractal Energy or Choppiness Index by E. W. Dreiss
Efficiency ratio - based on Kaufman Adaptive Moving Average calculation
DMI - Directional Movement Index (only ADX is drawn)
Fast DMI - same as DMI, but without secondary smoothing
If no Adaptation is selected (None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set.
Before an Oscillator, a High Pass filter may be executed to remove cyclic components longer than the provided Highpass Length (no High Pass filter, if Highpass Length = 0). Both before and after the Oscillator a Moving Average can be applied. The following Moving Averages are included: SMA, RMA, EMA, HMA , VWMA, 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. For more details on these Moving Averages, you can check my other Adaptive Constructor indicator:
The Oscillator output may be renormalized and postprocessed with the following Normalization algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Inverse Fisher Transform - Inverse Fisher Transform
Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers
Except for Inverse Fisher Transform, all Normalization algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Oscillator length is used.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Komut dosyalarını "如何用wind搜索股票的发行价和份数" için ara
Runners & Laggers (scanner)Firstly, seems to me this may only work with crypto but I know nothing about the other sectors so i could be wrong. I was trying to think up a good way to find moving coins(other than by volume bc theres holes in the results when using it this way). Thought this was an interesting concept so decided to publish it as I've seen no others like it (though i did not extensively search for it. We need to start with a little Tradingview(TV) common knowledge. When there is no update of trades/volume in a candle TV does not print the candle. So when looking at (let's say) a 1 second chart, if the coin being observed by the user has no update from a trade in the time of that 1 sec candle it is skipped over. This means that a coin with a ton of volume might fill an entire 60 seconds with 60 candles and conversely with a low volume coin there could be as little as 0 1-second candles. BUT even for normally low volume coins, when a pump is beginning with the coin it could literally go from 0 1-second candles within a minute to 60 1-second candles within the next minute. ***NOTE: This DOES NOT show ANY information if the coin is going up or down but rather that a LOT more trading volume is occurring than normal.*** What this script does is scans (via request.security feature) up to 40 coins at a time and counts how many candles are printed within a user set timespan calculated in minute. 1 candle print per incremented timeframe that the chart is on. ie. if the chart is a 1 min chart it counts how many 1 min candles are printed. So, (as is in the captured image for the script) if you wanted to count how many 5 second candles are printed for each coin in 1 min then you would have to put the charts timeframe on 5sec and the setting titled 'Window of TIME(in minutes) to count bars' as 1.0 (which bc it's in minutes 1.0m = 60sec and bc 60s / 5s = 12 there would be 12 possible values that each coin can be at depending on how many bars are counted within that 1min/60sec. *** I will update to show an image of what I'm talking about here. Now, the exchange I'm scanning here is Kucoin's Margin Coins. There are 170 something coins total but I removed a few i didn't care for to make it a round 40 coins per set (there being 4 sets of 40 coins total=160 coins being scanned). To scan all 4 sets the indicator must be added 4 times to the chart and a different 'set' selected for each iteration of the script on the chart. Free users can only scan 3 at the most. All others can scan all 4 sets. In the script you can change the exchange and coins as necessary. If there done so and there are not 40 coins total just put '' '' in the extra coins spots that are not filled and the script will skip over these blankly filled spots. The suffix (traded pair) for the tickerID on all Kucoin's Margin Coin's is USDT so that's what i have inputted in the main function on line 46 (will need to be changed if that differs from the coins you want to scan. Next in the line of settings is 'Window of TIME(in minutes) to count bars' which has already been discussed. Following that is the setting "Table Shows" which the results are all in a table and the table will present the coins that have either "Passed" or "Failed" depending on which you choose. The next setting determines what passes or fails. If there are 12 possible rows for the coins to be in (as described above) then this setting is the "Pass/Fail Cutoff" level. So if you want to show all the coins that are in rows 11 and 12 (as in the image at top) then 11 should be selected here. At this point you will see all the coins that have a lot of volume in them. Finding coin names in the table that are usually not with a ton of volume will present your present movers. NOTE: coins like BTC and ETH will almost always be in these levels so it does not indicate anything different from the norm of these coins. Last setting is the ability to show the table on the main window or not. Hope you enjoy and find use in it. BTW this screener format is the same as the others I have published. If you like, check those out too. If you find difficulty using then refer to those as well as they have additional info in them on how to use the scanner and its format. Lastly, in the script is the ability to print the plots and labels but I commented them out bc its really just a jumbled mess. In the commented out sections there is a Random Color Function (provided by @hewhomustnotbenamed which was developed on the basis of Function-HSL-color by @RicardoSantos. All right, peace brothers....and sisters.
**** Also, I see how the "levels" could be confusing so I will put them into a % format soon (probably not today) so that the "Pass/Fail Cutoff" can be in % format so that if "passed" is chosen and 50% is chosen (in the new setting that will be changed) then it'll show you all the coins that have more than 50% of the bars printed within the time window chosen. Goodluck in all your trading adventures. ChasinAlts out.
JohnEhlersFourierTransformLibrary "JohnEhlersFourierTransform"
Fourier Transform for Traders By John Ehlers, slightly modified to allow to inspect other than the 8-50 frequency spectrum.
reference:
www.mesasoftware.com
high_pass_filter(source) Detrended version of the data by High Pass Filtering with a 40 Period cutoff
Parameters:
source : float, data source.
Returns: float.
transformed_dft(source, start_frequency, end_frequency) DFT by John Elhers.
Parameters:
source : float, data source.
start_frequency : int, lower bound of the frequency window, must be a positive number >= 0, window must be less than or 30.
end_frequency : int, upper bound of the frequency window, must be a positive number >= 0, window must be less than or 30.
Returns: tuple with float, float array.
db_to_rgb(db, transparency) converts the frequency decibels to rgb.
Parameters:
db : float, decibels value.
transparency : float, transparency value.
Returns: color.
BjCandlePatternsLibrary "BjCandlePatterns"
Patterns is a Japanese candlestick pattern recognition Library for developers. Functions here within detect viable setups in a variety of popular patterns. Please note some patterns are without filters such as comparisons to average candle sizing, or trend detection to allow the author more freedom.
