Pulu's Moving AveragesPulu's Moving Averages
This script allows you to customize sets of moving averages. It is configured default as 3 Vegas tunnels + an MA12. You can re-configure it for any of your moving average studies. At the first release, it supports up to 7 moving averages, many parameters, and eight types of algorithms:
ALMA, Arnaud Legoux Moving Average
EMA, Exponential Moving Average
RMA, Adjusted exponential moving average (aka Wilder’s EMA)
SMA, Simple Moving Average
SWMA, Symmetrically-Weighted Moving Average
VWAP, Volume-Weighted Average Price
VWMA, Volume-Weighted Moving Average
WMA, Weighted Moving Average
If you are looking for only 3 moving averages, there is another script "Pulu's 3 Moving Averages".
ค้นหาในสคริปต์สำหรับ "algo"
Vigia blai5VIGÍA is the latest and current version of this weighted indicator that collects, combines and harmonizes the values of four other classic indicators: RSI, MFI, Bollinger Bands and Stochastic.
It is a 2nd Generation indicator, as it does not base its algorithm on pure price data, but on its evolution (volatility, volume differences, power variations, cycle phase ...) working from first generation indicators included and mixed in the algorithm.
With the RSI we detect current power or depletion; the MFI adds the harmonization between price and volume; Bollinger Bands warn us of positions in areas close to support and resistance, and Stochastic informs us of the favorable and unfavorable phases of its cycle. VIGÍA tries to gather all this information in a single value and signal. This is how the curve of this indicator emerges.
The layout of this curve is its own and different from that of the other four separately. But the key idea of this complex indicator is to harmonize the signals.
By "harmonizing" we mean that an exaggerated value of one of the individual indicators, being part of a set, is nuanced. On the other hand, a simultaneous good look in two or more, enhances the resulting signal making it more visible and clear for trading.
One of the main effects that I have tried to enhance in the various versions of VIGÍA is its geometry, so one of the best ways to operate the indicator is divergences, which are generally quite reliable.
But, unlike so many conventional indicators, VIGÍA allows us a relatively large number of operations, which can satisfy both lovers of the most daring techniques and those who are more prudent in their trading.
In the first place, the black line is properly the Watch Signal (SV), the soul and central element of this entire invention.
On it you will see that a red line is oscillating. It is an Exponential Average of the indicator itself (by default, value 20). It is of enormous interest for trading since the SV cuts on its Average can be taken as entry and exit signals. (To check it, you just have to check it on the history of any value or index).
But there are more elements. An important change is the transformation of fixed levels into variable trading bands. This system allows the environment to adapt to changes in the asset price, recognizing and transforming itself according to the trend or laterality phases through which it runs. The signal moves above and below a central zero value and (as always) with no extreme limits, because it is important to remember that VIGÍA is not an oscillator and that prevents it from reaching a predefined extreme and being 'keyed in'.
On the upper variable band, we enter the overload zone, in Vigía's own jargon, while under the lower variable band, the situation of the indicator is on discharge. It is interesting to observe how, precisely the crossing of these variable bands by Vigía coincides on many occasions with the fastest and most productive phase of the entire price shift, far from concepts that in this phase we should already abandon as outdated and unreliable such as "overbought" or "oversold."
The last two elements remain to be described: a timid blue dashed line and that flickering central area of color called the Astro.
The blue dashed line is named Filter. It is a much more useful element than its smooth and modest journey appears. The Filter has some really fascinating features. Notice, for example, that it is the only line that I keep in visible numerical value, to know exactly when it has a positive and negative value. In periods of laterality, it is a good ally to help us make decisions. It does more things, but that is a prize reserved for whoever pays some attention to it… :-))
We will finish by Astro. Astro is an indicator with its own personality that I designed separately, it is available independently, but I ended up incorporating it into Watcher, which also happens with the Medium Proportional Volume (MPV). Both can be presented or hidden, according to the tastes or needs of the user.
Astro is an adjustable trend indicator, a very useful little tool that will help us identify the critical points where we must consider entries or changes in position. Its default value is 8 cycles, which is a good fit for daily stocks, but I have left open the possibility of modifying its period to be able to take advantage of all its power in intraday temporalities. Once again, I invite you to DO NOT believe me, but to launch the indicator on any asset and evaluate the signals that Astro has offered on its history.
VWMA with kNN Machine Learning: MFI/ADXThis is an experimental strategy that uses a Volume-weighted MA (VWMA) crossing together with Machine Learning kNN filter that uses ADX and MFI to predict, whether the signal is useful. k-nearest neighbours (kNN) is one of the simplest Machine Learning classification algorithms: it puts input parameters in a multidimensional space, and then when a new set of parameters are given, it makes a prediction based on plurality vote of its k neighbours.
Money Flow Index (MFI) is an oscillator similar to RSI, but with volume taken into account. Average Directional Index (ADX) is an indicator of trend strength. By putting them together on two-dimensional space and checking, whether nearby values have indicated a strong uptrend or downtrend, we hope to filter out bad signals from the MA crossing strategy.
This is an experiment, so any feedback would be appreciated. It was tested on BTC/USDT pair on 5 minute timeframe. I am planning to expand this strategy in the future to include more moving averages and filters.
Robust Channel [tbiktag]Introducing the Robust Channel indicator.
This indicator is based on a remarkable property of robust statistics , namely, the resistance to the presence of data points that deviate significantly from the established trend (generally speaking, outliers ). Being outlier-resistant, the Robust Channel indicator “remembers” a pre-existing trend and thus exhibits a very peculiar "lag" in case of a sharp price change. This allows high-confidence identification of such price actions as a trend reversal, range break, pullback, etc.
