DK BandsThis Bands are formed based on Bollinger Bands. The middle line shows moving average and remaining upper and lower bands are like zones wheh this this band is narrow then price consolidation stage similarly this band are expand then market will trending
Bands
Implied Volatility BandsThis script produces price bands around an EMA based on a manually inputted Implied Volatility. The idea builds on my previous "Implied Move" script which helps visualize the distribution of prices that the market is 'pricing in' via options/implied volatility. It's up to the user to determine the implied volatility level they use, I like using the free version of QuikStrike that you can access via the CME Group website and then update the script's input daily. Another way to use the script is to input the implied volatility based on a forecast that you produce independently. Say implied volatility on June 2021 Crude Oil is 30% and you think it's rich by 2%, you can input 28% into the script to tweak the bands for a declining vol regime.
VWAP Alerts V3VWAP Alerts signal over bought/over sold conditions, relative to volume weighted average price, while deviation bands plot an extremely accurate point of mean reversion.
VWAP Alerts V3 includes multiple timeframe selection, along with multiplier input for deviation band setting
Alerts can be set for each individual band, for extreme oversold/overbought conditions, use "Vwap Low Deviation 4" and "Vwap High Deviation 4".
Alerts can also be set for VWAP bounces, by simply setting "VWAP Alert"
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!
Quadratic Regression Trend ChannelIt's been a while since I have published anything meaningful for all members, but here is my next step in evolution of trend channel technology, my attempt at "Quadratic Regression Trend Channel" custom tailored for regression enthusiasts. I'm actually doing a lot more than my profile shall ever reveal. Many members may have heard of "polynomial regression channel"(PRC), but I wouldn't accurately label this as having the "poly-" capability in it with differing amounts of nth degrees/orders.
This indicator is derived from my "HLC Banded Quadratic Regression" indicator, the 3rd indicator I had ever published in my earliest days of tinkering around with Pine Script. It always had a destiny, and TV has graciously delivered on upgrading Pine with many new capabilities to run this algorithm with ease and in the manner that I wished to write it. Any subscribing TradingViewer has the freedom to use this indicator and as many as they shall desire.
Blessed is the "Immense Power of Pine" in 2021, as I utilized a multitude of new Pine features including extensive use of arrays for the quadratic regression formula, arrays of line.new(), input(group=), and input(inline=). I spent an incredible amount of time creating this, and it was no easy task to condense this amount of sophistication within less than 150 lines of code at the time of this original debut release. I have striven to achieve the indicator's computational efficiency potential to be as fast as possible with highly optimized code to handle the large amount of sampling it utilizes and is capable of. I hope you find it analytically favorable and beyond your expectations.
First of all, it has different sampling methods I haven't seen in any other PRC available, providing tightly snug and fit curvatures dependent on my optional choices not found in comparable indicators. This yields the best quality of fit I can provide by employing quadratic regression in order to provide a superb "visual analysis" of your price action in high noise environments. I also included my novel time warp feature to rewind the indicator regression into a previous state of time. If you're trading on really fast timeframes, I included an option to only calculate once per bar at it's closure. This will aid with computational efficiency of the TV servers, and it's intended to not to slow down your charting experience amongst a wide assortment of other indicators in your overlay chart.
I allowed a couple of variability methods for the confidence bands. A variety of coloring options, line thickness, and other perks are there to accommodate your distinct visual acuity. There is also a nifty option to color the regression by the slope of the curvatures. This is enabled by default, and I anticipate that you may find that color option uniquely useful. The amount of chords in the curvature are automatically calculated depending on the regression period selected to achieve a nice fluid arch for any setting.
Anyhow, I believe that sums up most of it's important characteristics in a brief explanation. It's potential is best personally discovered by simply using it with the myriad of control settings available. I published it with protected code, because I simply wanted to confine this monstrosity to my TradingView laboratory. I would rather not have this thing uncaged, rabidly running around the planet frothing out of the mouth on a Frankenstein AI later, unless it's mine on a short leash. Besides, I'm still trying to figure out the math behind "cubic regression". :)
Sorry in advance about not providing the source code, I hope you'll understand... We ALL know what devastation happens when things are "unleashed" from a BSL-4 lab to run amok. Countless billions have yet to learn a horrific lesson about the mania of evil at a future Geneva convention. If you don't know the mythical story about Pandora's box(a jar actually), look it up!
Features List Includes:
Calculation Throttling
Regression Period
Time Warp
Multiple Sampling Methods
Confidence Bands Variability Controls
Indicator Customization Options
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
Combo Backtest 123 Reversal & High Low Bands This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
As the name suggests, High low bands are two bands surrounding the underlying’s
price. These bands are generated from the triangular moving averages calculated
from the underlying’s price. The triangular moving average is, in turn, shifted
up and down by a fixed percentage. The bands, thus formed, are termed as High
low bands. The main theme and concept of High low bands is based upon the triangular
moving average.
WARNING:
- For purpose educate only
- This script to change bars colors.
Bollinger Bands Width with Compression by UJBBollinger Band width % with compression line and color changing area.
Monte Carlo Range Forecast [DW]This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation.
Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results.
These types of algorithms have a number of applications in numerous fields of study including physics, engineering, behavioral sciences, climate forecasting, computer graphics, gaming AI, mathematics, and finance.
Although the applications vary, there is a typical process behind the majority of Monte Carlo methods:
-> First, a distribution of possible inputs is defined.