doji(dojiSize, dojiWickSize) Detects "Doji" candle patterns
Parameters:
dojiSize : (float) The relationship of body to candle size (ie. body is 5% of total candle size). Default is 5.0 (5%)
dojiWickSize : (float) Maximum wick size comparative to the opposite wick. (eg. 2 = bottom wick must be less than or equal to 2x the top wick). Default is 2
Returns: (series bool) True when pattern detected
dLab(showLabel, labelColor, textColor) Produces "Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bullEngulf(maxRejectWick, mustEngulfWick) Detects "Bullish Engulfing" candle patterns
Parameters:
maxRejectWick : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a top wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a top wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick : (bool) input to only detect setups that close above the high prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bewLab(showLabel, labelColor, textColor) Produces "Bullish Engulfing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bearEngulf(maxRejectWick, mustEngulfWick) Detects "Bearish Engulfing" candle patterns
Parameters:
maxRejectWick : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a bottom wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a botom wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick : (bool) Input to only detect setups that close below the low prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bebLab(showLabel, labelColor, textColor) Produces "Bearish Engulfing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
hammer(ratio, shadowPercent) Detects "Hammer" candle patterns
Parameters:
ratio : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent : (float) The maximum allowable top wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
hLab(showLabel, labelColor, textColor) Produces "Hammer" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
star(ratio, shadowPercent) Detects "Star" candle patterns
Parameters:
ratio : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent : (float) The maximum allowable bottom wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
ssLab(showLabel, labelColor, textColor) Produces "Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
dragonflyDoji() Detects "Dragonfly Doji" candle patterns
Returns: (series bool) True when pattern detected
ddLab(showLabel, labelColor) Produces "Dragonfly Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
Returns: (series label) A label visible at the chart level intended for the title pattern
gravestoneDoji() Detects "Gravestone Doji" candle patterns
Returns: (series bool) True when pattern detected
gdLab(showLabel, labelColor, textColor) Produces "Gravestone Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tweezerBottom(closeUpperHalf) Detects "Tweezer Bottom" candle patterns
Parameters:
closeUpperHalf : (bool) input to only detect setups that close above the mid-point of the candle prior increasing its bullish tendancy. Default is false
Returns: (series bool) True when pattern detected
tbLab(showLabel, labelColor, textColor) Produces "Tweezer Bottom" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tweezerTop(closeLowerHalf) Detects "TweezerTop" candle patterns
Parameters:
closeLowerHalf : (bool) input to only detect setups that close below the mid-point of the candle prior increasing its bearish tendancy. Default is false
Returns: (series bool) True when pattern detected
ttLab(showLabel, labelColor, textColor) Produces "TweezerTop" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTopBull(wickSize) Detects "Bullish Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stwLab(showLabel, labelColor, textColor) Produces "Bullish Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTopBear(wickSize) Detects "Bearish Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stbLab(showLabel, labelColor, textColor) Produces "Bearish Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTop(wickSize) Detects "Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stLab(showLabel, labelColor, textColor) Produces "Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
morningStar() Detects "Bullish Morning Star" candle patterns
Returns: (series bool) True when pattern detected
msLab(showLabel, labelColor, textColor) Produces "Bullish Morning Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
eveningStar() Detects "Bearish Evening Star" candle patterns
Returns: (series bool) True when pattern detected
esLab(showLabel, labelColor, textColor) Produces "Bearish Evening Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBull() Detects "Bullish Harami" candle patterns
Returns: (series bool) True when pattern detected
hwLab(showLabel, labelColor, textColor) Produces "Bullish Harami" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBear() Detects "Bearish Harami" candle patterns
Returns: (series bool) True when pattern detected
hbLab(showLabel, labelColor, textColor) Produces "Bearish Harami" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBullCross() Detects "Bullish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcwLab(showLabel, labelColor, textColor) Produces "Bullish Harami Cross" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBearCross() Detects "Bearish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcbLab(showLabel, labelColor) Produces "Bearish Harami Cross" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
Returns: (series label) A label visible at the chart level intended for the title pattern
marubullzu() Detects "Bullish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mwLab(showLabel, labelColor, textColor) Produces "Bullish Marubozu" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
marubearzu() Detects "Bearish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mbLab(showLabel, labelColor, textColor) Produces "Bearish Marubozu" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
abandonedBull() Detects "Bullish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abwLab(showLabel, labelColor, textColor) Produces "Bullish Abandoned Baby" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
abandonedBear() Detects "Bearish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abbLab(showLabel, labelColor, textColor) Produces "Bearish Abandoned Baby" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
piercing() Detects "Piercing" candle patterns
Returns: (series bool) True when pattern detected
pLab(showLabel, labelColor, textColor) Produces "Piercing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
darkCloudCover() Detects "Dark Cloud Cover" candle patterns
Returns: (series bool) True when pattern detected
dccLab(showLabel, labelColor, textColor) Produces "Dark Cloud Cover" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tasukiBull() Detects "Upside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
utgLab(showLabel, labelColor, textColor) Produces "Upside Tasuki Gap" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tasukiBear() Detects "Downside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
dtgLab(showLabel, labelColor, textColor) Produces "Downside Tasuki Gap" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
risingThree() Detects "Rising Three Methods" candle patterns
Returns: (series bool) True when pattern detected
rtmLab(showLabel, labelColor, textColor) Produces "Rising Three Methods" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
fallingThree() Detects "Falling Three Methods" candle patterns
Returns: (series bool) True when pattern detected
ftmLab(showLabel, labelColor, textColor) Produces "Falling Three Methods" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
risingWindow() Detects "Rising Window" candle patterns
Returns: (series bool) True when pattern detected
rwLab(showLabel, labelColor, textColor) Produces "Rising Window" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
fallingWindow() Detects "Falling Window" candle patterns
Returns: (series bool) True when pattern detected
fwLab(showLabel, labelColor, textColor) Produces "Falling Window" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
kickingBull() Detects "Bullish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kwLab(showLabel, labelColor, textColor) Produces "Bullish Kicking" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
kickingBear() Detects "Bearish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kbLab(showLabel, labelColor, textColor) Produces "Bearish Kicking" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
lls(ratio) Detects "Long Lower Shadow" candle patterns
Parameters:
ratio : (float) A relationship of the lower wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
llsLab(showLabel, labelColor, textColor) Produces "Long Lower Shadow" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
lus(ratio) Detects "Long Upper Shadow" candle patterns
Parameters:
ratio : (float) A relationship of the upper wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
lusLab(showLabel, labelColor, textColor) Produces "Long Upper Shadow" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bullNeck() Detects "Bullish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nwLab(showLabel, labelColor, textColor) Produces "Bullish On Neck" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bearNeck() Detects "Bearish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nbLab(showLabel, labelColor, textColor) Produces "Bearish On Neck" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
soldiers(wickSize) Detects "Three White Soldiers" candle patterns
Parameters:
wickSize : (float) Maximum allowable top wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
wsLab(showLabel, labelColor, textColor) Produces "Three White Soldiers" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
crows(wickSize) Detects "Three Black Crows" candle patterns
Parameters:
wickSize : (float) Maximum allowable bottom wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
bcLab(showLabel, labelColor, textColor) Produces "Three Black Crows" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
triStarBull() Detects "Bullish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tswLab(showLabel, labelColor, textColor) Produces "Bullish Tri-Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
triStarBear() Detects "Bearish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tsbLab(showLabel, labelColor, textColor) Produces "Bearish Tri-Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
wrap(cond, barsBack, borderColor, bgcolor) Produces a box wrapping the highs and lows over the look back.
Parameters:
cond : (series bool) Condition under which to draw the box.
barsBack : (series int) the number of bars back to begin drawing the box.
borderColor : (series color) Color of the four borders. Optional. The default is color.gray.
bgcolor : (series color) Background color of the box. Optional. The default is color.gray.
Returns: (series box) A box who's top and bottom are above and below the highest and lowest points over the lookback
topWick() returns the top wick size of the current candle
Returns: (series float) A value equivelent to the distance from the top of the candle body to its high
bottomWick() returns the bottom wick size of the current candle
Returns: (series float) A value equivelent to the distance from the bottom of the candle body to its low
body() returns the body size of the current candle
Returns: (series float) A value equivelent to the distance between the top and the bottom of the candle body
highestBody() returns the highest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
lowestBody() returns the lowest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
barRange() returns the height of the current candle
Returns: (series float) A value equivelent to the distance between the high and the low of the candle
bodyPct() returns the body size as a percent
Returns: (series float) A value equivelent to the percentage of body size to the overall candle size
midBody() returns the price of the mid-point of the candle body
Returns: (series float) A value equivelent to the center point of the distance bewteen the body low and the body high
bodyupGap() returns true if there is a gap up between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap up and no overlap in the real bodies of the current candle and the preceding candle
bodydwnGap() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapUp() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapDwn() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
dojiBody() returns true if the candle body is a doji
Returns: (series bool) true if the candle body is a doji. Defined by a body that is 5% of total candle size
Summary ChecklistThis works on daily charts
Summarizes some data as shown.
Projects volume for eod.
Sometimes it opens on new window. You have to move it to the price window.
vol_rangesThis script shows three measures of volatility:
historical (hv): realized volatility of the recent past
median (mv): a long run average of realized volatility
implied (iv): a user-defined volatility
Historical and median volatility are based on the EWMA, rather than standard deviation, method of calculating volatility. Since Tradingview's built in ema function uses a window, the "window" parameter determines how much historical data is used to calculate these volatility measures. E.g. 30 on a daily chart means the previous 30 days.
The plots above and below historical candles show past projections based on these measures. The "periods to expiration" dictates how far the projection extends. At 30 periods to expiration (default), the plot will indicate the one standard deviation range from 30 periods ago. This is calculated by multiplying the volatility measure by the square root of time. For example, if the historical volatility (hv) was 20% and the window is 30, then the plot is drawn over: close * 1.2 * sqrt(30/252).
At the most recent candle, this same calculation is simply drawn as a line projecting into the future.
This script is intended to be used with a particular options contract in mind. For example, if the option expires in 15 days and has an implied volatility of 25%, choose 15 for the window and 25 for the implied volatility options. The ranges drawn will reflect the two standard deviation range both in the future (lines) and at any point in the past (plots) for HV (blue), MV (red), and IV (grey).
FOTSI - Open sourceI WOULD LIKE TO SPECIFY TWO THINGS:
- The indicator was absolutely not designed by me, I do not take any credit and much less I want them, I am just making this fantastic indicator open source and accessible to all
- The script code was not recycled from other indicators, but was created from 0 following the theory behind it to the letter, thus avoiding copyright infringement
- Advices and improvements are accepted, as having very little programming experience in Pine Script I consider this work still rough and slow
WHAT IS THE FOTSI?