In the case of trending and range-bound market conditions, the price remains within the channel most of the time, fluctuating around the central line.
Technical details
The central line is calculated using the repeated median slope algorithm. For each data point in a lookback window of a user-specified Length , this method calculates the median slope of the lines that connect that point to all other points inside the window. The overall median of these median slopes is then calculated and used as an estimate of the trend slope. The algorithm is very efficient as it uses an on-the-fly procedure to update the array containing the slopes (new data pushed - old data removed).
The outer line is then calculated as the central line plus the Length -period standard deviation of the price data multiplied by a user-defined Channel Width Factor . The inner line is defined analogously below the central line.
Usage
As a stand-alone indicator, the Robust Channel can be applied similarly to the Bollinger Bands and the Keltner Channel:
A close above the outer line can be interpreted as a bullish signal and a close below the inner line as a bearish signal.
Likewise, a return to the channel from below after a break may serve as a bullish signal, while a return from above may indicate bearish sentiment.
Robust Channel can be also used to confirm chart patterns such as double tops and double bottoms.
If you like this indicator, feel free to leave your feedback in the comments below!
Max Drawdown Calculating Functions (Optimized)Maximum Drawdown and Maximum Relative Drawdown% calculating functions.
I needed a way to calculate the maxDD% of a serie of datas from an array (the different values of my balance account). I didn't find any builtin pinescript way to do it, so here it is.
There are 2 algorithms to calculate maxDD and relative maxDD%, one non optimized needs n*(n - 1)/2 comparisons for a collection of n datas, the other one only needs n-1 comparisons.
In the example we calculate the maxDDs of the last 10 close values.
There a 2 functions : "maximum_relative_drawdown" and "maximum_dradown" (and "optimized_maximum_relative_drawdown" and "optimized_maximum_drawdown") with names speaking for themselves.
Input : an array of floats of arbitrary size (the values we want the DD of)
Output : an array of 4 values
I added the iteration number just for fun.
Basically my script is the implementation of these 2 algos I found on the net :
var peak = 0;
var n = prices.length
for (var i = 1; i < n; i++){
dif = prices - prices ;
peak = dif < 0 ? i : peak;
maxDrawdown = maxDrawdown > dif ? maxDrawdown : dif;
}
var n = prices.length
for (var i = 0; i < n; i++){
for (var j = i + 1; j < n; j++){
dif = prices - prices ;
maxDrawdown = maxDrawdown > dif ? maxDrawdown : dif;
}
}
Feel free to use it.
@version=4
Resampling Reverse Engineering Bands [DW]This is an experimental study designed to reverse engineer price levels from centered oscillators at user defined sample rates.
This study aims to educate users on the process of oscillator reverse engineering, and to give users an alternative perspective on some of the most commonly used oscillators in the trading game.
Reverse engineering price levels from an oscillator is actually a rather simple, straightforward process.
Rather than plugging price values into a function to solve for oscillator values, we rearrange the function using some basic algebraic operations and plug in a specified oscillator value to solve for price values instead.
This process tells us what price value is needed in order for the oscillator to equal a certain value.
For example, if you wanted to know what price value would be considered “overbought” or “oversold” according to your oscillator, you can do that using this process.
In this study, the reverse engineering functions are used to calculate the price values of user defined high and low oscillator thresholds, and the price values for the oscillator center.
This allows you to visualize what prices will trigger thresholds as a sort of confidence interval, which is information that isn't inherently available when simply analyzing the oscillator directly.
This script is equipped with three reverse engineering functions to choose from for calculating the band values:
-> Reverse Relative Strength Index (RRSI)
-> Reverse Stochastic Oscillator (RStoch)
-> Reverse Commodity Channel Index (RCCI)
You can easily select the function you want to utilize from the "Band Calculation Type" dropdown tab.
These functions are specially designed to calculate at any sample rate (up to 1 bar per sample) utilizing the process of downsampling that I introduced in my Resampling Filter Pack.
The sample rate can be determined with any of these three methods:
-> BPS - Resamples based on the number of bars.
-> Interval - Resamples based on time in multiples of current charting timeframe.
-> PA - Resamples based on changes in price action by a specified size. The PA algorithm in this script is derived from my Range Filter algorithm.
The range for PA method can be sized in points, pips, ticks, % of price, ATR, average change, and absolute quantity.
Utilizing downsampled rates allows you to visualize the reverse engineered values of an oscillator calculated at larger sample scales.
This can be rather beneficial for trend analysis since lower sample rates completely remove certain levels of noise.
By default, the sample rate is set to 1 BPS, which is the same as bar-to-bar calculation. Feel free to experiment with the sample rate parameters and configure them how you like.
Custom bar colors are included as well. The color scheme is based on disparity between sources and the reverse engineered center level.
In addition, background highlights are included to indicate when price is outside the bands, thus indicating "overbought" and "oversold" conditions according to the thresholds you set.
I also included four external output variables for easy integration of signals with other scripts:
-> Trend Signals (Current Resolution Prices) - Outputs 1 for bullish and -1 for bearish based on disparity between current resolution source and the central level output.
-> Trend Signals (Resampled Prices) - Outputs 1 for bullish and -1 for bearish based on disparity between resampled source and the central level output.
-> Outside Band Signal (Current Resolution Prices) - Outputs 1 for overbought and -1 for oversold based on current resolution source being outside the bands. Returns 0 otherwise.
-> Outside Band Signal (Resampled Prices) - Outputs 1 for overbought and -1 for oversold based on resampled source being outside the bands. Returns 0 otherwise.