-> Next, values are generated randomly from the distribution.
-> The values are then fed through some form of deterministic algorithm.
-> And lastly, the results are aggregated over some number of iterations.
In this study, the Monte Carlo process used generates a distribution of aggregate pseudorandom linear price returns summed over a user defined period, then plots standard deviations of the outcomes from the mean outcome generate forecast regions.
The pseudorandom process used in this script relies on a modified Wichmann-Hill pseudorandom number generator (PRNG) algorithm.
Wichmann-Hill is a hybrid generator that uses three linear congruential generators (LCGs) with different prime moduli.
Each LCG within the generator produces an independent, uniformly distributed number between 0 and 1.
The three generated values are then summed and modulo 1 is taken to deliver the final uniformly distributed output.
Because of its long cycle length, Wichmann-Hill is a fantastic generator to use on TV since it's extremely unlikely that you'll ever see a cycle repeat.
The resulting pseudorandom output from this generator has a minimum repetition cycle length of 6,953,607,871,644.
Fun fact: Wichmann-Hill is a widely used PRNG in various software applications. For example, Excel 2003 and later uses this algorithm in its RAND function, and it was the default generator in Python up to v2.2.
The generation algorithm in this script takes the Wichmann-Hill algorithm, and uses a multi-stage transformation process to generate the results.
First, a parent seed is selected. This can either be a fixed value, or a dynamic value.
The dynamic parent value is produced by taking advantage of Pine's timenow variable behavior. It produces a variable parent seed by using a frozen ratio of timenow/time.
Because timenow always reflects the current real time when frozen and the time variable reflects the chart's beginning time when frozen, the ratio of these values produces a new number every time the cache updates.
After a parent seed is selected, its value is then fed through a uniformly distributed seed array generator, which generates multiple arrays of pseudorandom "children" seeds.
The seeds produced in this step are then fed through the main generators to produce arrays of pseudorandom simulated outcomes, and a pseudorandom series to compare with the real series.
The main generators within this script are designed to (at least somewhat) model the stochastic nature of financial time series data.
The first step in this process is to transform the uniform outputs of the Wichmann-Hill into outputs that are normally distributed.
In this script, the transformation is done using an estimate of the normal distribution quantile function.
Quantile functions, otherwise known as percent-point or inverse cumulative distribution functions, specify the value of a random variable such that the probability of the variable being within the value's boundary equals the input probability.
The quantile equation for a normal probability distribution is μ + σ(√2)erf^-1(2(p - 0.5)) where μ is the mean of the distribution, σ is the standard deviation, erf^-1 is the inverse Gauss error function, and p is the probability.
Because erf^-1() does not have a simple, closed form interpretation, it must be approximated.
To keep things lightweight in this approximation, I used a truncated Maclaurin Series expansion for this function with precomputed coefficients and rolled out operations to avoid nested looping.
This method provides a decent approximation of the error function without completely breaking floating point limits or sucking up runtime memory.
Note that there are plenty of more robust techniques to approximate this function, but their memory needs very. I chose this method specifically because of runtime favorability.
To generate a pseudorandom approximately normally distributed variable, the uniformly distributed variable from the Wichmann-Hill algorithm is used as the input probability for the quantile estimator.
Now from here, we get a pretty decent output that could be used itself in the simulation process. Many Monte Carlo simulations and random price generators utilize a normal variable.
However, if you compare the outputs of this normal variable with the actual returns of the real time series, you'll find that the variability in shocks (random changes) doesn't quite behave like it does in real data.
This is because most real financial time series data is more complex. Its distribution may be approximately normal at times, but the variability of its distribution changes over time due to various underlying factors.
In light of this, I believe that returns behave more like a convoluted product distribution rather than just a raw normal.
So the next step to get our procedurally generated returns to more closely emulate the behavior of real returns is to introduce more complexity into our model.
Through experimentation, I've found that a return series more closely emulating real returns can be generated in a three step process:
-> First, generate multiple independent, normally distributed variables simultaneously.
-> Next, apply pseudorandom weighting to each variable ranging from -1 to 1, or some limits within those bounds. This modulates each series to provide more variability in the shocks by producing product distributions.
-> Lastly, add the results together to generate the final pseudorandom output with a convoluted distribution. This adds variable amounts of constructive and destructive interference to produce a more "natural" looking output.
In this script, I use three independent normally distributed variables multiplied by uniform product distributed variables.
The first variable is generated by multiplying a normal variable by one uniformly distributed variable. This produces a bit more tailedness (kurtosis) than a normal distribution, but nothing too extreme.
The second variable is generated by multiplying a normal variable by two uniformly distributed variables. This produces moderately greater tails in the distribution.
The third variable is generated by multiplying a normal variable by three uniformly distributed variables. This produces a distribution with heavier tails.
For additional control of the output distributions, the uniform product distributions are given optional limits.
These limits control the boundaries for the absolute value of the uniform product variables, which affects the tails. In other words, they limit the weighting applied to the normally distributed variables in this transformation.
All three sets are then multiplied by user defined amplitude factors to adjust presence, then added together to produce our final pseudorandom return series with a convoluted product distribution.
Once we have the final, more "natural" looking pseudorandom series, the values are recursively summed over the forecast period to generate a simulated result.