The FOTSI is an oscillator that measures the relative strength of the individual currencies that make up the 28 major Forex exchanges.
By identifying the currencies that are in the overbought (+50) and oversold (-50) areas, it is possible to anticipate the correction of a currency pair following a strong trend.
THE THEORY BEHIND
1) At the base of everything is the 1-period momentum (close-open) of the single currency pairs that contain a certain currency. For example, the momentum of the USD currency is composed of all the exchange rates that contain the US dollar inside it: mom_usd = - mom_eurusd - mom_gbpusd + mom_usdchf + mom_usdjpy - mom_audusd + mom_usdcad - mom_nzdusd. Where the base currency is in second position, the momentum is subtracted instead of adding it.
2) The IST formula is applied to the momentum of the individual currencies obtained. In this way we get an oscillator that oscillates between 0 and its overbought and oversold areas. The area between +25 and -25 is an area in which we can consider the movements of individual currencies to be neutral.
3) The TSI is nothing more than a double smoothing on the momentum of individual currencies. This particularity makes the indicator very reactive, minimizing the delays of the trend reversal.
HOW TO USE
1) A currency is identified that is in the overbought (+50) or oversold (-50) area. Example GBP = 50
2) The second currency is identified as the one most opposite to the first. Example USD = -25
3) The currency pair consisting of the two currencies opens. So GBP / USD
4) Considering that GBP is oversold, we anticipate its future devaluation. So in this case we are short on GBP / SUD. Otherwise if GBP had been oversold (-50) we expect its future valuation and therefore we enter long.
5) It is used on the H1, H4 and D1 timeframes
6) Closing conditions: the position on the 50-period exponential moving average is split / the position at target on the 100-period exponential moving average is closed
7) Stoploss: it is recommended not to use it, if you want to use it it is equivalent to 5 times the ATR on the reference timeframe
8) Position sizing: go very slow! Being a counter-trend strategy, it is very risky to position yourself heavily. Use common sense in everything!
9) To insert the alerts that warn you of an overbought and oversold condition, it is necessary to enter the signals called "Overbought Signal" and "Oversold Signal" for each chart used, in the specific Trading View window. like me using multiple charts in the same window.
I hope you enjoy my work. For any questions write in the comments.
Thanks <3
//--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
TENGO A PRECISARE DUE COSE:
- L'indicatore non è stato assolutamente ideato da me, non mi assumo nessun merito e tanto meno li voglio, io sto solo rendendo questo fantastico indicatore open source ed accessibile a tutti
- Il codice dello script non è stato riciclato da altri indicatori, ma è stato creato da 0 seguendo alla lettere la teoria che sta alla sua base, evitando così di violare il copyright
- Si accettano consigli e migliorie, visto che avendo pochissima esperienza di programmazione in Pine Script considero questo lavoro ancora grezzo e lento
COS'È IL FOTSI?
Il FOTSI è un oscillatore che misura la forza relativa delle singole valute che compongono i 28 cambi major del Forex.
Individuando le valute che si trovano nelle aree di ipercomprato (+50) ed ipervenduto (-50) , è possibile anticipare la correzione di una coppia valutaria al seguito di un forte trend.
LA TEORIA ALLA BASE
1) Alla base di tutto c'è il momentum ad 1 periodo (close-open) delle singole coppie valutarie che contengono una determinata valuta. Ad esempio il momentum della valuta USD è composto da tutti i cambi che contengono il dollaro americano al suo interno: mom_usd = - mom_eurusd - mom_gbpusd + mom_usdchf + mom_usdjpy - mom_audusd + mom_usdcad - mom_nzdusd . Ove la valuta base si trova in seconda posizione si sottrae il momentum al posto che sommarlo.
2) Si applica la formula del TSI ai momentum delle singole valute ottenute. In questo modo otteniamo un oscillatore che oscilla tra lo 0 e le sue aree di ipercomprato ed ipervenduto. L'area compresa tra +25 e -25 è un area in cui possiamo considerare neutri i movimenti delle singole valute.
3) Il TSI non è altro che un doppio smoothing sul momentum delle singole valute. Questa particolarità rende l'indicatore molto reattivo, minimizzando i ritardi dell'inversione del trend.
COME SI USA
1) Si individua una valuta che si trova nell'area di ipercomprato (+50) o ipervenduto (-50) . Esempio GBP = 50
2) Si individua come seconda valuta quella più opposta alla prima. Esempio USD = -25
3) Si apre la coppia di valuta composta dalle due valute. Quindi GBP/USD
4) Considerando che GBP è in fase di ipervenduto prevediamo una sua futura svalutazione. Quindi in questo caso entriamo short su GBP/SUD. Diversamente se GBP fosse stato in fase di ipervenduto (-50) ci aspettiamo una sua futura valutazione e quindi entriamo long.
5) Si usa sui timeframe H1, H4 e D1
6) Condizioni di chiusura: si smezza la posizione sulla media mobile esponenziale a 50 periodi / si chiude la posizione a target sulla media mobile esponenziale a 100 periodi
7) Stoploss: è consigliato non usarlo, nel caso lo si voglia utilizzare esso equivale a 5 volte l'ATR sul timeframe di riferimento
8) Position sizing: andateci molto piano! Essendo una strategia contro trend è molto rischioso posizionarsi in modo pesante. Usate il buonsenso in tutto!
9) Per inserire gli allert che ti avvertono di una condizione di ipercomprato ed ipervenduto, è necessario inserire dall'apposita finestra di Trading View i segnali denominati "Segnale di ipercomprato" ed "Segnale di ipervenduto" per ogni grafico che si usa, nel caso come me che si utilizzano più grafici nella stessa finestra.
Spero che possiate apprezzare il mio lavoro. Per qualsiasi domanda scrivete nei commenti.
Grazie<3
KAMA Strategy - Kaufman's Adaptive Moving AverageThis strategy combines Kaufman's Adaptive Moving Average for entry with optional KAMA, PSAR, and Trailing ATR stops for exits.
Kaufman's Adaptive Moving Average is, in my opinion, a gem among the plethora of indicators. It is underrated considering it offers a solution that intuitively makes a lot of sense. When I first read about it, it was a real 'aha!' moment. Look at the top, pink line. Notice how during trending times it follows the trend quickly and closely, but during choppy, non-trending periods, the KAMA stays absolutely flat? Interesting! To trade with it, we simply follow the direction the KAMA is pointing. Is it up? Go long. Is it down? Go short. Is it flat? Hold on.
How does it manage to quickly follow real trends like a fast EMA but ignore choppy conditions that would whipsaw a fast EMA back and forth? It analyses whether recent price moves are significant relative to recent noise and then adapts the length of the EMA window accordingly. If price movement is big compared to the recent noise, the EMA window gets smaller. If price movement is relatively small or average compared to the recent noise, the EMA window gets bigger. In practice it means:
The KAMA would be flat if a 20 point upwards move occurred during a period that has had, on average, regular 20 point moves BUT
the KAMA would point up if a 20 point move occurred during a period that has, on average, had moves of only around 5 points.
In other words, it's a slow EMA during choppy flat / quiet flat periods, and a fast EMA as soon as significant volatility occurs. Perfect!
-----
The Strategy
The strategy is more than just a KAMA indicator. It contains:
KAMA exit (optional)
ATR trailing stop loss exit (optional)
PSAR stop loss exit (optional)
KAMA filter for entry and exits
All features are adjustable in the strategy settings
The Technical Details:
Check out the strategy's 'Inputs' panel. The buy and sell signals are based on the 'KAMA 1' there.
KAMA 1: Length -- 14 is the default. This is the length of the window the KAMA looks back over. In this instance, it c
KAMA 1: Fast KAMA Length -- 2 is the default. This is the tightest the EMA length is allowed to get. It will tend towards this length when volatility is high.
KAMA 1: Slow KAMA Length -- 20 is the default. This is the biggest the EMA length is allowed to get. It will tend towards this length when volatility is low.