To use these signals with another script, simply select the corresponding external output you want to use from your script's source input dropdown tab.
Reverse engineering oscillators is a simple, yet powerful approach to incorporate into your momentum or trend analysis setup.
By incorporating projected price levels from oscillators into our analysis setups, we are able to gain valuable insights, make (potentially) smarter trading decisions, and visualize the oscillators we know and love in a totally different way.
I hope you all find this script useful and enjoyable!
BuyTheDipWell, I often had arguments in online forum with a guy who claimed to time the market perfectly without any technical analysis or prior experience. He often claimed that technical analysis does not work and it only works when you trade on other's emotions. He also argued that algorithmic trading isn't profitable - if so, everyone would do that. Hence, I thought I will convert his idea to algorithm.
In his own words, the strategy is as below:
Chose an instrument which is in full uptrend.
Wait for the panic sell and buy the dip
Once market recovers back exit immediately
It seems to do just fine with indexes. But, not so good when it comes to stocks.
Resampling Filter Pack [DW]This is an experimental study that calculates filter values at user defined sample rates.
This study is aimed to provide users with alternative functions for filtering price at custom sample rates.
First, source data is resampled using the desired rate and cycle offset. The highest possible rate is 1 bar per sample (BPS).
There are three resampling methods to choose from:
-> BPS - Resamples based on the number of bars.
-> Interval - Resamples based on time in multiples of current charting timeframe.
-> PA - Resamples based on changes in price action by a specified size. The PA algorithm in this script is derived from my Range Filter algorithm.
The range for PA method can be sized in points, pips, ticks, % of price, ATR, average change, and absolute quantity.
Then, the data is passed through one of my custom built filter functions designed to calculate filter values upon trigger conditions rather than bars.
In this study, these functions are used to calculate resampled prices based on bar rates, but they can be used and modified for a number of purposes.
The available conditional sampling filters in this study are:
-> Simple Moving Average (SMA)
-> Exponential Moving Average (EMA)
-> Zero Lag Exponential Moving Average (ZLEMA)
-> Double Exponential Moving Average (DEMA)
-> Rolling Moving Average (RMA)
-> Weighted Moving Average (WMA)
-> Hull Moving Average (HMA)
-> Exponentially Weighted Hull Moving Average (EWHMA)
-> Two Pole Butterworth Low Pass Filter (BLP)
-> Two Pole Gaussian Low Pass Filter (GLP)
-> Super Smoother Filter (SSF)
Downsampling is a powerful filtering approach that can be applied in numerous ways. However, it does suffer from a trade off, like most studies do.
Reducing the sample rate will completely eliminate certain levels of noise, at the cost of some spectral distortion. The lower your sample rate is, the more distortion you'll see.
With that being said, for analyzing trends, downsampling may prove to be one of your best friends!
eha MA CrossIn the study of time series, and specifically technical analysis of the stock market, a moving-average cross occurs when, the traces of plotting of two moving averages each based on different degrees of smoothing cross each other. Although it does not predict future direction but at least shows trends.
This indicator uses two moving averages, a slower moving average and a faster-moving average. The faster moving average is a short term moving average. A short term moving average is faster because it only considers prices over a short period of time and is thus more reactive to daily price changes.
On the other hand, a long term moving average is deemed slower as it encapsulates prices over a longer period and is more passive. However, it tends to smooth out price noises which are often reflected in short term moving averages.
There are a bunch of parameters that you can set on this indicator based on your needs.
Moving Averages Algorithm
You can choose between three types provided of Algorithms
Simple Moving Average
Exponential Moving Average
Weighted Moving Average
I will update this study with more educational materials in the near future so be informed by following the study and let me know what you think about it.
Please hit the like button if this study is useful for you.
Renko RSIThis is live and non-repainting Renko RSI tool. The tool has it’s own engine and not using integrated function of Trading View.
Renko charts ignore time and focus solely on price changes that meet a minimum requirement. Time is not a factor on Renko chart but as you can see with this script Renko RSI created on time chart.
Renko chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify.
As source Closing price or High/Low can be used.
Traditional or ATR can be used for scaling. If ATR is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and brick size (ATR/Percentage) is 0.00124 then box size becomes 0.001. And also while using dynamic brick size (ATR), box size changes only when Renko closing price changed.
Renko RSI is calculated by own Renko RSI algorithm.
Alerts added:
Renko RSI moved below Overbought level
Renko RSI moved above Overbought level
Renko RSI moved below Oversold level
Renko RSI moved above Oversold level
RSI length is 2 by default, you can set as you wish.
You better to use this script with the following one:
Enjoy!
BitMEX pump catcher - MACDThis is a modified version of the BitMEX pump catcher by Jomy .
I have tweaked the algorithm to use the difference in MACD to get the correct direction of entries rather than using direction of candles which are not always indicative of trend direction. These changes increase net profit, profitable trades, while reducing drawdown.
Below is a copy and paste of Jomy's explanation of the algorithm.
What is going on here? This strategy is pretty simple. We start by measuring a very long chunk of volume history on BitMEX:XBTUSD 1 hour chart to find out if the current volume is high or low. At 1.0 the indicator is showing we are at 100% of normal historical volume . The blue line is a measure of recent volume! This indicator gets interested when the volume drops below 90% of the regular volume (0.9), and then comes back up over 90%. There's usually a pump of increased price activity during this time. When the 0.9 line is crossed by the blue line, the indicator surveys the last 2 bars of price action to figure out which way we're going, long or short. Green is long. Red is short. To exit the trade we use a 7 period fast ema of the volume crossing under an 11 ema slower period which shows declining interest in the market signifying an end to the pump or dump. The profit factor is quite high with 5x leverage, but historically we see 50% drawdown -- very risky. 1x leverage looks nice and tight with very low drawdown. Play with the inputs to see what matches your own risk profile. I would not recommend taking this into much lower timeframes as trading fees are not included in the profit calculations. Please don't get burned trading on stupid high leverage. This indicator is probably not going to work well on alts, as Bitcoin FOMO build up and behavior is different. This whole indicator is tuned to Bitcoin , and attempts to trade only the meatiest part of the market moves.