This process of generation, weighting, addition, and summation is repeated over the user defined number of simulations with different seeds generated from the parent to produce our array of initial simulated outcomes.
After the initial simulation array is generated, the max, min, mean and standard deviation of this array are calculated, and the values are stored in holding arrays on each iteration to be called upon later.
Reference difference series and price values are also stored in holding arrays to be used in our comparison plots.
In this script, I use a linear model with simple returns rather than compounding log returns to generate the output.
The reason for this is that in generating outputs this way, we're able to run our simulations recursively from the beginning of the chart, then apply scaling and anchoring post-process.
This allows a greater conservation of runtime memory than the alternative, making it more suitable for doing longer forecasts with heavier amounts of simulations in TV's runtime environment.
From our starting time, the previous bar's price, volatility, and optional drift (expected return) are factored into our holding arrays to generate the final forecast parameters.
After these parameters are computed, the range forecast is produced.
The basis value for the ranges is the mean outcome of the simulations that were run.
Then, quarter standard deviations of the simulated outcomes are added to and subtracted from the basis up to 3σ to generate the forecast ranges.
All of these values are plotted and colorized based on their theoretical probability density. The most likely areas are the warmest colors, and least likely areas are the coolest colors.
An information panel is also displayed at the starting time which shows the starting time and price, forecast type, parent seed value, simulations run, forecast bars, total drift, mean, standard deviation, max outcome, min outcome, and bars remaining.
The interesting thing about simulated outcomes is that although the probability distribution of each simulation is not normal, the distribution of different outcomes converges to a normal one with enough steps.
In light of this, the probability density of outcomes is highest near the initial value + total drift, and decreases the further away from this point you go.
This makes logical sense since the central path is the easiest one to travel.
Given the ever changing state of markets, I find this tool to be best suited for shorter term forecasts.
However, if the movements of price are expected to remain relatively stable, longer term forecasts may be equally as valid.
There are many possible ways for users to apply this tool to their analysis setups. For example, the forecast ranges may be used as a guide to help users set risk targets.
Or, the generated levels could be used in conjunction with other indicators for meaningful confluence signals.
More advanced users could even extrapolate the functions used within this script for various purposes, such as generating pseudorandom data to test systems on, perform integration and approximations, etc.
These are just a few examples of potential uses of this script. How you choose to use it to benefit your trading, analysis, and coding is entirely up to you.
If nothing else, I think this is a pretty neat script simply for the novelty of it.
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How To Use:
When you first add the script to your chart, you will be prompted to confirm the starting date and time, number of bars to forecast, number of simulations to run, and whether to include drift assumption.
You will also be prompted to confirm the forecast type. There are two types to choose from:
-> End Result - This uses the values from the end of the simulation throughout the forecast interval.
-> Developing - This uses the values that develop from bar to bar, providing a real-time outlook.
You can always update these settings after confirmation as well.
Once these inputs are confirmed, the script will boot up and automatically generate the forecast in a separate pane.
Note that if there is no bar of data at the time you wish to start the forecast, the script will automatically detect use the next available bar after the specified start time.
From here, you can now control the rest of the settings.
The "Seeding Settings" section controls the initial seed value used to generate the children that produce the simulations.
In this section, you can control whether the seed is a fixed value, or a dynamic one.
Since selecting the dynamic parent option will change the seed value every time you change the settings or refresh your chart, there is a "Regenerate" input built into the script.
This input is a dummy input that isn't connected to any of the calculations. The purpose of this input is to force an update of the dynamic parent without affecting the generator or forecast settings.
Note that because we're running a limited number of simulations, different parent seeds will typically yield slightly different forecast ranges.
When using a small number of simulations, you will likely see a higher amount of variance between differently seeded results because smaller numbers of sampled simulations yield a heavier bias.
The more simulations you run, the smaller this variance will become since the outcomes become more convergent toward the same distribution, so the differences between differently seeded forecasts will become more marginal.
When using a dynamic parent, pay attention to the dispersion of ranges.
When you find a set of ranges that is dispersed how you like with your configuration, set your fixed parent value to the parent seed that shows in the info panel.
This will allow you to replicate that dispersion behavior again in the future.
An important thing to note when settings alerts on the plotted levels, or using them as components for signals in other scripts, is to decide on a fixed value for your parent seed to avoid minor repainting due to seed changes.
When the parent seed is fixed, no repainting occurs.
The "Amplitude Settings" section controls the amplitude coefficients for the three differently tailed generators.
These amplitude factors will change the difference series output for each simulation by controlling how aggressively each series moves.
When "Adjust Amplitude Coefficients" is disabled, all three coefficients are set to 1.
Note that if you expect volatility to significantly diverge from its historical values over the forecast interval, try experimenting with these factors to match your anticipation.
The "Weighting Settings" section controls the weighting boundaries for the three generators.
These weighting limits affect how tailed the distributions in each generator are, which in turn affects the final series outputs.
The maximum absolute value range for the weights is . When "Limit Generator Weights" is disabled, this is the range that is automatically used.
The last set of inputs is the "Display Settings", where you can control the visual outputs.
From here, you can select to display either "Forecast" or "Difference Comparison" via the "Output Display Type" dropdown tab.
"Forecast" is the type displayed by default. This plots the end result or developing forecast ranges.
There is an option with this display type to show the developing extremes of the simulations. This option is enabled by default.
There's also an option with this display type to show one of the simulated price series from the set alongside actual prices.