KAMA Filter
The strategy buys when the KAMA begins to point up and sells when the KAMA points down. Generally, the KAMA is very good at filtering out the noise itself - it will go flat during noisy/choppy periods. But to add another layer of safety, its author, Perry Kaufman, proposed a KAMA filter. It works by taking the standard deviation of returns over the length of the the 'KAMA 1: Length' I mentioned above and multiplying it by an 'Entry Filter' (1 by default) and 'Exit Filter' (0.5 by default). The entry condition to go long is that the KAMA is pointing up and and it moved up more than 1 x St. Dev. of Returns. The exit condition is when the KAMA is pointing down and it moved down by more than 0.5 x St. Dev. of Returns.
Thanks
Thanks to ChuckBanger, cheatcountry, millerrh, and racer8 for parts of the code. I was able to build upon their good work.
-----
I hope this strategy is helpful to you.
Do you have any thoughts, ideas, or questions? Let me know in the comments or send me a message! I'd be glad to help you out.
If you need an indicator or strategy to be built or customised for you, let me know! I'll be glad to help and it'll probably be cheaper than you think!
Indicators all in oneHello Everyone . Sometimes we need some indicators and each one needs seperated window. with this tool we can see indicators by choosing it from pull down menu, in the same window.
Currently you can choose RSI, MACD, Commodity Channel Index (CCI), Momentum, Stochastic, Stochastic RSI, Directional Movement Index (DMI), Chaikin Money Flow (CMF), On-Balance Volume (OBV), Average True Range (ATR), Volume Weigthed MACD (VWMACD).
some screen shots:
DMI:
MACD:
Stochastic RSI
Let me know if you need any other indicator in this tool.
Enjoy!
RSI + Composite Index [SHK]One of the most powerful indicator based and divergence strategies i have ever seen was made by Constance Brown.
The Composite Index:
The best way to think of the Composite Index as it applies to the RSI is to think of the RSI as Windows 3.0 and the Composite Index as Windows 10. Constance Brown discovered that the RSI, while it does create and detect divergences, does is not as accurate as it could be. It’s a bit of an oxymoron to say this but the RSI is a momentum indicator without any momentum calculation attached to it. The RSI actually misses a significant amount of important moves and even generates some bad moves. What Constance Brown did with the RSI is to input a momentum calculation within the RSI itself.
Usage:
1. Check hidden and regular divergences on RSI+COMPOSITE_INDEX and PRICE+COMPOSITE_INDEX.
2. After finding divergence wait for COMPOSITE_INDEX to cross under/over it's moving averages to trigger.
Useful Note:
"RSI overbought/oversold as filter", "RSI and COMPOSITE_INDEX trendline as trigger", "RSI 50 Over/Under as trend direction detection", ... can be add to this strategy.
Enjoy!
Center of Gravity Oscillator - Ehlers by KIVANC fr3762Center of Gravity OSCILLATOR by JOHN EHLERS
Converted the original code from his book "Cybernetic Analysis for Stocks and Futures"
This article describes a new oscillator that is unique because it is both smoothed
and has essentially zero lag. The smoothing enables clear identification of turning
points and the zero lag aspect enables action to be taken early in the move. This
oscillator is the serendipitous result of my research into adaptive filters. While the filters
have not yet produced the result I seek, this oscillator has substantial advantages over
conventional oscillators used in technical analysis . The “CG” in the name of the
oscillator stands for the Center of Gravity of the prices over the window of observation.
The Center of Gravity ( CG ) of a physical object is its balance point. For example,
if you balance a 12 inch ruler on your finger, the CG will be at its 6 inch point. If you
change the weight distribution of the ruler by putting a paper clip on one end, then the
balance point (e.g. the CG ) shifts toward the paper clip. Moving from the physical world
to the trading world, we can substitute the prices over our window of observation for the
units of weight along the ruler. With this analogy, we see that the CG of the window
moves to the right when prices increase sharply. Correspondingly, the CG of the
window moves to the left when prices decrease.
For further information:
www.mesasoftware.com
Here's the link to a complete list of all my indicators:
t.co
Şimdiye kadar paylaştığım indikatörlerin tam listesi için: t.co
Support and Resistance lines - version 2I created a new version of the Support and Resistance lines script. Compared to the original script this version
1. works with a lot more currency pairs
2. SR line width can be set in the indicator settings window
3. the vertical lines, arrows and the SR lines can be turned off in the indicator settings window
4. the indicator settings window can be opened by clicking on a star symbol that is placed in the upper right corner of the graph window
PT Feeder - HighLowPricePercentageYet another script to help people set the Addon PT Feeder for a trading bot Profit Trailer. Same rule applies if you do not own this the following explanation will not help you.
- Add the script to your favourites
- Edit Minutes for short term and long term for both indicators
- Set candle size you are using default is 5 Minutes
HighLowPricePercentage (Source PT Feeder Wiki)
"This is a property to try and check the variance of the price from the norm and is over the MinutesToMeasureTrend time window. The math is:
firstVariance = (high.ActualPrice - low.ActualPrice) / 2
medianVariance = high.ActualPrice - firstVariance
highLowPercentage = (latestActualPrice - medianVariance) / latestActualPrice * 100".
LongerTermHighLowPricePercentage (Source PT Feeder Wiki)
"This is a property to try and check the variance of the price from the norm and is over the LongerTermMinutesToMeasureTrend time window. The math is the same as the HighLowPricePercentage".
Sources:
PT Feeder Wiki - github.com
LTC: LYHj4WDN7BPu5294cSpqK3SgWSWdDX56Qt
BTC: 1NPVzeDSsenaCS9QdPro877hkMk93nRLcD
EEI Strategy — Greedy/Guarded v1.2Purpose
Day‑trading strategy (5‑min focus) that hunts “armed” setups (PRE) and confirms them (GO) with greedy-but‑guarded execution. It adapts to symbol type, trend strength, and how long it’s been since the last signal.
Core signals & regime
Trend/Regime: EMA‑200 (intraday bias), VWAP, and a non‑repainting HTF EMA (via request.security(...) ).
Momentum/Structure: Manual Wilder DMI/ADX, micro‑ribbon (EMA 8/21), Bollinger‑Keltner squeeze + “squeeze fire,” BOS (break of swing high/low), pullback to band.
Liquidity/Vol: RVOL vs SMA(volume) + a latch (keeps eligibility a few bars after the first spike).
Volatility: ATR + ATR EMA (expansion).
PRE / GO engine
Score (0–100) aggregates trend, momentum, RVOL, squeeze, OBV slope, ribbon, pullback, BOS, and an Opening‑Range (OR) proximity penalty.
PRE arms when the adjusted score ≥ threshold and basic hygiene passes (ATR%, cooldown, etc.).
GO confirms within a dynamic window (1–3 bars):
Wick‑break mode on hot momentum (trend‑day / high ADX+RVOL): stop orders above/below the PRE high/low with a tick buffer.
Close‑through mode otherwise: close must push through PRE high/low plus ATR buffer.
Chase guard: entry cannot be too far from PRE price (ATR‑based), with a tiny extra allowance when the 8/21 ribbon aligns.
Multiple PREs per squeeze (capped) + per‑entry cooldown.
Adaptive behavior
Presets (Conservative/Balanced/Aggressive/Turbo) shift score/ADX/RVOL/ATR gates, GO window, cooldown, and max chase.
Profiles / Auto by Symbol:
Mega Trend (e.g., AMD/NVDA/TSLA/AAPL): looser chase, ATR stop, chandelier trail.
Mid Guarded (e.g., TTD/COIN/SOFI): swing stop, EMA trail, moderate gates.
Small Safe (e.g., BTAI/BBAI class): tighter gates, more guardrails.
BBAI micro‑override: easier arming (lower score/ADX/RVOL), multi‑PRE=3, swing stop + EMA trail, lighter OR penalty.
Trend‑day detector: if ADX hot + RVOL strong + ATR expanding + distance from day‑open large → GO window = 1 and wick‑break mode.
Mid‑day relaxers: mild score bonus between 10:30–14:30 to keep signals flowing in quieter tape.
Auto‑Relaxer (no‑signal fallback): after N bars without PRE/GO, gradually lowers score/ADX/RVOL/ATR% gates and raises max chase so the engine doesn’t stall on sleepy symbols.
Auto‑Session fallback: if RTH session isn’t detected (some tickers/premarket), it falls back to daily boundaries so Opening Range and day‑open logic still work.
Risk & exits
Initial stop per side chosen by ATR, Swing, or OR (computed every bar; no conditional calls).
Scaled targets: TP1/TP2 (R‑based) + runner with optional Chandelier or EMA trailing.