Jomy should get full credit to this indicator
My Recursive Bands [ChuckBanger]This is a different type of bands. I modified Alex Pierrefeu Recursive Bands algo. It is a smoothed version of Alex's algo and imo it suites better for heikin ashi candles but it works well with regular candles.
How to use it:
When price hugs the upper band. It is a potential long and when price hugs the lower band it is a potential short.
Credits to Alex Pierrefeu: figshare.com
[Autoview][BackTest] Blank R0.13BThis is a fork of JustUncleL's
Dual MA Ribbons R0.13
It is now a blank template for making new strategies / alerts for autoview
The changes are as follows:
Removed actual algo
Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos
Make allow Long and allow short and invert trade directions independent options
Added support for alternate candle types
Added autoset backtest period feature, and optional coloring
Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
[Autoview][Alerts]Blank R0.13BThis is a fork of JustUncleL's
Dual MA Ribbons R0.13
It is now a blank template for making new strategies / alerts for autoview
The changes are as follows:
Removed actual algo
Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos
Make allow Long and allow short and invert trade directions independent options
Added support for alternate candle types
Added autoset backtest period feature, and optional coloring
Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
Top Bottom Finder Public version- Jayy This script plots a 6 algos from the Coles/Hawkins "Midas Technical Analysis" book:
Top finder / Bottom Finder (Levine Algo by Bob English)* - onlinelibrary.wiley.com
MIDAS VWAP Gen-1) -
MIDAS VWAP average and deltas
VWAP (Gen-1) using a date or a bar n number can be initiated at bar 0 - useful for a new IPO
Standard Deviation of MIDAS VWAP
MIDAS Displacement Channels (Coles) - edmond.mires.co
An%20Anchored%20VWAP%20Channel%20For%20Congested%20Markets.pdf
* for better results with topfinder and bottomfinder use the companion TB-F Matcher script.
See wiki for a synopsis: en.wikipedia.org
Relevant info can be found in: Midas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by
Andrew Coles, David G. Hawkins Copyright © 2011 by Andrew Coles and David G. Hawkins.
Appendix C: TradeStation Code for the MIDAS Topfinder/Bottomfinder Curves ported to Tradingview
This script requires a working understanding of "Midas Technical Analysis" Google "Midas Technical Analysis" and a variety of information will appear.
To find fit the curve as described in the Midas book a companion script is required that will after a few manual iterative inputs guide you to the appropriate D value for the for input into this program ( see the TB-F Matcher script). You might also try the Midas average and Deltas as described in the book. I have added the 2nd, 3rd and 4th multiples of Delta.
The advantage is that there is no curve fitting. You still need to select a starting point for Midas or the topfinder bottomfinder (TB_F)
or the VWAP.
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
See the notes in the script below
Cheers Jayy
Volume Range EventsChanges in the feelings (positive, negative, neutral) in the market concerning the valuation of an instrument are often preceded with sudden outbursts of buying and selling frenzies. The aim of this indicator is to report such outbursts. We can see them as expansions of volume, sometimes 10 times more than usual. and as extensions of the trading range, also sometimes 10 times more than usual (e.g. usual range is 10 cent suddenly a whole dollar.) The changes are calculated in such a way that these fit between plus and minus 100 percent, the bars are scaled in some sort of logarithmic way. The Emoline is the same as the one in the True Balance of Power indicator, which I already published
ONLY RISES ARE EVENTS
Sometimes analysts are tempted to give meaning to low volume or small ranges. These simply mean that the market has little interest in trading this instrument. I believe that in such cases the trader needs to wait for expansion and extension events to happen, then he can make a better guess of where the market is heading. As events often mark the beginning or ending of a trend, this indicator provides an early and clear signal, because it doesn’t bother us about non-events.
WHAT IS USUAL?
If the algorithm would use an average as a normal to scale volume or range events, then previous peaks will act as spoilers by making the average so high that a following peak is scaled too small. I developed a function, usual() , that kicks out all extremes of a ‘population of values’ and which returns the average of the non-extreme values. It can be called with any serial. This function is called by both algorithms that report volume and range peaks, which guarantees that the results are really comparable. As this function has a fixed look back of 8 periods, we might state that ‘usual’ is a short lived relative value. I think this doesn’t matter for the practical use of the indicator.
COLORING AND INTERPRETATION
I follow the categories in the ‘Better Volume Indicator’, published by LeazyBear, these are:
1. Climactic Volumes, event >40 % (this means peak is 1.5 X usual)
LIME: Climax Buying Volume, direction up, range event also > 30 %
RED: Climax Selling Volume, direction down, range event also > 30 %
AQUA: Climax Churning Volume, both directions, range event < 30%
2. Smaller Volumes, event <40 %
GREEN: Supportive Volume, both directions, if combined with range event
BLUE: Churning Volume, both directions, if not combined with range event (Professional Trading)
3. Just Range Events
BLACK histogram bars (Amateurish Trading)
BUY & SELL VOLUME TO PRICE PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE
By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb"
Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx
Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona
WHAT IS THIS?
The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME --
Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant.
Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation.
Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT.
ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona
Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
BUY & SELL VOLUME TO PRICE PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE
By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb"
Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx
Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona
WHAT IS THIS?
The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME --
Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant.
Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation.
Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT.
ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona
Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
BUY & SELL VOLUME PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE
By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb"
Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx
Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona
WHAT IS THIS?
The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME --
Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant.
Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation.
Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT.
ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona
Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
Safe Supertrend Strategy (No Repaint)Overview
The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator.
Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes.
This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting.
Why This Supertrend Doesn’t Repaint
Most Supertrend indicators calculate their trend direction using the current bar’s data.
But during a live candle:
ATR expands and contracts
The upper/lower bands move
Price moves above/below the band temporarily
A false flip appears → then disappears when the candle closes
That is classic repainting.
This indicator avoids all of that by using:
close > upper
close < lower
This means:
Trend direction flips only based on the previous candle,
No intrabar calculations,
No flickering signals,
No “perfect but fake” historical performance.
Every signal you see on the chart is exactly what was available in real-time.
How It Works
Calculates ATR (Average True Range) and SMA centerline
Builds upper and lower volatility bands
Confirms trend flips only after the previous bar closes
Plots clear bull and bear reversal signals
Works on all markets (crypto, stocks, forex, indices)
No repainting, no recalc, no misleading flips.
Bullish Signal (Trend Up)
A bullish trend begins only when:
The previous candle closes above the upper ATR band,
And this flip is fully confirmed.
A green triangle marks the start of a new uptrend.
Bearish Signal (Trend Down)
A bearish trend begins only when:
The previous candle closes below the lower ATR band,
And the downtrend is confirmed.
A red triangle signals the start of a new downtrend.
Inputs
ATR Length - default 10
ATR Multiplier - default 3.0
Works on all timeframes and market
Simple, but powerful.
Why Use This Version Instead of a Regular Supertrend?
Most Supertrends:
Look great historically
But repaint continuously on live charts
Give false trend flips intrabar
Cannot be reliably used in strategies
This version:
Uses strict previous-bar logic
Never repaints trend direction
Works perfectly in live trading
Backtests accurately
Is ideal for algorithmic strategies
Ideal For:
Trend-following strategies
Breakout trading
Algo trading systems
Reversal detection
Filtering market noise
Swing trading & scalping
Final Note
This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions.
If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
Bitgak [Osprey]🟠 INTRODUCTION
Bitgak , translated as "Oblique Angle" in Korean, is a strategy used by multi-hundred-million traders in Korea, sometimes more heavily than Fibonacci retracement.
It is a concept that by connecting two or more pivot points on the chart and creating equidistant parallel lines, we can spot other pivot points. As seen in the example, a line at a different height but with the same angle spots many pivot points.
This indicator spots pivot points on the chart and tests all different possible Bitgak lines with a brute-force method. Then it shows the parallel line configuration with the most pivots hitting it. You may use the lines drawn on the chart as possible reversal points.
It is best to use on Day and Week candles . In the very short range of time, the noise makes it hard to capture meaningful data.
🟠 HOW TO USE
The orange dots are the major pivot points (you can set the period of the long-term pivot) upon which the lines are built.
Change the "Manual Lookback Bars" from 300 to a meaningful period upon your inspection.
"Hit Tolerance %" means how close a pivot needs to be to the line to be considered as having touched the line.
If the line is too narrow, which is not very useful, you may consider increasing the "Long-term Pivot Bars" and experimenting with different settings for Channel Lines and Heuristics.
The result:
"Top Anchors to Test (L)" is how many L highest peaks and L lowest troughs should be weighed heavily when testing the lines. That is, with L = 1, the algorithm will reward the Bitgak lines that touch 1 highest peak and 1 lowest trough. It doesn't make much intuitive sense, so I suggest just testing it out.
🟠 HOW IT WORKS
Step 1: Pivot Detection
The indicator runs two parallel detection systems:
Short-term pivots (default: 7 bars on each side) - Captures minor swing highs/lows for detailed analysis
Long-term pivots (default: 17 bars on each side) - Identifies major structural turning points
These pivots form the foundation for all channel calculations.
Step 2: Anchor Point Selection
From the detected long-term pivots, the algorithm identifies:
The L highest peaks (default L=1, meaning the single highest peak)
The L lowest troughs (default L=1, meaning the single lowest trough)
These become potential "anchor points" for channel construction. Higher L values test more combinations but increase computation time.
Step 3: Channel Candidate Generation
For support channels: Every pair of troughs becomes a potential base line (A-B)
For resistance channels: Every pair of peaks becomes a potential base line (A-B)
The algorithm then tests each peak (for support) or trough (for resistance) as pivot C.
Step 4: Optimal Spacing Calculation
For each A-B-C combination, the algorithm calculates:
Unit Spacing = (Distance from C to A-B line) / Multiplier
It tests multipliers from 0.5 to 4.0 (or your custom range), asking: "If pivot C sits on the 1.0 line, what spacing makes the most pivots hit other lines?"
Step 5: Scoring & Selection
Each configuration is scored by counting how many pivots fall within tolerance (default 1% of price) of any parallel line in the range . The highest-scoring channel is drawn on your chart.
Simplified Percentile ClusteringSimplified Percentile Clustering (SPC) is a clustering system for trend regime analysis.
Instead of relying on heavy iterative algorithms such as k-means, SPC takes a deterministic approach: it uses percentiles and running averages to form cluster centers directly from the data, producing smooth, interpretable market state segmentation that updates live with every bar.
Most clustering algorithms are designed for offline datasets, they require recomputation, multiple iterations, and fixed sample sizes.