This allows you to visually compare simulated prices alongside the real prices.
"Difference Comparison" allows you to visually compare a synthetic difference series from the set alongside the actual difference series.
This display method is primarily useful for visually tuning the amplitude and weighting settings of the generators.
There are also info panel settings on the bottom, which allow you to control size, colors, and date format for the panel.
It's all pretty simple to use once you get the hang of it. So play around with the settings and see what kinds of forecasts you can generate!
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ADDITIONAL NOTES & DISCLAIMERS
Although I've done a number of things within this script to keep runtime demands as low as possible, the fact remains that this script is fairly computationally heavy.
Because of this, you may get random timeouts when using this script.
This could be due to either random drops in available runtime on the server, using too many simulations, or running the simulations over too many bars.
If it's just a random drop in runtime on the server, hide and unhide the script, re-add it to the chart, or simply refresh the page.
If the timeout persists after trying this, then you'll need to adjust your settings to a less demanding configuration.
Please note that no specific claims are being made in regards to this script's predictive accuracy.
It must be understood that this model is based on randomized price generation with assumed constant drift and dispersion from historical data before the starting point.
Models like these not consider the real world factors that may influence price movement (economic changes, seasonality, macro-trends, instrument hype, etc.), nor the changes in sample distribution that may occur.
In light of this, it's perfectly possible for price data to exceed even the most extreme simulated outcomes.
The future is uncertain, and becomes increasingly uncertain with each passing point in time.
Predictive models of any type can vary significantly in performance at any point in time, and nobody can guarantee any specific type of future performance.
When using forecasts in making decisions, DO NOT treat them as any form of guarantee that values will fall within the predicted range.
When basing your trading decisions on any trading methodology or utility, predictive or not, you do so at your own risk.
No guarantee is being issued regarding the accuracy of this forecast model.
Forecasting is very far from an exact science, and the results from any forecast are designed to be interpreted as potential outcomes rather than anything concrete.
With that being said, when applied prudently and treated as "general case scenarios", forecast models like these may very well be potentially beneficial tools to have in the arsenal.
MACD BandsThis is MACD indicator on the price chart. You can read the same information as the original MACD but much more.
You can use it the same way as MACD but it won't use any space below your chart. Also you can use signal line and cloud as trend confirmation: e.g. if above them it can be a stronger uptrend.
The signal line (yellow by default) can be used as a support-resistance line.
If teal line is above maroon line, MACD is positive, otherwise it is negative
MACD value is the width of the cloud
Cloud color is green when MACD histogram is positive, red if negative
You can change MA types
MACD and histogram values can be seen in Data Window
PIN HUNTERScript Components
- Volume Weighted Averages (Daily, Weekly, Monthly and Yearly)
- Price bands created with Standard Deviation
- ALMA Indicator
- Automatic Trend Lines
How to use :
* The script has been written to work properly in all time periods. It is more appropriate to use visually in periods of 4 hours or less.
* First of all, it should be checked whether the price is below or above the yellow colored "ALMA Indicator".
* When the price crosses the yellow line down, it tends to touch the price below (curve, trend line or price line). These touches are used to determine the buying level by looking at the trend direction.
It is also necessary to calculate that the number of items to break below will change depending on the strength of the trend. The script doesn't teach you this experience, the decisions you make are always up to you.
The price, which starts to rise again by touching the lower level, will show an upward trend towards the "ALMA Indicator".
* When the price crosses the yellow "ALMA Indicator" line up, it tends to touch the price (curve, trend line or price line) above it. These touches are used to determine the selling level by looking at the direction of the trend.
* The main levels that are intended to be traded are Standard Deviation bands. (Example: Price crossing StD1 level upwards targets StD2 level in Uptrend. If the trend is still up StD3 level becomes target.)
* Automatic Trend Lines are created by the script as the price moves. Extend the trend lines to the right. These lines will serve as support and resistance in the next candles. Newly formed trend lines appear solid, old trend lines appear dashed.
I wish the script will be useful to everyone. I would like to thank you in advance for any contribution and criticism you will make.
Please have a look at my other scripts. Pivot STRTGY V1 is worth a try.
(Turkish)
Script Bileşenleri
- Hacim Ağırlıklı Ortalamalar ( Günlük, Haftalık, Aylık ve Yıllık)
- Standart Sapma ile oluşturulan fiyat bantları
- ALMA İndikatörü
- Otomatik Trend Çizgileri
Nasıl Kullanılır :
* Script tüm zaman periyodlarında sağlıklı olarak çalışacak şekilde yazılmıştır. Görsel olarak 4 saat ve altındaki periyodlarda kullanılması daha uygundur.
* Öncelikle fiyatın sarı renkli "ALMA İndikatörünün" altında veya üstünde oluduğuna bakılmalıdır.
*Fiyat sarı çizgiyi aşağıya kestiğinde bir altında bulunan fiyata ( eğri, trend çizgisi ya da fiyat hattı) dokunma eğilimi gösterir. Bu dokunuşlar trend yönüne de bakılarak alım seviyesini saptamaya yarar.
Trendin gücüne bağlı olarak aşağıda kırılacak öğe sayısının değişeceğini de hesaplamak gerekir. Script size bu deneyimi öğretmez, alacağınız kararlar her zaman size aittir.
Alt seviyeye dokunarak tekrar yükselmeye başlayan fiyat "ALMA İndikatörüne" doğru yükselme eğilimi gösterecektir.