BE logic: optional move to breakeven after TP1; trailing can start after TP1 if configured.
Opening Range (OR)
Computes day open, OR high/low over configurable minutes; applies a penalty when entries are too close to OR boundary (lighter for small caps/BBAI). Protects against boundary whips.
Alerts & visuals
Alertconditions: PRE Long/Short Armed, GO Long/Short + explicit alert() calls for once‑per‑bar automation.
Plots: EMA‑200, HTF EMA, BB/KC bands, OR lines, squeeze shading, and PRE markers.
Why it’s robust
Non‑repainting HTF technique, all series precomputed every bar, no function calls hidden in conditionals that could break history dependence, and consistent state handling (var + sentinels).
Tuning cheat‑sheet (fast wins)
More trades: lower scoreBase, adxHot, or rvolMinBase a notch; reduce cooldownBase; increase maxPREperSqueeze.
Fewer whips: increase closeBufferATR, wickBufferTicks, or atrMinPct; reduce maxChaseATRBase.
Trend capture: use trailType="Chandelier", smaller trailLen, slightly larger trailMult; set preset="Aggressive".
Choppy names: prefer stopMode="Swing", enable EMA trail, keep OR penalty on.
Breakout Volume Momentum [5m]Breakout Volume Momentum Indicator (Pine Script v5)
This TradingView Pine Script v5 indicator plots a green dot below a 5-minute price bar whenever all the breakout and volume conditions are met. It is optimized for live intraday trading (not backtesting) and includes customizable inputs for thresholds and trading session times. Key features and conditions of this indicator:
Gap Up Threshold: Current price is up at least X% (default 20%) from the previous day’s close (uses higher-timeframe daily data) before any signal can trigger.
Relative Volume (RVOL): Current bar’s volume is at least Y× (default 2×) the average volume of the last 20 bars. This ensures unusually high volume is present, indicating strong interest.
Trend Alignment: Price is trading above the VWAP (Volume-Weighted Average Price) and above a fast EMA. In addition, the fast EMA (default 9) is above the slower EMA (default 20) to confirm bullish momentum
tradingview.com
tradingview.com
. These filters ensure the stock is in an intraday uptrend (above the average price and rising EMAs).
Intraday Breakout (optional): Optionally require the price to break above the recent intraday high (default last 30 bars). If enabled, a signal only occurs when the stock exceeds its prior range high, confirming a breakout. This can be toggled on/off in the settings.
Avoid Parabolic Spikes: The script skips any bar with an excessively large range (default >12% from low to high), to avoid triggering on spiky or unsustainable parabolic candles.
Time Window Filter: Signals are restricted to a specific session window (by default 09:30 – 11:00 exchange time, typically the morning session) and will not trigger outside these hours. The session window is adjustable via inputs
stackoverflow.com
.
Alerts: An alert condition is provided so you can set a Trading View alert to send a push notification when a green dot signal fires. The alert message includes the ticker and price at the time of signal.
Time-Decaying Percentile Oscillator [BackQuant]Time-Decaying Percentile Oscillator
1. Big-picture idea
Traditional percentile or stochastic oscillators treat every bar in the look-back window as equally important. That is fine when markets are slow, but if volatility regime changes quickly yesterday’s print should matter more than last month’s. The Time-Decaying Percentile Oscillator attempts to fix that blind spot by assigning an adjustable weight to every past price before it is ranked. The result is a percentile score that “breathes” with market tempo much faster to flag new extremes yet still smooth enough to ignore random noise.
2. What the script actually does
Build a weight curve
• You pick a look-back length (default 28 bars).
• You decide whether weights fall Linearly , Exponentially , by Power-law or Logarithmically .
• A decay factor (lower = faster fade) shapes how quickly the oldest price loses influence.
• The array is normalised so all weights still sum to 1.
Rank prices by weighted mass
• Every close in the window is paired with its weight.
• The pairs are sorted from low to high.
• The cumulative weight is walked until it equals your chosen percentile level (default 50 = median).
• That price becomes the Time-Decayed Percentile .
Find dispersion with robust statistics
• Instead of a fragile standard deviation the script measures weighted Median-Absolute-Deviation about the new percentile.
• You multiply that deviation by the Deviation Multiplier slider (default 1.0) to get a non-parametric volatility band.
Build an adaptive channel
• Upper band = percentile + (multiplier × deviation)
• Lower band = percentile – (multiplier × deviation)
Normalise into a 0-100 oscillator
• The current close is mapped inside that band:
0 = lower band, 50 = centre, 100 = upper band.
• If the channel squeezes, tiny moves still travel the full scale; if volatility explodes, it automatically widens.
Optional smoothing
• A second-stage moving average (EMA, SMA, DEMA, TEMA, etc.) tames the jitter.
• Length 22 EMA by default—change it to tune reaction speed.
Threshold logic
• Upper Threshold 70 and Lower Threshold 30 separate standard overbought/oversold states.
• Extreme bands 85 and 15 paint background heat when aggressive fade or breakout trades might trigger.
Divergence engine
• Looks back twenty bars.
• Flags Bullish divergence when price makes a lower low but oscillator refuses to confirm (value < 40).
• Flags Bearish divergence when price prints a higher high but oscillator stalls (value > 60).
3. Component walk-through
• Source – Any price series. Close by default, switch to typical price or custom OHLC4 for futures spreads.
• Look-back Period – How many bars to rank. Short = faster, long = slower.
• Base Percentile Level – 50 shows relative position around the median; set to 25 / 75 for quartile tracking or 90 / 10 for extreme tails.
• Deviation Multiplier – Higher values widen the dynamic channel, lowering whipsaw but delaying signals.
• Decay Settings
– Type decides the curve shape. Exponential (default 1.16) mimics EMA logic.
– Factor < 1 shrinks influence faster; > 1 spreads influence flatter.
– Toggle Enable Time Decay off to compare with classic equal-weight stochastic.
• Smoothing Block – Choose one of seven MA flavours plus length.
• Thresholds – Overbought / Oversold / Extreme levels. Push them out when working on very mean-reverting assets like FX; pull them in for trend monsters like crypto.
• Display toggles – Show or hide threshold lines, extreme filler zones, bar colouring, divergence labels.
• Colours – Bullish green, bearish red, neutral grey. Every gradient step is automatically blended to generate a heat map across the 0-100 range.
4. How to read the chart
• Oscillator creeping above 70 = market auctioning near the top of its adaptive range.
• Fast poke above 85 with no follow-through = exhaustion fade candidate.
• Slow grind that lives above 70 for many bars = valid bullish trend, not a fade.
• Cross back through 50 shows balance has shifted; treat it like a micro trend change.
• Divergence arrows add extra confidence when you already see two-bar reversal candles at range extremes.
• Background shading (semi-transparent red / green) warns of extreme states and throttles your position size.
5. Practical trading playbook
Mean-reversion scalps
1. Wait for oscillator to reach your desired OB/ OS levels
2. Check the slope of the smoothing MA—if it is flattening the squeeze is mature.
3. Look for a one- or two-bar reversal pattern.
4. Enter against the move; first target = midline 50, second target = opposite threshold.
5. Stop loss just beyond the extreme band.
Trend continuation pullbacks
1. Identify a clean directional trend on the price chart.
2. During the trend, TDP will oscillate between midline and extreme of that side.
3. Buy dips when oscillator hits OS levels, and the same for OB levels & shorting
4. Exit when oscillator re-tags the same-side extreme or prints divergence.
Volatility regime filter
• Use the Enable Time Decay switch as a regime test.
• If equal-weight oscillator and decayed oscillator diverge widely, market is entering a new volatility regime—tighten stops and trade smaller.
Divergence confirmation for other indicators
• Pair TDP divergence arrows with MACD histogram or RSI to filter false positives.
• The weighted nature means TDP often spots divergence a bar or two earlier than standard RSI.
Swing breakout strategy
1. During consolidation, band width compresses and oscillator oscillates around 50.
2. Watch for sudden expansion where oscillator blasts through extreme bands and stays pinned.
3. Enter with momentum in breakout direction; trail stop behind upper or lower band as it re-expands.
6. Customising decay mathematics
Linear – Each older bar loses the same fixed amount of influence. Intuitive and stable; good for slow swing charts.
Exponential – Influence halves every “decay factor” steps. Mirrors EMA thinking and is fastest to react.
Power-law – Mid-history bars keep more authority than exponential but oldest data still fades. Handy for commodities where seasonality matters.