SPC borrows from both statistical normalization and distance-based clustering theory , but simplifies them. Percentiles ensure that cluster centers are resistant to outliers , while the running mean provides a stable mid-point reference.
Unlike iterative methods, SPC’s centers evolve smoothly with time, ideal for charts that must update in real time without sudden reclassification noise.
SPC provides a simple yet powerful clustering heuristic that:
Runs continuously in a charting environment,
Remains interpretable and reproducible,
And allows traders to see how close the current market state is to transitioning between regimes.
Clustering by Percentiles
Traditional clustering methods find centers through iteration. SPC defines them deterministically using three simple statistics within a moving window:
Lower percentile (p_low) → captures the lower basin of feature values.
Upper percentile (p_high) → captures the upper basin.
Mean (mid) → represents the central tendency.
From these, SPC computes stable “centers”:
// K = 2 → two regimes (e.g., bullish / bearish)
=
// K = 3 → adds a neutral zone
=
These centers move gradually with the market, forming live regime boundaries without ever needing convergence steps.
Two clusters capture directional bias; three clusters add a neutral ‘range’ state.
Multi-Feature Fusion
While SPC can cluster a single feature such as RSI, CCI, Fisher Transform, DMI, Z-Score, or the price-to-MA ratio (MAR), its real strength lies in feature fusion. Each feature adds a unique lens to the clustering system. By toggling features on or off, traders can test how each dimension contributes to the regime structure.
In “Clusters” mode, SPC measures how far the current bar is from each cluster center across all enabled features, averages these distances, and assigns the bar to the nearest combined center. This effectively creates a multi-dimensional regime map , where each feature contributes equally to defining the overall market state.
The fusion distance is computed as:
dist := (rsi_d * on_off(use_rsi) + cci_d * on_off(use_cci) + fis_d * on_off(use_fis) + dmi_d * on_off(use_dmi) + zsc_d * on_off(use_zsc) + mar_d * on_off(use_mar)) / (on_off(use_rsi) + on_off(use_cci) + on_off(use_fis) + on_off(use_dmi) + on_off(use_zsc) + on_off(use_mar))
Because each feature can be standardized (Z-Score), the distances remain comparable across different scales.
Fusion mode combines multiple standardized features into a single smooth regime signal.
Visualizing Proximity - The Transition Gradient
Most indicators show binary or discrete conditions (e.g., bullish/bearish). SPC goes further, it quantifies how close the current value is to flipping into the next cluster.
It measures the distances to the two nearest cluster centers and interpolates between them:
rel_pos = min_dist / (min_dist + second_min_dist)
real_clust = cluster_val + (second_val - cluster_val) * rel_pos
This real_clust output forms a continuous line that moves smoothly between clusters:
Near 0.0 → firmly within the current regime
Around 0.5 → balanced between clusters (transition zone)
Near 1.0 → about to flip into the next regime
Smooth interpolation reveals when the market is close to a regime change.
How to Tune the Parameters
SPC includes intuitive parameters to adapt sensitivity and stability:
K Clusters (2–3): Defines the number of regimes. K = 2 for trend/range distinction, K = 3 for trend/neutral transitions.
Lookback: Determines the number of past bars used for percentile and mean calculations. Higher = smoother, more stable clusters. Lower = faster reaction to new trends.
Lower / Upper Percentiles: Define what counts as “low” and “high” states. Adjust to widen or tighten cluster ranges.
Shorter lookbacks react quickly to shifts; longer lookbacks smooth the clusters.
Visual Interpretation
In “Clusters” mode, SPC plots:
A colored histogram for each cluster (red, orange, green depending on K)
Horizontal guide lines separating cluster levels
Smooth proximity transitions between states
Each bar’s color also changes based on its assigned cluster, allowing quick recognition of when the market transitions between regimes.
Cluster bands visualize regime structure and transitions at a glance.
Practical Applications
Identify market regimes (bullish, neutral, bearish) in real time
Detect early transition phases before a trend flip occurs
Fuse multiple indicators into a single consistent signal
Engineer interpretable features for machine-learning research
Build adaptive filters or hybrid signals based on cluster proximity
Final Notes
Simplified Percentile Clustering (SPC) provides a balance between mathematical rigor and visual intuition. It replaces complex iterative algorithms with a clear, deterministic logic that any trader can understand, and yet retains the multidimensional insight of a fusion-based clustering system.
Use SPC to study how different indicators align, how regimes evolve, and how transitions emerge in real time. It’s not about predicting; it’s about seeing the structure of the market unfold.
Disclaimer
This indicator is intended for educational and analytical use.
It does not generate buy or sell signals.
Historical regime transitions are not indicative of future performance.
Always validate insights with independent analysis before making trading decisions.
Advanced Speedometer Gauge [PhenLabs]Advanced Speedometer Gauge
Version: PineScript™v6
📌 Description
The Advanced Speedometer Gauge is a revolutionary multi-metric visualization tool that consolidates 13 distinct trading indicators into a single, intuitive speedometer display. Instead of cluttering your workspace with multiple oscillators and panels, this gauge provides a unified interface where you can switch between different metrics while maintaining consistent visual interpretation.
Built on PineScript™ v6, the indicator transforms complex technical calculations into an easy-to-read semi-circular gauge with color-coded zones and a precision needle indicator. Each of the 13 available metrics has been carefully normalized to a 0-100 scale, ensuring that whether you’re analyzing RSI, volume trends, or volatility extremes, the visual interpretation remains consistent and intuitive.
The gauge is designed for traders who value efficiency and clarity. By consolidating multiple analytical perspectives into one compact display, you can quickly assess market conditions without the visual noise of traditional multi-indicator setups. All metrics are non-overlapping, meaning each provides unique insights into different aspects of market behavior.