* Fiyat sarı çizgiyi yukarıya kestiğinde bir üstünde bulunan fiyata ( eğri, trend çizgisi ya da fiyat hattı) dokunma eğilimi gösterir. Bu dokunuşlar trend yönüne de bakılarak satma seviyesini saptamaya yarar.
* Ticaret yapılması amaçlanan ana seviyeler Standart Sapma bandlarıdır. (Örnek : StD1 seviyesini yukarı yönde geçen fiyat Yukarı trendde StD2 seviyesini hedefler. Trend halen yukarı ise StD3 seviyesi hedef haline gelir.)
* Otomatik Trend Çizgileri fiyat hareket ettikçe script tarafından oluşturulur. Trend çizgilerini sağa doğru şekilde uzatın. Bu çizgiler sonraki mumlarda destek ve direnç vazifesi göreceklerdir. Yeni oluşan trend çizgileri katı, eskiden oluşmuş trend çizgileri kesikli olarak gözükürler.
Scriptin herkese faydalı olmasını dilerim. Yapacağınız her türlü katkı ve eleştiri için şimdiden teşekkürlerimi sunuyorum.
Lütfen diğer scriptlerime de göz atınız. Özellikle Pivot STRTGY V1 denemeye değer bir çalışmadır.
Implied volatility indicator - Bouhmidi-Bands Volatility trading with the Bouhmidi-Bands
Most known indicators such as Bollinger Bands or Keltner Channel focus only on historical volatility. Bouhmidi bands follow a different approach, namely an indicator based on implied volatility.
Style tags: Implied Volatility, Volatility Trading, Trend Analysis
Asset class: Equities, Futures, Commodities
Dataset: Minutes / Hours
Description
The most famous volatility indicators such as Bollinger Bands , Keltner Channel , Donchian Channels , etc. all use the historical volatility of the underlying asset. However, volatility is determined not only by historical volatility but also by implied volatility. The additional analysis of implied volatility sharpens the view and improves trading.
The Bouhmidi Bands ® were developed by myself and are based on implied volatility. They calculate an expected daily bandwidth under the assumption of normally distributed returns. The bandwidth is based on 1σ or 2σ. This means that an underlying closes with a probability of 68% or 95% within the expected Bouhmidi bandwidth at the end of the day. Check the historical development. The track record over the past 20 years shows a strong robustness of the indicator.
Benefits using Bouhmidi bands
- The Bouhmidi bands can be used to identify and filter "invisible" resistance and support that cannot be detected with simple chart analysis.
- The Bouhmidi bands can be used for different trading approaches. For example, they are suitable for mean reversion and volatility breakouts.
- If you combine the Bouhmidi bands with e.g. Keltner channel or Bollinger bands, you have the historical and implied volatility in one view in your tradingview chart.
Which underlyings can I trade with the Bouhmidi bands?
To determine the Bouhmidi bands, we need the underlying and the corresponding implied volatility index:
- S&P 500 - VIX
- DAX - VDAX-NEW
- Dow Jones - VXD
- Nasdaq 100 - VXN
- Gold - GVZ
- WTI - OVX
- Apple - VXAPL
- Amazon - VXAZN
- Google - VXGOG
- IBM - VXIBM
Torben BandsExtending the Works of Torben Mogensen, on Torben Median
Median Filtering is an important technique !
The median filter is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise (but see the discussion below), also having applications in signal processing.
How its made?
Torben Medians of high and low of period of 21 are combined with ATR adjustments and plotted over the price
Enjoy!
VIX Implied Move Bands for ES/Emini futuresThis script uses the close of the VIX on a daily resolution to provide the 'implied move' for the E-mini SP500 futures. While it can be applied to any equity index, it's crucial to know that the VIX is calculated using SPX options, and may not reflect the implied volatility of other indices. The user can adjust the length of the moving average used to calculate the bands, the window of days used to calculate the implied move, and the multiplier that effects the width of the bands.
Arnaud Legoux Moving Average With ATR BandsArnaud Legoux Moving Average With ATR Bands to get an idea of the volatility.
MACD Price Projected Bands [MPPB] Strategy for NIFTY / BTC 2 minMACD Price Projected Bands is an intraday NON REPAINTING Strategy to be used over BTCUSD and NIFTY on 2mins charts for optimum results!!
How the Strategy works
The strategy uses MACD with standard configuration as its main component.
The adaptive Bands are calculated over the MACD lookback, and MACD crosses of the adaptive bands are projected over the Price for creating a decision logic
A cyclic Trend Filter is used to calculate the Optimum Entry and Exit Points for the Strategy,
Levels are also plotted over the price projected bands for better visualisation of the targets!
What is used !
Macd_config : { fast:12 , slow:26 , signal:9 }
Lookback Length : 55
The Strategy has Provision for Alerts
You get Two signals
1. MPPBS Buy Signal
2. MPPBS Sell Signal
How the Visual Target System Works and How to trade Using this Strategy
An Adaptive Projected Band is constructed using MACD for traders to get Visual inputs regarding targets!!
The Trading Methodologies are in below Charts
For Short Trades
For Long Trades
Strategy Configurations for Backtest
For Englishmen!