Logarithmic – The gentlest curve; weight drops sharply at first then levels off. Mimics how traders remember dramatic moves for weeks but forget ordinary noise quickly.
Turn decay off to verify the tool’s added value; most users never switch back.
7. Alert catalogue
• TD Overbought / TD Oversold – Cross of regular thresholds.
• TD Extreme OB / OS – Breach of danger zones.
• TD Bullish / Bearish Divergence – High-probability reversal watch.
• TD Midline Cross – Momentum shift that often precedes a window where trend-following systems perform.
8. Visual hygiene tips
• If you already plot price on a dark background pick Bullish Color and Bearish Color default; change to pastel tones for light themes.
• Hide threshold lines after you memorise the zones to declutter scalping layouts.
• Overlay mode set to false so the oscillator lives in its own panel; keep height about 30 % of screen for best resolution.
9. Final notes
Time-Decaying Percentile Oscillator marries robust statistical ranking, adaptive dispersion and decay-aware weighting into a simple oscillator. It respects both recent order-flow shocks and historical context, offers granular control over responsiveness and ships with divergence and alert plumbing out of the box. Bolt it onto your price action framework, trend-following system or volatility mean-reversion playbook and see how much sooner it recognises genuine extremes compared to legacy oscillators.
Backtest thoroughly, experiment with decay curves on each asset class and remember: in trading, timing beats timidity but patience beats impulse. May this tool help you find that edge.
TrendShift [MOT]📈 TrendShift – Multi-Factor Momentum & Trend Signal Suite
TrendShift is a precision-built momentum and confluence tool designed to highlight directional shifts in price action. It combines EMA slope structure, oscillator confirmation, volume behavior, and dynamic SL/TP logic into one cohesive system. Whether you're trading with the trend or catching reversals, TrendShift provides data-backed clarity and visual confidence — and it’s available free to the public.
🔍 Core Signal Logic
Buy (🟢 Long) and Sell (🔴 Short) signals are triggered when multiple conditions align within a set bar window (default: 5 bars):
Stochastic RSI K/D cross
RSI crosses above 20 (long) or below 80 (short)
Stochastic RSI breaks 20 (long) or 80 (short)
Volume exceeds 20-bar average
🧭 Visual Trend Dashboard – Signal Table
A real-time on-chart dashboard displays:
EMA Trend: Bullish / Bearish / Mixed (based on 4 EMA slopes)
Stoch RSI: Oversold / Overbought / Neutral
RSI: Exact value with zone label
Volume: Above or Below average
Dashboard theme and position are fully customizable.
📐 Trend Structure with EMA Slope Logic
Plots four EMAs (21, 50, 100, 200) color-coded by slope:
Green = Rising
Red = Falling
These feed into the dashboard's EMA Trend display.
🎯 Optional Take Profit / Stop Loss Zones
When enabled, SL/TP lines plot automatically on valid signals:
Fixed-distance targets (e.g., 10pt TP, 5pt SL)
Auto-remove on TP or SL hit
Separate lines for long vs. short trades
Fully customizable styling
🔁 Trailing Stop Filter (Internal Logic)
A custom ATR-based trailing stop helps validate directional strength:
ATR period
HHV window
ATR multiplier
Used internally — not plotted — to confirm trend progression before entry.
⚙️ Customizable Parameters
Every core component is user-configurable:
EMA periods: 21 / 50 / 100 / 200
ATR trailing logic: period, HHV, multiplier
Oscillator settings: Stoch RSI & RSI
Volume length
SL/TP toggles and point values
Bar clustering window
Dashboard theme and location
🔔 Alerts Included
BUY Signal Triggered
SELL Signal Triggered
Compatible with webhook automation or mobile push notifications.
⚠️ Disclaimer
This tool is for educational purposes only and is not financial advice. Trading involves risk — always do your own research and consult a licensed professional before making trading decisions.
Big Trade % Heatmap### Big Trade % Heatmap
**Quick overview**
This indicator highlights where “whale” activity is clustered by showing what fraction of the recent candles contained *large‑value trades*. A candle is considered “big” when its notional volume (`volume × close`) exceeds your chosen USD threshold. You instantly see:
* **Percent of big candles** in the last *N* bars, refreshed at the cadence you pick.
* **On‑chart labels & markers** every refresh, so the chart stays clean.
* **Optional heat‑map background** that turns orange (>20 %) or green (>50 %) when big‑trade concentration spikes.
* **Ready‑made alert** when big‑trade dominance crosses 50 %.
---
#### How it works
1. **Trade size per candle** – Calculates `close × volume` to estimate dollars traded.
2. **Threshold filter** – Flags candles whose value is above *Big Trade Threshold (\$)*.
3. **Look‑back window** – Counts what percentage of the last *Lookback Window (X Candles)* were “big.”
4. **Refresh interval** – Repeats the measurement only every *Refresh Interval (Every X Candles)* to avoid label spam.
5. **Visuals** –
* A small blue ▼ above the bar + a text label such as `35.00 % > $25 000`.
* Background shading (green/orange) for quick, at‑a‑glance sentiment.
---
#### Inputs
| Input | Purpose | Default |
| -------------------------------------- | ----------------------------------------------------- | ------- |
| **Lookback Window (X Candles)** | How many recent bars to sample for the % calculation. | 20 |
| **Refresh Interval (Every X Candles)** | How often to display a new label/marker. | 5 |
| **Big Trade Threshold (\$)** | Minimum USD value for a candle to count as “big.” | 10 000 |
Tune these to the symbol and timeframe you trade (e.g., raise the threshold for BTC‑USDT 1‑h, lower it for micro‑caps).
---
#### Alerts
Enable **“High Big Trade %”** to get notified the moment more than half of the last *N* candles qualify as big trades—handy for spotting sudden accumulation or distribution.
---
#### Typical use cases
* **Breakout confirmation** – A surge in big‑trade % just before price escapes a range can validate the move.
* **Whale spotting** – Detect hidden accumulation on pullbacks or aggressive selling into rallies.
* **Filter noise** – Combine with your favorite trend indicator; only act when both align.
---
> *Built with Pine Script v6. Always back‑test before trading live; this tool is for educational purposes and not financial advice.*
LANZ Strategy 5.0🔷 LANZ Strategy 5.0 — Intraday BUY Signals, Dynamic Lot Size per Account, Real-Time Dashboard and Smart Execution
LANZ Strategy 5.0 is a powerful intraday tool designed for traders who need a visual-first, data-backed BUY system, enhanced with risk-aware lot size calculation and a real-time performance dashboard. This indicator intelligently detects strong momentum setups and provides visual and statistical clarity throughout the session.
📌 This is an indicator, not a strategy — It does not place trades automatically but provides precise conditions, alerts, and visual guides to support execution.
🧠 Core Logic & Features
BUY Entry Conditions (Signal Engine)
A BUY signal is triggered when:
The current price is above the EMA200 (trend filter)
The last 3 candles are bullish (candle body close > open)
You are within the defined session window (NY time)
When all conditions are met and you haven’t reached the daily trade limit, a signal appears on the chart and an optional alert is triggered.
Operational Hours Filter (NY Time)
You define:
Start time (e.g., 01:15 NY)
End time (e.g., 16:00 NY)
The system only evaluates and executes signals within this period. If a BUY setup occurs outside the window, it’s ignored. The chart is also highlighted with a transparent teal background to visually show active trading hours.
Lot Size Panel with Per-Account Risk Management
Designed for traders managing multiple accounts or capital sources. You can enable up to 5 accounts, each with:
Its own capital
Its own risk percentage per trade
The system uses the defined SL in pips, plus the instrument’s pip value, to calculate the lot size per account. All values are shown in a dedicated panel at the bottom-right, automatically updating with each new trade.
The emojis (🐣🦊🦁🐲🐳) distinguish each account visually.
Trade Visualization with Customizable Lines
When a signal is triggered:
An Entry Point (EP) line is drawn at the candle’s close.
A Stop Loss (SL) line is placed X pips below the entry.
A Take Profit (TP) line is placed Y pips above the entry.
All three lines are fully customizable in style, color, and thickness. You define how many bars the lines should extend.
Outcome Tracking & Real-Time Dashboard
Each trade outcome is measured:
SL hit = –1.00%
TP hit = +3.00%
Manual close = calculated dynamically based on price at close time
Each result is labeled on the chart near its level, and stored.