🚀 Points of Innovation
13 selectable metrics covering momentum, volume, volatility, trend, and statistical analysis, all accessible through a single dropdown menu
Universal 0-100 normalization system that standardizes different indicator scales for consistent visual interpretation across all metrics
Semi-circular gauge design with 21 arc segments providing smooth precision and clear visual feedback through color-coded zones
Non-redundant metric selection ensuring each indicator provides unique market insights without analytical overlap
Advanced metrics including MFI (volume-weighted momentum), CCI (statistical deviation), Volatility Rank (extended lookback), Trend Strength (ADX-style), Choppiness Index, Volume Trend, and Price Distance from MA
Flexible positioning system with 5 chart locations, 3 size options, and fully customizable color schemes for optimal workspace integration
🔧 Core Components
Metric Selection Engine: Dropdown interface allowing instant switching between 13 different technical indicators, each with independent parameter controls
Normalization System: All metrics converted to 0-100 scale using indicator-specific algorithms that preserve the statistical significance of each measurement
Semi-Circular Gauge: Visual display using 21 arc segments arranged in curved formation with two-row thickness for enhanced visibility
Color Zone System: Three distinct zones (0-40 green, 40-70 yellow, 70-100 red) providing instant visual feedback on metric extremes
Needle Indicator: Dynamic pointer that positions across the gauge arc based on precise current metric value
Table Implementation: Professional table structure ensuring consistent positioning and rendering across different chart configurations
🔥 Key Features
RSI (Relative Strength Index): Classic momentum oscillator measuring overbought/oversold conditions with adjustable period length (default 14)
Stochastic Oscillator: Compares closing price to price range over specified period with smoothing, ideal for identifying momentum shifts
MFI (Money Flow Index): Volume-weighted RSI that combines price movement with volume to measure buying and selling pressure intensity
CCI (Commodity Channel Index): Measures statistical deviation from average price, normalized from typical -200 to +200 range to 0-100 scale
Williams %R: Alternative overbought/oversold indicator using high-low range analysis, inverted to match 0-100 scale conventions
Volume %: Current volume relative to moving average expressed as percentage, capped at 100 for extreme spikes
Volume Trend: Cumulative directional volume flow showing whether volume is flowing into up moves or down moves over specified period
ATR Percentile: Current Average True Range position within historical range using specified lookback period (default 100 bars)
Volatility Rank: Close-to-close volatility measured against extended historical range (default 252 days), differs from ATR in calculation method
Momentum: Rate of change calculation showing price movement speed, centered at 50 and normalized to 0-100 range
Trend Strength: ADX-style calculation using directional movement to quantify trend intensity regardless of direction
Choppiness Index: Measures market choppiness versus trending behavior, where high values indicate ranging markets and low values indicate strong trends
Price Distance from MA: Measures current price over-extension from moving average using standard deviation calculations
🎨 Visualization
Semi-Circular Arc Display: Curved gauge spanning from 0 (left) to 100 (right) with smooth progression and two-row thickness for visibility
Color-Coded Zones: Green zone (0-40) for low/oversold conditions, yellow zone (40-70) for neutral readings, red zone (70-100) for high/overbought conditions
Needle Indicator: Downward-pointing triangle (▼) positioned precisely at current metric value along the gauge arc
Scale Markers: Vertical line markers at 0, 25, 50, 75, and 100 positions with corresponding numerical labels below
Title Display: Merged cell showing “𓄀 PhenLabs” branding plus currently selected metric name in monospace font
Large Value Display: Current metric value shown with two decimal precision in large text directly below title
Table Structure: Professional table with customizable background color, text color, and transparency for minimal chart obstruction
📖 Usage Guidelines
Metric Selection
Select Metric: Default: RSI | Options: RSI, Stochastic, Volume %, ATR Percentile, Momentum, MFI (Money Flow), CCI (Commodity Channel), Williams %R, Volatility Rank, Trend Strength, Choppiness Index, Volume Trend, Price Distance | Choose the technical indicator you want to display on the gauge based on your current analytical needs
RSI Settings
RSI Length: Default: 14 | Range: 1+ | Controls the lookback period for RSI calculation, shorter periods increase sensitivity to recent price changes
Stochastic Settings
Stochastic Length: Default: 14 | Range: 1+ | Lookback period for stochastic calculation comparing close to high-low range
Stochastic Smooth: Default: 3 | Range: 1+ | Smoothing period applied to raw stochastic value to reduce noise and false signals
Volume Settings
Volume MA Length: Default: 20 | Range: 1+ | Moving average period used to calculate average volume for comparison with current volume
Volume Trend Length: Default: 20 | Range: 5+ | Period for calculating cumulative directional volume flow trend
ATR and Volatility Settings
ATR Length: Default: 14 | Range: 1+ | Period for Average True Range calculation used in ATR Percentile metric
ATR Percentile Lookback: Default: 100 | Range: 20+ | Historical range used to determine current ATR position as percentile
Volatility Rank Lookback (Days): Default: 252 | Range: 50+ | Extended lookback period for Volatility Rank metric using close-to-close volatility
Momentum and Trend Settings
Momentum Length: Default: 10 | Range: 1+ | Lookback period for rate of change calculation in Momentum metric
Trend Strength Length: Default: 20 | Range: 5+ | Period for directional movement calculations in ADX-style Trend Strength metric
Advanced Metric Settings
MFI Length: Default: 14 | Range: 1+ | Lookback period for Money Flow Index calculation combining price and volume
CCI Length: Default: 20 | Range: 1+ | Period for Commodity Channel Index statistical deviation calculation
Williams %R Length: Default: 14 | Range: 1+ | Lookback period for Williams %R high-low range analysis
Choppiness Index Length: Default: 14 | Range: 5+ | Period for calculating market choppiness versus trending behavior