The Backtesting Rules in the Strategy calculates only when order gets filled, the basic pyramiding in the strategy is set to 1, i.e The maximum number of entries allowed in the same direction is set to 1,
Also we trade only 1 quantity of the security with initial capital of 100000USD, and The commission type used in the strategy is set to 0.05 USD that means we pay 0.05USD as commissions in every trade!
For Coders!
{
calc_on_order_fills=true,
pyramiding=1,
default_qty_type=strategy.fixed,
default_qty_value=1,
initial_capital=100000,
currency=currency.USD,
commission_type= strategy.commission.cash_per_order,
commission_value = 0.05
}
How can you get access
Only do private message to me, donot use comment box for requesting access!
FibBand, Perfect Trendline Trader and Target SystemSo, Dear Friends, I am open-sourcing one of my scripts which I created as a thesis project,
The Auto Trader System is a Scalping Tool , to be used mostly in intraday Setups!!
and is designed using,
1. Fibonacci Bands
Fibo Bands are Calculated by defining dynamic Fibonacci Pivots Lines over a history of Lookup values (Default is 89 periods lookback),
The bands help in identifying the Target Points for the setup
2. Perfect TrendLine Setup
The script uses PTS, as a filter to define the optimum entry and exit points
Which timeframe it works for ?
Works for Any Time Frame, but Intraday setups are good!
Who is this System for ?
Beginner and Intermediate Traders
Provision For Alerts
The Script has provision for both long and short alerts!!
Enjoy!
Ethereum: Confidence BandsPurpose of this Script
Similar to "Bitcoin: Confidence Bands", this script is designed to show regions of positive and negative overextension for Ethereum, where price is expected to either reverse long-term or at least shorter-term, using custom price loops tuned for the Ethereum case. Again, the idea is that one can be highly confident that Ethereum's price stays within the Confidence Bands, especially when looking at weekly closes. It might be wise to reduce exposure to Ethereum when price gets very near to the red band, and vice versa for an approach of the blue band. Of course this constitutes no financial advice, and one should always consider all available information for making trading decisions.
Settings
This indicator should only be used:
- with the default inputs (but of course feel free to play around a bit for testing purposes)
- on the weekly (W) time frame
- and for the following ticker setup, used to get well averaged Ethereum price data (ideally just copy this and paste it into the ticker field in the upper left area of the chart interface): (KRAKEN:ETHUSD+COINBASE:ETHUSD+BITFINEX:ETHUSD+POLONIEX:ETHUSD)/4
Otherwise the intended functionality cannot be guaranteed.
Access
For access please contact me via DM on TradingView or on Twitter (linked on my TradingView profile and in my signature).
Bitcoin: Confidence BandsPurpose of this Script
This script is designed to show regions of positive and negative overextension for Bitcoin, where price is expected to either reverse long-term or at least shorter-term, using custom price loops. The idea is that one can be highly confident that Bitcoin's price stays within the Confidence Bands, especially when looking at weekly closes. It might be wise to reduce exposure to Bitcoin when price gets very near to the red band, and vice versa for an approach of the blue band. Of course this constitutes no financial advice, and one should always consider all available information for making trading decisions.
Settings
This indicator should only be used:
- with the default inputs (but of course feel free to play around a bit for testing purposes)
- on the weekly (W) time frame
- and for the BraveNewCoin Liquid Index for Bitcoin (BNC:BLX).
Otherwise the intended functionality cannot be guaranteed.
Access
For access please contact me via DM on TradingView or on Twitter (linked on my TradingView profile and in my signature).
Flunki RSI Candles 2x LinReg 2x BandsHerewith ;
RSI as Candles
With Linear Regression and a multiplied Linear Regression
With Adaptive Deviation Bands
Background highlighter highlights breaking of the slow / wide band.
I like it for scalping tops and bottoms on low time frames, but have a play..
The linear regression slopes show trend and divergence, might include divergence flags later....
Last script of 2020, wew.
TradeChartist Donchian Channels Breakout Filter™TradeChartist Donchian Channels Breakout Filter is an elegant version of the classic Donchian Channels with few extra variations and option to filter breakouts based on user preferred Breakout price selection to generate Trade Entries.
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Features of ™TradeChartist Donchian Channels Breakout Filter
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Option to plot Donchian Channels of user preferred length, based on the Source price in addition to High/Low Donchian Channels.
Generates trade entries based on user preferred Breakout Price. For example, if the user prefers HL2 as breakout price, irrespective of the Donchian Channels type, trade entries are generated only when hl2 price (average of high/low) breaks out of the upper or lower band.
Option to plot background colour based on Breakout trend. The bull zones are filled with green background, the Bear zones are filled with red background and the bar that broke out is filled with orange background.
Option to colour price bars using Donchian Channels price trend. The Donchian Channels basis line is plotted using the same colours as coloured bars as default.
Alerts can be created for long and short entries using Once per Bar Close .
Note: This script does not repaint . To use the script for trade entries, wait for the bar close and use a second confirmator (includes fundamentals) based on asset type as some markets require users to have good pulse on the fundamentals as trading by Technicals/price action dynamic alone may not be safe.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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This is not a free to use indicator. Get in touch with me (PM me directly if you would like trial access to test the indicator)
Premium Scripts - Trial access and Information
Trial access offered on all Premium scripts.
PM me directly to request trial access to the scripts or for more information.
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PHInkTrade Price FinderHello there, fellow trader!
Welcome to Price Finder indicator for TradingView page.