The top-right dashboard updates in real time:
✅ Number of trades
📈 Cumulative % gain/loss of the day (color-coded)
Alerts You Can Trust:
You’ll get a Buy Alert when a valid signal is formed
You’ll get a Trade Executed Alert when the visual operation is plotted
You’ll get a SL/TP Hit Alert with price and result
You’ll get a Manual Close Alert if the configured time is reached and the trade is still active
⚙️ Step-by-Step Execution Flow
At every bar, the system checks:
Are we within the session time window?
Is price above EMA?
Are the last 3 candles bullish?
✅ If yes:
A BUY signal is plotted
Entry/SL/TP lines are drawn
Lot sizes are calculated and displayed
Trade is added to the daily count
🕐 At the configured Manual Close time (e.g., 16:00 NY):
If the trade is still open, it's closed
A label is added with the exact result in %
💡 Ideal For:
Intraday traders who operate within fixed time sessions
Traders managing multiple accounts or capital pools
Anyone who wants full visual clarity of every decision point
Traders who appreciate dynamic lot size calculation and clean execution tracking
👨💻 Credits:
💡 Developed by: LANZ
🧠 Strategy concept & execution model: LANZ
🧪 Tested on: 1H charts with visual-only execution
📈 Designed for: Clarity, adaptability, and full intraday control
Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator
What Is It?
The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis.
Scientific Foundation
The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets.
The indicator also borrows from Log-Periodic Power Law (LPPL).
Core Concepts
1. Entropy Deficit
The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness:
Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets
Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness
High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior
Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events
2. Multi-Scale Analysis
The indicator calculates entropy across different timeframes:
Short-term Entropy (blue line): Captures recent market behavior (20-day window)
Long-term Entropy (green line): Captures structural market behavior (120-day window)
Main Entropy (purple line): Primary measurement (60-day window)
3. Scale Ratio
This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations.
How It Works
Data Collection: The indicator samples price returns over specific lookback periods
Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution
Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy
Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure
Risk Assessment: Multiple factors are combined to generate a composite risk score and classification
Market Interpretation
Low Risk Environments (Risk Score < 25)
Market is functioning efficiently with reasonable randomness
Price discovery is likely effective
Normal trading and investment approaches appropriate
Medium Risk Environments (Risk Score 25-50)
Increasing correlation in price movements
Beginning of trend formation or momentum
Time to monitor positions more closely
High Risk Environments (Risk Score 50-75)
Strong herding behavior present
Market potentially becoming one-sided
Consider reducing position sizes or implementing hedges
Extreme Risk Environments (Risk Score > 75)
Highly ordered market behavior
Significant imbalance between buyers and sellers
Heightened probability of sharp reversals or corrections
Practical Application Examples
Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top
Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization
Range-Bound Markets: Typically display low and stable entropy deficit measurements
Trending Markets: Often show moderate entropy deficit that remains relatively consistent
Advantages Over Traditional Indicators
Forward-Looking: Identifies changing market structure before price action confirms it
Statistical Foundation: Based on robust mathematical principles rather than empirical patterns
Adaptability: Functions across different market regimes and asset classes
Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations
Limitations
Not a Timing Tool: Signals market risk conditions, not precise entry/exit points
Parameter Sensitivity: Results can vary based on the chosen parameters
Historical Context: Requires some historical perspective to interpret effectively
Complementary Tool: Works best alongside other analysis methods
Enjoy :)
Open Range Breakout (ORB) with Alerts
🚀 ChartsAlgo – Open Range Breakout (ORB) with Alerts
The Open Range Breakout (ORB) Indicator by ChartsAlg is designed for intraday traders looking to capitalize on price movements after the market’s opening range. This tool is especially effective for futures (MNQ, MES) and high-volatility stocks or crypto where initial volatility sets the tone for the session.
This indicator identifies a user-defined opening range window, plots the high/low lines of that range, and visually alerts users when price breaks out above or below the range — with options to customize breakout repetitions, background fill, and alerts.
💡 What is an Open Range Breakout (ORB)?
The opening range represents the high and low established during the first few minutes of the trading session — usually 15 or 30 minutes. Many intraday strategies are based on the idea that breaking out of this initial range often signals strong momentum and trend continuation.
Traders often enter:
Long when price breaks above the range high.
Short when price breaks below the range low.
⚙️ How It Works
You define a session window (e.g., 09:30–09:45 EST).
The indicator tracks the high and low during this time.
Once the session ends, the high and low become your range breakout levels.
The indicator then:
Plots lines for visual clarity
Optionally fills background between the range
Triggers breakout signals if price crosses the levels
Provides alerts when breakouts occur
🛠️ Settings Breakdown
🔹 Session Settings
Range Session: Set your preferred window (e.g., 0930–0945). Can be premarket, first 30 mins, or any custom time.
Time zone: Use "America/New York" for EST (default) or change to "GMT+0" for international traders.
🔹 Breakout Settings
Bullish Breakout Signals: Number of allowed breakout alerts above the range.
Bearish Breakout Signals: Number of allowed breakout alerts below the range.
This prevents repeated alerts once breakout has been confirmed.
🔹 Display Settings
Show Background Fill: Fills area between high/low of the range for easier visual analysis.
Show Breakout Signals: Triangle markers plotted on the chart when breakouts happen.
Only Show Today’s Range: Keeps the chart clean by showing only the most current day’s range.
🔹 Color Settings
Range High/Low Line Colors: Choose any color for clarity.
Range Fill Color: Customize the highlight area for your chart style.
📊 Chart Features
Range High/Low Lines: Automatically plotted after range session ends.
Visual Fill Box: Optional background shading between the opening range.
Triangle Breakout Markers: Appear at the breakout candle.
Alerts: Can be used with TradingView’s alert system to notify you of breakouts in real-time.
🔔 Alerts
Two alert conditions are built in:
Bullish Breakout: Triggers when price breaks above the high of the range.
Bearish Breakout: Triggers when price breaks below the low of the range.
Example Alert Message:
📈 “Bullish Breakout above Open Range on AAPL!”
To activate:
Click “🔔 Alerts” on TradingView.
Set condition to this script.
Choose “ORB Breakout Up” or “ORB Breakout Down”.
Choose alert frequency and notification method.
⚠️ DISCLAIMER
ChartsAlgo tools are for informational and educational purposes only.
They are not financial advice or signals. Past performance does not guarantee future results. Use at your own risk and always implement solid risk management.
By using this indicator, you agree that you are solely responsible for any trades or decisions made based on the information provided.
SIP Evaluator and Screener [Trendoscope®]The SIP Evaluator and Screener is a Pine Script indicator designed for TradingView to calculate and visualize Systematic Investment Plan (SIP) returns across multiple investment instruments. It is tailored for use in TradingView's screener, enabling users to evaluate SIP performance for various assets efficiently.
🎲 How SIP Works
A Systematic Investment Plan (SIP) is an investment strategy where a fixed amount is invested at regular intervals (e.g., monthly or weekly) into a financial instrument, such as stocks, mutual funds, or ETFs. The goal is to build wealth over time by leveraging the power of compounding and mitigating the impact of market volatility through disciplined, consistent investing. Here’s a breakdown of how SIPs function:
Regular Investments : In an SIP, an investor commits to investing a fixed sum at predefined intervals, regardless of market conditions. This consistency helps inculcate a habit of saving and investing.
Cost Averaging : By investing a fixed amount regularly, investors purchase more units when prices are low and fewer units when prices are high. This approach, known as dollar-cost averaging, reduces the average cost per unit over time and mitigates the risk of investing a large amount at a peak price.
Compounding Benefits : Returns generated from the invested amount (e.g., capital gains or dividends) are reinvested, leading to exponential growth over the long term. The longer the investment horizon, the greater the potential for compounding to amplify returns.
Dividend Reinvestment : In some SIPs, dividends received from the underlying asset can be reinvested to purchase additional units, further enhancing returns. Taxes on dividends, if applicable, may reduce the reinvested amount.
Flexibility and Accessibility : SIPs allow investors to start with small amounts, making them accessible to a wide range of individuals. They also offer flexibility in terms of investment frequency and the ability to adjust or pause contributions.