Price Distance MA Length: Default: 50 | Range: 10+ | Moving average period used for Price Distance standard deviation calculation
Visual Customization
Position: Default: Top Right | Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Right | Controls gauge placement on chart for optimal workspace organization
Size: Default: Normal | Options: Small, Normal, Large | Adjusts overall gauge dimensions and text size for different monitor resolutions and preferences
Low Zone Color (0-40): Default: Green (#00FF00) | Customize color for low/oversold zone of gauge arc
Medium Zone Color (40-70): Default: Yellow (#FFFF00) | Customize color for neutral/medium zone of gauge arc
High Zone Color (70-100): Default: Red (#FF0000) | Customize color for high/overbought zone of gauge arc
Background Color: Default: Semi-transparent dark gray | Customize gauge background for contrast and chart integration
Text Color: Default: White (#FFFFFF) | Customize all text elements including title, value, and scale labels
✅ Best Use Cases
Quick visual assessment of market conditions when you need instant feedback on whether an asset is in extreme territory across multiple analytical dimensions
Workspace organization for traders who monitor multiple indicators but want to reduce chart clutter and visual complexity
Metric comparison by switching between different indicators while maintaining consistent visual interpretation through the 0-100 normalization
Overbought/oversold identification using RSI, Stochastic, Williams %R, or MFI depending on whether you prefer price-only or volume-weighted analysis
Volume analysis through Volume %, Volume Trend, or MFI to confirm price movements with corresponding volume characteristics
Volatility monitoring using ATR Percentile or Volatility Rank to identify expansion/contraction cycles and adjust position sizing
Trend vs range identification by comparing Trend Strength (high values = trending) against Choppiness Index (high values = ranging)
Statistical over-extension detection using CCI or Price Distance to identify when price has deviated significantly from normal behavior
Multi-timeframe analysis by duplicating the gauge on different timeframe charts to compare metric readings across time horizons
Educational purposes for new traders learning to interpret technical indicators through consistent visual representation
⚠️ Limitations
The gauge displays only one metric at a time, requiring manual switching to compare different indicators rather than simultaneous multi-metric viewing
The 0-100 normalization, while providing consistency, may obscure the raw values and specific nuances of each underlying indicator
Table-based visualization cannot be exported or saved as an image separately from the full chart screenshot
Optimal parameter settings vary by asset type, timeframe, and market conditions, requiring user experimentation for best results
💡 What Makes This Unique
Unified Multi-Metric Interface: The only gauge-style indicator offering 13 distinct metrics through a single interface, eliminating the need for multiple oscillator panels
Non-Overlapping Analytics: Each metric provides genuinely unique insights—MFI combines volume with price, CCI measures statistical deviation, Volatility Rank uses extended lookback, Trend Strength quantifies directional movement, and Choppiness Index measures ranging behavior
Universal Normalization System: All metrics standardized to 0-100 scale using indicator-appropriate algorithms that preserve statistical meaning while enabling consistent visual interpretation
Professional Visual Design: Semi-circular gauge with 21 arc segments, precision needle positioning, color-coded zones, and clean table implementation that maintains clarity across all chart configurations
Extensive Customization: Independent parameter controls for each metric, five position options, three size presets, and full color customization for seamless workspace integration
🔬 How It Works
1. Metric Calculation Phase:
All 13 metrics are calculated simultaneously on every bar using their respective algorithms with user-defined parameters
Each metric applies its own specific calculation method—RSI uses average gains vs losses, Stochastic compares close to high-low range, MFI incorporates typical price and volume, CCI measures deviation from statistical mean, ATR calculates true range, directional indicators measure up/down movement, and statistical metrics analyze price relationships
2. Normalization Process:
Each calculated metric is converted to a standardized 0-100 scale using indicator-appropriate transformations
Some metrics are naturally 0-100 (RSI, Stochastic, MFI, Williams %R), while others require scaling—CCI transforms from ±200 range, Momentum centers around 50, Volume ratio caps at 2x for 100, ATR and Volatility Rank calculate percentile positions, and Price Distance scales by standard deviations
3. Gauge Rendering:
The selected metric’s normalized value determines the needle position across 21 arc segments spanning 0-100
Each arc segment receives its color based on position—segments 0-8 are green zone, segments 9-14 are yellow zone, segments 15-20 are red zone
The needle indicator (▼) appears in row 5 at the column corresponding to the current metric value, providing precise visual feedback
4. Table Construction:
The gauge uses TradingView’s table system with merged cells for title and value display, ensuring consistent positioning regardless of chart configuration
Rows are allocated as follows: Row 0 merged for title, Row 1 merged for large value display, Row 2 for spacing, Rows 3-4 for the semi-circular arc with curved shaping, Row 5 for needle indicator, Row 6 for scale markers, Row 7 for numerical labels at 0/25/50/75/100
All visual elements update on every bar when barstate.islast is true, ensuring real-time accuracy without performance impact
💡 Note:
This indicator is designed for visual analysis and market condition assessment, not as a standalone trading system. For best results, combine gauge readings with price action analysis, support and resistance levels, and broader market context. Parameter optimization is recommended based on your specific trading timeframe and asset class. The gauge works on all timeframes but may require different parameter settings for intraday versus daily/weekly analysis. Consider using multiple instances of the gauge set to different metrics for comprehensive market analysis without switching between settings.