Please join me as I present you an overview about it.
Before we begin, a few quick notes:
Availability information is presented at the last section of this content. Please check it out to know how to get access.
In addition to this description, there is also an overview video available. Please refer to the last section on this content as well.
With time, some of the functionality described below may change. Please refer to Release Notes for most up-to-date information.
Ok now, let's get started!
What is Price Finder?
Price Finder is a technical analysis indicator (aka "Indi" ), built on a mathematical foundation which recognizes price's fractal, multi-layered nature -- a key aspect, related to the multiple time-frames process different size traders use to make their decisions.
The objective of the indicator, naturally, is to help identify high probability opportunities for successful trades , especially those which can provide a good return : risk ratio (greater than 3:1). This is very important to foster sustainable equity growth over time .
In order to do that, it helps identify new positions of previously successful support and resistance levels , out of both its multi time-frame mathematical approach, and empirical evidence. By mapping these, indicator provides a good way to anticipate next levels with high success probability, as well as to validate or invalidate expectations in relation to what price is more likely to do next.
Last, but not least, it also helps identify price state , in terms of trend and consolidation . Meaning that, if price is trending, we can expect it to go farther -- either higher or lower --, in a more consistent way. Or, if it is consolidating, we can expect it to remain trading inside a range.
Combined, these aspects help you develop an enhanced view of the market , and a better edge for your trades.
Feedbacks from beta phase
Before diving into more details, i'd like to let you know that, besides internal tests, the indicator has gone through a public beta testing phase , having received quite nice feedback from participants . You can find more information about it in the overview video, as mentioned above.
How it works?
As seen on chart below, indicator is composed of:
a Trend Band
two Expansion Threshold Bands and
Bar colors .
Let's get through each of these.
Trend Band
The Trend Band is the one which runs around the middle of the indicator, and helps you assess if you should be leaning bullish or bearish, locally -- considering the time frame you are looking at. Its inflection points , also known as death crosses and golden crosses, are important events to anticipate -- and pay attention to when they happen. There's also a middle line , which helps you evaluate if price is leaning towards crossing the band to the other side.
The following chart shows some examples* of how lines can help identify potential places to have new trades.
* More information about specific trading approaches is available through complementary materials.
So, Trend Band helps us adjust our bias towards a direction. But how far can we expect price to go?
To help answer this question, the indicator also provides two other bands. Let's talk about them, next.
Expansion Threshold Bands
The Expansion Threshold Bands are the ones usually surrounding price (not always, as you'll notice). They are called the Upper Expansion Threshold Band and the Lower Expansion Threshold Band . Their purpose is to help identify potential limits , or places where price is more likely to face a contrarian force , and will probably have to decide whether to continue in the same direction, or to pull back -- end eventually revert.
On the following chart we have an example (Bitcoin, 15 minutes time-frame). It was retracing locally, but once it hit the corresponding Lower Expansion Threshold, it found strong support, making it pull back, and look to test upper structures, next . In fact, as can be seen, this support was tested and respected three times on this chart. Conversely, the Upper Expansion Threshold Band, resistance, was tested and broken twice -- an effect, and validation, of the overall uptrend Bitcoin was in.
Broken Expansion Threshold Bands
Indicator also helps adjust expectations when price breaks an Expansion Threshold . As an example, on the following chart, we see Bitcoin breaking the 15 mins lower band, after having respected it multiple times during the rise. The result was a significant correction.
So, when price breaks an Expansion Threshold Band of a particular time-frame, we can expect it to expand in that same direction for a while. In other words, we can expect it to trend in that direction, until it finds a larger time-frame Expansion Threshold which can hold it.
To help with this aspect, here enters indicator's distinctive multiple time-frame overlays functionality .
Multiple time-frame overlays
Multiple time-frames is a very important aspect to understand and consider when dealing with an asset's price, as different size traders make decisions based on each of them -- and, naturally, this requires us to deal with the combined results of all such decisions.
On the chart below, (again, Bitcoin 15 minutes time-frame), standard indicator deployment is showing where supports are for some of the lows. But there are moments when price stop "mid-air". Why is it so?
Well, this happens due to the influence of another time-frame structure (in this case, a smaller one). To identify which structures are working, it is possible to apply the indicator one or more times to the chart, and perform an empirical research . In this case, bounces were caused by the 10 minute lower threshold band, approximately.
This feature allows you to see, on a single chart, multiple time-frame structures working at once -- which, besides bringing greater clearness, can also help you save time, by skipping the handling of multiple charts.
Note : TradingView recommends using a lower time-frame chart and deploying a higher time-frame overlay. However, within a good margin, the reverse practice has proven itself to work for Price Finder, as indicator's approach is evidence-based. So, whichever smaller time-frame overlay which shows itself as working, even though on a higher time-frame chart, should continue to do so, as calculations remain proportional.
Another example below, now showing 5 minutes working as support multiple times too (besides 10 and 15).
So, by researching which supports and resistances are being repeatedly respected, out of price's multi time-frame / multi layered reality, and finding their current price levels -- both through the means of the indicator --, it is possible to anticipate high probability places for successful trades -- either in favor of the structure, if you believe in a stop-and-reverse move, or against it, if structure gets broken and allows price to start expanding / trending. Always based on both a mathematical foundation, and an empirical observation (evidence / confirmation).