In the context of the SIP Evaluator and Screener , the script simulates an SIP by calculating the number of units purchased with each fixed investment, factoring in commissions, dividends, taxes and the chosen price reference (e.g., open, close, or average prices). It tracks the cumulative investment, equity value, and dividends over time, providing a clear picture of how an SIP would perform for a given instrument. This helps users understand the impact of regular investing and make informed decisions when comparing different assets in TradingView’s screener. It offers insights into key metrics such as total invested amount, dividends received, equity value, and the number of installments, making it a valuable resource for investors and traders interested in understanding long-term investment outcomes.
🎲 Key Features
Customizable Investment Parameters: Users can define the recurring investment amount, price reference (e.g., open, close, HL2, HLC3, OHLC4), and whether fractional quantities are allowed.
Commission Handling: Supports both fixed and percentage-based commission types, adjusting calculations accordingly.
Dividend Reinvestment: Optionally reinvests dividends after a user-specified period, with the ability to apply tax on dividends.
Time-Bound Analysis: Allows users to set a start year for the analysis, enabling historical performance evaluation.
Flexible Dividend Periods: Dividends can be evaluated based on bars, days, weeks, or months.
Visual Outputs: Plots key metrics like total invested amount, dividends, equity value, and remainder, with customizable display options for clarity in the data window and chart.
🎲 Using the script as an indicator on Tradingview Supercharts
In order to use the indicator on charts, do the following.
Load the instrument of your choice - Preferably a stable stocks, ETFs.
Chose monthly timeframe as lower timeframes are insignificant in this type of investment strategy
Load the indicator SIP Evaluator and Screener and set the input parameters as per your preference.
Indicator plots, investment value, dividends and equity on the chart.
🎲 Visualizations
Installments : Displays the number of SIP installments (gray line, visible in the data window).
Invested Amount : Shows the cumulative amount invested, excluding reinvested dividends (blue area plot).
Dividends : Tracks total dividends received (green area plot).
Equity : Represents the current market value of the investment based on the closing price (purple area plot).
Remainder : Indicates any uninvested cash after each installment (gray line, visible in the data window).
🎲 Deep dive into the settings
The SIP Evaluator and Screener offers a range of customizable settings to tailor the Systematic Investment Plan (SIP) simulation to your preferences. Below is an explanation of each setting, its purpose, and how it impacts the analysis:
🎯 Duration
Start Year (Default: 2020) : Specifies the year from which the SIP calculations begin. When Start Year is enabled via the timebound option, the script only considers data from the specified year onward. This is useful for analyzing historical SIP performance over a defined period. If disabled, the script uses all available data.
Timebound (Default: False) : A toggle to enable or disable the Start Year restriction. When set to False, the SIP calculation starts from the earliest available data for the instrument.
🎯 Investment
Recurring Investment (Default: 1000.0) : The fixed amount invested in each SIP installment (e.g., $1000 per period). This represents the regular contribution to the SIP and directly influences the total invested amount and quantity purchased.
Allow Fractional Qty (Default: True) : When enabled, the script allows the purchase of fractional units (e.g., 2.35 shares). If disabled, only whole units are purchased (e.g., 2 shares), with any remaining funds carried forward as Remainder. This setting impacts the precision of investment allocation.
Price Reference (Default: OPEN): Determines the price used for purchasing units in each SIP installment. Options include:
OPEN : Uses the opening price of the bar.
CLOSE : Uses the closing price of the bar.
HL2 : Uses the average of the high and low prices.
HLC3 : Uses the average of the high, low, and close prices.
OHLC4 : Uses the average of the open, high, low, and close prices. This setting affects the cost basis of each purchase and, consequently, the total quantity and equity value.
🎯 Commission
Commission (Default: 3) : The commission charged per SIP installment, expressed as either a fixed amount (e.g., $3) or a percentage (e.g., 3% of the investment). This reduces the amount available for purchasing units.
Commission Type (Default: Fixed) : Specifies how the commission is calculated:
Fixed ($) : A flat fee is deducted per installment (e.g., $3).
Percentage (%) : A percentage of the investment amount is deducted as commission (e.g., 3% of $1000 = $30). This setting affects the net amount invested and the overall cost of the SIP.
🎯 Dividends
Apply Tax On Dividends (Default: False) : When enabled, a tax is applied to dividends before they are reinvested or recorded. The tax rate is set via the Dividend Tax setting.
Dividend Tax (Default: 47) : The percentage of tax deducted from dividends if Apply Tax On Dividends is enabled (e.g., 47% tax reduces a $100 dividend to $53). This reduces the amount available for reinvestment or accumulation.
Reinvest Dividends After (Default: True, 2) : When enabled, dividends received are reinvested to purchase additional units after a specified period (e.g., 2 units of time, defined by Dividends Availability). If disabled, dividends are tracked but not reinvested. Reinvestment increases the total quantity and equity over time.
Dividends Availability (Default: Bars) : Defines the time unit for evaluating when dividends are available for reinvestment. Options include:
Bars : Based on the number of chart bars.
Weeks : Based on weeks.
Months : Based on months (approximated as 30.5 days). This setting determines the timing of dividend reinvestment relative to the Reinvest Dividends After period.
🎯 How Settings Interact
These settings work together to simulate a realistic SIP. For example, a $1000 recurring investment with a 3% commission and fractional quantities enabled will calculate the number of units purchased at the chosen price reference after deducting the commission. If dividends are reinvested after 2 months with a 47% tax, the script fetches dividend data, applies the tax, and adds the net dividend to the investment amount for that period. The Start Year and Timebound settings ensure the analysis aligns with the desired timeframe, while the Dividends Availability setting fine-tunes dividend reinvestment timing.
By adjusting these settings, users can model different SIP scenarios, compare performance across instruments in TradingView’s screener, and gain insights into how commissions, dividends, and price references impact long-term returns.
🎲 Using the script with Pine Screener
The main purpose of developing this script is to use it with Tradingview Pine Screener so that multiple ETFs/Funds can be compared.
In order to use this as a screener, the following things needs to be done.
Add SIP Evaluator and Screener to your favourites (Required for it to be added in pine screener)
Create a watch list containing required instruments to compare
Open pine screener from Tradingview main menu Products -> Screeners -> Pine or simply load the URL - www.tradingview.com
Select the watchlist created from Watchlist dropdown.
Chose the SIP Evaluator and Screener from the "Choose Indicator" dropdown
Set timeframe to 1 month and update settings as required.
Press scan to display collected data on the screener.
🎲 Use Case
This indicator is ideal for educational purposes, allowing users to experiment with SIP strategies across different instruments. It can be applied in TradingView’s screener to compare SIP performance for stocks, ETFs, or other assets, helping users understand how factors like commissions, dividends, and price references impact returns over time.
WLSMA: fast approximation🙏🏻 Sup TV & @alexgrover
O(N) algocomplexity, just one loop inside. No, you can't do O(1) @ updates in moving window mode, only expanding window will allow that.
Now I have time series & stats models of my own creation, nowhere else available, just TV and my github for now, ain’t no legacy academic industry I always have fun about, but back in 2k20 when I consciously ain’t known much about quant, I remember seeing post by @alexgrover recreating Moving Regression Endpoint dropped on price chart (called LSMA here) as a linear filter combination of filters (yea yeah DSP terms) as 3WMA - 2SMA. Now it’s my time to do smth alike aye?
...
This script is remake of my 1st degree WLSMA via linear filter combo. It’s much faster, we aint calculate moving regression per se, we just match its freq response. You can see it on the screen (WLSMAfa) almost perfectly matching the original one (WLSMA).
...
While humans like to overfit, I fw generalizations. So your lovely WMA is actually just one case of a more general weight pattern: pow(len - i, e), where pow is the power function and e is the exponent itself. So:
- If e = 0, then we have SMA (every number in 0th power is one)
- If e = 1, we get WMA
- If e = 2, we get quadratic weights.
We can recreate WLSMA freq response then by combining 2 filters with e = 1 and e = 2.
This is still an approximation, even tho enormously precise for the tasks you’ve shared with me. Due to the non-linear nature of the thing it’s all we can do, and as window size grows, even this small discrepancy converges with true WLSMA value, so we’re all good. Pls don’t try to model this 0.00xxxx discrepancy, it’s not natural.
...
DSP approach is unnatural for prices, but you can put this thing on volume delta and be happy, or on other metrics of yours, if for some reason u dont wanna estimate thresholds by fitting a distro.
All good TV
∞
P.S.: strangely, the first script made & dropped in the location in Saint P where my actual quant way has started ~5 years ago xD, very thankful