Bar colors
As an additional information to help you understand if price is trending (or starting to develop trend intentions), or if it is consolidating , the indicator provides bar color schemes.
By default, it uses dark green and dark red colors for initial developments of bullish and bearish trends , bright green and bright red colors for developed, stronger trends , and orange for consolidations . Knowing such states help you build more confidence in the movement -- or not.
Color-blind friendly setting
Colors-wise, indicator also offers the possibility to use a second scheme, more friendly to color-blind users. You can change color scheme on settings panel.
Other settings
There are other ways to customize the presentation of the indicator , especially regarding multiple time-frame overlays , as we saw, but also to help you manage and reduce chart clutter , for example, in terms of number of lines being plotted.
It's possible to decide to just plot backgrounds, or some part of the structure, or avoid painting bars, etc.
Sample chart settings, explained
What you see on the chart above:
3 deployments of Price Finder, one for each of the following time frames: 1 hour ('Chart' time-frame), 15 and 4 minutes.
Custom settings:
1 hour: Upper and lower expansion threshold bands plotted in full. Trend band hidden;
15 minutes: Trend band hidden, expansion thresholds with just backgrounds (for better visibility);
4 minutes: likewise.
Price Finder working with other assets
Here are some other examples of the indicator, now working with other assets.
Time-frames used to 'calibrate' readings were observed from previous evidence on the same charts.
Ethereum / US Dollar, 4 hour chart, with 100, 50 and 25 minutes overlays.
S&P 500, 1 hour chart, with 30, 15 and 5 minutes overlays.
Dow Jones Industrial Average, also 1 hour chart, with 4 hours, 15 and 5 minutes overlays.
Gold / US Dollar, 1D chart, with 600 minutes, 4 hours, 140 and 80 minutes overlays.
Euro / US Dollar, 4 days chart, with 1 day, 700 minutes and 4 hours overlays.
Availability and more information
For indicator availability, access instructions, and/or additional information, please use the corresponding link in the external links section below.
Thank you very much for your attention!
Cheers!
PHInkTrade
Acceleration BandsAcceleration Bands
Description:
Acceleration Bands serve as a trading envelope that factor in an assets typical volatility over standard settings of 20 or 80 bars. They can be used across any time period, though traders prefer to use them most across weekly and monthly timeframes as breakout indicators outside these bands.
Using the shorter time frames can define likely support and resistance levels at the lower and upper Acceleration Bands.
Entry is usually made at the breakout point. Once the price closes back within the Acceleration Bands, this is taken as a signal that the acceleration period is over and it’s best to close out the trade.
ATR BandsIt has happened to everybody. You enter the market, the position gets a stop loss, then later the market goes in the direction you originally planned. Worse yet - you enter a position, the market goes in your favor, gets near the target, and then it reverses and you get stopped.
We brazilians call this a "violinado", or getting violinated. It happens either because:
1. You put the stop loss too close, or the target too far
2. You entered in the right direction, but at a wrong time
While the second point cannot be programmly adressed, the first can. One popular way of setting a stop loss is by using the average of the true range, it even has a built-in indicator in TV. The problem with it is that you can still get violinated, since as the trend develops, the stop loss only goes up, never down. So if you enter at the wrong time, one slip can still take you out of the market.
Since I got sick of losing money using a conventional stop loss, I made these ATR bands. When you add this indicator to your graph, 6 lines are going to show up, 3 above the price, 3 below it. These lines are calculated from the ATR of the last 20 periods (can be configurated). The upper lines are the high of the last candle + the ATR * the multiplicator factor, the lower lines are the low - ATR * multiplicator factor. There are three multiplicator factors: 1.0, 1.618 and 2.0, and you change them to be whatever you want.
The logic behind it is that theses bands represents the region in which the market is more likely to stay. So if you enter the market at 50.00, you can't expect it to reach 500.00 in the next hour if the ATR is 5.00. And if you set the stop loss at 49.99, it is very likely that the market is going to stop you. By using the ATR bands, you can get a more reasonable price range, so you would set the stop loss at 45.00 and the take profit level at 60.00.
There are two types os ATR you can use: the regular, calculated with RMA, and another using a custom WMA, which puts greater emphasis on large amplitudes. By default, the average uses the past 20 true ranges. You can also choose to use either the closing price or the extremes of the candle as a basis.
Another thing I've added is the violation statistics, which shows the percentages of the times that a band was violated in the next 5 candles (can be configurated). With this, you can get a broader view on the probability of the bands actually being reached.
You may have notice that the bands are lagged by 1 period. I did this so that there is no way you can use future data. You can disable it or increase it, but I recommend just letting it be 1. These bands are the range in which the price is most likely to stay in, if you change the lag you are essentially breaking it's whole purpose.
Exponential Deviation Bands Width [ChuckBanger]This indicator is a compliment to Exponential Deviation Bands . It is the difference between the upper and the lower bands divided by the middle band. It is an easy way to visualize consolidation before price movements or periods of higher volatility.
How it works
During a period of high volatility, the distance between the two bands will widen and Exponential Deviation Bands width will increase. And the opposite occurs during a period of low volatility, the distance between the two bands will contract and Exponential Deviation Bands width will decrease. Meaning there is a tendency for bands to alternate between expansion and contraction.
When the bands are relatively far apart, that is often is a sign that the current trend is ending. When the distance between the two bands is relatively narrow that often is a sign that the market is about to initiate a bigger move in either direction.
